A DSM Approach for Distribution Systems with High Wind Power Penetration

Abstract

The basic objectives of demand side management (DSM) are shifting load from peak hours to off-peak hours and reducing consumption during peak hours. The DSM operation is cleared when deregulated electricity market is considered where the retailer purchases electricity from the electricity market to cover the end users requirements of energy. In this paper, DSM techniques (load shifting and peak clipping) are used to maximize the profit for retailer company by reducing total demand at peak hours and achieve an optimal daily load schedule using linear programing (LP) and genetic algorithm (GA). These techniques are implemented on the 33-bus radial network included wind generation penetration. A short term artificial neural network technique (ANN) is used to get forecasted wind speed and forecasted users load for date 25-March-2018. The ANN uses an actual hourly load data and an actual hourly wind speed data. Then the forecasted data is used in the optimization to get optimal daily load schedule to maximize the profit for retailer company. Finally, comparison is carried out between profit using LP and GA. The optimized DSM succeeded to increase the profits of the company by around 4.5 times its old profit using LP and around 2.5 times using GA.