Multi-Objective Optimization of Combined Heat and Power Industrial Microgrid

Abstract

With the advent of distributed energy resources (DERs), such as solar photovoltaic (PV), distributed storages (DSs), and combined heat and power (CHP) generators, an opportunity was given to various customers to be satisfied with their local electricity and heat providers. Microgrid is a small-scale, localized power network that encompasses DERs, loads, and controllers. Microgrids could be a promising alternative for the conventional power system to solve environmental and economic concerns. Recently, CHP-based microgrids have widely attracted attention due to the cost effectiveness and pollution reduction. Most of the recent studies attempted to simplify microgrid components, loads, and constraints to decrease the analysis complexity; however, in this work, a comprehensive study of an industrial microgrid (IMG) comprising natural gas-based CHPs with different generation limits, PVs with intermittent outputs, PV storages, and boilers is taken into the consideration to totally satisfy variant electrical and heat demand over 24-hour period. Emission and cost are conflicting concerns in microgrid generation scheduling optimization and simultaneous optimization of these objectives was challenging. Optimization process is viable using various algorithms and techniques. Among all different approaches, NSGA-II and PSO are among the top-rated algorithms. In this innovative study, NSGA-II and PSO have been developed to reduce cost and emission objectives simultaneously with applying the most critical constraints and variable loads. The practical ability of the optimization process using the applied algorithms are demonstrated by analyzing two scenarios at the presence and absence of PV systems. Although both methods could satisfy electrical and thermal demands, the NSGA-II presented an improved solution compared to PSO method. Also, PV system effect on cost and pollution reduction was significant.