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The demand of electrical energy has become utmost requirement for the consumers now a days and a shortage of electrical energy can affect the daily lifestyle of human being (Yadav et al, 2020). The electrical energy has become an essential commodity for day-to-day life of residential and commercial consumers. The electrical energy has become a measure of prosperity of a nation based on per capita energy consumption. It means the per capita energy consumption is equivalent to per capita income, which means energy is equivalent to money (Wang & Ponce, 2019). In conventional grid system huge portion of electricity is generated from fossil fuels which intern produces carbon footprint. The natural resources are depleting very fast, so use of renewable energy resources with optimal utilization of electrical energy has become essential need in smart grid environment (Yadav et al, 2019 & Gellins et al, 1988). The increase in energy requirement stresses new power plants to fulfill the energy needs but it requires large amount of fund. This increase in energy requirement can also be fulfilled by adding distributed generation and electric vehicles in the distribution system (Aswani et al, 2018, and Maurya et al, 2019). The alternate way to fulfill energy demand is adoption of Demand Side Management (DSM) in smart grid environment, featured with time of use (TOU) pricing scheme. The evolution of smart grid system by replacing conventional old grid creates a platform for the execution of DSM programs (Gellings & Chamberlin, 1993). The DSM programs also provide more flatten load curve along-with reduction of carbon footprints with the deployment of distributed generations in smart grid system (Siano, 2014).
DSM provides an opportunity to participating consumers to shift the non-critical loads in off peak operating hours. The peak load burden on utility can be avoided by deploying DSM along with creating a delay in installing new generating units for few years (Costanzo et al, 2012 & Esther et al, 2016). The indirect benefit of delaying the capacity expansion reduces the emission of carbon footprint and budget of concern Government. DSM can be carried out in different ways to benefit the utility primarily with improved power quality. DSM can be executed in two ways named as direct and indirect control. In direct control of DSM, utility switch off the excess load based on some preference for the load decided by utility (Ng & Sheble, 1998). The direct load removal may be on the ground of type of load or area or something else. In the indirect control of DSM, utility uses a variety of methodologies to shift the load from one time slot to another. Indirect method popularly classified as time shifting of loads, incentive-based time shifting, imposing TOU pricing and many more technologies available so far (Kinhekar et al, 2016).
The extensively used DSM techniques in smart grid environment are peak clipping, valley filling, load shifting, strategic conservation, strategic load growth and flexible load shape. Peak clipping is the direct method of DSM in which excess load on utility is removed without taking any concern from the user. The purpose of peak clipping is to exonerate the utility burden in case a country or region facing energy shortage. In valley filling the consumers are encouraged to increase the load during lower tariff schedule (Harish & Kumar, 2016). Strategic conservation is caried out at user end by using energy efficient appliances to reduce the energy consumption. Strategic load growth is applied to increase the consumers load to balance the load on smart grid system. Smart grid reliability enhancement is done by flexible load shape technique. Load shifting is the most widely used method of DSM in the literature. A pictorial representation of DSM techniques is shown in Fig 1(Kinhekar et al, 2013).