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A Multistage Solution Approach for Dynamic Reactive Power Optimization Based on Interval Uncertainty

机译：基于区间不确定性的动态无功优化的多阶段求解方法

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摘要

In order to solve the uncertainty and randomness of the output of the renewable energy resources and the load fluctuations in the reactive power optimization, this paper presents a novel approach focusing on dealing with the issues aforementioned in dynamic reactive power optimization (DRPO). The DRPO with large amounts of renewable resources can be presented by two determinate large-scale mixed integer nonlinear nonconvex programming problems using the theory of direct interval matching and the selection of the extreme value intervals. However, it has been admitted that the large-scale mixed integer nonlinear nonconvex programming is quite difficult to solve. Therefore, in order to simplify the solution, the heuristic search and variable correction approaches are employed to relax the nonconvex power flow equations to obtain a mixed integer quadratic programming model which can be solved using software packages such as CPLEX and GUROBI. The ultimate solution and the performance of the presented approach are compared to the traditional methods based on the evaluations using IEEE 14-, 118-, and 300-bus systems. The experimental results show the effectiveness of the presented approach, which potentially can be a significant tool in DRPO research.
机译：为了解决可再生能源资源输出的不确定性和随机性以及无功优化中的负载波动，本文提出了一种新颖的方法来解决动态无功优化（DRPO）中提到的问题。使用直接区间匹配和极值区间选择的理论，可以通过两个确定的大型混合整数非线性非凸规划问题来表示具有大量可再生资源的DRPO。但是，已经承认，大规模混合整数非线性非凸规划是很难解决的。因此，为了简化解决方案，采用启发式搜索和变量校正方法来放宽非凸型潮流方程，以获得混合整数二次规划模型，可以使用CPLEX和GUROBI等软件包进行求解。基于使用IEEE 14总线，118总线和300总线系统的评估结果，将所提出的方法的最终解决方案和性能与传统方法进行了比较。实验结果表明了该方法的有效性，该方法可能是DRPO研究中的重要工具。

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