Abstract
Photovoltaic (PV) power generation has developed rapidly in recent years. Owing to its volatility and intermittency, PV power generation has an impact on the power quality and operation of the power system. To mitigate the impact caused by the PV generation, an energy storage (ES) system is applied to the PV plants. The capacity configuration and control strategy based on the stochastic optimization method have become an important research topic. However, the accuracy of the probability distribution model is insufficient and a stochastic optimization method is rarely used in a control strategy. In this paper, a stochastic optimization method for the energy storage system (ESS) configuration considering the self-regulation of the battery state of charge (SoC) is proposed. Firstly, to reduce the sampling error when typical scenarios of PV power are generated, a time-divided probability distribution model of the ultra-short-term predicted error of PV power is established. On this basis, to solve the problem that SoC reaches the threshold frequently, a self-regulation model of the SoC based on multiple scenarios is established, which can regulate the SoC according to rolling PV power prediction. A stochastic optimization configuration model of the energy storage system is constructed, which can reduce the impact of PV uncertainty on the configuration result. Finally, the proposed stochastic optimization method is validated. The fitting error of the time-divided probability distribution model is 15.61% lower than that of the t-distribution. The expected revenue of the optimal configuration in this paper is 8.86% higher than the scheme with a fixed probability distribution model, and 16.87% higher than without considering the stochastic optimization method.
Highlights
In the context of energy and environmental challenges becoming one of the world’s key problems, renewable energy is receiving an increasing amount of attention and research [1]
The second part analyzes the state of charge self-regulation strategy and the optimal configuration results of the energy storage system
This paper investigated the stochastic optimization configuration method for the energy storage system in a Photovoltaic-Energy Storage (PV-ES) combined system
Summary
In the context of energy and environmental challenges becoming one of the world’s key problems, renewable energy is receiving an increasing amount of attention and research [1]. The development of renewable energy is of great significance to the world’s sustainability. Photovoltaic (PV) power generation is an essential component of renewable energy generation that has grown quickly in recent years [2,3]. Its application contributes a lot to the sustainability of energy development and utilization. PV is an important way to reduce greenhouse gas emissions. PV power generation is influenced by weather conditions and is characterized by volatility and intermittency. As the penetration of PV power generation increases, it will bring new challenges to the power grid, such as PV consumption, power quality, and so Sustainability 2022, 14, 553.
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