A Review on Demand Side Management and Case Study Using Optimization Tool

Abstract

Utilities around the world are now considering Demand Side Management (DSM) in their strategic planning. The costs of constructing and operating a new capacity generation unit are increasing everyday, which force the utilities to search for another alternative without any additional constraints on customers comfort level or quality of delivered product. DSM encompasses a broad range of utility initiated activities to encourage end users to willingly modify their electricity consumption without any impact on service quality or customer satisfaction. It was found that an objective function reflecting the user electricity expenses did widely serve the best for both the electric utility as well as the end user. From a utility point of view, benefits are meterized as freed capacity, deferred investment or increased revenues. Other developed target objective functions such as maximizing the load factor or the utility revenues did serve to achieve its targets but without much impact on end user electricity expenses or even increased ones. Demand side management (DSM) is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced overall operational cost and carbon emission levels. Most of the existing demand side management strategies used in traditional energy management systems employ system specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. This research presents a review on different prevalent demand side management strategies and case study based on peak clipping & load shifting technique for demand side management. Simulations were carried out on a load profile which contains a variety of loads in different hours of the day. The simulation results show that the proposed demand side management strategy achieves substantial savings, while reducing the peak load demand of the smart grid.