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Of pilferers and poachers: Combating electricity theft in India
... Existing studies either concentrate on the drivers of electricity theft (Smith, 2004;Yakubu et al., 2018;Razavi and Fleury, 2019;Jamil, 2018;Saini, 2017;Depuru et al., 2011) or dominantly articulate measurement controversies regarding electricity security (Wabukala et al., 2022;Neelawela et al., 2019b;Sarhan et al., 2021;Larsen et al., 2017) without providing the associated impacts between the two constructs. Second, while deterrence and punitive measures (technological and legal) exist and have adequately been profiled in literature (Jamil and Ahmad, 2019;Smith, 2004;Sharma et al., 2016;Shokoya and Raji, 2019;Dike et al., 2015;Saini, 2017;Depuru et al., 2011) their implementation has not yielded expected targets. Given that electricity theft has a socio-economic dimension, a strategy that targets on reducing electricity theft while providing affordable alternatives for households may improve electricity security in Uganda. ...
... However, attention has largely been directed at efforts that combat or alleviate electricity thefts. Important to note, majority of theft-combat interventions continue to emphasize technology (Sharma et al., 2016;Shokoya and Raji, 2019;Dike et al., 2015) and downplay psycho-social factors (Jamil and Ahmad, 2019;Yakubu et al., 2018;Razavi and Fleury, 2019). ...
... As reported by (Otuoze et al., 2020/08), over 50% of anticipated revenue is loss to electricity thefts in most developing countries and in terms of actual revenue. Likewise, United States, India and Malaysia reportedly incur annual loss of about $6 billion, $16.2 billion and RM500 million, respectively as result of electricity theft (Sharma et al., 2016;Otuoze et al., 2020/08;Jiang et al., 2014). In Turkey, the Turkish Electricity Distribution Company ed that annually, about 16 billion kWh of electricity as stolen, which represents about 15% of the total supply of electricity, translating to billions of dollars in financial loss (Yurtseven, 2015/12). ...
Renewable energy sources (RES) dominance in Uganda's electricity mix is challenged by affordability and theft. To assess electricity affordability, the study proposed a probabilistic method to quantify the households into different electricity categories for both urban and rural areas. Alternative electricity billing schemes based on Scenarios A to D for the households to enhance legal connection and consumption of electricity were proposed. The study established that the utility registers the highest electricity theft losses in rural households. The monthly utility revenue collected in urban areas was about 2.9 times that collected in rural areas because of the higher number of legally connected households with a monthly consumption of 1.5 times than that of rural households. From the monthly income spendable on electricity, rural and urban households could only afford 25.07 kWh and 38.29 kWh, respectively, which are less than the average household electricity consumption for Uganda. Also, the initial connection fee to the power grid is very high for the households to afford it in a single down payment. Of the proposed alternative billing schemes, Scenario B and Scenario D yield the least monthly utility revenue collected for the urban and rural households, respectively.
... As one of the development challenges confronting developing countries, electricity theft ranks third among commonly stolen itemspreceded by credit card and automobile theft, which are ranked first and second respectively. Annually, a total of USD 89.3 billion worth of electricity is reported stolen (Jamil, 2018;Kelly-Detwiller, 2013;Sharma et al., 2016). With variations between industry, residential, and other sectors, about 50% of generated electricity in sub-Saharan Africa end up stolen and illicitly consumed (Antmann, 2009;Adongo et al., 2021). ...
... Profound of these has been the deployment of technology-based measures targeted at counterbalancing the phenomenon of electricity theft (Han & Xiao, 2017;Ahmad, 2017). The institution of these mechanisms notwithstanding, electricity theft is still on the rise, and this partly explains limitations of technology to counter these measures -as highlighted by Sreenivasan (2016) and Sharma et al., (2016). The inefficiencies of these measures underscore the insufficiency of technology in combating electricity theft perhaps owing to the innovative measures deployed by perpetrators to overcome them (Sharma et al., 2016). ...
... The institution of these mechanisms notwithstanding, electricity theft is still on the rise, and this partly explains limitations of technology to counter these measures -as highlighted by Sreenivasan (2016) and Sharma et al., (2016). The inefficiencies of these measures underscore the insufficiency of technology in combating electricity theft perhaps owing to the innovative measures deployed by perpetrators to overcome them (Sharma et al., 2016). ...
Electricity theft is a challenge for developing countries including Ghana. Given its detrimental impacts on utility companies’ fiscal outlook and investment attractiveness, countervailing measures have been instituted. However, these have yielded suboptimal outcomes and thus excited whistleblowing discourses. Therefore, the current study engages a behavior paradigm to probe individual electricity theft whistleblowing intention behavior. With 471 responses, the results from structural equation modelling affirmed a positive relationship between awareness of consequences and attitude. Also, a positive relationship between awareness of consequences and subjective norm was confirmed. Moreover, whereas the positive relationship between subjective norm and attitude was verified, the positive relationships between perceived behavior control and personal norm was established. Attitude was also certified to be positively related to whistleblowing intention. In addition, perceived behavior control and personal norm were confirmed to be positively related to intention. Ascription of consequences was also revealed to be significantly related to personal norm. Similarly, ascription of responsibility was confirmed to moderate the relationships between attitude and intention, and personal norm and intention. In addition to demonstrating the appropriateness, applicability and efficacy of the proposed model in predicting electricity theft whistleblowing intention, the study outcomes form grounds for instituting anti-theft policy interventions.
... Electricity theft constitutes the illegal consumption of electricity by bypassing meter, tampering with energy meters, and several other methods to evade payment for consumed services (Depuru et al., 2011). Though reliable estimates on the extent of power theft remain elusive, it is believed that more than US $89.3 billion worth of electricity is pirated every year (Lan, 2002;Mirza and Hasmi, 2015;Northeast Group, 2015;Sharma et al., 2016), making electricity the third most stolen item after credit card data and automobiles (Kelly-Detwiler, 2013). The electricity theft menace is alarmingly high in low-income countries. ...
... But the fact that electricity theft continues to show upward trends amid these smart technology measures implies that technological fixes alone are not enough to curb the menace. The limitation of intelligent technology systems in completely resolving electricity theft, despite some marked successes, has been duly recognised by various researchers (McLaughlin et al., 2009;Sharma et al., 2016;Sreenivasan, 2016). The lamentation is that technology alone cannot be a panacea for electricity theft prevention as perpetrators still find innovative ways of circumventing these smart systems. ...
... Unfortunately, behavioural interventionists lack evidence on what issues to pursue to nudge reporting of electricity theft because reporting behaviour of energy crimes remains less understood due to less sociopsychological research attention on the matter (Isenring et al., 2016;Sharma et al., 2016). Next, while much has been written about electricity theft and the role of smart technologies, no empirical research examined electricity theft reporting behaviour of bystanders in the commercial accommodation sector much less the underlying reasons, despite the sector being one of the major perpetrators. ...
Electricity theft is one of the most critical sources of non-technical losses in the utility sector, of which commercial accommodation facilities are significant perpetrators. Though crime resolution has socio-economic, psychological, ethical and technical underpinnings, the latter is mostly sought in electricity theft. Meanwhile, technological means to combat this menace have not been very successful, which calls for the integration of social interventions. Employing the social-psychological model of crime reporting and three other deontological and teleological lenses, we taxonomised electricity theft whistleblowing intentions and distilled the underlying reasons using a sequential mixed-methods research design. Three segments of whistleblowers, namely Kantians, spectators and utilitarians, are identified. Reasons including criminalising electricity theft, government revenue gatekeeping, avoidance of trouble and empathetic feeling uniquely define these segments. The study advances that addressing the characteristics of the segments along with the fundamental human motivations of accuracy, connection and ego could be profound engines of change for increased electricity theft reporting.
... It is because NTLs cause a decrease in the legally collected tariffs [68] and affect the tariff system [74]. Besides, losses due to electricity fraud and theft prevent countries from taking action to reduce tariffs to be paid by consumers [83] and directly impact consumers in sensitive situations and the composition of subsidies for electricity companies. Another severe consequence of non-technical losses for all affected countries is that part of the lost electricity revenues could be applied to social programs [11], extending access to electricity to the poorest and most socially unprotected population [83]. ...
... Besides, losses due to electricity fraud and theft prevent countries from taking action to reduce tariffs to be paid by consumers [83] and directly impact consumers in sensitive situations and the composition of subsidies for electricity companies. Another severe consequence of non-technical losses for all affected countries is that part of the lost electricity revenues could be applied to social programs [11], extending access to electricity to the poorest and most socially unprotected population [83]. It affects social justice, making it necessary to expand subsidies to make these users' electricity consumption feasible [6,83]. ...
... Another severe consequence of non-technical losses for all affected countries is that part of the lost electricity revenues could be applied to social programs [11], extending access to electricity to the poorest and most socially unprotected population [83]. It affects social justice, making it necessary to expand subsidies to make these users' electricity consumption feasible [6,83]. In most cases, NTL leads authorities to subsidize electricity directly to society, but sometimes it is also necessary to provide financing to electricity companies, thereby increasing government spending [12]. ...
Non-technical losses refer to all electricity consumption not billed and represent a significant problem that has consequences to all sectors and a substantial negative impact on some geographical areas. These losses are complex and are attributed to several factors, leading researchers, concessionaires, and regulatory agents to seek successful solutions to reduce their effects. Thus, this article aims to identify the worldwide panorama on non-technical losses, presenting their impacts and the leading strategies and policies to mitigate them, helping the public and private sectors to understand the theme to outline effective solutions to combat this problem. A systematic review of the literature has been performed using the review protocol Preferred Reporting Items for Systematic Reviews and Meta-Analyzes, which resulted in 121 journal articles published between 2000 and 2020. The results comprise a complete definition of non-technical loss, its consequences for countries, distribution utilities, and society, the barriers and strategies for their identification, and the principal policies and regulations in countries of all levels of Gross National Income per capita. The main contribution of this article is to demonstrate the impact of non-technical losses to society and the economy, and the research and investigation directions so that frauds in the electricity sector are mitigated.
... The AMI faces series of attacks due to its complex structure and network dependency. Although, greatly reduced by the introduction of SEMs, electricity thefts remain a major concern to the deployment of AMI as adversaries continue to explore the vulnerabilities presented, majorly owned to the network facilities (Jiang et al., 2014;Sharma et al., 2016). Securing the CPS poses some challenges due to increased adoption of IoT entailing development of efficient threat models, assessment of the vulnerabilities for improved security, design of a reliable and self-healing security architecture (Alguliyev et al., 2018) etc., hence, the need for the protection of smart utility networks against cyber-attacks usually by computer and information security. ...
... It is a major concern in SG implementation due to the associated possible large scale losses (Jindal et al., 2016). These include shortage of revenues for utilities, dampening investment opportunities and commitments, increased billings on honest consumers, the need for subsidy payment by government to make for shortfalls (Jamil and Ahmad, 2014;Mohammad et al., 2013;Sharma et al., 2016) etc. ...
... Nigeria reportedly lose about 34%. In terms of yearly revenue, US, UK, India, Malaysia and Brazil reportedly lose over $6 billion, GBP 173 million, $16.2 billion, RM500 million and $5 billion, respectively (Jiang et al., 2014;Sharma et al., 2016), to the same menace. Northeast group LLC reported that worldwide, $89.3 billion are lost due to electricity theft on yearly basis (Jindal et al., 2016). ...
The successful deployment of Smart Grids (SG) clearly hinges on energy efficiency, relying majorly on the operations of the Advanced Metering Infrastructure (AMI) with Smart Electricity Meters (SEM) as its key aspect. Like every Cyber-Physical System (CPS), it is threatened by cyber-attacks and electricity theft is a notable motive of these attacks. Nonetheless, SEM offer adequate data being leveraged upon for analytical inferences. However, various research efforts mainly utilising artificial intelligence and machine learning are aimed at generating suspicious customer lists rather than a holistic approach to curbing the various aspects of the menace. In this thesis, a proactive scheme for preventing, detecting and penalizing electricity thefts is proposed. To achieve the prevention phase, a cyber security layer based on a novel Monkey-Banana Deceptive Algorithm (MBDA) for intrusion detection is introduced. This algorithm is developed from the popular 5 or 8-monkey theory by first presenting each of the stages to scenarios and then formulated to a probability assignment model. MBDA probability assignment is then applied to develop the algorithm for detecting intrusion in SEM’s communication gateway. To strengthen the prevention phase, selected factors indicative of electricity thefts are then modelled by defining a set of rules to infer security risk level using Fuzzy Inference System (FIS). The detection phase utilises a Long Short-Term Memory (LSTM) network based on time series prediction of the energy consumption data. The forecast values of the energy consumption are compared with the observed values to detect suspicious consumers based on defined anomaly detection model. To confirm true fraudulent consumers, a confirmation model is introduced based on selected monitoring parameters using FIS model. In the penalization phase, a cost estimation-based model by an analytical approach is introduced to deduce the penalty fine on confirmed fraudulent customers with considerations to energy consumed during reported theft period and modifications of some existent Electricity Theft Acts. A self-generated attack was used to implement the MBDA while the results of the FIS model determines the prevention status. The detection phase was implemented using the SEM energy consumption data of four selected consumers of different profiles to build consumer-dependent LSTM models. The anomaly and confirmation models are used to justify true fraudulent customers based on the states of the monitored parameters. The results of the cost estimation-based model implemented on twenty randomly selected electricity fraudulent consumers for the penalization phase indicate fraudulent customers reported at second and third attempts incurring 42% and 60% increase in the imposed fines, respectively. Implementation of this proactive scheme will enhance real-time protection of the SEM, reduces over reliance on energy consumption data analytics, reduces false positive rates, eliminates the usual practice of bogus financial sanctions, drastically reduce the need for the complicated on-site customer-to-customer inspections thereby saving manpower, stress, cost and time. In addition, the penalization phase also helps shift electricity theft burden from honest consumers. This proposed scheme is a suitable deployment for electricity theft prevention, detection and penalization in a smart utility network.
... In developing countries, about 20 -45% of the revenue is reportedly lost to electricity theft while the figure stands between 3.5 -30% in developed nations [43]. In United States alone, over $6 billion dollars are lost to energy theft while about $25 billion are reportedly lost, worldwide [2,18,22,39]. ...
... Some governments even grant subsidies to enable utility companies make up for the losses in revenue due to energy theft [18,44]. For efficient SC planning, these losses must be eliminated or at least, controlled to within relatively very low values by monitoring and controlling the energy consumption and billings for desired energy management and efficiency. ...
... This necessitates the inclusion of the detection and correction scheme. Evidently, theft or related attacks on the AMI cause huge losses and militates against further investment plans [18] except with assurance based on adequate security provision, hence, necessitating efficient tracing of threats and detection techniques for curbing these menaces [5]. The energy management scheme presented in Fig. 3 is a key aspect of smart city planning and must be well articulated especially by capitalising on available data. ...
Smart city adoption and deployment has taken the centre stage worldwide with its realisation clearly hinged on
energy efficiency, but its planning is threatened by the vulnerability of smart grids (SGs). Adversaries launch attacks with various motives, but the rampaging electricity theft menace is causing major concerns to SGs deployments and consequently,
energy efficiency. Smart electricity meters (SEMs) deployments via the advanced metering infrastructure (AMI) present promising solutions and even greater potential as it provides adequate data for analytical inferences to achieving proactive
measures against various cyber-attacks. This study suggests the sources of threats as the first step of such proactive measures
of curbing electricity thefts. It provides a framework for monitoring, identifying and curbing the threats based on factors indicative of electricity thefts in a smart utility network. The proposed framework basically focuses on these symptoms of the identified threats indicative of possible electricity theft occurrence to decide on preventing thefts. This study gives a useful background to smart city planners in realising a more reliable, robust and secured energy management scheme required for a sustainable city.
... Between 2004 and 2012, India recorded 15% increase in its populations' access to electricity from 59% to 74% but also has to deal with growing demand put at 5% per annum through 2030 [43]. As an action plan, India established a National Smart Grid Mission and budgeted over USD 5.8 billion for the period from 2012 to 2017 to deploy SGs [44]. ...
... Electricity theft inflicts the energy sector with shortage of fund for increased investments. Also, the governments are forced to consider subsidy payments else honest customers may be burdened in making up for the losses [43,63,64]. This also contributes to the everincreasing demand-supply gap since accurate records for proper planning are tampered and consequently discourages the utilities from further commitments. ...
... This also contributes to the everincreasing demand-supply gap since accurate records for proper planning are tampered and consequently discourages the utilities from further commitments. Some of the modes by which this unfortunate act is committed include physical manipulations of the meters, partial bypass involving connections of only a few loads, complete bypass of the meter where the meter is merely mounted to deceive officials but never connected, receipts of tips from customers to perpetuate billing irregularities, unpaid bills by unfaithful customers which usually lead to what is termed as 'bad debt', issuance of threats by thugs (which may prevent utility staff from either issuing bills or sanctioning some customers for unpaid bills) [43,64] etc. The authors in [56] blamed high level of corruption as being responsible for power theft in most developing countries citing India and Pakistan scenarios. ...
Considerable efforts in huge investments are being made to achieve a resilient Smart Grids (SGs) deployment for the improvement of power delivery scheme. Unsurprisingly, many developing nations are making slow progress to the achievement of this feat, which is set to revolutionize the power industry, own to several deployment and security issues. Studying these threats and challenges from both technical and non-technical view, this paper presents a highlight and assessment of each of the identified challenges. These challenges are assessed by exposing the security and deployment related threats while suggesting ways of tackling these challenges with prominence to developing nations. Although, a brief highlight, this review will help key actors in the region to identify the related challenges and it's a guide to sustainable deployments of SGs in developing nations.
... Hence, posing appalling challenges to the deployment of SGs in a country like Nigeria. One of the major source of loss for utility companies is electricity theft causing them huge losses and preventing further investment plans (Sharma, et al., 2016). Unpaid electricity bills, billing irregularities, smart meter manipulations and cyber-attacks, corruption of employees (e.g. ...
... Each year, utilities reportedly lose more than $25 billion worldwide (Jiang et al., 2014) causing every player high dissatisfaction. As a palliative measure, some governments reportedly grant subsidies to enable utility companies keep customers' bills low (Mohammad, et al., 2013;Sharma et al., 2016). About $25 billion is reportedly lost to power theft globally on yearly basis (Jiang et al., 2014;Sharma et al., 2016). ...
... As a palliative measure, some governments reportedly grant subsidies to enable utility companies keep customers' bills low (Mohammad, et al., 2013;Sharma et al., 2016). About $25 billion is reportedly lost to power theft globally on yearly basis (Jiang et al., 2014;Sharma et al., 2016). In some Sub-Saharan African, South-East Asia, Latin America and Middle east, huge losses in various range have been reported (Gaur and Gupta, 2016;Jamil and Ahmad, 2014;Jiang et al., 2014;Nikovski et al., 2013) and many cases are either partially reported or left unreported. ...
Smart Grids (SGs) have taken a centre stage in achieving a smarter, more reliable, robust, secured, economically efficient and more environmentally friendly mode of power generation and utilisation. Massive deployment is being recorded in developed worlds. While most of these countries are investing heavily in the development of SGs, well-articulated areas of research and development are key aspects with special emphasis on its security since it involves complex interconnection of units and systems which are expensive to install and maintain. In developing nations, especially those of Africa, realisation of adequate power supply to meeting the ever-growing demand has been a mirage with demand on geometric increase and with every increase largely meaning a drift away from the supply. Hence, attention is focused on capacity expansion in most developing nations rather than SGs deployments especially considering the various challenges militating against the development despite the huge advantages. Although, some of these nations have made tremendous achievements in this regard, the associated challenges have become major source of worry for most of the nations. This paper gives highlights of these issues and possible measures of overcoming them in order to enhance sustainable SGs deployments in developing coUntries like Nigeria
... Second, commercial losses to the operators withstanding, these unauthorized connections cause power supply disruptions, and adversely affect system reliability. While technological innovations [88,96], particularly, smart metering have been adopted, more punitive measures and social acceptance interventions, combined, may reduce power thefts and increase electricity security. ...
... From a technical perspective, diligent load management can increase capacity factors (or reduce the need for new capacity), lower electricity prices, and enhance reliability [67,84]. As government continues to increase T&D infrastructure, investment in underground distribution networks provide better security [83,88,96] and could improve reliability of electricity supply in Uganda. ...
Electricity propels economic development through improvement in the quality of life. Even though government's strategy to increase power generation and supply exists, Uganda experiences regular power outages and has one of the lowest electrification rates in the world. This study employs a systematic review approach and extends securitisation theory to the electricity sector to characterise electricity security and assess its barriers in Uganda. In this context, five dimensions of electricity security are identified and compared. Based on this set of dimensions, results show that Uganda is electricity “insecure.” Further, six (6) barriers to electricity security in Uganda are identified, and each of them is assessed as either existential, potential, or both. Thus, interventions that alleviate or mitigate these barriers can improve Uganda's electricity security. A quantitative empirical analysis using longitudinal data could offer superior evidence and conclusion on electricity security in Uganda.
... For instance, the CFE reports that in the first semester of 2021, the company lost over US$1.750mn in electricity thefts; this number is equivalent to a 36,6GWh which accounts for 11.6 % of CFE's total sales during the first six months of 2021 (Cervantes, 2021). Theft of electricity happens through several forms, including consumer meter tampering, illegal tapping (using a foul nightline or diablitos), and billing problems (unpaid bills irregularities or with billing) (Sharma, Pandey, Punia, & Rao, 2016;Smith, 2004;Wong, Blankenship, Urpelainen, Ganesan, & Balani, 2021). The shared element that these illegal activities have in common is that they result in revenue loss for the utility companies. ...
... households and the focus groups) 33 openly admitted to stealing electricity, while others, although they did not explicitly mention in the interviews they stole electricity, they did not have a meter installed. Some of the main reasons for electricity theft that are reported in the literature include the following: high electricity prices, corruption, poor enforcement of the law against electricity theft, and poor quality of power supplied (Lewis, 2015;Sharma et al., 2016;Smith, 2004;Wong et al., 2021;Yakubu, 2018). However, our research goes beyond these and found that at least in the MCMA, other reasons for stealing electricity existed as Table 6 presents. ...
So-called ''slum-dwellers" living in informal settlements in Mexico City Metropolitan Area (MCMA) often confront poor health outcomes, face chronic accommodation insecurity and are frequent victims of social intolerance, discrimination and racism. In addition, they usually reside in living environments with precariously hazardous conditions that often lead to their well-being endangerment. Based on extensive original research with slum-dwellers from the MCMA including focus groups (N = 18 participants), household interviews (N = 51 participants), and site visits (N = 5), this study investigates their energy and housing needs, transport and mobility patterns and challenges to their overall quality of life and health. The MCMA is one of the largest metropolitan regions globally, and most of its inhabitants experience a ''double energy vulnerability," circumstances whereby people are at an intensified risk of energy and transport poverty simultaneously. Our investigation circles around three key themes. In exploring the subject of extreme poverty and vulnerability, we show not only the problems they confront but also illegal practices such as electricity thefts and coping strategies. In investigating the subject of perpetual peripheralization, we show troubling patterns of discrimination, racism and social intolerance. In exploring the subject of spatial justice, we suggest a set of policies that ought to help achieve it.
... The computation of TL is generally needed for the correct estimation of NTL [2]. TLs are unavoidable as these occur in the equipment during the transmission and distribution (T&D) process, whereas NTLs are labeled as administrative losses that occur because of non-billed electricity, malfunction of the equipment, error in billings, low-quality infrastructure, and illegal usage of electricity [3]. The fraudulent behavior of energy customers is usually associated with electricity theft, regularized corruption, and organized crime [4]. ...
... The finalized lists of the articles selected from the journals and the conferences are depicted in tabular form in Tables 1 and 2, respectively and the flow chart of the article selection procedure is shown in Figure 1. [52,53] IET Generation, Transmission and Distribution 2 [54,55] Renewable and sustainable energy 2 [7,56] IEEE Journal on selected areas in communication 2 [8,57] Computers and Electrical Engineering 2 [58,59] Energy Research and social science 1 [3] International Journal of Artificial Intelligence and Applications 1 [2] Tsinghua science and technology 1 [9] IEEE Transactions on information forensics and security 1 [60] Energy 1 [61] Computers and Security 1 [62] Electronics 1 [63] ACM Transactions on Information and System Security 1 [64] Measurement: Journal of the International Measurement Confederation 1 [65] Knowledge-Based Systems 1 [66] Utilities Policy 1 [67] Expert Systems with Applications 1 [68] Machine Learning and Data Mining in Pattern Recognition 1 [69] IEEE/ACM International Conference on big data computing [70] IEEE PES Transmission and Distribution Conference and Exposition [71] International Conference on Information Technology and Multimedia [72] IEEE International Conference on Data Science and Advanced Analytics [73] International Conference on Critical Information Infrastructures Security (CRITIS) [74] International Conference on Power Systems (ICPS) [75] North American Power Symposium, NAPS 2015 [76] IEEE Symposium on Computational Intelligence and Applications in Smart Grid. [77] International Conference on Advances in Science, Engineering and Robotics Technology 2019 [78] IEEE Power and Energy Society Innovative Smart Grid Technologies Conference. ...
Electricity theft and fraud in energy consumption are two of the major issues for power distribution companies (PDCs) for many years. PDCs around the world are trying different methodologies for detecting electricity theft. The traditional methods for non-technical losses (NTLs) detection such as onsite inspection and reward and penalty policy have lost their place in the modern era because of their ineffective and time-consuming mechanism. With the advancement in the field of Artificial Intelligence (AI), newer and efficient NTL detection methods have been proposed by different researchers working in the field of data mining and AI. The AI-based NTL detection methods are superior to the conventional methods in terms of accuracy, efficiency, time-consumption, precision, and labor required. The importance of such AI-based NTL detection methods can be judged by looking at the growing trend toward the increasing number of research articles on this important development. However, the authors felt the lack of a comprehensive study that can provide a one-stop source of information on these AI-based NTL methods and hence became the motivation for carrying out this comprehensive review on this significant field of science. This article systematically reviews and classifies the methods explored for NTL detection in recent literature, along with their benefits and limitations. For accomplishing the mentioned objective, the opted research articles for the review are classified based on algorithms used, features extracted, and metrics used for evaluation. Furthermore, a summary of different types of algorithms used for NTL detection is provided along with their applications in the studied field of research. Lastly, a comparison among the major NTL categories, i.e., data-based, network-based, and hybrid methods, is provided on the basis of their performance, expenses, and response time. It is expected that this comprehensive study will provide a one-stop source of information for all the new researchers and the experts working in the mentioned area of research.
... The greatest problem facing the distribution companies is the level of non-technical losses which include commercial losses (unbilled used energy), and collection losses (unpaid billed energy). These losses are associated with electricity theft and fraud, a huge amount of losses are incurred through electricity theft which is consequently preventing further investment plans for the utilities (Otuoze et al., 2017;Sharma et al., 2016). Unpaid billed energy, unbilled used energy, billing irregularities, defective meters, conventional meter manipulations, corruption of the employees (misappropriation of funds, illegal procurement, sales of distribution equipment, meter bypass and more) and other associated fraudulent activities (Otuoze et al., 2017). ...
... NTL, also known as commercial and collection losses, are non-natural losses associated with the amount of non-billed electricity and billed electricity that is not paid for (Agha and Alfaoury, 2016;Sharma et al., 2016) or even paid but not properly remitted. The non-billed electricity occurs due to either error in the metering or billing systems or as a result of illegitimate behaviour of customers (Agha and Alfaoury, 2016;Bandim et al., 2003). ...
Energy losses in the distribution network and its subsystems have been
issues of great concerns in Nigeria’s power sector. For decades, several
studies have been conducted on the challenges facing the power sector
in Nigeria with most focus directed on the distribution subsystems. The
major challenge in the distribution system is the high energy losses
which are detrimental to the techno-economic benefits of the power
systems. However, details of the distribution system challenges and the
probable solutions have not been efficiently presented. In this study, some of these challenges are presented and the potential solutions are
proposed. The features of the Nigeria distribution network, the
technical and non-technical sources of losses as well as the identified
challenges are presented before discussing the potential solutions. The
panaceas so provided were from the understanding of some published
works and other related materials as well as the in-depth understanding
of the authors. This article can serve as a guide for the utilities and
stakeholders in the power sector for efficient management operations
and improved customer service delivery
... Therefore, it is a major concern in SG implementation due to the associated large scale investments which may, by implication, translate to huge losses (Jindal et al., 2016) if not curbed. Other effects of this rampaging act include shortage of revenues for utilities, dampening investment opportunities and commitments, increased billings on honest consumers, the need for subsidy payment by the government to make for shortfalls (Jamil and Ahmad, 2014a;Mohammad et al., 2013;Sharma et al., 2016) etc. Existing data reveal India loses about 25% of their generated power, Brazil faces about 16% loss while China and US reportedly lose 6% and 5%, respectively. Over 50% is lost in revenue to electricity thefts in most developing countries and in terms of revenue, United States, India and Malaysia reportedly incur annual loss of about $6 billion, $16.2 billion and RM500 million, respectively (Sharma et al., 2016;Krishna et al., 2016;Jiang et al., 2014), with several other nations incurring the distress in various degrees. ...
... Other effects of this rampaging act include shortage of revenues for utilities, dampening investment opportunities and commitments, increased billings on honest consumers, the need for subsidy payment by the government to make for shortfalls (Jamil and Ahmad, 2014a;Mohammad et al., 2013;Sharma et al., 2016) etc. Existing data reveal India loses about 25% of their generated power, Brazil faces about 16% loss while China and US reportedly lose 6% and 5%, respectively. Over 50% is lost in revenue to electricity thefts in most developing countries and in terms of revenue, United States, India and Malaysia reportedly incur annual loss of about $6 billion, $16.2 billion and RM500 million, respectively (Sharma et al., 2016;Krishna et al., 2016;Jiang et al., 2014), with several other nations incurring the distress in various degrees. Northeast group LLC reported that worldwide, $89.3 billion are lost due to electricity theft on yearly basis (Jindal et al., 2016). ...
Electricity theft menace has attracted various research efforts with most proposed detection algorithms relying on analysing customers' consumption profile to determine fraudulent electricity consumers (FEC). This necessitates the need for on-site inspections before penalties are sanctioned despite the manpower, cost, energy, time, and stress associated with such tedious routine. Moreover, the penalty-imposed fines are bogusly determined and uncoordinated, and losses in revenue are burdened on the honest consumers. Fortunately, the advent of advanced metering infrastructure offers a flexible and efficient platform which can be leveraged to provide additional functionality of curbing these complicated procedures. In this work, a cost estimation-based model deploying a forced corrective measure for a real-time enforcement of penalties on FEC in a smart utility network is proposed. It relies on the results of commonly applied intelligent algorithms for electricity theft detection to obtain the amount and cost of energy consumed by reported FEC while also providing efficient monitoring till imposed fines are cleared. The results of the developed model give proportionate sanctions and enhances the functions of the system manager's monitoring of the operational status to ensure compliance and is suitable for deployment in a smart utility network.
... It poses huge and weighty issues for PDCs since, in some cases, half of electricity supplies translate into NTLs and thus loss of billions of dollars per year [4]. It is estimated that PDCs worldwide lose around $25 billion worth of electricity each year alone as a result of electricity theft [5]. Although, countries with stable economies are not facing severe concerns related to NTLs, the search for suitable solutions to mitigate these losses are still a concern. ...
... Although, countries with stable economies are not facing severe concerns related to NTLs, the search for suitable solutions to mitigate these losses are still a concern. For example, in the USA and UK, the revenue loss due to electricity theft aggregates to $6 billion and $173 million Great Britain Pounds (GBP), respectively each year [5,6]. The most damaging effect of NTLs is present in those countries where economies are in an evolutionary phase [7]. ...
Non-technical losses (NTLs) have been a major concern for power distribution companies (PDCs). Billions of dollars are lost each year due to fraud in billing, metering, and illegal consumer activities. Various studies have explored different methodologies for efficiently identifying fraudster consumers. This study proposes a new approach for NTL detection in PDCs by using the ensemble bagged tree (EBT) algorithm. The bagged tree is an ensemble of many decision trees which considerably improves the classification performance of many individual decision trees by combining their predictions to reach a final decision. This approach relies on consumer energy usage data to identify any abnormality in consumption which could be associated with NTL behavior. The key motive of the current study is to provide assistance to the Multan Electric Power Company (MEPCO) in Punjab, Pakistan for its campaign against energy stealers. The model developed in this study generates the list of suspicious consumers with irregularities in consumption data to be further examined on-site. The accuracy of the EBT algorithm for NTL detection is found to be 93.1%, which is considerably higher compared to conventional techniques such as support vector machine (SVM), k-th nearest neighbor (KNN), decision trees (DT), and random forest (RF) algorithm.
... Brazil's social, cultural, geographical, and economic complexities High rate of customer default due to the pressure of non-technical losses on the electricity bill Need for the constant evolution of sector regulation Aggregation of harmonic distortions in the distribution network to non-technical losses in Brazil Political cost of large-scale disconnections Legal impunity for fraudsters Investment in smart meters, network monitoring, and infrastructure shielding Development of more robust technologies (Sharma et al., 2016) and adopting strict measures in partnership with government regulatory agencies (Ghajar et al., 2000). ...
Non-technical losses (NTLs) directly affect the electricity distribution system's quality and create significant economic problems in developing countries. There has been an advance in Brazil's regulations to combat this kind of loss in the last 15 years. However, the electricity consumed and not billed is still high, impacting the electricity tariff and distributors' investment capacity and creating difficulties in developing public policies to mitigate the problem. Thus, this article seeks to present the panorama of NTLs in Brazil and propose legislative, regulatory, business, and academic directions. For this, 28 semi-structured interviews were carried out with specialists, resulting in identifying the main challenges for identifying and mitigating NTLs in Brazil and the factors that help overcome this problem. The results demonstrate that coordinated strategic actions among all stakeholders need to be developed to combat NTLs. The cultural change in acceptance of electricity theft needs to be one of the country's main focuses. The main contribution is to disseminate information to regulatory and legislative authorities, government, concessionaires, and researchers to develop practical actions for mitigating NTLs in Brazil.
... Electricity thefts remain a major concern to the deployment of AMI as huge losses are reportedly incurred worldwide in addition to the increasing reports of cyber threats [28,37]. Despite the relief presented by AMI, a new dimension of threats posing unique challenges to the detection of NTL necessitate the need for the development of robust techniques for a timely identification and elimination of threats [12,28,35]. ...
The deployment of smart electricity meter (SEM) via the advanced metering infrastructure (AMI) has come under cyber-attacks as adversaries continue to exploit the communication links for possible evasion of electricity bill payments. Various detection models relying on energy consumption data offer a disadvantage of delayed detection and consequent huge financial losses before frauds are detected. Moreover, existing techniques mostly concentrate on detection of electricity thefts and rely on energy consumption data alone as the basis of theft perpetration whereas other potential parameters which could be exploited for electricity theft prevention exist in AMI. In this study, AMI parameters, which are indicative of electricity thefts are preselected and modelled for electricity theft prevention. First, a given AMI network is sectioned into zones with the selected parameters modelled to define security risks by formulated set of rules based on real-time scenarios. Fuzzy inference system is then employed to model the security risks to ascertain the compromised state of the monitored parameters at the defined scenarios. The result of the developed model at 50% weight of each of the modelled parameters with interdependencies show clear indications of the modelled parameters and their interactions in the determination of risks. The decisions on monitored parameters evaluated at every timestep reveal varied dense velocity behaviours for every scenario. The result is suitable for monitoring the AMI in reporting and/or disconnecting any compromised SEM within a considerable timestep before huge losses are incurred. Implementation of this scheme will contribute a significant success in the attempt to prevent electricity theft perpetration via the AMI.
... Attitudes regarding stealing, normalisation of theft and views on theft behaviour control all influence theft intention. Environmental, organisational structure, society, administration and communication and corporate governance practises to prevent data theft, unfairness and work overload provide opportunity factors for employees to engage in data theft [111]. To solve this challenge, new cyber security procedures are needed to identify vulnerable locations in the smart grid and prevent power disruptions [112]. ...
The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the end- users, and enhances the user experience by monitoring and controlling the energy transmission. The smart grid deals with an enormous amount of energy data, and the absence of proper techniques for data collection, processing, monitoring and decision-making ultimately makes the system ineffective. Big data analytics, in association with the smart grid, enable better grid visualization and contribute toward the attainment of sustainability. The current research work deals with the achievement of sustainability in the smart grid and efficient data management using big data analytics, that has social, economic, technical and political impacts. This study provides clear insights into energy data generated in the grid and the possibilities of energy theft affecting the sustainable future. The paper provides insights about the importance of big data analytics, with their effects on the smart grids’ performance towards the achievement of SDGs. The work highlights efficient real-time energy data management involving artificial intelligence and machine learning for a better future, to short out the effects of the conventional smart grid without big data analytics. Finally, the work discusses the challenges and future directions to improve smart grid technologies with big data analytics in action.
... As of 2016, the peak demand met was 145.103 GW [11]. It has been forecasted that there shall arise in energy demand of about 900 GW till 2032, out of which 183 GW would be contributed by the renewable energy sector [4]. ...
Electricity theft is one of the biggest concerns in the present energy sector. Controlling such a phenomenon is very challenging. It is a prime constituent of AT&C losses in the system. It is a very big concern from the energy perspective, especially the distribution companies. It affects the quantity and quality of energy used in the load. In this paper, the causes, methods, and reduction techniques of AT&C losses and the measures taken by various utilities for future scope of improvement have been discussed. A detailed statistical analysis of the trend of AT&C losses in various zones of India from 2012 to 2022 and the percentage of electricity theft from 2016 to 2019 in the above losses has been done and compared. The study finds that there is a decreasing trend of AT&C losses and electricity theft.
... One of the fundamental advancements in the power grid is the inclusion of Advanced Metering Infrastructure (AMI) that enables bi-directional communication between customers and utilities [7,8,9,10,11]. In reality, smart meters (SMs) are considered a vital part of the AMI that encourage productive and effective data trading in power utility systems [12,13,14,15,16]. Almost all electricity companies face electrical power losses, which lead to huge economic losses [17,18,19]. ...
... Statistics on electricity losses in India shows that around 10-12% of AT&C losses amount to technical reasons, while remaining 18-20% comprises commercial reasons [1] known as commercial losses (CL). According to U.S. Energy Information Administration (EIA) [2] in the countries with low rate of theft and optimal technical efficiency TD losses generally span between 6 and 8%. Figure 1 shows graphical representation of AT &C loss percentage of different Indian states. ...
Stealing of electricity through meter tampering has always been a major cause not only for loss of revenue to the governments but also for irregular electricity supply. Advanced Metering Infrastructure (AMI) has replaced traditional analog devices with the digital ones like smart meters thereby enabling bidirectional flow of information between the utility and consumers via communication network. This two-way communication has the potential to flat the demand and supply curve between the utility companies and consumers. However with the adoption of new technology such as smart grid new security challenges have emerged. Although smart meters may have provided an edge over traditional methods of stealing electricity, they have opened doors for next generation of hackers. In this paper, we have provided an overview of various energy theft detection techniques in Smart Meters along with their implementation challenges with context to Indian Power Sector. A comprehensive performance comparison between different available approaches is attributed and a distinguished attack technique at the hardware level is also being proposed.
... With limited man power in hand it is difficult to detect theft cases in all areas. Employee Theft: In some cases DU employee indulge in malpractices like recording lesser consumption than actual metered consumption or simply not providing meter to the consumer [6]. This affects revenue generated by the utility. ...
Distribution of electricity becomes inefficient when rural areas are sparse or remote. Un-metered/illegal connections, poor bill collection efficiencies are some common practices found in villages, especially remote areas. Consumers also remain unsatisfied with service provided by Distribution Utility due to long hours of supply cut, unscheduled outages, low voltage levels, and wrong meter readings. To address these problems at the last mile and to improve the performance of the electricity distribution sector, Electricity Act 2003 has introduced Distribution Franchisees (DF). DFs are contracted to manage the last mile functions of the electricity sector for a specified area. This paper presents a study of an initiative by a DF in the state of Odisha, which contracted 142 women self-help groups (SHGs) to undertake metering, billing, and revenue collection, leading to reduction in electricity losses by 30%. The objective of this study is to gain deeper understanding of different aspects of the role played by SHGs in handling these last mile governance functions. The study relies on semi-structured and unstructured interviews with different stakeholders. The study would help understand the feasibility and relevance of SHGs in addressing the governance crisis in the last mile of the electricity sector.
... In their analysis of the issue, Nagi et al. (2010) observe that energy theft is not only occurring in developing countries in the Asian and African regions, but is also confronting the developed countries, such as the United States of America and the United Kingdom. Sharman et al. (2016) laments that about $25 billion is annually lost to energy theft by electricity companies worldwide. Depuru et al. (2011) estimate the annual loss due to energy theft in India to about $9 billion. ...
Energy theft is among the dominant problems confronting the Nigerian electricity sector. Therefore, this study examined the factors underlying the perpetration of this illegal act among electricity consumers in Lagos and Ibadan metropolis, Nige-ria. Rational choice perspective and situational crime prevention perspective were employed as theoretical guide. Data were generated using in-depth interview and key-informant interview methods. Snowball sampling was utilised for the selection of 59 electricity consumers engaging in energy theft, while nine officials of two electricity distribution companies were purposively chosen. Findings indicated that electricity tapping was the most common form of energy theft. Most of the electricity consumers engaging in energy theft considered it a rational response to the ineptitude and inefficiency of electricity distribution companies.
... Electricity theft is more prominent in the developing countries [24] than it is in the developed countries [25]. Most of the electricity theft occurrences in the developing countries are as a result of poverty [3], while others are due to greed and moral laxity [26]. The moral laxity displayed by corrupt utility employees or representatives who compromise their call to duty and connive with electricity consumers to negotiate personal terms of financial settlement, instead of being honest and objective. ...
Electricity theft is a pervasive problem all over the world. With electricity generation in Nigeria falling short of the required generation ca-pacity, it is disturbing that the little power generated is also being stolen by some unscrupulous consumers. Electricity distribution compa-nies in Nigeria (DisCos) lose about ₦30 billion every month owing to electricity theft. This amount is whopping, and if significantly re-duced and spent on the power infrastructure and management, it would improve the power situation in the country. This paper proffers the deployment of Smart Grid (SG) with its inherent smart metering as a solution to the electricity theft situation in Nigeria, as a result of its improved flexibility, security and reliability. Smart Grid also supports energy diversification, by allowing the integration of various renewa-ble energy sources into the conventional power grid. This will tend to help in improving the epileptic power situation in the country.
... The rate of electricity theft is low in the developed countries, while it is high in the developing countries. Electricity theft in developing countries is associated with poverty [18], moral laxity and greed [19]. One of the moral laxity issues is the opinion that, it is not a crime to steal from the government or the government owned utility companies but only criminal to steal from a neighbour, family or friends [20]. ...
Electricity theft is a menace in Africa and the world at large. South Africa is one of the countries in Africa that could largely boast of a reliable electricity supply. However, this reliability could be jeopardized by the incessant electricity theft that is ravaging the country. As a result of electricity theft, Eskom, the national electricity utility provider and the municipalities run into geometric losses amounting to at least R20 billion annually. Deployment of Smart Grid (SG) would drastically reduce electricity theft as a result of improved flexibility, security and reliability brought about by the system. Also, with the SG advantage of the incorporation of renewable energy generation into the conventional electrical power grid, the current tentative outage of electricity brought about by load shedding in the country would be nipped in the bud. This paper analyses the huge merits of SG technology and how it would assist in curbing the scourge of electricity theft in South Africa.
... With limited man power in hand it is difficult to detect theft cases in all areas. Employee Theft: In some cases DU employee indulge in malpractices like recording lesser consumption than actual metered consumption or simply not providing meter to the consumer [6]. This affects revenue generated by the utility. ...
The distribution of electricity becomes inefficient when rural areas are sparse or remote. Un-metered/illegal connections, poor bill collection efficiencies are the common practices found in villages, especially remote areas. Consumers also remain unsatisfied with service provided by Distribution Utility due to long hours of supply cut, unscheduled outages, low voltage levels, and wrong meter readings. To address these problems at the last mile and to improve the performance of the electricity distribution sector, Electricity Act 2003 has introduced Distribution Franchisees (DF). DFs are contracted to manage the last mile functions of the electricity sector for a specified area. This paper presents a study of an initiative by a DF in the state of Odisha, which gave contracts to 142 women SHGs to undertake metering, billing, and revenue collection, leading to a reduction in electricity losses by 30%. The objective of the study is to gain a deeper understanding of different aspects of the role played by SHGs in handing these last-mile governance functions. The study relies on semi-structured and unstructured interviews with different stakeholders. The study would help understand the feasibility and relevance of SHGs in addressing the governance crisis in the last-mile of the electricity sector.
... The consumers take advantage of the deficiencies in regulatory regimes and poor governance to avoid electricity charges. Sometimes electricity theft occurs without connivance of the utility employees while in most of the instances, utility employees facilitate electricity theft signifying the role of corruption (Jamil and Ahmad, 2014;Sharma et al., 2016). ...
The study analyzed electricity theft through a three layered principal-agent-client model. The factors that entrench corruption and theft are its beneficial features of lowering the cost of electricity for the consumers and generating private illegal incomes for the corruptible employees. We show that an individual steals electricity only if the subjective pecuniary gains are higher than the associated costs e.g. fine imposed in case of detection or dismissal from job. The study finds that efficiency wages along with higher deterrence and active consumer involvement in reporting the crime can help in combating corruption and pilferage in electricity sector.
... When defined as social problems, spaces are created for social innovations and participatory methods [6]. Evidence suggests that technical interventions alone are insufficient [10,11] to address the social, financial and governmental purposes. In the case of sub-Saharan Africa, Welsch et al. [12] call for a focus on smart planning, smart people, just access and smart and just financing. ...
How smart grids are understood and defined will influence the kinds of smart grids users will encounter in the future and their potential impacts. Practitioners and policymakers largely perceive smart grids as technological interventions. However, a number of social, financial and governmental interventions can also make grids smart, i.e., more efficient, more responsive, more inclusive and more robust. Drawing on qualitative research done using elite interviews, site visits and document analysis of eight micro-grids in India, this paper provides concrete examples of what could be understood as social, financial and governmental smartness, and in doing so, broadens the knowledge on smart grids beyond the technical understanding.
This paper argues that social, financial and governmental interventions are central to ‘smartness’, and that multifaceted and relational sociotechnical approaches will build cheaper, just, more democratic and sustainable smart grids. The paper observes that smart grids are not conceived as smart grids but rather develop incrementally. An incremental approach, rather than pushing a premeditated set of ideas and technologies, reduces adoption of non-contextual interventions as well as unnecessary investments in new technologies. The paper recommends that policymakers and practitioners should understand and develop smart grids as sociotechnical and incremental grids.
... Rural financial institutions and the private sector have a role both in lending and information dissemination to support the creation and growth of rural solar market [89]. Most importantly, these institutions must engage more deeply with communities to bridge the existing gaps related to financing, information and societal issues [90]. In particular, solar entrepreneurs should engage rural consumers to assist them to opt for a suitable technology based on their needs, budgets and locations, while addressing the problem of their unrealistic expectations from solar PV. ...
A transformation in energy structures and governance models are required to meet the needs of communities living in rural and remote areas and particularly for those subject to energy and economic poverty. New models must be reflexive to global climate concerns, align with social, economic and environmental agendas of national, state, and local governments, and be compatible with embedded energy infrastructure. Decentralised solar solutions are a resilient technology which can support energy transformation to spatially, economically and socially disadvantaged communities yet the deployment of this technology is hamstrung by path dependencies including policy frameworks, business models and infrastructure. In this study, the multi-level perspective has been used to examine energy transformation within rural and remote communities in India through interviews with regime and niche level actors. We identify various barriers impeding successful deployment of decentralised solar PV including a disconnect between policy makers and implementers, poor coordination within and between actors, and limited institutional focus and competence. To support a successful transition to off-grid solar based regimes for rural and remote communities, participants suggested strong political determination, setting enabling policy frameworks, and implementing a collaborative ecosystem with businesses, system suppliers, financial intermediaries, distribution companies, civil society and end users.
... Such mistakes are generally not illegal and can always happen. However, in some cases, bribes made by customers may result in incomplete invoicing by distribution company staff [11]. The other example is the irregularities made during payment and changing the bills of clients. ...
... This paper proposes various ways to overcome electricity theft that are by applying technical solutions such as tamper-proof meters, and managerial strategies such as strict inspection and monitoring. T. Sharma et al. [10] propose the value chain of the Indian power sector giving special attention on its distribution segment. The key idea of AT&C losses was introduced in 2001-02 in India to compensate the gap between billing and collection. ...
... They have empirically evaluatedthat lesser poverty, lesser corruption, higher literacy and higher income, are accounted for lower distribution losses. Sharma et al. (2016) have emphasized on the need of understanding the interaction of social factors such as employee morale, motivation, capacity, organizational culture and processes, and technical factors namely improved transformers, smart cards, high voltage distribution system etc. Distribution losses cause precarious situation of utilities and several adverse consequences like power disruptions to legitimate consumers, overloading/short circuiting of power distribution systems, poor quality of supply, and higher electricity price ( Lewis, 2015).Many countries have progressed further in direction of zero distribution losses by bringing paradigm shift in billing systems. ...
This paper addresses the scenario of distribution losses in the Sonepat district of Haryana, India for last three financial years. The utilities in the State of Haryana are facing severe financial distresses and the prominent reason is the distribution losses. These distribution losses are mainly due to the gap between billed units and supplied unitsdue to billing irregularities on account of system inefficiency, tampering with the energy meters, electricity theft etc.Distribution losses in the State also get affected by the socioeconomic factors like literacy, income, urbanization etc. The State of Haryana has 65.
... The authors have discussed various financial impacts of electricity theft like need to charge more from consumers due to less income from the revenue collected from consumers.Additionally, they have proposeddifferent ways to overcome electricity theft, for instance, technical solutions likeproperly sealed meters, and some managerial strategies also like stringent inspection and vigilance rules. T. Sharma et al. [14] illustrate the value chain of the Indian power sector having focus on its distribution segment. They have pondered over four types of theft in all power systems, namely, deliberate deception by consumers, stealing electricity, billing irregularities, V. Ranganathan [15] proposes the study to reduce transmission and distribution losses. ...
Electricity theft has become the main factor responsible for distribution losses in Indian States. It has become troublesome for both the consumers as well as for the utilities which supply electricity to the consumers. Due to the electricity theft, utilities are suffering from huge losses especially in the rural areas. This paper puts emphasis on the major consequences that the common people & the utility are facing due to such thefts. Various socioeconomic factors have been taken into account as well. In the state of Haryana, Gurugram has been reported to have very high electricity theft cases. Sohna, a tehsil of Gurugram district, has been considered for the case study of distribution losses. Three types of feeder lines have been analyzed in this work, i.e., urban, rural & industrial. Secondary data of distribution losses clearly shows that losses in the rural areas have been tremendously high for the period 2015-2017. Electricity theft has become a major issue of concern and its rate needs to be lowered so as to bring down the high losses that the utility is suffering financially.
... All the consumers need to be educated about the cons of installing smart meters in a neighborhood like operation of harmonic generator and possible damage to their equipment. Sharma, T. et al. (2016) propose the value chain of the Indian power sector giving special attention on its distribution segment. The major threat to the Indian power sector in our society is electricity theft that attributes to large portion of commercial losses. ...
Menace of electricity theft has plagued the power sector. Electricity theft is the primary facet of the non-technical losses. On account of its adverse impacts on the utility finances, it has become a major concern drawing the attention of many analysts. Numerous significant works have been accomplished in the field of losses analysis. Consequently, author in this work has briefed all the major contributions in the concerned field focusing over social and economic aspects of electricity theft and the possible mitigation strategies. The electricity theft originates from the attitude of electricity customers and the utility employees. Therefore, bringing the change in the attitude of both customers and employees has become incumbent to put check on electricity theft and make the recovery of utility possible from substantial non-technical losses. Hence, author has also posited some suggestive measures for putting the brakes on electricity theft.
... Additionally, they have proposed different ways to overcome electricity theft, for instance, technical solutions such as tamper-proof meters, and managerial strategies such as strict inspection and monitoring. Sharma et al. (2016) illustrate the value chain of the Indian power sector having focus on its distribution segment. They have pondered over four types of theft in all power systems, namely, deliberate deception by consumers, stealing electricity, billing irregularities, unpaid bills etc. ...
Power theft, a primary cause of distribution losses, has become a major issue. It has become troublesome for both the consumers as well as for the utilities that have to supply electricity to these consumers. Due to these thefts, utilities are suffering from huge losses especially in the rural areas. This paper gives emphasis on the major consequences that the common people & the utility are facing
due to such thefts. Various socio-economic factors have been taken into account as well. In the state of Haryana, Bhiwani has been reported to maximum such cases. Charkhi-Dadri a district of Bhiwani has been considered for the case study of losses. Three types of feeder lines have been analyzed in this work, i.e., urban, rural & industrial. The current pattern of losses has also been taken up for the
consideration. The data clearly shows that the losses in the rural areas have been tremendously high for the period 2015-2017. The suggestions for prevention of power theft have also been discussed in
this work. Power theft has become a major issue of concern and its rate needs to be lowered so as to bring down the hefty amount of losses which the utility is suffering financially.
Electricity theft has become a matter of trouble for both customers and electricity distribution companies. Due to electricity theft, distribution companies are facing lots of T&D losses every year. Despite several technical measures adopted, there is no significant reduction in losses due to electricity theft. This fact diverts the attention towards non-technical measures which include formulation and enforcement of stringent rules and regulations. As the policies need to be enforced on electricity customers, policies should be designed in accordance with the customers’ attitude towards electricity theft. Therefore, this work has analyzed their attitude towards the role of certain socio-economic factors which strongly impact the practice of electricity theft. This study has surveyed the electricity customers of two distribution companies, UHBVN and DHBVN in State Haryana. The findings of this work may help the electricity distribution companies to chalk out better and more effective plans to put check upon the practice of electricity theft in the society.
Non-technical loss (NTL) is one of the problems in distribution utilities and electric cooperatives, comprising electricity theft, malfunction or broken meters, and arranging false meter readings. This paper assessed the level of electricity fraud activity in the Isabela Electric II Cooperative (ISELCO II) system and helped identify and detect non-technical loss activities and abnormalities. Findings of the study revealed that the forms and natures of practice of non-technical loss (NTL) in ISELCO II are jumpering, direct tapping, tampered meter, broken glass, defective meter, tilting of meter, and separate grounding. The study utilized mixed-method research, and an interview method was conducted to support the quantitative data gathered from the cooperative. The findings further revealed that the two primary sources of NTL are the kWhr meter and the billing procedure. The Pearson Product Moment Correlation was used to test the relationship between the cooperative's reported non-technical losses (NTL) and the measurement of the monthly power rate per kilowatt hour (kWh) consumed by the customers. The results showed that as non-technical losses increase, the monthly power rate per kWh increases. Hence, there is a direct effect of NTL on the monthly bill the consumer pays off. Likewise, the t-test revealed that the non-technical loss and technical loss have no significant relationship with each other despite their nature. The increasing number of people involved in electricity theft has a direct impact on consumers and the system of ISELCO II.
In many developing countries, non-technical losses and electricity stealing constitute serious problems for electric power companies. This paper demonstrates a practical scheme for determining and reducing non-technical losses in the power network by detecting the suspected area where incorrect meter readings and electricity theft occur. The method is cast as a mathematical optimization problem to be resolved using the dispersive flies algorithm to identify and minimize measurement errors while lowering electricity losses and costs. The findings demonstrate the approach’s effectiveness and its applicability in real-world scenarios.
For accommodating rapidly increasing power demands, power systems are transitioning from analog systems to systems with increasing digital control and communications. Although this modernization brings many far-reaching benefits, the hardware and software newly incorporated into the power systems also incur many vulnerabilities. By taking advantage of these vulnerabilities, adversaries can launch various cyber/physical attacks to tamper with electricity meter readings, i.e., to steal electricity. It is reported that total worldwide annual economic losses caused by electricity theft reached up to almost one hundred billion dollars in recent years. With methods to tamper with meter readings becoming more versatile, secret, and flexible, electricity theft tends to get even more serious in modernized power systems. For preventing adversaries from stealing electricity, researchers have done a lot of works. Although some related surveys on these works exist, they are not updated or just discuss electricity theft in a specific region. This survey aims to gain a comprehensive and in-depth understanding of the electricity theft issue. After investigating how adversaries tamper with meter readings, we systematically survey all existing detection methods up to date, which is classified into machine learning- and measurement mismatch-based methods. Adverse effects and political and socioeconomic factors of electricity theft are also provided. This survey can help relevant researchers to shape future research directions, especially in the area of developing new effective electricity theft detection methods.
To address issues of non-payment, high costs, and theft, paying a fixed fee for electricity is common among many developing countries. We use a conjoint experiment to study electricity billing preferences among urban and rural communities in Uttar Pradesh, India. We find that 59.5% of respondents (95% CI: 58.2%–60.9%) prefer consumption-based tariffs as opposed to fixed fee ones, favoring lower base charges among a number of factors. We additionally use Bayesian Additive Regression Trees to test for heterogeneous treatment effects. Respondents with more appliances, using more hours of electricity, and who live in rural areas with meters prefer consumption-based plans with lower base rates. Our results suggest that policy reforms should move beyond fixed rate schemes especially if respondents would accept higher unit tariffs with improved service.
The revolution of power grids from traditional grids to Smart Grids (SGs) requires effective Demand Side Management (DSM) and reliable Renewable Energy Sources (RESs) incorporation in order to maintain demand, supply balance and optimize energy in an environment friendly manner. Data analytics provide solutions to the emerging challenges of power systems, such as DSM, environmental pollution (due to carbon emission), fossil fuel dependency mitigation, RESs incorporation, cost curtailment, grid’s stability and security. To efficiently manage electricity and maximize the profit of power utilities several tasks are focused in this thesis, i.e., prediction of electricity load to avoid demand and generation mismatch, wind power forecasting to satisfy energy demand effectively, electricity price forecasting for regulating market operations, carbon emissions forecasting for reducing payment of carbon tax, Electricity Theft Detection (ETD) for recovering power utilities’ revenue loss caused by electricity theft. In addition to that, a wind power forecast based DSM scheme is proposed. Furthermore, impact of RESs integration level on carbon emissions, electricity price and consumption cost is quantified. Both forecasting and classification techniques are utilized for efficient energy management. Forecasting of electricity load, price, wind power and carbon emissions is performed, whereas, classification of fair and fraudulent electricity consumers is performed. To balance electricity demand and supply, electricity load forecasting is required. Three models are proposed for this purpose, i.e., Deep Long Short-Term Memory (DLSTM), Efficient Sparse Autoencoder Nonlinear Autoregressive eXogenous network (ESAENARX) and Differential Evolution Recurrent Extreme Learning Machine (DE-RELM). DLSTM utilizes univariate data and gives single result, whereas, ESAENARX and DE-RELM model multivariate data and predict electricity load and price simultaneously. Due to adaptive and automatic feature learning mechanism, DLSTM achieves accurate results for separate forecasting of electricity load and price. ESAENARX and DE-RELM models are enhanced by newly proposed efficient feature extractor and model’s parameter tuning, respectively. Real-world datasets of ISO-NE, PJM, NYISO are used for load and price forecasting. The purpose of regulating the electricity market operations is achieved by forecasting of electricity load, price, wind power and carbon emissions. Wind power generation is predicted by an efficient model named Efficient Deep Convolution Neural Network (EDCNN). Moreover, a DSM strategy is also proposed based on predicted wind power generation. Power utilities have to pay carbon emissions tax imposed by government. To pay less carbon emissions tax, carbon emissions prediction is required, which helps in encouraging electricity consumers to shift their consumption load to low carbon price time periods of the day. For accomplishing the carbon emissions forecasting task, an efficient model named as Improved Particle Swarm Optimization based Deep Neural Network (IPSO DNN) is proposed. This model is improved by tunning the parameters of DNN by newly proposed improved optimization technique named as IPSO. ISO-NE dataset is used for wind power and carbon emissions forecasting. To reduce the financial loss of power utilities ETD is very important. For this purpose four models are proposed, named as, Differential Evolution Random Under Sampling Boosting (DE-RUSBoost), Jaya-RUSBoost, RUS Ensemble CNN (RUSE-CNN) and anomaly detection based ETD. In DE-RUSBoost and Jaya-RUSBoost, the parameters of RUSBoost classifier are tunned by DE and Jaya optimization techniques, respectively. In RUSE-CNN, RUS data balancing technique is applied along with ensemble CNN to improve ETD performance. DE-RUSBoost, Jaya-RUSBoost and RUSE-CNN are supervised model that work on labeled electricity theft data. Whereas, anomaly detection based ETD model is capable of identifying electricity theft from unlabeled electricity consumption data. Real-world datasets of SGCC, UMass, PRECON, CER, EnerNOC and LCL are used for ETD. Simulation results show that all the proposed models perform significantly better on real-world dataset as compared to their state-of-the-art counterpart models. The improved feature engineering and model hyper-parameter tuning enhance the performance of the proposed models in terms of prediction and classification results.
As household electrification rates continue to increase globally, the focus in energy access planning is increasingly shifting towards quality of service. To inform this planning, we explore changes in household electricity and people's use and satisfaction with their service over time in rural India. Fielded in 2015, the ACCESS survey collected data on energy access from more than 8,500 households living across six Indian states. In 2018, the same households were re-surveyed. Using this longitudinal dataset, we sketch the changes in electricity access that took place during these three years. We find that access and the quality of supply have both improved substantially, with a 17 percentage points increase in electrification rates (95% CI: [15,19]). However, a large minority (about one fifth) remains unsatisfied with its electricity access. People's satisfaction levels were more sensitive to the quality of supply in 2018 compared to 2015. We propose that this change is a result of evolving expectations of electricity services that are offered. As households climb electricity access tiers and acquire more and larger electric appliances (such as fans or TVs), their demands increasingly shift from focusing on the extensive margin of supply to its intensive margin.
The revolution of power grids from traditional grids to Smart Grids (SGs) requires effective
Demand Side Management (DSM) and reliable Renewable Energy Sources (RESs) incorporation
in order to maintain demand, supply balance and optimize energy in an environment
friendly manner. Data analytics provide solutions to the emerging challenges of power systems,
such as DSM, environmental pollution (due to carbon emission), fossil fuel dependency
mitigation, RESs incorporation, cost curtailment, grid’s stability and security. To efficiently
manage electricity and maximize the profit of power utilities several tasks are focused in
this thesis, i.e., prediction of electricity load to avoid demand and generation mismatch,
wind power forecasting to satisfy energy demand effectively, electricity price forecasting for
regulating market operations, carbon emissions forecasting for reducing payment of carbon
tax, Electricity Theft Detection (ETD) for recovering power utilities’ revenue loss caused by
electricity theft. In addition to that, a wind power forecast based DSM scheme is proposed.
Furthermore, impact of RESs integration level on carbon emissions, electricity price and
consumption cost is quantified.
Both forecasting and classification techniques are utilized for efficient energy management.
Forecasting of electricity load, price, wind power and carbon emissions is performed, whereas,
classification of fair and fraudulent electricity consumers is performed. To balance electricity
demand and supply, electricity load forecasting is required. Three models are proposed for
this purpose, i.e., Deep Long Short-Term Memory (DLSTM), Efficient Sparse Autoencoder
Nonlinear Autoregressive eXogenous network (ESAENARX) and Differential Evolution
Recurrent Extreme Learning Machine (DE-RELM). DLSTM utilizes univariate data and
gives single result, whereas, ESAENARX and DE-RELM model multivariate data and predict
electricity load and price simultaneously. Due to adaptive and automatic feature learning
mechanism, DLSTM achieves accurate results for separate forecasting of electricity load and
price. ESAENARX and DE-RELM models are enhanced by newly proposed efficient feature
extractor and model’s parameter tuning, respectively. Real-world datasets of ISO-NE, PJM,
NYISO are used for load and price forecasting. The purpose of regulating the electricity
market operations is achieved by forecasting of electricity load, price, wind power and carbon
emissions. Wind power generation is predicted by an efficient model named Efficient Deep
Convolution Neural Network (EDCNN). Moreover, a DSM strategy is also proposed based on
predicted wind power generation. Power utilities have to pay carbon emissions tax imposed
by government. To pay less carbon emissions tax, carbon emissions prediction is required,
which helps in encouraging electricity consumers to shift their consumption load to low
carbon price time periods of the day. For accomplishing the carbon emissions forecasting
task, an efficient model named as Improved Particle Swarm Optimization based Deep Neural
Network (IPSO DNN) is proposed. This model is improved by tunning the parameters of
DNN by newly proposed improved optimization technique named as IPSO. ISO-NE dataset
is used for wind power and carbon emissions forecasting. To reduce the financial loss of
power utilities ETD is very important. For this purpose four models are proposed, named as,
Differential Evolution Random Under Sampling Boosting (DE-RUSBoost), Jaya-RUSBoost,
RUS Ensemble CNN (RUSE-CNN) and anomly detection based ETD. In DE-RUSBoost
and Jaya-RUSBoost, the parameters of RUSBoost classifier are tunned by DE and Jaya
optimization techniques, respectively. In RUSE-CNN, RUS data balancing technique is
applied along with ensemble CNN to improve ETD performance. DE-RUSBoost, Jaya-
RUSBoost and RUSE-CNN are supervised model that work on labeled electricity theft data.
Whereas, anomaly detection based ETD model is capable of identifying electricity theft from
unlabeled electricity consumption data. Real-world datasets of SGCC, UMass*, PRECON,
CER, EnerNOC and LCL are used for ETD. Simulation results show that all the proposed
models perform significantly better on real-world dataset as compared to their state-of-the-art
counterpart models. The improved feature engineering and model hyper-parameter tuning
enhance the performance of the proposed models in terms of prediction and classification
results.
The high incidence of electricity theft, meter tampering, meter bypassing, reading errors, and defective and aged meters, among others, increases utility losses, especially non-technical losses (NTL). A utility in Ghana piloted a non-technical loss reduction program in 2019 to replace postpaid meters with anti-tamper, anti-fraud, and anti-theft smart prepaid meters. By using customer-level residential billing panel data from 2018 to 2019 obtained from the utility, we assess the effectiveness of this program using the difference-in-differences fixed-effect approach. On average, the results indicated that the reported amount of customers’ monthly electricity consumption increases by 13.2% when any tampered postpaid meter is replaced with a smart prepaid meter, indicating the NTLs by customers. We further employed quantile difference-in-differences regression and observed that reported energy consumption has increased for all households except those at the lower quantile (25th quantile). We conclude that smart prepaid metering could be a remedy to reduce NTLs for the electricity distribution sector in areas where electricity theft is rampant.
This study aimed to provide an overview of the research on non-technical losses, presenting a bibliometric analysis of 392 studies in conference proceedings. The research was conducted using Scopus database from 1987 to 2019. The results showed an increasing trend in the number of publications on this subject, demonstrating the worldwide interest of the scientific community in non-technical losses. In addition, it was found that the predominant language in the writing of publications was English, the countries that most published articles in the area were India, Brazil and USA and the cumulative number of articles tends to reach 600 at the end of 2021. Developing countries are encouraging research in the area to reduce the damage caused by non-technical losses in electricity distribution, contributing to society as a large part of these costs are passed on to the consumer. The main contribution of this article is to present an overview of the research on non-technical losses in conference proceedings, indicating the main trends through the measured indicators.
This book is a collection of best selected high-quality research papers presented at the International Conference on Advances in Energy Management (ICAEM 2019) organized by the Department of Electrical Engineering, Jodhpur Institute of Engineering & Technology (JIET), Jodhpur, India, during 20–21 December 2019. The book discusses intelligent energy management technologies which are cost effective compared to the high cost of fossil fuels. This book also explains why these systems have beneficial impact on environmental, economic and political issues of the world. The book is immensely useful for research scholars, academicians, R&D institutions, practicing engineers and managers from industry.
In many developing countries, theft remains a significant obstacle to ensuring proper public service provision and access. We argue that social acceptability of theft constitutes an understudied barrier to curbing power theft. Using a conjoint experiment, we study perceptions of theft in the form of using illegal wires, katiya, among rural and urban households in Uttar Pradesh, India (n = 1800). Social acceptability of theft is influenced by the income and electricity supply quality contexts of offenders. For a 1000-rupee (approx. 15 USD) income difference between hypothetical vignette agents, the odds of choosing a higher acceptability rating for an offender increases by 11%. One fewer hour of electricity supply received by the vignette person would increase the acceptability of their theft activity by 4%. The majority of respondents chose a warning as the appropriate punishment severity; income and supply quality distinguishes the odds of choosing higher punishment categories. While there exists a sense of social reprimand for stealing power, desired punishment is nuanced and context-dependent.
The process of mitigating non-technical losses (NTL) in power distribution utilities is done in two stages. The first determines which distribution transformers have high NTL values. The second attempts to locate fraudulent consumers, powered by these transformers. This paper proposes a new methodology to improve the calculation of technical losses (TL), leading to a better estimation of the NTL, using temperature sensors. It is also presented a new process to identify possible energy theft locations using voltage drop differences. The identification of possible energy pilfering spots is done with the aid of the measurement of technical losses obtained in the first stretches of the low voltage network, near the transformer, where the TL is more significant. A Backward/Forward Sweep algorithm using the power summation technique is used to calculate the voltage drops in two situations: with power data read only from the smart meters and power data including the TL readings. An analysis of the differences in voltage drop at each point between the two situations makes it possible to locate the probable energy thief.
Electricity theft is a major concern for power distribution utilities. The increase in non-technical losses give rise to imbalance between electricity supply and demand resulting into overloading of existing distribution network, reduction in reliability and stability of supply and additional tariff posed on genuine consumers. Although, the smart metering systems has resolved meter related power theft problems, however, direct tapping on distribution line remains perpetual issue which should be stringently annihilated. Thus, this paper presents real-time electricity theft detection using energy consumption data of all legal consumers and outgoing distribution transformer energy meter data. In order to prevent the hook-line activity, a fuzzy inference based scheme is implemented in LabVIEW to operate electricity theft prevention system (ETPS). The ETPS develops unsuitable voltage across illegal consumer and hinders normal operation of their appliances. The consumer care unit (CCU) interlocked with ETPS maintains normal supply voltage at legal consumers end. The suitability, flexibility in operation and effectiveness of the proposed ETPS and CCU based theft prevention scheme is experimentally and practically demonstrated as case study under various voltage regulation and energy loss scenarios.
Rural electrification has advanced rapidly in many developing countries. Under conditions of poverty and weak infrastructure, however, households face a risk of backsliding. We use two rounds from the ACCESS survey of rural households in six northern Indian states to explore factors that drive losses in household electricity access. About 7% of households with electricity in 2015 lost it by 2018. We identify household wealth and off-grid access as major drivers of lost energy access. A standard deviation's increase in a household's wealth index reduces the likelihood of disconnection by 1.5 percentage points. Off-grid households are 8 percentage points more likely to lose access than grid-connected households. These findings underscore the importance of defending realized gains in countries where household electrification is driven by policy while rural poverty remains prevalent.
More than a fifth of the total electricity production in India is lost due to theft. Previous research indicates that technical solutions, on their own, are not sufficient to curb electricity theft and that social and economic factors should additionally be taken into account. Using disaggregated district-level data from Uttar Pradesh, the largest state of India, over seven years (2006–2012), this study examines the socio-economic determinants of electricity theft behaviors. The study deploys an array of advanced machine-learning regression models to a) quantify the predictive power of socio-economic indicators in explaining the electricity theft behaviors at the district level, and, b) capture and illustrate non-linear relationships between relevant socio-economic indicators and electricity theft. In addition, the study explores the temporal-spatial correlation of electricity theft across districts and over the years. The results suggest that in using a random forest regression model in particular, 87% of the variability of loss rate could be explained by the underlying socio-economic attributes considered in this study. Specifically, crime rate, literacy rate, income, urbanization, and the average electricity consumption per capita are shown to be statistically significant. The results also suggest strong temporal-spatial correlations of electricity theft across some districts, when the average correlation was 0.39 to neighboring districts and only 0.14 to distant districts.
Many households indulge in different forms of electricity theft and illegal tampering of electric metering devices. These lead to distribution system faults and overload as well as loss of revenue by the distribution companies,this paper envisages the utilization of the global system for mobile communication (GSM) into the prepaid energy meter for increased generation of revenue in developing countries like Nigeria. The proposed meter is set to carry a unique identification number such as the consumer’s phone number which may be encrypted into the memory of the microcontroller. Electricity theft is being detected as the GSM module sends message to the distribution company. Revenue generated can be increased through the use of the proposed meter as unaccountability by utility workers and billing irregularities are eliminated. The results obtained from the simulation shows that immediately an illegal load is connected to the utility system either within the residential meter jurisdiction or otherwise stated, the GSM module alerts the utility company no
matter how small the illegal load is
Research dealing with various aspects of* the theory of planned behavior (Ajzen, 1985,
1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is
found to be well supported by empirical evidence. Intentions to perform behaviors of different
kinds can be predicted with high accuracy from attitudes toward the behavior, subjective
norms, and perceived behavioral control; and these intentions, together with perceptions of
behavioral control, account for considerable variance in actual behavior. Attitudes, subjective
norms, and perceived behavioral control are shown to be related to appropriate sets of salient
behavioral, normative, and control beliefs about the behavior, but the exact nature of these
relations is still uncertain. Expectancy value formulations are found to be only partly
successful in dealing with these relations. Optimal rescaling of expectancy and value
measures is offered as a means of dealing with measurement limitations. Finally, inclusion of
past behavior in the prediction equation is shown to provide a means of testing the theory*s
sufficiency, another issue that remains unresolved. The limited available evidence concerning
this question shows that the theory is predicting behavior quite well in comparison to the
ceiling imposed by behavioral reliability.
While consumer utility subsidies are widespread in both the water and electricity sectors, their effectiveness in reaching and distributing resources to the poor is the subject of much debate. Water, Electricity, and the Poor brings together empirical evidence on subsidy performance across a wide range of countries. It documents the prevalence of consumer subsidies, provides a typology of the many variants found in the developing world, and presents a number of indicators useful in assessing the degree to which such subsidies benefit the poor, focusing on three key concepts: beneficiary incidence, benefit incidence, and materiality. The findings on subsidy performance will be useful to policy makers, utility regulators, and sector practitioners who are contemplating introducing, eliminating, or modifying utility subsidies, and to those who view consumer utility subsidies as a social protection instrument.
Fraud in corporations is a topic that receives significant and growing attention from regulators, auditors, and the public. Increasingly external auditors are being asked to play an important role in helping organizations prevent and detect fraud. Detecting fraud is not an easy task and requires thorough knowledge about the nature of fraud, how it can be committed and concealed. This paper aims at broadening external auditors’ knowledge about fraud and why it occurs. It explains Cressey’s fraud theory and shows its significance, presents the other fraud models and relates them to Cressey’s model, and proposes a new fraud triangle model that external auditors could consider when assessing the risk of fraud.
Purpose
The purpose of this article is to expand and extend previous work on the role of organizations in influencing deviant or dysfunctional behavior in those organizations.
Design/methodology/approach
Conclusions from previous work on the role of individuals and organizations in influencing dysfunctional behavior is used to lead to a discussion of the interactions between those two especially through organizational culture and leadership.
Findings
A model is developed that more carefully identifies how all of these factors come together, resulting in no, little, some, or a lot of dysfunctional behavior.
Research limitations/implications
The model developed here can be employed to improve understanding of the role of organization culture and leadership in motivating dysfunctional work behaviors. Both the individual and the organization constructs utilized in the framework need more complete conceptual development. In each instance, a more complex and integrative analysis of diverse literatures needs to be undertaken. Clear messages regarding individual tendencies toward violent behaviors are embedded in the literatures from such diverse areas as psychology, psychiatry, criminal justice, medicine, sociology, organizational behavior, biology, social psychology, and anthropology. A comprehensive review and synthesis could theoretically yield far more insights than currently exist.
Practical implications
The proposed manifestations of dysfunctional behavior are most likely to occur as the result of the interactive relationship between an individual displaying a relatively high predisposition for violent behavior and an organization with a relatively high propensity to elicit violence. Clearly, a better understanding of the characteristics of such an organization would assist practicing managers in reducing the likelihood of occurrence of dysfunctional behavior.
Originality/value
This paper fills a gap in the literature about the role of organizations in influencing dysfunctional behavior by delineating more fully the role of organizational culture and leadership.
Based on evidence from press articles covering 39 corporate fraud cases that went public during the period 1992–2005, the objective of this article is to examine the role of managers’ behavior in the commitment of the fraud. This study integrates the fraud triangle (FT) and the theory of planned behavior (TPB) to gain a better understanding of fraud cases. The results of the analysis suggest that personality traits appear to be a major fraud-risk factor. The analysis was further validated through a quantitative analysis of keywords which confirmed that keywords associated with the attitudes/rationalizations component of the integrated theory were predominately found in fraud firms as opposed to a sample of control firms. The results of the study suggest that auditors should evaluate the ethics of management through the components of the TPB: the assessment of attitude, subjective norms, perceived behavioral control and moral obligation. Therefore, it is potentially important that the professional standards that are related to fraud detection strengthen the emphasis on managers’ behavior that may be associated with unethical behavior.
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First published in 1980, Street-Level Bureaucracy received critical acclaim for its insightful study of how public service workers, in effect, function as policy decision makers, as they wield their considerable discretion in the day-to-day implementation of public programs. Three decades later, the need to bolster the availability and effectiveness of healthcare, social services, education, and law enforcement is as urgent as ever. In this thirtieth anniversary expanded edition, Michael Lipsky revisits the territory he mapped out in the first edition to reflect on significant policy developments over the last several decades. Despite the difficulties of managing these front-line workers, he shows how street-level bureaucracies can be and regularly are brought into line with public purposes. Street-level bureaucrats-from teachers and police officers to social workers and legal-aid lawyers-interact directly with the public and so represent the frontlines of government policy. In Street-Level Bureaucracy, Lipsky argues that these relatively low-level public service employees labor under huge caseloads, ambiguous agency goals, and inadequate resources. When combined with substantial discretionary authority and the requirement to interpret policy on a case-by-case basis, the difference between government policy in theory and policy in practice can be substantial and troubling. The core dilemma of street-level bureaucrats is that they are supposed to help people or make decisions about them on the basis of individual cases, yet the structure of their jobs makes this impossible. Instead, they are forced to adopt practices such as rationing resources, screening applicants for qualities their organizations favor, "rubberstamping" applications, and routinizing client interactions by imposing the uniformities of mass processing on situations requiring human responsiveness. Occasionally, such strategies work out in favor of the client. But the cumulative effect of street-level decisions made on the basis of routines and simplifications about clients can reroute the intended direction of policy, undermining citizens' expectations of evenhanded treatment. This seminal, award-winning study tells a cautionary tale of how decisions made by overburdened workers translate into ad-hoc policy adaptations that impact peoples' lives and life opportunities. Lipsky maintains, however, that these problems are not insurmountable. Over the years, public managers have developed ways to bring street-level performance more in line with agency goals. This expanded edition of Street-Level Bureaucracy underscores that, despite its challenging nature, street-level work can be made to conform to higher expectations of public service.
This cross-level field study, involving 187 employees from 35 groups in 20 organizations, examined how individuals' antisocial behaviors at work are shaped by the antisocial behavior of their coworkers. We found a positive relationship between the level of antisocial behavior exhibited by an individual and that exhibited by his or her coworkers. We also found that a number of factors moderated this relationship. Finally, we found that dissatisfaction with coworkers was higher when individuals engaged in less antisocial behavior than their coworkers.
Five studies examined the relations between attitude importance and 3 of its hypothesized determinants: self-interest, social identification with reference groups or reference individuals, and cherished values. Verbal protocols, multivariate analysis of survey data, and laboratory experimentation revealed that (1) people's theories of the causes of attitude importance pointed to all 3 hypothesized predictors, (2) the 3 predictors each had significant, unique statistical associations with importance, and (3) a manipulation of self-interest yielded a corresponding change in importance. These results help clarify the nature and origins of attitude importance, challenge the widely believed claim that self-interest has little or no impact on political cognition, and identify new likely consequences of social identification processes and values.
The central role of corporate leaders in setting the ethical tone for their organization is widely accepted. Four well known former CEOs are profiled to illustrate how their managerial ethical leadership not only influenced their firms but also the practice of business. Insights are drawn from their writings and speeches as well as other sources which examine demonstrated leadership abilities. Their behavior not only provides examples of leadership but also is exemplary from an ethical point of view. The article concludes with five common themes that describe these individuals and the essence of managerial ethical leadership.
In a recent meta-analysis of attitude-behavior research, the authors of this article found a strong overall attitude-behavior relationship (r = .79) when methodological artifacts are eliminated. The trend in A-B research, however, is to conceive of behavioral intentions (BI) as a mediator between attitudes (A) and behaviors (B). In this study, it is hypothesized that (a) A-BI correlation would be higher than A-B correlation, (b) BI-B correlation would be higher than A-B correlation, (c) A-BI correlation would be higher than BI-B correlation, (d) the variation in BI-B correlations would be greater than that of A-BI, and (e) attitudinal relevance would affect the magnitude of the A-BI correlation. A series of meta-analyses, integrating the findings of 92 A-BI correlations (N = 16,785) and 47 B-BI correlations (N = 10,203) that deal with 19 specified categories and a variety of miscellaneous topics was performed. The results were consistent with all five hypotheses. The theoretical and methodological implications are discussed.
This whitepaper will provide with insight information about natural gas industry in India. The reader will be able to understand about market, demand-supply gap, trends and challenges faced by the industry, what would be the industry outlook for next 10 years, new projects. The whitepaper is useful for consultant, policy makers, consumers and non-Oil & Gas professional.Indian Natural Gas Industry is growing at a very fast pace with a current CAGR of 6.7% and is expected to grow at much faster rate in near future to come. The main consumer of natural gas are Power, Fertilizer and City Gas Distribution (CGD), all these sectors are very energy intensive and contribute almost 70% of the total demand. As the demand-supply gap increases, it will be very important to have considerable investment in developing domestic output as well as infrastructure to import Natural Gas in the form of LNG. With slow approval policies by various government agencies, it has become difficult to execute the projects on time. Some of the road locks in executing the projects are.The key sectors contributing the rise in demand are Fertilizer, CGD and Power. Tremendous growth is anticipated in these industries, which would lead to gas shortage. Also, it would be challenging to afford expensive imported RLNG. Due to US shale gas revolution and the more recent methane hydrate, it is anticipated that, the international prices of natural gas might come down. The future of Indian natural gas depends on our focus to solve the existing challenges. As Demand-Supply gaps are widening, India can additionally focus on other unconventional forms of energy like shale gas and gas hydrates.
Evidence is presented that (a) employees in an organization form global beliefs concerning the extent to which the organization values their contributions and cares about their well-being, (b) such perceived organizational support reduces absenteeism, and (c) the relation between perceived organizational support and absenteeism is greater for employees with a strong exchange ideology than those with a weak exchange ideology. These findings support the social exchange view that employees’ commitment to the organization is strongly influenced by their perception of the organization’s commitment to them. Perceived organizational support is assumed to increase the employee’s affective attachment to the organization and his or her expectancy that greater effort toward meeting organizational goals will be rewarded. The extent to which these factors increase work effort would depend on the strength of the employee’s exchange ideology favoring the trade of work effort for material and symbolic benefits.
Self-control affects, among other things, individuals’ performance and criminal or deviant behavior. Herein, the construct of self-control is linked to rather specific criteria in an academic context, as derived from findings in the area of organizational psychology. Specifically, it is assumed that students’ self-control impacts university citizenship behavior positively and counterproductive academic behavior negatively. Two correlative field studies, at which one is predictive, using different questionnaires to assess self-control support both hypotheses.
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In a rare opportunity, the authors gathered data from two matched health care providers managed by an insurance company where auditors had discovered theft by employees in one of the matched organizations. Data were gathered about the organizations' ethical work climates (EWCs). Analysis revealed statistically significant differences in EWCs across the two organizations. As predicted, the organization with the morally preferred EWCs did not have theft. Both macro- and micro-organizational influences are explored to explain these differences, along with implications for practitioners and academic research. This is the first study to suggest that a priori EWCs can be useful in predicting observable behavior.
Although Gottfredson and Hirschi (1987, 199015.
Gottfredson , M. and
T. Hirschi . 1990. A General Theory of Crime . Stanford , CA : Stanford University Press. View all references) maintain that low self-control can account for white-collar/corporate offending, there have been few and inconclusive empirical tests in this area. One area of white-collar crime, in particular, which could benefit from an examination of the role of low self-control in predicting offending, is employee theft. Although employee theft is one of the more costly and pervasive crimes impacting the American economy each year, there has been very little research examining the role of individual characteristics and personality traits in predicting this type of deviant behavior. The current research is a preliminary attempt at integrating the two bodies of literature, employee theft and low self-control.
This paper attempts to integrate etiological research on white-collar crime under the hypothesis that criminal behavior results from the confluence of appropriate motivation and opportunity. The starting point is the interactionist theory of motivation basic to most of the social psychological research on white-collar crime. Interactionist theory helps us understand white-collar crime in terms of the offenders' symbolic construction of their social worlds but ultimately fails to explain its causes. It is argued that the origins of symbolic motivational patterns are to be found in the social structure of industrial capitalism and the "culture of competition" to which it gives rise. But no theory of motivation, however sophisticated, is sufficient to explaint the causes of white-collar crime, and the paper therefore concludes with an analysis of the patterns of opportunities presented to social actors in different structural positions in advanced capitalist nations.
In a field study, we build on previous research examining employee theft, which has focused on the influence of job dissatisfaction and pay inequity (distributive injustice). In a survey of employees at 18 fast food restaurants, where employee theft was a problem, we examine the relationship between employee-observed theft and justice perceptions (distributive, procedural, and interactional justice), employees' job satisfaction, and judgments regarding the deviancy of theft. As expected, perceptions of procedural justice and employees' judgments regarding the deviancy of theft explained a significant amount of variance in employee-observed theft; the other predictor variables did not. Theoretical and practical implications for managing employee theft are discussed.
The present study contrasts a newly developed measure of self-control as outlined in the General Theory of Crime, the Retrospective Behavioral Self-Control scale (RBS), with the most widespread measure of this construct. The RBS is based exclusively on an assessment of prior behavior with possible long-term negative consequences for the actor, whereas the latter scale is an example of attitudinal measures based on a listing of specific personality traits. By means of confirmatory factor analysis, it is demonstrated that the RBS measured the intended general factor of behavior across three samples, whereas the Grasmick et al. scale did not (only administered in one sample). In addition, the nomological net of self-control is explored by relating both instruments to a comprehensive battery of psychological tests and behavioral indicators. The RBS is included as an appendix.
Investigated the relationship between 2 industry characteristics, technology and growth, and organizational culture. This relationship was examined by comparing the cultures of organizations within and across industries. 15 firms representing 4 industries in the service sector completed the Organizational Culture Profile. Results show that stable organizational culture dimensions existed and varied more across industries than within them. Specific cultural values associated with levels of industry technology and growth were innovation, stability, an orientation toward people, and an orientation toward outcomes or results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)