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A trust-region based sequential linear programming approach for AC optimal power flow problems

机译:交流最优潮流问题的基于信任域的顺序线性规划方法

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This study proposes a new trust-region based sequential linear programming algorithm to solve the AC optimal power flow (OPF) problem. The OPF problem is solved by linearizing the cost function, power balance and engineering constraints of the system, followed by a trust-region to control the validity of the linear model. To alleviate the problems associated with the infeasibilities of a linear approximation, a feasibility restoration phase is introduced. This phase uses the original nonlinear constraints to quickly locate a feasible point when the linear approximation is infeasible. The algorithm follows convergence criteria to satisfy the first order optimality conditions for the original OPF problem. Studies on standard IEEE systems and large-scale Polish systems show an acceptable quality of convergence to a set of best-known solutions and a substantial improvement in computational time, with linear scaling proportional to the network size.
机译:这项研究提出了一种新的基于信任区域的顺序线性规划算法,以解决交流最优潮流(OPF)问题。通过线性化成本函数,功率平衡和系统工程约束,然后通过信任区域来控制线性模型的有效性,可以解决OPF问题。为了减轻与线性近似的不可行性相关的问题,引入了可行性恢复阶段。当线性逼近不可行时,此阶段使用原始的非线性约束条件快速定位可行点。该算法遵循收敛准则,以满足原始OPF问题的一阶最优性条件。对标准IEEE系统和大规模波兰语系统的研究表明,与一组最著名的解决方案的融合质量令人满意,并且计算时间得到了显着改善,线性缩放比例与网络规模成正比。

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