Configuration strategy and operation mode design under multi-objective optimisation framework in an off-grid optical storage microgrid
Published Online: Mar 17, 2025
Received: Oct 27, 2024
Accepted: Feb 12, 2025
DOI: https://doi.org/10.2478/amns-2025-0185
Keywords
© 2025 Zhaobin Wu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
In recent years, off-grid photovoltaic (PV) storage microgrid technologies have attracted widespread attention in improving energy efficiency and reducing carbon emissions. Combining photovoltaic (PV) power generation and energy storage systems, these microgrids are highly autonomous and flexible, and are particularly suitable for power supply in remote areas. However, the configuration strategy and operation mode of microgrids directly affect the economics and reliability of their operation, so a reasonable and optimized design is particularly important. In this paper, a multi-objective optimal configuration strategy and operation mode design method for off-grid photovoltaic (PV) and storage microgrids is proposed. By optimizing the configuration of the photovoltaic power generation and storage system and operating mode, the economic efficiency and operational stability of the system can be improved. A mathematical model based on the multi-objective optimisation algorithm is adopted, and an energy management system is constructed by combining the energy scheduling scheme in order to achieve a balance between economy, reliability and environmental benefits. The microgrid operation under different scenarios is analysed through experimental simulation, and the proposed method can effectively reduce the system cost and show better optimisation effects in terms of energy storage equipment capacity and power generation utilisation. The study shows that under the framework of multi-objective optimisation, the rational configuration of the optical storage system and the design of the operation mode can significantly improve the overall performance of off-grid microgrids and provide effective theoretical support and data basis for the wide application of microgrid systems in the future.