Optimal Sizing of Smart Home Renewable Energy Resources and Battery Under Prosumer-Based Energy Management

Abstract

This article presents the framework of a two-stage optimization model for the optimal planning of smart home renewable energy resources (RERs) and battery integration with the association of prosumer-based energy management. The optimal sizing problem of in-house RERs and battery is addressed in the first-stage optimization with the objective function of RERs and battery's total life-cycle cost minimization. The smart home daily energy operation problem is formulated in the second stage with the help of multiobject home energy management (MOHEM). In the second-stage operation problem, the MOHEM is implemented with two different objective functions such as minimization of consumer's daily energy cost and maximization of consumer's total comfort level index. The particle swarm optimization algorithm and a mixed-integer linear programming technique are, respectively, used in this article to optimize the proposed two-stage optimization model. A typical smart home which consists of various controllable appliances is considered in this analysis to evaluate the performance of the proposed two-stage optimization model. Three different case studies are considered in the simulation to assess the effectiveness of the proposed model. Finally, an economic analysis is also done in this article to examine the smart home consumer's capital investment benefits.