Muhammad B. Rasheed

University of Alcalá | UAH · Department of Automatics

Due to changes in meteorological factors, the instability in the power at the end of the transmission system demands considerable attention. The temperature of the transmission line varies, which has a significant impact on the line parameters. An accurate prediction of line parameters behaviour is necessary to ensure system reliability. The presen...

A large number of sensors are deployed for performing various tasks in the smart cities. The sensors are connected with each other through the Internet that leads to the emergence of Internet of Things (IoT). As the time passes, the number of deployed sensors is exponentially increasing. Not only this, the enhancement of sensors has also laid the b...

Peak load forecasting plays an integral part in the planning and operating of energy plants for the utility companies and policymakers to devise reliable and stable power infrastructure. However, the electricity load profile is considered a complex signal due to the non-linear and stochastic behavior of the consumer. Therefore, a rigid forecasting...

Residential demand response is one of the key enabling technologies which plays an important role in managing the load demand of prosumers. However, the load scheduling problem becomes quite challenging due to the involvement of dynamic parameters and renewable energy resources. This work has proposed a bi-level load scheduling mechanism with dynam...

Residential demand response is one of the key enabling technologies which plays an important role in managing the load demand of prosumers. However, the load scheduling problem becomes quite challenging due to the involvement of dynamic parameters and renewable energy resources. This work has proposed a bi-level load scheduling mechanism with dynam...

Peak load forecasting plays an integral part in the planning and operating of energy plants for the utility companies and policymakers to devise reliable and stable power infrastructure. However, the electricity load profile is considered a complex signal due to the non-linear and stochastic behavior of the consumer. Therefore, a rigid forecasting...

This paper proposes a new hybrid framework for short-term load forecasting (STLF) by combining the Feature Engineering (FE) and Bayesian Optimization (BO) algorithms with Bayesian Neural Network (BNN). The FE module comprises feature selection and extraction phases. Firstly, by merging the Random Forest (RaF) and Relief-F (ReF) algorithms, we devel...

Recently, multi-agent systems (MASs) have received attention due to the consideration of distributed optimization and control in blockchain (BC) based energy trading applications. However, due to the dynamic behavior of uncertain and random variables, the coordination and control of MAS are still challenging to attain resilience and dynamicity. Tra...

Recently, multi-agent systems (MASs) have received attention due to the consideration of distributed optimization and control in blockchain (BC) based energy trading applications. However, due to the dynamic behavior of uncertain and random variables, the coordination and control of MAS are still challenging to attain resilience and dynamicity. Tra...

This paper presents the integration of shunt capacitors in the radial distribution grids (RDG) with constant and time-varying load consideration for the reduction of power losses and total annual cost, which turns to enhance the voltage profile and annual net savings. To gather the stated goals, three objective functions are formulated with system...

With the rapid increase in the world’s population, the global electricity demand has increased drastically. Therefore, it is required to adopt efficient energy management mechanisms. Since the energy consumption trends are rather dynamic. Therefore, precise energy demand estimation and short and/or long-term forecasting results with higher accuracy...

Short-term load forecasting plays an essential role in the efficient management of electrical systems. Building an optimization model that will enhance forecasting accuracy is a challenging task and a concern for electrical load prediction. Due to Artificial Neural Networks (ANNs), the final result depends on initial random weights and thresholds t...

Floods can cause significant problems for humans and can damage the economy. Implementing a reliable flood monitoring warning system in risk areas can help to reduce the negative impacts of these natural disasters. Artificial intelligence algorithms and statistical approaches are employed by researchers to enhance flood forecasting. In this study,...

This paper considers the time of use (TOU) pricing scheme to propose a consumer aware pricing policy (CAPP), where each customer receives a separate electricity pricing signal. These pricing signals are obtained based on individualized load demand patterns to optimally manage the flexible load demand. The main objective of CAPP is to reduce the pea...

The performance of a power system can be measured and evaluated by its power flow analysis. Along with the penetration of renewable energies such as wind and solar, the power flow problem has become a complex optimization problem. In addition to this, constraints handling is another challenging task of this problem. The main critical problem of thi...

With rapid development in wireless sensor networks and continuous improvements in developing artificial intelligence-based scientific solutions, the concept of ambient assisted living has been encouraged and adopted. This is due to its widespread applications in smart homes and healthcare. In this regard, the concept of human activity recognition (...

Price based demand response is an important strategy to facilitate energy retailers and end-users to maintain a balance between demand and supply while providing the opportunity to end users to get monetary incentives. In this work, we consider real-time electricity pricing policy to further calculate the incentives in terms of reduced electricity...

In this paper, a two-stage approach is proposed on a joint dispatch of thermal power generation and variable resources including a storage system. Although, the dispatch of alternate energy along with conventional resources has become increasingly important in the new utility environment. However, recent studies based on the uncertainty and worst-c...

There are surplus applications in modern smart cities where localization of indoor environments is critical ranging from surveillance and trailing in smart structures to the localized wireless distribution of advertising content in shopping malls. These applications are only successful if a robust and cost-effective real-time system is developed fo...

Vehicular edge computing (VEC) is a potential field that distributes computational tasks between VEC servers and local vehicular terminals, hence improve vehicular services. At present, vehicles' intelligence and capabilities are rapidly improving, which will likely support many new and exciting applications. The network resources are well-utilized...

Software Architectural Process (SAP) is a core and excessively knowledge intensive phase of software development life cycle, as it consumes and produces knowledge artifacts, simultaneously. SAP is about making design decisions, and the changes in these verdicts may pose adverse effects on software projects. The performance and properties of softwar...

This study investigates the feasibility of advanced metering infrastructure (AMI) based on narrowband power line communications (NB‐PLC) by incorporating all possible types of low voltage (LV) and medium voltage (MV) power line channels. The extensive field measurements are carried out on six selected sites that include residential, commercial, and...

This paper aims to investigate the feasibility of smart metering system based on narrowband power line communications (NB-PLC) by using low-voltage (LV) and medium voltage (MV) power line channels. The LV and MV networks of two different sites are selected to carry out comprehensive field measurements to investigate the characteristics of NB-PLC ch...

An Intrabody Area Nanonetwork (Intra-BANN) is a set of nanoscale devices, which have outstanding cellular level precision and accuracy for enabling non-invasive healthcare monitoring and disease diagnosis. In the proposed work, we design a novel Feedforward Neural Networks (FFNNs) based data aggregation scheme that integrates the attributes of arti...

In this paper, the exact analysis of a multi-hop multi-branch (MHMB) relaying network is investigated wherein each relay can operate in amplify-and-forward (AF) or decode-and-forward (DF) mode depending upon the decoding result of its received signal. If a relay decodes the received signal correctly, it works in DF mode, otherwise, the relay operat...

In recent past, to meet the growing energy demand of electricity, integration of renewable energy resources (RESs) in an electrical network is a center of attention. Furthermore, optimal integration of these RESs make this task more challenging because of their intermittent nature. Therefore, in the present study power flow problem is treated as a...

In this paper, the exact analysis of a multi-hop multi-branch (MHMB) relaying network is investigated wherein each relay can operate in amplify-and-forward (AF) or decode-and-forward (DF) mode depending upon the decoding result of its received signal. If a relay decodes the received signal correctly, it works in DF mode, otherwise, the relay operat...

This paper is focused on the channel modeling techniques for implementation of narrowband power line communication (NB-PLC) over medium voltage (MV) network for the purpose of advanced metering infrastructure (AMI). Three different types of models, based on deterministic method, statistical method, and network parameters based method are investigat...

With the negative climate impact of fossil fuel power generation and the requirement of global policy to shift towards a green mix of energy production, the investment in renewable energy is an opportunity in developing countries. However, poor economy associated with limited income, funds availability, and regulations governing project funding and...

An Intrabody Nanonetwork (IBNN) is constituted by nanoscale devices that are implanted inside the human body for monitoring of physiological parameters for disease diagnosis and treatment purposes. The extraordinary accuracy and precision of these nanoscale devices in cellular level disease diagnosis and drug delivery are envisioned to advance the...

An Intrabody Nanonetwork (IBNN) is constituted by nanoscale devices that are implanted inside the human body for monitoring of physiological parameters for disease diagnosis and treatment purposes. The extraordinary accuracy and precision of these nanoscale devices in cellular level disease diagnosis and drug delivery are envisioned to advance the...

Despite the universal importance of price based demand response (DR) for managing electric vehicle (EV) charging load, the academic literature has explored various mechanisms to its implementation. The prequel to this work has demonstrated that implementation of load management schemes on the basis of price based DR programs leads to costlier sched...

In most demand response (DR) based residential load management systems, shifting a considerable amount of load in low price intervals reduces end user cost, however, it may create rebound peaks and user dissatisfaction. To overcome these problems, this work presents a novel approach to optimizing load demand and storage management in response to dy...

Despite the universal importance of price based demand response (DR) for managing electric vehicle (EV) charging load, the academic literature has explored various mechanisms to its implementation. The prequel to this work has demonstrated that implementation of load management schemes on the basis of price based DR programs leads to costlier sched...

Day-ahead electricity pricing is an important strategy for electricity providers to improve grid stability through load scheduling. In this paper, we investigate a general framework for modelling electricity retail pricing based on load demand and market price information. Without any a priori knowledge, we have considered a finite time approach wit...

The smart grid (SG) has emerged as a key enabling technology facilitating the integration of variable energy resources with the objective of load management and reduced carbon-dioxide (CO 2 ) emissions. However, dynamic load consumption trends and inherent intermittent nature of renewable generations may cause uncertainty in active resource managem...

In order to ensure optimal and secure functionality of Micro Grid (MG), energy management system plays vital role in managing multiple electrical load and distributed energy technologies. With the evolution of Smart Grids (SG), energy generation system that includes renewable resources is introduced in MG. This work focuses on coordinated energy ma...

https://ieeexplore.ieee.org/document/8714571/authors#authors ******************************************************************************************************************************************** This paper aims to provide an overview of recent research on buildings’ energy management. A recent overview of some of the research published mai...

Today’s power systems are subject to high penetration of dynamic load. Volatility and intermittency of the dynamic load demand need to be compensated through optimization and scheduling without compromising user comfort. This work proposes a multi-agent based multi-layered hierarchical control system for residential load management under real time...

Smart grid (SG) vision has come to incorporate various communication technologies, which facilitate residential users to adopt different scheduling schemes in order to manage energy usage with reduced carbon emission. In this work, we have proposed a residential load management mechanism with the incorporation of energy resources (RESs) i.e., solar...

This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity ma...

This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity ma...

Abstract—In this paper, we adopt a model that concentrates on problem of load scheduling under utility through demand response programs. Therefore, demand response model used in this paper is based on real time electricity price; that changes over the course of time which may reflect the generation cost of utility as well as wholesale electricity p...

In this paper, we adopt a model that concentrates on solving load scheduling problem through demand response (DR) programs. Where, DR has been designed to maintain supply demand balance while reducing the total energy cost of end users. Therefore, DR model used in this paper is based on real time electricity price (RTP) with the objective of cost a...

The residential sector is responsible for the consumption of almost 40% energy along-with carbon dioxide emissions. Approximately 50% of overall energy consumed in residential sector is directly related to cooling, heating, ventilation and lighting. Thus, it is crucial to optimally control heating, cooling and ventilation systems for the reduction...

Power Point Presentation of PhD Thesis of Muhammad Babar Rasheed - PDF

Recently, Home Energy Management (HEM) controllers have been widely used for residential load management in a smart grid. Generally, residential load management aims {to reduce the electricity bills and also curtail the Peak-to-Average Ratio (PAR)}. In this paper, we design a HEM controller on the {basis} of four heuristic algorithms: Bacterial For...

Wireless body area networks are captivating growing interest because of their suitability for wide range of applications. However, network lifetime is one of the most prominent barriers in deploying these networks for most applications. Moreover, most of these applications have stringent QoS requirements such as delay and throughput. In this paper,...

This work proposes a residential load management system using multiagent technology with the objective of cost and comfort management. Smart appliances in a residential unit are modelled as agents which are controlled using optimization algorithm. These agents cooperate and communicate with each other using agent communication language (ACL) to red...

This paper proposes a novel demand response (DR) mechanism based on real time electricity prices with the objective of cost reduction. The novelty of the proposed mechanism lies in the concept that electricity sub-prices are calculated based on the fraction of energy consumed by each unit/home. While, in traditional residential energy management pr...

In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally cont...

This paper presents real time information based energy management algorithms to reduce electricity cost and peak to average ratio (PAR) while preserving user comfort in a smart home. We categorize household appliances into thermostatically controlled (tc), user aware (ua), elastic (el), inelastic (iel) and regular (r) appliances/loads. An optimizat...

In this paper, we investigate some aspects related to microgrid (MG) stability. Due to different applications of MG, its structure and deployment topology vary depending upon the nature of application and operating modes (islanded or grid connected). So, the stability of MGs varies accordingly. This paper precisely explains the stability aspects (e...

In Smart Grid (SG), integration of renewable energy sources such as solar and wind is a challenging task due to their intermittent nature. Most of the existing Demand Side Management (DSM) techniques are based on Day Ahead Pricing (DAP) or Time of Use (TOU) pricing which can deviate from Real Time Pricing (RTP) due to unpredictable energy consumpti...

In this paper, we propose mathematical optimization models of household energy units to optimally control the major residential energy loads while preserving the user preferences. User comfort is modeled in a simple way which considers appliance class, user preferences and weather conditions. The Wind Driven Optimization (WDO) algorithm with the ob...

Demand Side Management (DSM) mechanism is used for the implementation of different strategies to encourage residential users to reduce electricity bill as well as energy demand. There is also a close relationship between the consumer and utility for equally benefiting to both in terms of grid stability and bill reduction. Extensive research is unde...

Wireless Sensor Networks (WSNs) were envisaged to become the fabric of our environment and society. However, they are yet unable to surmount many operational challenges such as limited network lifetime, which strangle their widespread deployment. To prolong WSN lifetime, most of the existing clustering schemes are geared towards homogeneous WSN. Th...

Computer assisted analysis of electroencephalogram (EEG) has a tremendous potential to assist clinicians during the diagnosis of epilepsy. These systems are trained to classify the EEG based up on the ground truth provided by the neurologists. So, there should be a mechanism in these systems using which a system's incorrect markings can be mentione...