Technologies and Methods for Optimizing Multi-level Energy Storage Systems
Year: 2025
Type: article
Abstract: The study explores advanced optimization methods for multi-level energy storage systems (ESS) within distributed energy systems integrating renewable energy sources (RES). It addresses critical challenges posed by the variability and intermittency of RES generation, highlighting the need for effective solutions to maintain energy supply stability and reliability. The research categorizes ESS technologies into mechanical, electrochemical, electrical, chemical, and thermal systems, evaluating their technical and economic features, including energy density, efficiency, cost, and environmental impact. Key optimization approaches are analyzed, such as dynamic programming, model predictive control, genetic algorithms, particle swarm optimization, and mixed-integer linear programming. These methods focus on optimizing ESS parameters, including sizing, placement, and charge-discharge scheduling, to enhance performance and reduce operational costs. Particular attention is given to ecological aspects, such as minimizing greenhouse gas emissions and mitigating battery degradation to support sustainable energy systems. Advanced management algorithms, including artificial intelligence-based techniques like neural networks, fuzzy logic, and heuristic optimization, are proposed to adaptively manage ESS under changing conditions of generation and consumption. These smart management systems can also balance energy supply and demand, support frequency regulation, and improve grid reliability. Recommendations are made for integrating ESS into distributed energy systems to facilitate the effective use of renewable resources while addressing uncertainties in energy generation. The study highlights the importance of robust optimization methods to tackle the increasing complexity of energy systems. By incorporating ESS into smart grid frameworks and adopting innovative control strategies, it is possible to enhance network stability, increase energy efficiency, and contribute significantly to decarbonization efforts.
Author: Ihor Bohoiko
Language: English
Subfield: Energy Engineering and Power Technology
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410755127