A Hybrid Bacterial Foraging Tabu Search Heuristic Optimization for Demand Side Management in Smart Grid

With the advent of Smart Grid (SG), it provides the consumers with the opportunity to schedule their power consumption load efficiently in such a way that it reduces their energy cost while also minimizing their Peak to Average Ratio (PAR) in the process. We in this paper target the appliances to schedule in such a way that it increases User Comfort (UC) and decreases electricity consumption load which benefits both consumer and utility. In this paper, we proposed hybrid of Bacterial Forging Algorithm (BFA) and Tabu Search (TS) Algorithm using different Operational time Interval (OTI) to schedule appliances while balancing User Comfort which is the main objective of the Demand Side Management (DSM). This paper tries to reduce both waiting time and electricity cost simultaneously in the new hybrid Bacterial Foraging Tabu Search (BFTS) technique. Real time pricing (RTP) scheme was used to get the total cost of electricity consumed. We compared the results of proposed hybrid scheme with Bacterial Forging (BFA) and Tabu Search (TS) Algorithm using different Operational time Interval (OTI). The result shows effectiveness of using hybrid Bacterial Foraging Tabu Search (BFTS) technique for Demand Side Management (DSM).