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Insurance Premium Setting Based On Power System Reliability Analysis
... Linnerooth-Bayer et al. 18 examined the risk in emerging regions with previously recorded insurance data collected from developed countries to shed light on the efficiency of insurance for lowering economic insecurity. Zhao et al. 19 examined a power system based on insurance premiums for different users. ...
The terms reliability, warranty and insurance are interwoven in some ways. The warranty of system and insurance coverage offered by the manufacturer or third party reflects its potential reliability. In certain situations, the insurance may expire before the warranty time. To address this issue, the reliability and sensitivity analysis of a single-unit insured system has been carried out. The system may functions in warranty period with or without insurance cover whereas no insurance cover is given during nonwarranty period. If faults are covered under warranty or the insurance terms, the manufacturer or insurance company is liable to pay all the repair/replacement costs; otherwise, the user must pay the entire cost. The reliability metrics of the system and factors impacting system profitability are derived using Markov and regenerative processes. Profit equations and sensitivity functions are established for all stakeholders. The sensitivity function for system availability is also derived for all the possible considered periods. Exponential distribution is used to illustrate the developed model numerically.
In a smart grid power system, reliability performance plays a crucial factor and requires additional focus. Moreover, the integration of Battery Energy Storage (BES) scheme, Solar Photovoltaic (SPV) and wind system in the smart grid system provide significant proficiency and reliability to the utilities. However, the grid coordination with the PV and other resources tends to cause major problems such as power interruption or else power outage. The outage of the power in the grid can cause power loss to the distribution system. Therefore, the novel reliability valuation of smart grid system is developed for exaggeration of the SPV, wind and BES utilities based on the grid incorporation in Saudi Arabia. Furthermore, a novel Hobbled Shepherd Optimization (HSO) for boost converter control and Multi-Objective Based Golden Eagle (MOGE) algorithm for inverter control is proposed. The execution of this work has been done in MATLAB/Simulink. The simulation outcomes show that the projected method has attained the finest Total Harmonic Distortion (THD) and power loss. Also, the optimal reliability improvement has achieved by the projected methods while compared with the conventional methods in terms of Loss of Load Expected (LOLE), Loss of Load Probabilities (LOLP) and Expected Energy Not Supplied (EENS).
Recently risk management has become a standard prerequisite for all financial institutions. Value-at-Risk is the main tool of reporting to the bank regulators the risk that the financial institutions face. As it is essential to estimate it accurately, numerous methods have been proposed in order to minimize the forecast error. This chapter provides a selective survey of the risk management techniques that have been applied and discusses potential improvements in estimating, evaluating and adjusting Value-at-Risk and Expected Shortfall.
Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution systems reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. A transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.
The increasing penetration of intermittent renewables and the accelerated climate change are challenging the power system operation in China, and understanding the cost of reducing power outage durations is essential in supporting the equipment maintenance, infrastructure investments and regulation policies. Therefore, this study first uses production theory combined with a parametric distance function approach to estimate the marginal costs (MCs) of reducing power outage durations by 1 h. Then, we establish a fixed-effects panel data model to investigate the impacts of different environmental factors on the estimated MCs. Finally, the estimated MCs are applied to the evaluations and designs of interruption compensation prices in the demand response mechanism. The significant findings are that: (1) The national MC shows an increasing trend during the period from 2002 to 2017 in China, ranging from 1.27 billion yuan/hour to 11.63 billion yuan/hour. (2) The MCs vary substantially among different provinces, and provinces with better reliability levels will have higher MCs. (3) The current compensations for power outages are only about 6% to 61% of the estimated MCs, indicating that grid companies would like to pay for the compensations rather than to enhance the system reliability from the supply side.
Households’ demand for electricity continues to increase. This trend per se should indicate increased disutility from power outages. Additionally, batteries and other back-up systems have been improved, and the frequency and duration of outages have been reduced in many countries. By comparing the results from two stated preference studies on Swedish households’ willingness to pay (WTP) to avoid power outages in 2004 and 2017, we investigate whether the WTP has changed. The WTP is assessed for power outages of 1- and 4 -h durations, and whether it is planned or unplanned. We find three main differences: (i) the proportion of households stating zero WTP to avoid power outages decreased significantly from 2004 to 2017, meaning that more households are willing to pay to avoid a power outage in 2017 than in 2004; (ii) the overall WTP was considerably higher in 2017 than in 2004, but (iii) the conditional WTP, that is, WTP for those that have a positive WTP for an outage, has decreased. These results have implications for how regulators incentivize and regulate electricity suppliers, because the results suggest that a reliable supply of electricity is of greater importance now than what the literature has suggested.
Due to the electricity market risks and lack of various purchasing options, electricity customers are reluctant to participate in the electricity market. On the other hand, due to the electricity grid conditions and the absence of enough information about customers’ preferences, most utilities do not differentiate electricity services at the customer level. To provide various service options, this paper proposes the utility company provides financial and outage insurance mechanisms (FIM and OIM). In the FIM, electrical energy is sold via the real-time pricing (RTP) method. Each of the electricity customers selects a strike price, as an insurance deductible, based on his/her preferences. When the electricity market price exceeds the deductible, the utility company pays the difference between the deductible and the market price. In the OIM, a customer receives outage reimbursement based on his/her outage value. In this paper, the concept of the utility function is utilized to identify the customer’s and insurer’s behavior against different insurance contracts. Results illustrate the proposed FIM reduces the electricity market fluctuations and the average of the customers’ costs. According to the OIM, the outage is divided differently between the customers based on their outage value.
Energy storage technologies are key to improving grid flexibility in the presence of increasing amounts of intermittent renewable generation. We propose an insurance contract that suitably compensates energy storage systems for providing flexibility. Such a contract provides a wider range of market opportunities for these systems while also incentivizing higher renewable penetration in the grid. We consider a day-ahead market in which generators, including renewables and storage owners, bid to be scheduled for the next operating day. Due to production uncertainty, renewable generators may be unable to meet their day-ahead production schedule, and thus be subject to a penalty. As a hedge against these penalties, we propose an insurance contract between a renewable producer and a storage owner, in which the storage reserves some energy to be used in case of renewable shortfalls. We show that such a contract incentivizes the renewable player to bid higher, thus increasing renewable participation in the electricity mix. It also provides an extra source of revenue for storage owners that may not be profitable with a purely arbitrage-based strategy in the day-ahead market. We validate our analysis through two case studies.
With the increasing application of Information and Communication Technologies (ICTs), cyberattacks have become more prevalent through physical or virtual networks. Various methods have been proposed to model the cybersecurity threats on the Cyber-Physical Systems (CPSs), while limited studies have been focused on the defensive strategies subject to limited security budget. In this paper, the reliability is evaluated in a large-scale power system by allocating the defense resources. Specifically, the optimal mixed strategies are formulated by the Stackelberg Security Game (SSG) to allocate the defense resources on multiple targets subject to cyberattacks. The cyberattacks against the intrusion-tolerant Supervisory Control and Data Acquisition (SCADA) system are mathematically modeled by SemiMarkov Process (SMP) kernel. Specifically, the intrusion
tolerance capability of the SCADA system provides buffered residence time before the substation failure, enhancing the network robustness against cybersecurity threats. Case
studies of the cyberattack scenarios are carried out to demonstrate the intrusion tolerance capability. Depending on the defense resource allocation scheme, the intrusion tolerant SCADA system provides varying degrees of self-healing capability that restores the substation to the good state and prevents the substations from failure. If more defense resources are invested in the substations, the intrusion tolerant capability can be further enhanced for protecting the substations. Finally, the actuarial insurance principle is designed to estimate utilities’ individual premiums considering correlated cybersecurity risks. The proposed insurance premium principle is designed to provide an incentive for investments on enhancing the intrusion tolerance capability, which is verified by the results of the case studies.
Power loss during blackouts shows an increasing complexity with the increase in the size of power grids. Traditional statistical methods based on the assumption of stationarity can lead to inappropriate assessments of blackouts. This study builds on the generalized extreme value (GEV) distribution by introducing time as a covariate to account for possible non-stationarities. The location, scale, and shape parameters of GEV are modeled step-by-step through the one-factor-at-a-time experiment. The results indicate that the GEV model of the annual maximum power loss in China exhibits a significant change of the scale parameter. By contrast, changes in location and shape parameters are not significant. Overall, the power loss during blackouts is tested to change with time, which reflects the sustained increase in the variability of power loss due to the growing size of power grids. The mean tends to be stable and the distribution type remains the same, which can be related to technological advances that improve the reliability of power grids. The non-stationary GEV model with time as a covariate can effectively analyze power loss during blackouts in China. It has the potential to be extended to describe non-stationary high-dimensional characteristics of power grids.
A concept of power distribution reliability insurance, which is an application of insurance theory in the management of power distribution reliability, is proposed. Based on the insurance premium prepaid by the customer, insurance company can master customer's preference extent to power supply reliability and this information, which can offer a good price signal for both power supply reliability management and investment decision of power distribution company, is transmitted to power distribution company. Meanwhile, four possible application modes of reliability insurance are analyzed, calculation models of insurance premium under each application mode are put forward respectively and corresponding calculation examples are given. The results of calculation examples show that through insurance company the reliability insurance finally transfers the risk of outage loss from customer to power distribution company, so the power distribution company is incited to improve its working efficiency.
We report results from a large randomized natural field experiment conducted in southwestern China in the context of insurance for sows. Our study sheds light on two important questions about microinsurance. First, how does access to formal insurance affect farmers' production decisions? Second, what explains the low takeup rate of formal insurance, despite substantial premium subsidy from the government? We find that providing access to formal insurance significantly increases farmers' tendency to raise sows. We argue that this finding also suggests that farmers are not previously insured efficiently through informal mechanisms. We also provide several pieces of evidence suggesting that trust, or lack thereof, for government-sponsored insurance products is a significant barrier for farmers' willingness to participate in the insurance program.
The IEEE Reliability Test System (RTS) developed by the
Application of Probability Method Subcommittee has been used to compare
and test a wide range of generating capacity and composite system
evaluation techniques and subsequent digital computer programs. A basic
reliability test system is presented which has evolved from the
reliability education and research programs conducted by the Power
System Research Group at the University of Saskatchewan. The basic
system data necessary for adequacy evaluation at the generation and
composite generation and transmission system levels are presented
together with the fundamental data required to conduct
reliability-cost/reliability-worth evaluation
Principles and Applications of Power System Reliability Second Edition”[M]
- Lin Cheng
- Jian He
Non-life insurance actuarial science”[M]
- Meng Shengwang
- Liu Leping
- Xiao Zhengyan