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首页> 外文期刊>IEEE Transactions on Power Systems >Identification of Umbrella Constraints in DC-Based Security-Constrained Optimal Power Flow
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Identification of Umbrella Constraints in DC-Based Security-Constrained Optimal Power Flow

机译:基于DC的安全约束的最佳潮流中的伞约束识别

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Security-constrained optimal power flow (SCOPF) problems are essential tools to transmission system operators for long-term and operational planning and real-time operation. The general goal of SCOPF problems is to optimize electricity network operation while ensuring that operational and planning decisions are consistent with technical limits under both pre- and post-contingency states. The solution of SCOPF problems is challenging because of the inherent size and scope of modern grids. As empirical evidence and longstanding operator experience show, relatively few of the constraints of SCOPF problems actually serve to enclose their feasible region. Hence, all those constraints not contributing directly to set up the SCOPF feasible space are superfluous and could be discarded. In light of this observation, this paper proposes an optimization-based approach for identifying so-called umbrella constraints in SCOPF problems where the network operation is approximated by the dc power flow. Umbrella constraints are constraints which are necessary and sufficient to the description of the feasible set of an SCOPF problem. The resulting umbrella constraint discovery problem (UCD) is a convex optimization problem with a linear objective function. For SCOPF problems of practical importance, the UCD is also quite large and requires the use of a decomposition technique. In this paper, we concentrate on an SCOPF formulation for preventive security generation dispatch. We show that by removing superfluous constraints, the resulting sizes of SCOPF problems are much smaller and can be solved significantly faster.
机译:受安全约束的最佳潮流(SCOPF)问题是传输系统运营商进行长期和运营计划以及实时运营的基本工具。 SCOPF问题的总体目标是优化电网运行,同时确保运行和规划决策与应急前和应急后状态下的技术限制相一致。由于现代电网固有的尺寸和范围,解决SCOPF问题具有挑战性。正如经验证据和长期的操作员经验所表明,SCOPF问题的约束相对较少,实际上只能用来围住它们的可行区域。因此,所有不直接有助于建立SCOPF可行空间的约束都是多余的,可以丢弃。根据这一观察结果,本文提出了一种基于优化的方法,用于在SCOPF问题中识别所谓的伞式约束,在该问题中,网络运行由直流潮流估算。伞约束是描述SCOPF问题的可行集所必需和充分的约束。结果伞约束发现问题(UCD)是具有线性目标函数的凸优化问题。对于具有实际重要性的SCOPF问题,UCD也相当大,需要使用分解技术。在本文中,我们专注于SCOPF公式以进行预防性安全生成调度。我们表明,通过消除多余的约束,SCOPF问题的结果大小要小得多,并且可以更快地解决。

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