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Within-day Rolling Optimization of Active Distribution Network with Wind and Photovoltaic Distributed Generation

机译:风力和光伏分布式发电主动配电网的日内滚动优化

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Due to the randomness and uncertainty of wind and solar energy and the change of the active load, the power grid will face great challenges. After large-scale access to the distributed generations, the active distribution network must be optimized. This paper focuses on the within-day rolling optimization of active distribution network. Considering the influence of distribution generation and load characteristics and the randomness of wind and light in the active distribution network, an integrated model of within-day rolling optimization scheduling for active distribution network is established. The output of the distributed generations needs to be controlled. And the three objective functions of the minimum active network loss, the minimum active output reduction rate of controllable power supply and the lowest operating cost are also appropriately optimized. Then, the combination of the improved particle swarm optimization algorithm and the interior point method is beneficial to the calculation of large-scale nonlinear reactive power optimization. Finally, the feasibility of the algorithm and the rapidity of the optimization are verified on the IEEE118 node system. The superiority of the within-day rolling optimization and reactive power optimization algorithm is also confirmed.
机译:由于风能和太阳能的随机性和不确定性以及有功负载的变化,电网将面临巨大的挑战。在大规模访问分布式世代之后,必须优化活动的分布式网络。本文重点研究主动配电网的日内滚动优化。考虑到主动配电网中配电网的产生和负荷特性以及风和光的随机性的影响,建立了主动配电网日内滚动优化调度的集成模型。分布式世代的输出需要被控制。并且,还适当地优化了最小有功网络损耗,可控电源的最小有功输出降低率和最低运行成本这三个目标函数。然后,将改进的粒子群算法与内点法相结合,有利于大规模非线性无功优化的计算。最后,在IEEE118节点系统上验证了该算法的可行性和优化的快速性。还证实了日内滚动优化和无功优化算法的优越性。

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