Implementation of demand response in home energy management system using immune clonal selection algorithm

Demand response (DR) is one of the crucial issues in the modern smart grid. DR allows end-users to participate the power regulations in the power system according to the electricity tariffs by changing end-users´ behaviors of using electricity without affecting the lifestyle quality. A smart home integrates the remote medical care, security, entertainment and energy management systems using intelligent techniques. This paper aims to developing the core algorithm based on the immune algorithm in a home energy management system. The optimal day-ahead temperature scheduling of both air conditioner and water heater in accordance with day-ahead electricity price and outdoor temperature forecasting is attained. The electricity expense is minimized and the comfort of life quality is remained. The simulation result validates the applicability of the proposed method using realistic electricity prices and outdoor temperatures.