Multicriteria optimization in the problem of computer-aided design of hybrid solar energy systems

Abstract

This paper reports an approach to optimizing the structure of a hybrid solar energy system (HSES), used in the task of automated design, under two modes: independent and connected to the network. The proposed HSES includes a solar energy system (SES), an energy storage system (ESS) powered by rechargeable batteries (RBs), a set of diesel generators (DGs), and a network-connecting system. This paper has identified models of the HSES elements' power and proposed a control algorithm based on rules that assess the state of the system during operation. The energy models in conjunction with the control algorithm make it possible to model the system's operation stage over a predefined time interval. The proposed approach is based on solving a multicriteria optimization problem (MCO). MCO takes into consideration the minimization of system costs and the total cost of the system, minimizing fuel use, maximizing reliability, and minimizing the use of non-renewable energy sources. A solution to the MCO problem is based on using a Pareto-optimal solution search algorithm, underlying which is the NSGA-II genetic algorithm employing the proposed set of crossbreeding, mutation, and breeding operators. The devised procedure makes it possible to determine the structure of HSES, which includes a set of the number of solar panels, RBs, and DGs. The result is three variants of HSES for a household for two people (Kyiv, Ukraine), under an autonomous mode and in the regime connected to the electricity grid. Given the possibility of selling electricity at a green tariff during the year, the reported solution makes it possible to reduce the estimated cost of the system by up to 45 %. The use of simulation has helped conduct a detailed analysis of the system's performance throughout the year