Optimal operation of residential energy Hubs include Hybrid electric vehicle & Heat storage system by considering uncertainties of electricity price and renewable energy

Abstract

In this paper proposes an efficient hybrid method for optimizing the Residential Energy Hubs (REH), which is incorporated into Plug-in Hybrid Electric Vehicle (PHEV) and Heat Storage System (HSS). The proposed hybrid method is the hybrid wrapper of Balancing Composite Motion optimization (BCMO) and Political Optimizer (PO), named as BCMPO approach. The BCMO approach properties are enhanced by PO approach. The proposed approach is processed based on uncertainties of electricity price and uncertainties of renewable distributed generations. The main purpose of this work is to estimate the operating cost of REHs in a stochastic environment. The proposed BCMPO approach simultaneously considers factors like uncertainty of renewable energy sources and uncertainty of electricity prices. The proposed approach implementation is done by the MATLAB/Simulink platform and performance of the proposed model is compared with other techniques. The proposed approach is analyzed based on the seasons like spring, summer, fall and winter.