Resumen de Scheduling of residential shiftable smart appliances by metaheuristic approaches
Smart grids' demand-side management has great importance because of its peak load reduction and load shifting effects resulting in more efficient and stable distribution grids and enabling more renewable energy sources integration. Residential household appliances can be scheduled and controlled by emerging smart grid technologies through demand response programs applied to smart grids. Metaheuristic optimization algorithms, as a part of artificial intelligence techniques, can be used to schedule time-shiftable loads in the residences. This chapter introduces scheduling of time-shiftable smart appliances in residences by smart metaheuristic approaches and gives performance results of the utilized metaheuristic algorithms which include BAT, Firefly, Cuckoo Search, and Symbiotic Organisms Search (SOS). By coding these metaheuristic algorithms developed in the literature they were tested and compared to each other. The case study results show that SOS algorithm gives better fitness value. Also, the case study results indicate that peak consumption can be decreased by 36.3%, and the distribution line losses can be reduced by 45.2% compared to the unscheduled case thanks to scheduling of the time-shiftable appliances.
