Optimization Methods of the Size of Hybrid Energy Complexes Powered by Renewable Energy Sources
Year: 2025
Type: article
Abstract: The purpose of the work is to analyze existing and developing optimization methods used in the field of designing hybrid energy complexes and identify the most promising areas of development. In the course of a systematic review of scientific literature in the field under consideration, the method of meta-analysis of published articles was used. The paper analyzes various optimization methods for hybrid energy complexes, which include wind and solar modules, as well as an electric power storage module. During the analysis, an idea is given about the applicability of the optimization methods under consideration in real-world scenarios, taking into account such factors as the cost of computing power, the rate of convergence, as well as the difficulty of implementation. In addition, the most frequently used optimization criteria are highlighted, divided into two groups: reliability criteria and economic criteria. It is noted that the LPSP indicator (probability of power supply disruption) is the most common criterion for evaluating the reliability of a hybrid energy complex. Optimization methods were divided into two groups, traditional and modern, and a group of hybrid methods combining two or more algorithms was identified. The features are highlighted, as well as the existing advantages and disadvantages of various optimization methods. An analysis of the literature in the field of optimization of hybrid energy complexes has shown that the most promising methods include elements of artificial intelligence, in particular, evolutionary and metaheuristic algorithms. The analysis also showed the advantage of using hybrid methods, which make it possible to use the strengths of various methods, while compensating for their disadvantages.
DOI: 10.14529/power250101
Authors: S.V. Mitrofanov, R.R. Temirgaliev
Institution: Orenburg State University
Language: English
Subfield: Energy Engineering and Power Technology
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409220201