Optimal scheduling of storage device, renewable resources and hydrogen storage in combined heat and power microgrids in the presence plug-in hybrid electric vehicles and their charging demand

Abstract

Microgrids have faced an increasing penetration rate of renewable energy resources (RERs), plug-in hybrid electric vehicles (PHEVs), combined heat and power (CHP), and storage systems. These elements need to be optimally scheduled so that the optimal operation of the microgrid is obtained. This study employs a novel random structure to optimally manage energy in microgrids which contain proton exchange membrane fuel cell-combined heat and power (PEMFC-CHP), RERs, PHEVs, as well as storage devices. The aim is to take into account the uncertainty of PHEVs and RERs models, in which Monte Carlo Simulation (MCS) is incorporated. The hydrogen storage strategy for PEMFC-CHP units is also used in this study, this strategy is considered by a mixed integer nonlinear programming (MINLP) problem. Moreover, smart charging plans are utilized to charger PHEVs. The objective function aims to maximize the market profit. This paper uses the modified adaptive differential evolution (MADE) technique for analyzing the optimal operation of the microgrid, where the intermittent behavior of uncertainty parameters is investigated. Differential evolution (DE) adopts an iteration-based strategy to enhance a candidate solution using a quality criterion and optimize the problem. Moreover, the algorithm is modified in order to enhance its search capability to be able to search and find local and global points. A conventional test system is implemented for verifying the efficiency of the suggested strategy and various planning durations are considered. A comparison is also made between this method and its counterparts for various situations and conditions.