A Hybrid Tabu-Enhanced Differential Evolution Meta-Heuristic Optimization Technique for Demand Side Management in Smart Grid

Abstract

Energy management is a demanding task which needs efficient scheduling of multiple appliances in a smart home. In this paper, for the scheduling of different appliances in a smart home, we proposed a hybrid of two meta-heuristic techniques. The proposed technique is the hybrid of enhanced differential evolution (EDE) and tabu search algorithm (TS) and it is named tabu EDE (TEDE). This technique is used in a smart home for the scheduling of appliances to reduce peak to average ratio (PAR) for the utility and increase user comfort. For evaluating the performance of TEDE, we produced home energy management system. In this work, we have considered a single home with different smart appliances. These appliances are categorized into three groups: interruptible appliances, non-interruptible and base appliances. We compare a hybrid TEDE with EDE and TS in three parameters: cost, PAR and waiting time. Results show that TEDE performed well in reducing PAR at consumer side as compare to EDE and TS. TEDE also help in increasing user comfort as compared to EDE and TS algorithm. We considered user comfort in terms of waiting time. However, cost is compromised in TEDE but perform well in terms of other parameters: PAR and user comfort. In addition, the relationships between PAR, electricity cost and user comfort are also calculated in all techniques.