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A Lagrange Multiplier Based State Enumeration Reliability Assessment for Power Systems With Multiple Types of Loads and Renewable Generations

Zeyu Liu, Kai Hou, Hongjie Jia, Junbo Zhao, Dan Wang, Yunfei Mu, Lewei Zhu

2020IEEE Transactions on Power Systems69 citationsDOI

Abstract

With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impact-increment method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy.

Topics & Concepts

Lagrange multiplierElectric power systemEnumerationMultiplier (economics)Renewable energyMathematical optimizationEconomic dispatchWind powerPhotovoltaic systemComputer sciencePower flowMathematicsPower (physics)EngineeringElectrical engineeringQuantum mechanicsCombinatoricsPhysicsEconomicsMacroeconomicsPower System Reliability and MaintenanceOptimal Power Flow DistributionElectric Power System Optimization