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Wide area measurement systems based Power System State Estimation using a Robust Linear-Weighted Least Square method

机译:基于广域测量系统的电力系统状态估计,使用鲁棒线性加权最小二乘法

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摘要

The accuracy and robustness of Power System State Estimation (PSSE) are paramount for monitoring and surveillance of Energy Management Systems (EMS). To enhance the PSSE accuracy, phasor measurement units (PMUs) are widely used in Wide-area measurement systems (WAMS). The essential aspects of enhancing PSSE accuracy are systems observability and redundancy. These can be accomplished through an optimal PMU placement strategy. Iterative-based algorithms for estimating power system states using PMU and traditional Supervisory Control and Data Acquisition (SCADA) measurements face challenges such as non-linearity and lack of convergence. In this paper, a Robust Linear Weighted Least Square (RLWLS) estimator is proposed by combining conventional SCADA data with phasor measurements. Further, The RLWLS state estimator overcomes the issues mentioned above. Extensive simulations on various test systems, including traditional IEEE 14, 30, 57, and IEEE-118 bus systems and the real-time Indian Northern Region Power Grid (INRPG)-246 bus system in India, have shown to prove the resilience of this technique. Finally, compared to the prior PSSE approaches, the RLWLS methodology significantly improves the efficacy and performance of the state estimate solution.
机译:电力系统状态估计 (PSSE) 的准确性和鲁棒性对于能源管理系统 (EMS) 的监测和监视至关重要。为了提高PSSE精度,相量测量单元(PMU)广泛用于广域测量系统(WAMS)。提高PSSE精度的基本方面是系统的可观测性和冗余性。这些可以通过最佳的PMU放置策略来实现。使用PMU和传统监控和数据采集(SCADA)测量估计电力系统状态的基于迭代的算法面临着非线性和缺乏收敛性等挑战。本文将常规SCADA数据与相量测量相结合,提出了一种鲁棒线性加权最小二乘法(RLWLS)估计器。此外,RLWLS 状态估计器克服了上述问题。对各种测试系统(包括传统的 IEEE 14、30、57 和 IEEE-118 总线系统以及印度的实时印度北部地区电网 (INRPG)-246 总线系统)的广泛仿真已证明该技术的弹性。最后,与之前的PSSE方法相比,RLWLS方法显著提高了状态估计解决方案的功效和性能。

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