Linearized Optimization for Reactive Power Dispatch at Transmission Grid Level considering Discrete Transformer Tap-Settings

Neelotpal Majumdar, Marcel Sarstedt, T. Leveringhaus, L. Hofmann
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Abstract

Research indicates that an efficient operation of power systems, requires the use of optimization techniques for minimizing objectives such as grid losses, dispatch costs, reducing potential technical constraint violations etc. These are referred to as optimal power flow (OPF) techniques. Over the years different optimization techniques have been developed based on analytical methods, heuristics and stochastic based approaches. Analytical methods include for example linear and quadratic optimization approaches. Metaheuristic methods like Particle Swarm optimization (PSO) and Genetic Algorithms (GA) have also been developed and researched upon. In this paper, a successive mixed integer linear optimization programming (sMILP) based method in the context of optimal reactive power flow (ORPF) is developed considering continuous reactive power flexibilities and discrete transformer tap-sets. The novel formulation of the transformer tap sensitivities indicate its efficiency of using discrete tap-settings and ease of implementation in the context of Linear Programming. This method is further compared to an already established PSO-based method subject to similar initial grid conditions and three different voltage constraint violation case studies. Results indicate the reliability and efficiency of the method.
考虑离散变压器分接设置的输电网级无功调度线性化优化
研究表明,电力系统的有效运行,需要使用优化技术来最小化目标,如电网损耗,调度成本,减少潜在的技术约束违规等。这些被称为最优潮流(OPF)技术。多年来,基于分析方法、启发式方法和基于随机方法的不同优化技术得到了发展。分析方法包括线性和二次优化方法。粒子群优化(PSO)和遗传算法(GA)等元启发式方法也得到了发展和研究。本文在考虑连续无功柔性和离散变压器分接集的情况下,提出了一种基于连续混合整数线性优化规划的最优无功潮流求解方法。变压器抽头灵敏度的新公式表明其使用离散抽头设置的效率和易于在线性规划的背景下实现。在相似的初始电网条件和三种不同电压约束违反情况下,进一步将该方法与已经建立的基于pso的方法进行了比较。结果表明了该方法的可靠性和有效性。
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