A Set of Novel Global Sensitivity Analysis Indices for Probabilistic Static Voltage Stability Assessment With Correlated Uncertainty Sources

IEEE Transactions on Power Systems, vol. 39, pp. 2543–2557

Abstract

Global sensitivity analysis (GSA) can measure the contributions of emerging uncertainty sources as random inputs for the probabilistic static voltage stability assessment (PSVSA). The correlation among these random inputs in power systems is significant and inherent, however, the importance of such correlated uncertainty sources has not been thoroughly and deeply interpreted by the existing GSA methods. To fill this gap, an innovative variance-based GSA approach is proposed herein. At the initial step, orthogonalization independence transformation (OIT) technology is introduced to transform these correlated random inputs into the independent ones with orthogonality. Based on these, a new set of univocal sensitivity indices (SI), including uncorrelated marginal contribution, data correlation contribution, physical interaction contribution, and a whole effect contribution from them together, are defined accordingly. To achieve an acceptable computational burden, two strategies are proposed to determine these novel SI, which are efficient for both low-dimensional and high-dimensional inputs, respectively. At last, the proposed GSA approach is tested on the modified IEEE 5-bus and IEEE 118-bus systems, through which its effectiveness and superiority are verified, compared to the existing GSA approaches in tackling the correlated uncertainty sources of PSVSA.

Authors 6

1. Sui Peng

   Chongqing University · Guangdong Power Grid Company (China) · China Southern Power Grid (China)

   Affiliation as printed

   State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China

   Grid Planning and Research Center, Guangdong Power Grid Corporation, CSG, Guangzhou, China

2. Xingyu Lin

   Chongqing University

   Affiliation as printed

   State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China

3. Junjie Tang

   Chongqing University

   Affiliation as printed

   State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China

4. Kaigui Xie

   Chongqing University

   Affiliation as printed

   State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing, China

5. Ferdinanda Ponci Aachen Institute for Automation of Complex Power Systems of the E.ON Energy Research Center

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems of the E.ON Energy Research Center, RWTH Aachen University, Aachen, Germany

6. Antonello Monti Aachen Institute for Automation of Complex Power Systems of the E.ON Energy Research Center

   RWTH Aachen University · Fraunhofer Institute for Applied Information Technology

   Affiliation as printed

   Institute for Automation of Complex Power Systems of the E.ON Energy Research Center, RWTH Aachen University, Aachen, Germany

   Digital Energy Fraunhofer FIT, Aachen, Germany