Anzar Mahmood

Minimizing Electricity Theft Using Smart Meters in AMI

Global energy crises are increasing every moment. Every one has the attention towards more and more energy production and also trying to save it. Electricity can be produced through many ways which is then synchronized on a main grid for usage. The main issue for which we have written this survey paper is losses in electrical system. Weather these losses are technical or non-technical. Technical losses can be calculated easily, as we discussed in section of mathematical modeling that how to calculate technical losses. Where as nontechnical losses can be evaluated if technical losses are known. Theft in electricity produce non-technical losses. To reduce or control theft one can save his economic resources. Smart meter can be the best option to minimize electricity theft, because of its high security, best efficiency, and excellent resistance towards many of theft ideas in electromechanical meters. So in this paper we have mostly concentrated on theft issues.

A Survey of Home Energy Management Systems in Future Smart Grid Communications

In this paper we present a systematic review of various home energy management (HEM) schemes. Employment of home energy management programs will make the electricity consumption smarter and more efficient. Advantages of HEM include, increased savings for consumers as well as utilities, reduced peak to average ratio (PAR) and peak demand. Where there are numerous applications of smart grid technologies, home energy management is probably the most important one to be addressed. Utilities across the globe have taken various steps for efficient consumption of electricity. New pricing schemes like, Real Time Pricing (RTP), Time of Use (ToU), Inclining Block Rates (IBR), Critical Peak Pricing (CPP) etc, have been proposed for smart grid. Distributed Energy Resources (DER) (local generation) and/or home appliances coordination along with different tariff schemes lead towards efficient consumption of electricity. This work also discusses a HEM systems general architecture and various challenges in implementation of this architecture in smart grid.

Efficient and Autonomous Energy Management Techniques for the Future Smart Homes

Smart grid with latest technologies provides solid foundation for the implementation of energy management systems at home premises. This paper proposes an autonomous energy management-based cost reduction solution for peak load times using a home energy management system (HEMS). Within a home environment, both the real time and the schedulable appliances are connected with smart meter through HEMS. We formulate an optimization problem under various practical constraints, which is shown to be a mixed integer programming problem that can be solved through a step-wise approach. A novel scheme based on Dijkstra algorithm is proposed, which results in the similar performance to that of the proposed optimal scheme while exhibiting much lower complexity. To further save the computational efforts, a low complexity scheme is also proposed, which produces considerably better results than the non-optimized scheme with the same complexity yet. Simulation results are presented at show the performance and complexity comparison of different proposed solutions and the existing methods.

Energy Efficient MAC Protocols

This paper presents a survey of energy efficiency of Medium Access Control (MAC) protocols for Wireless Body Area Sensor Networks (WBASNs). We highlight the features of MAC protocols along with their advantages and limitations in context of WBASNs. Comparison of Low Power Listening (LPL), Scheduled Contention and Time Division Multiple Access (TDMA) is also elaborated. MAC protocols with respect to different approaches and techniques which are used for energy minimization, traffic control mechanisms for collision avoidance are discussed. We also present a survey of path loss models for In-body, On-body and Off-body communications in WBASNs and analytically discuss that path loss is maximum in In-body communication because of low energy levels to take care of tissues and organs located inside the body. Survey of Power model for WBANs of CSMA/CA and beacon mode is also presented.

Home Appliances Coordination Scheme for Energy Management (HACS4EM) using Wireless Sensor Networks in Smart Grids

In this paper, a home energy management (HEM) scheme based on appliances coordination has been proposed for future smart grids. This scheme is based on communication among home appliances, a central energy management unit (EMU), smart meter and the storage unit inside home. A wireless sensor home area network (WSHAN) using ZigBee protocol is employed for relaying messages among different entities involved in our proposed HEM scheme. The performance of WSHAN is analyzed with respect to different networking properties. HEM implementation will lead to socially and economically beneficial environment by addressing the consumers’ and utilities concerns. Increased savings, better peak load management and reduction in peak to average ratio are some of the benefits achieved by proposed scheme. Appropriate use of HEMs in a system integrated with distributed resources along with appliances co-ordination and dynamic pricing scheme provides the optimized solutions for energy management issues in smart grids as confirmed by simulation results. c

Residential Energy Consumption Controlling Techniques to Enable Autonomous Demand Side Management in Future Smart Grid Communications

This paper presents an overview of home appliances scheduling techniques to implement demand side management in smart grid. Increasing demand of consumers have affected the power system badly as power generation system faces a number of challenges both in quality and quantity. Economical generation and efficient consumption can solve this problem in future smart grid as it is integrated with information and communication technologies. Smart grid has opportunities to employ different pricing schemes which help also in increasing the efficiency of appliances scheduling techniques. Optimal energy consumption scheduling minimizes the energy consumption cost and reduces the Peak-to-Average Ratio (PAR) as well as peak load demand. In this work, we discuss different energy consumption scheduling schemes that schedule the household appliances in real-time to achieve minimum energy consumption cost and reduce peak demand to shape the load curve.

Monitoring and Controlling Power Using Zigbee Communications

Smart grid is a modified form of electrical grid where generation, transmission, distribution and customers are not only connected electrically but also through strong communication network with each other as well as with market, operation and service provider. For achieving good communication link among them, it is very necessary to find suitable protocol. In this paper, we discuss different hardware techniques for power monitoring, power management and remote power controlling at home and transmission side and also discuss the suitability of Zigbee for required communication link. Zigbee has major role in monitoring and direct load controlling for efficient power utilization. It covers enough area needed for communication and it works on low data rate of 20Kbps to 250Kbps with minimum power consumption. This paper describes the user friendly control home appliances, power on/off through the internet, PDA using Graphical User Interface (GUI) and through GSM cellular mobile phone.

A New Scheme for Demand Side Management in Future Smart Grid Networks

Abstract This paper presents a new energy consumption scheduling scheme to enable Demand Side Management (DSM) in future Smart Grid Networks (SGNs). Electrical grid has been facing important challenges regarding quality and quantity to meet the increasing requirements of consumers. Environment friendly and economical generation along with efficient consumption through effective DSM in future SGNs will help in addressing most of these challenges because of integration of advanced information and commu- nication technologies. In this work, we propose an autonomous energy scheduling scheme for household appliances in real-time to achieve minimum consumption cost and reduction in peak load. We assume that every user is equipped with smart meter which has an Energy Consumption Controlling (ECC) unit. Every ECC unit is connected with its neighbours through local area network to share power consumption information. ECC units run a distributed algorithm to minimize the peak load by transferring the shiftable loads from peak hours to off-peak hours. This ultimately minimizes the total energy consumption cost. Simulation results confirm that our proposed algorithm significantly reduces the peak load and energy consumption cost.

Application of PSO for HEMS and ED in Smart Grid

Two way communication of information and electricity in smart grid provides the promising solution to all the major problems of existing grid especially the classical problem of peak load management. Optimization of generation, transmission and distribution in smart grid is major concern of researchers. Demand Side Management (DSM) allows the active participation of users in order to shape the load curve according to utility requirements and Economic Dispatch (ED) ensures the power supply at minimum cost. Optimization of DSM and ED has great importance to realize the smart grid. Researchers have applied many techniques of Artificial Intelligence (AI) in order to optimize these applications like Genetic Particle Swarm Optimization (PSO). This paper presents a comprehensive review of PSO applications for HEMS and ED. Various cases of ED and Home Energy Management System (HEMS) in smart grid for DSM applications are presented to show the diverse applications of PSO. In second part of paper a HEMS with interrupting loads has also been implemented using PSO.

An optimized approach for home appliances scheduling in smart grid

In this paper, we present a novel home energy management model with enhanced load categorization and multiple scheduling options. Concepts of partial baseline and reserved interrupting loads are used to enhance the traditional load categorization. The proposed model uses multiple pricing schemes namely Time of Use (ToU) and Real Time Pricing (RTP) day ahead case. The energy cost minimization problem has been solved by multiple optimization techniques namely Knapsack and Particle Swarm Optimization (PSO). Comparative results of multiple pricing schemes have been discussed which prove the effectiveness of the proposed model.