Stochastic Contingency Analysis Based on Voltage Stability Assessment in Islanded Power System Considering Load Uncertainty Using MCS and k-PEM

Stochastic Contingency Analysis Based on Voltage Stability Assessment in Islanded Power System Considering Load Uncertainty Using MCS and k-PEM

Farkhondeh Jabari (University of Tabriz, Iran), Heresh Seyedia (University of Tabriz, Iran), Sajad Najafi Ravadanegh (Azarbaijan Shahid Madani University, Iran) and Behnam. Mohammadi Ivatloo (University of Tabriz, Iran)
DOI: 10.4018/978-1-4666-9911-3.ch002
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Abstract

Increased electricity demands and economic operation of large power systems in a deregulated environment with a limited investment in transmission expansion planning causes interconnected power grids to be operated closer to their stability limits. Meanwhile, the loads uncertainty will affect the static and dynamic stabilities. Therefore, if there is no emergency corrective control in time, occurrence of wide area contingency may lead to the catastrophic cascading outages. Studies show that many wide area blackouts which led to massive economic losses may have been prevented by a fast feasible controlled islanding decision making. This chapter introduces a novel computationally efficient approach for separating of bulk power system into several stable sections following a severe disturbance. The splitting strategy reduces the large initial search space to an interface boundary network considering coherency of synchronous generators and network graph simplification. Then, a novel islanding scenario generator algorithm denoted as BEM (Backward Elimination Method) based on PMEAs (Primary Maximum Expansion Areas) has been applied to generate all proper islanding solutions in the simplified network graph. The PPF (Probabilistic Power Flow) based on Newton-Raphson method and Q-V modal analysis has been used to evaluate the steady-state stability of created islands in each generated scenario. BICA (Binary Imperialistic Competitive Algorithm) has then been applied to minimize total load-generation mismatch considering integrity, voltage permitted range and steady-state voltage stability constraints. The best solution has then been applied to split the entire power network. A novel stochastic contingency analysis of islands based on PSVI (Probability of Static Voltage Instability) using MCS (Monte Carlo Simulation) and k-PEM (k-Point Estimate Method) have been proposed to identify the critical PQ buses and severe contingencies. In these approaches, the ITM (Inverse Transform Method) has been used to model uncertain loads with normal probability distribution function in optimal islanded power system. The robustness, effectiveness and capability of the proposed approaches have been validated on the New England 39-bus standard power system.
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Introduction

Power industry restructuring and competition in the deregulated electricity markets to provide increased demand causes operation of large power systems close to their stability boundaries. Although an interconnected power system may be stable against small disturbances, if there is no emergency corrective control to resynchronize all generators and prevent from fault spreading into the entire network, occurrence of large contingency may cause the system to lose stability and even lead to wide area blackout. Studies show that many wide area blackouts such as 2012 India blackout which led to massive economic losses may have been prevented by a fast feasible controlled splitting decision making (Wang, Shao, & Vittal, 2005). Hence, power system islanding is the last defense line to protect power grids from incidence of wide-area blackout. In other words, controlled system islanding also known as controlled system splitting provides the final remedial action against power system major incidence following a severe disturbance. If there is no proper remedial action in time, immediately after occurrence of large disturbance, it may lead to a catastrophic failures and power system blackout. If a system is encountered with severe instability problem, and emergency control fail to bring the faulted system back to the normal state, an islanding strategy executes by splitting the interconnected power network into several islands by disconnecting proper selected transmission lines. Achieving the proper islanding strategy which satisfies all steady-state and dynamic constraints within islands is a complicated scenario. Major efforts are needed to determine a splitting scheme with two following important characteristics (Ibrahim, 2011):

  • When to Split: Islanding starts exactly after separating detection. There are many different techniques to detect the interconnected power system islanding.

  • Where to Split: Many wide area blackouts may have been prevented and load-generation mismatch could have been reduced by fast, accurate, feasible controlled splitting strategies (Andersson et al, 2005; Yang, Vittal & Heydt, 2006).

Controlled intentional islanding separates a bulk power system into a number of stable islands by tripping selected transmission lines according to the minimum load-generation mismatch (L. Liu, W. Liu, Cartes & Chung, 2009). Hence, once separation is detected, the most important step is to find the optimal splitting points. In the literature, several approaches have been proposed to split a large power system into a number of stable sections following a wide area contingency. These procedures can be divided into two general categories. The first one is based on the coherent generators clustering and the second one is based on the network graph theory (Najafi, Hosseinian & Abedi, 2010).

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