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Adaptive Critic Design-Based Dynamic Stochastic Optimal Control Design for a Microgrid With Multiple Renewable Resources

机译:具有多种可再生资源的微电网基于自适应批评设计的动态随机最优控制设计

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摘要

This paper proposes a three-layer optimization and an intelligent control algorithm for a microgrid with multiple renewable resources. A dual heuristic dynamic programming-based system control layer is used to ensure the dynamic performance and voltage dynamics of the microgrid as the system operation conditions change. A local layer maximizes the capability of the photovoltaic (PV) wind power generators and battery systems, and a model predictive control-based device layer increases the tracking accuracy of the converter control. The proposed control scheme, system wide adaptive predictive supervisory control (SWAPSC) smooths the output of PV and wind generators under intermittencies, maintains bus voltage by providing dynamic reactive power support to the grid, and reduces the total system losses while minimizing degradation of battery life span. Performance comparisons are made with and without SWAPSC for an IEEE 13 node test system with a PV farm, a wind farm, and two battery-based energy storage systems.
机译:针对具有多种可再生资源的微电网,提出了一种三层优化算法和一种智能控制算法。基于双重启发式动态编程的系统控制层用于确保随着系统操作条件的变化微电网的动态性能和电压动态。局部层使光伏(PV)风力发电机和电池系统的功能最大化,并且基于模型预测控制的设备层提高了转换器控制的跟踪精度。拟议的控制方案,系统范围的自适应预测监督控制(SWAPSC)使间歇性情况下的PV和风力发电机的输出变得平滑,通过为电网提供动态无功功率支持来保持总线电压,并减少了总系统损耗,同时最大程度地降低了电池寿命跨度。对于带有PV场,风场和两个基于电池的储能系统的IEEE 13节点测试系统,是否使用SWAPSC进行了性能比较。

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