Abstract
Abstract Due to the influence of weather factors, distributed photovoltaics exhibit a characteristic of high output in the afternoon and low output in the evening, resulting in an imbalanced supply and demand of rural electricity, a low utilization rate of distributed photovoltaics, and slow progress in poverty alleviation in rural areas. This paper proposes a distributed energy storage optimization configuration model that takes into account various factors such as rural household electricity consumption, aquaculture load power supply characteristics, distributed photovoltaic output characteristics, and the lease period of distributed energy storage box battery modules. The optimization objective is to maximize the benefits of distributed photovoltaic systems in rural areas and minimize the investment costs of farmers, with distributed photovoltaic capacity and the lease period of distributed energy storage as decision variables. Further, considering the problem of the Slap Swarm Algorithm being prone to falling into local optima when solving the model, a set of optimal points is introduced to initialize the population and improve the algorithm’s global search ability. Finally, the effectiveness of the proposed model was verified through a comprehensive example of rural distributed photovoltaics.
Published Version
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