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Energy Management System in Residential Sector with Renewable Energy Source Under Demand Response Consideration

Demand response programs are being implemented worldwide in order to maintain the underutilized power capacity which can lead to the problems like peak to average power ratio, increased line capacity, wastage of power and thus increased electricity prices. This paper presents Binary Particle Swarm Optimization (BPSO) algorithm to schedule residential load in order to minimize peak to average ratio (PAR) of power and electricity cost of a household, considering the time of use (ToU) pricing scheme. Household appliances are categorized into schedulable and un-schedulable appliances. The load of a household is evenly distributed throughout twenty-four hours to achieve minimum peak to average ratio as well as minimum cost. The model is simulated by analyzing the results of the customers that have home energy management system (HEMS) and the customers that have HEMS with renewable energy source. The results show that the customers that have HEMS with the renewable energy source can reduce PAR and the cost of electricity much better than the customers that uses only HEMS.