Home Energy Management Using Social Spider and Bacterial Foraging Algorithm
Electricity is a controllable and convenient form of energy and it provides power to appliances. As the population of world is increasing, the electricity demand is also increasing which leads to energy crisis. This problem can be control by using Demand Side Management (DSM) and Energy Management Scheduler (EMS). In this paper, we design EMS for residential area using two heuristic algorithms: Bacteria Foraging Algorithm (BFA) and Social Spider Optimization (SSO) algorithm. Our main objectives are to minimize electricity cost and Peak to Average Ratio (PAR). These algorithms help to shift the load from on-peak to off-peak hours. We use Real Time Price (RTP) signal for electricity bill calculation. Simulation results demonstrate that our designed EMS achieved our objectives effectively. SSO perform better in term of PAR and User Comfort (UC).
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