基于粒子群算法的混合储能系统容量优化配置

发布时间：2018-01-15 13:35

本文关键词：基于粒子群算法的混合储能系统容量优化配置　出处：《宁夏大学》2014年硕士论文　论文类型：学位论文

【摘要】：为了提高供电的稳定性、可靠性,实现日夜发电,在太阳能、风能资源比较丰富的区域,建立风能、太阳能互补发电系统。但是由于系统投入成本过高,风、光又存在间歇性和不稳定性等问题,需要配置储能系统来平抑功率波动。超级电容器储能技术的功率密度高、充放电速度快、使用寿命长,蓄电池储能技术比较成熟、价格便宜,但是蓄电池的体积重量大、功率密度低、使用寿命比较短。鉴于二者的互补特征,将超级电容器和蓄电池混合作为风光互补发电系统中的储能装置。首先对光伏电池、风力机、蓄电池和超级电容器的特性进行了分析,建立了超级电容器-蓄电池直接并联、通过电感并联和通过功率变换器并联三种储能方法的模型,通过理论分析和仿真实验表明,当负载脉动时,将二者混合的储能系统提高了储能系统的功率输出能力,减少了蓄电池的输出电流,延长工作时间,减少了内部损耗。其次,建立了以储能装置的生命周期费用为目标函数,以负荷缺电率等为约束条件的独立风电储能系统的容量优化模型,比较传统蓄电池储能、改进蓄电池储能、传统混合储能和改进的混合储能这四种储能方法的优缺点。再次,在风光互补发电系统中,以蓄电池和超级电容器作为混合储能装置,以储能系统的全生命周期年费用最小为目标,以系统的缺电率等运行指标为约束条件,建立了一种混合储能系统容量优化配置模型。分别用标准的粒子群算法、权重改进的粒子群算法和加速因子改进的粒子群算法进行求解。最后,在MATLAB软件中,分别对独立风电储能系统的容量优化配置和风光互补混合储能容量优化配置系统进行仿真,仿真结果表明：改进的混合储能系统具有更低的全生命周期费用；采用加速因子改进的粒子群优化算法可以得到更好优化效果,不仅能加快收敛速度,同时也降低了生命周期费用。
[Abstract]:In order to improve the stability and reliability of power supply and realize power generation day and night, in the region with abundant solar and wind energy resources, wind and solar complementary power generation system is established. However, due to the high cost of the system, wind. Because of the intermittent and instability of light, the energy storage system is needed to stabilize the power fluctuation. The energy storage technology of supercapacitor has high power density, fast charge and discharge speed and long service life. Battery energy storage technology is more mature, cheap, but the battery volume weight, low power density, short service life, in view of the complementary characteristics of the two. Supercapacitors and batteries are mixed as energy storage devices in wind-wind complementary power generation systems. Firstly, the characteristics of photovoltaic cells, wind turbines, batteries and supercapacitors are analyzed, and the direct parallel connection between supercapacitors and batteries is established. Through the model of three kinds of energy storage methods: inductor parallel and power converter, the theoretical analysis and simulation results show that when the load fluctuates. The hybrid energy storage system improves the power output capacity of the energy storage system, reduces the output current of the battery, prolongs the working time and reduces the internal loss. The capacity optimization model of the independent wind energy storage system with the life cycle cost of energy storage unit as the objective function and the load shortage rate as the constraint condition is established to compare the traditional storage battery and improve the storage energy of the battery. The advantages and disadvantages of the traditional hybrid energy storage and the improved hybrid energy storage methods. Thirdly, in the wind-wind complementary generation system, batteries and supercapacitors are used as hybrid energy storage devices. Aiming at the minimum annual cost of the whole life cycle of the energy storage system and taking the running index of the system such as the power shortage rate as the constraint condition, an optimal configuration model of the capacity of the hybrid energy storage system is established. Standard particle swarm optimization (PSO) algorithm is used respectively. The weight improved particle swarm optimization algorithm and the acceleration factor improved particle swarm optimization algorithm are solved. Finally, in the MATLAB software. The simulation results show that the improved hybrid energy storage system has lower life cycle cost. The particle swarm optimization (PSO) algorithm improved by the acceleration factor can not only accelerate the convergence speed but also reduce the life cycle cost.
【学位授予单位】：宁夏大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM53;TM912

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