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Multi-objective Interval Optimization of Virtual Power Plant Considering the Uncertainty of Source and Load

机译:考虑源和负荷不确定性的虚拟电厂的多目标间隔优化

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As the proportion of electric vehicles and distributed power sources connected to the power grid continues to increase, virtual power plants provide new ideas for effectively solving electric vehicles and distributed power sources connected to the grid. Considering that there are obvious uncertainties in the number of dispatchable electric vehicles and the output of distributed power sources, this paper focuses on the multi-objective interval optimization problem of virtual power plants considering the uncertainty of source load. Based on the analysis of the virtual power plant architecture, aiming at the uncertainty of the source load, a multi-objective interval optimization model of the virtual power plant was established using the interval number theory; in order to verify the validity of the established model, a virtual power plant in a certain area was selected as an example for analysis. The results show that the uncertainty of distributed power sources and electric vehicles can be better avoided in the interval optimization process, and the proposed scheme has strong robustness.
机译:随着连接到电网的电动车辆和分布式电源的比例继续增加,虚拟发电厂提供了有效解决电动车辆和连接到电网的分布式电源的新思路。考虑到分配电动车辆数量和分布式电源的产出存在明显的不确定性,专注于考虑到源负荷不确定性的虚拟发电厂的多目标区间优化问题。基于对虚拟电厂架构的分析,旨在源于源负荷的不确定性,使用间隔数理论建立了虚拟电厂的多目标区间优化模型;为了验证已建立的模型的有效性,选择某个区域中的虚拟发电厂作为分析示例。结果表明,在间隔优化过程中可以更好地避免分布式电源和电动车辆的不确定性,并且该方案具有强大的鲁棒性。

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