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The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch between generation and utilization in power systems is a challenging task and also a very hot topic in the current research era. Researchers of the conventional power grid in the traditional power setup are confronting difficulties to figure out the above problem. Smart grid technology can handle these issues efficiently. In the smart grid, consumer demand can be efficiently managed and handled by employing demand-side management (DSM) algorithms. In general, DSM is an important element of smart grid technology. It can shape the consumers’ electricity demand curve according to the given load curve provided by the utilities/supplier. In this survey, we focused on DSM and potential applications of DSM in the smart grid. The review in this paper focuses on the research done over the last decade, to discuss the key concepts of DSM schemes employed for consumers’ demand management. We review DSM schemes under various categories, i.e., direct load reduction, load scheduling, DSM based on various pricing schemes, DSM based on optimization types, DSM based on various solution approaches, and home energy management based DSM. A comprehensive review of DSM performance metrics, optimization objectives, and solution methodologies is’ also provided in this survey. The role of distributed renewable energy resources (DERs) in achieving the optimization objectives and performance metrics is also revealed. The unpredictable nature of DERs and their impact on DSM are also exposed. The motivation of this paper is to contribute by providing a better understanding of DSM and the usage of DERs that can satisfy consumers’ electricity demand with efficient scheduling to achieve the performance metrics and optimization objectives.

The sustainability of the power systems assures consumers to have efficient and cost-effective energy consumption. Consumers' energy management is one of the solutions that in fact boosts the power system stability via efficiently scheduling the appliances. In addition to energy management, consumers fulfill their low-cost energy consumption using decentralized energy generation (such as solar, wind, plugin hybrid electric vehicles, and small diesel generator). This decentralized energy generation and its trading among the prosumers and consumers help in the distribution grid stability and continuous supply. In this paper, the joint energy management and energy trading model is presented, which provides low-cost electricity consumption to the distribution system. The proposed framework is a twofold system. In the first fold, the distribution system is divided into a number of microgrids, where each microgrid electricity demand is managed using a unified energy management approach. While the local energy produced is traded among the microgrids in the second fold, through energy trading concepts that fulfill the consumers' demand without stressing the utility company. The results indicate that the proposed model reduced the electricity cost of the microgrids with maximum share of self-generation. Moreover, the results also indicate that each microgrid either fulfills its electricity demand from self-generation or purchases it from the nearby microgrid. INDEX TERMS Smartgrid, Unified demand side management, Peak to average power ratio, Consumer comfort level.. Nomenclature β 1 , β 2 Set of appliances having various priorities, e.g., β 1 ∈ {Washing machine, dish washer} and β 2 ∈{Dryer, sterilizer}, etc. γ t Peak clipping maximum limit. λ t,n v,a Consumer preference factor A n Set of appliances of consumer's n.

Summary Energy management in residential buildings is one of the major keys for achieving the ambitious goals of efficient energy consumption, minimum carbon footprint, and reduced consumers energy expenditures. In this paper, we propose a novel residential energy management (REM) approach that is different from the conventional approaches. We formulate a REM problem with the objective to maximize the consumers utility under various practical constraints that include human interaction factor, unavailability of power supply, consumers preferences, and priorities. These constraints involve very high number of binary decision variables and result in extremely high search space that renders the solution of the REM problem prohibitively difficult. The application of standard optimization methods to this problem either require huge computational complexity or cannot find its optimal solution. Therefore, to optimally solve this problem, we propose a novel approach where we convert the original problem into an equivalent mathematical model with reduced number of constraints and decision variables. This significantly reduces the solution space of the problem, and standard optimization methods can be used for finding its optimal solution. The simulation conforms that the solution of the reformulated equivalent problem obtains optimal solution to the original REM problem with remarkably reduced computational complexity.

Summary Peak power consumption is one of the most critical issues for power system operation and sustainability. To overcome this issue, the available energy resources may be utilized in an efficient way. Demand‐side management (DSM) may be used for the efficient utilization of the available resources to reduce the peak power consumption by rescheduling the shiftable appliances. Apart from this, a number of other objectives are also achieved by DSM. In the literature, DSM is used to reduce the electricity cost, curtail peak hour's demand, diminish peak‐to‐average power ratio, and minimize the distribution losses. To the best knowledge of the authors, none of the research articles has considered all the mentioned objectives in a single model. To fill this research gap, we propose a unified DSM model where we focus to get the abovementioned objectives of DSM in a single framework. This unified DSM framework also gives liberty to the power system administration for the operation of the system with exchange policies of government and the company itself. While getting the abovementioned objectives, our proposed unified model can take care of a number of DSM features including importance of heterogeneous load, load shedding, human interaction factor, peak clipping, valley filling, load shifting, appliances priorities, and consumer preferences.