A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is pro...
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A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is proposed to develop a scheme for eco-efficient operation of HEMS. The proposed method provides the trade-off between the net cost of energy (CEnet) and the time-based discomfort (TBD) due to shifting of home appliances (HAs). At step-1, primary trade-offs for CEnet, TBD and minimal emissions TEMiss are generated through a heuristic method. This method takes into account photovoltaic availability, the state of charge, the related rates for the storage system, mixed shifting of HAs, inclining block rates, the sharing-based parallel operation of power sources, and selling of the renewable energy to the utility. The search has been driven through multi-objective genetic algorithm and Pareto based optimization. A filtration mechanism (based on the trends exhibited by TEMiss in consideration of CEnet and TBD) is devised to harness the trade-offs with minimal emissions. At step-2, a constraint filter based on the average value of TEMiss is used to filter out the trade-offs with extremely high values of TEMiss. At step-3, another constraint filter (made up of an average surface fit for TEMiss) is applied to screen out the trade-offs with marginally high values of TEMiss. The surface fit is developed using polynomial models for regression based on the least sum of squared errors. The selected solutions are classified for critical trade-off analysis to enable the consumer choice for the best options. Furthermore, simulations validate our proposed method in terms of aforementioned objectives.
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