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Capacity Optimization of Hybrid Energy Storage in Wind/PV Complementary Power Generation System Based on Improved Particle Swarm Optimization

机译:基于改进粒子群优化的风/ PV互补发电系统混合储能的容量优化

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In order to improve the power quality and economic benefits of independent scenery hybrid system, energy storage technology needs to be introduced, and the key technical issue of energy storage technology research is the capacity allocation of energy storage system. In this paper, a mathematical model of battery and super-capacitor is established firstly. Based on the complementary characteristics of battery and super-capacitor, a capacity optimization strategy of the hybrid energy storage system is proposed. Based on this strategy, the improved particle swarm optimization algorithm is taken to optimize the capacity of the independent wind-solar hybrid power generation system with loss of power supply probability (LPSP) and loss of produced power probability (LPPP) as the system operation index. At the same time, the capacity optimization configuration model with the constraint of the reliability index of LPPP and LPSP of independent wind and solar hybrid power system is established with the objective of full life cycle cost of hybrid energy storage device. Aiming at the problem of insufficient local search ability and easy falling into local optimum of particle swarm optimization algorithm, an improved particle swarm optimization algorithm is proposed to solve this optimization problem. The results of the example analysis show that the optimization model and the improved algorithm are correct and effective.
机译:为了提高独立风景混合系统的电能质量和经济效益,需要介绍储能技术,能量存储技术研究的关键技术问题是能量存储系统的能力分配。在本文中,首先建立了电池和超级电容的数学模型。基于电池和超电容的互补特性,提出了混合能储能系统的容量优化策略。基于该策略,采用改进的粒子群优化算法来优化独立风力太阳能混合发电系统的容量,随着电源概率(LPSP)的损失以及产生的功率概率(LPPP)作为系统操作索引。同时,利用混合能量存储装置的全生命周期成本,建立了具有LPPP和LPSP的可靠性指标的容量优化配置模型,其具有混合能量存储装置的全生命周期成本。针对本地搜索能力不足的问题,并且容易陷入粒子群优化算法的局部最优,提出了一种改进的粒子群优化算法来解决该优化问题。示例性分析的结果表明,优化模型和改进的算法是正确有效的。

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