基于自适应粒子群算法的直流微网能量优化管理
发布时间：2019-04-01 20:18
【摘要】：针对含储能原件的风电直流微网,提出考虑储能系统运行综合成本的能量管理优化模型。该模型将储能系统成本进行综合考量,实现系统的经济运行,通过约束条件的制定,保证系统运行安全性。采用自适应粒子群算法对能量优化管理模型进行求解,并基于MATLAB建立仿真模型,进行仿真验证。结果表明所提能量优化管理模型可有效降低混合储能系统综合成本,并可基于预测信息实现最佳运行参考节点的求取,实现直流微网系统经济、高效、稳定的运行目标。
[Abstract]:For the wind power DC micro-grid with energy storage components, an energy management optimization model considering the comprehensive operation cost of the energy storage system is proposed. In this model, the cost of energy storage system is considered comprehensively, the economic operation of the system is realized, and the security of the system is guaranteed by the formulation of constraint conditions. The energy optimization management model is solved by adaptive particle swarm optimization (PSO) algorithm, and the simulation model is established based on MATLAB and verified by simulation. The results show that the proposed energy optimization management model can effectively reduce the integrated cost of hybrid energy storage system, and can realize the best operation reference node based on the prediction information, and realize the economical, efficient and stable operation goal of DC micro-grid system.
【作者单位】： 四川大学电气信息学院;
【分类号】：TM73;TP18
[Abstract]:For the wind power DC micro-grid with energy storage components, an energy management optimization model considering the comprehensive operation cost of the energy storage system is proposed. In this model, the cost of energy storage system is considered comprehensively, the economic operation of the system is realized, and the security of the system is guaranteed by the formulation of constraint conditions. The energy optimization management model is solved by adaptive particle swarm optimization (PSO) algorithm, and the simulation model is established based on MATLAB and verified by simulation. The results show that the proposed energy optimization management model can effectively reduce the integrated cost of hybrid energy storage system, and can realize the best operation reference node based on the prediction information, and realize the economical, efficient and stable operation goal of DC micro-grid system.
【作者单位】： 四川大学电气信息学院;
【分类号】：TM73;TP18
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