This paper presents a combined optimization/reliability technique to evaluate the reliability of large power systems. It uses Monte Carlo simulation for the individual operation/failure random performance of elements of a power network. This simulation overcomes the difficulty in constructing the many possible states for large power systems of complex topology. A simplified power-flow representation of the power network is used and a network reduction is implemented to reduce the size of the power-flow problem, such that only the effective part of the network (for a given contingency) is retained. The control parameters are optimized in order to simulate practical contingency situations in which suitable controls are invoked to preserve, as much as possible, the continuity of supply. The optimization problem is solved by linear programming in which the generator powers are manipulated as optimization variables to maximize the load power supplied and subject to the power flow equations as well as upper and lower bounds on the optimization variables. The outputs of the performance simulation and the optimization problem are subsequently used to compute the system reliability indices. The paper describes the computerized algorithm as well as numerical results for the IEEE 118-bus power system to demonstrate the applicability of the algorithm to actual systems.

Reliability Evaluation for Optimally Operated, Large, Electric Power Systems

Purpose – The purpose of this paper is to present a practical method for computing contingency‐based reliability and quality indices in power systems and to answer questions related to how much the system is reliable, how robust it is in surviving random contingencies, how much it is costing to maintain appropriate system security and reliability levels and, finally, to what extent the desired balance is maintained between generation facilities, transmission capabilities and consumer demand levels in various zones of the electric power system.Design/methodology/approach – The methodology adopted in this paper is based on a combined contingency analysis/reliability evaluation scheme. A three‐component system model is utilized, which can be used effectively for evaluation and sensitivity analysis of reliability and quality in power systems. The model is a reduced (equivalent) system representation that comprises generation, transmission and load components with multi‐state values. The computational scheme p...

Composite reliability and quality assessment of interconnected power systems

The paper summarizes the results of a recent industry supported research and development study in which a novel framework for evaluating meaningful power system reliability and quality indices was developed and applied. The system-wide integrated performance indices are capable of addressing and revealing areas of deficiencies and bottle-necks as well as redundancies in the composite generation–transmission–demand structure of large-scale power grids. The novel technique utilizes a basic linear programming formulation, which offers a general and comprehensive framework to assess the harmony and compatibility of generation, transmission, and demand in a power system. Practical application to a portion of the Saudi power grid is also presented in the paper for demonstration purposes. Copyright © 2010 John Wiley & Sons, Ltd.

Power system performance quality indices

Contingency analysis (CA) is a well-known function in power system planning and operation. In accordance with CA results, the system operator dispenses information regarding static security of the power system (overloads and/or voltage outside tolerable limits). However, classic CA with remedial action schemes cannot distinguish safe operating regimes from potentially dangerous ones in terms of voltage (in)stability. In fact, voltage instability is considered as one of the major threats leading to power system insecurity. Therefore, in this study an enhanced contingency analysis (ECA) is presented where the classical CA is extended with static voltage analysis based on the modal analysis. The article presents a dedicated methodology for the proposed ECA tool, with special emphasis on the analysis of corrective measures provided by the system operator, intended for enhancing power system security (regulation transformer action, distributed generation and energy storage). Also the influence of the load model was analyzed by simulation and the main conclusions are presented. The study demonstrated the advantages that distributed generation resources and energy storage can provide in the context of voltage stability. Also, the simulations acknowledged the importance of correct load modeling, since over or under estimation of a certain load-type component can result in too optimistic or too pessimistic power system operation limits.

https://www.mdpi.com/1996-1073/14/4/923/pdf

Enhanced Contingency Analysis—A Power System Operator Tool

In this paper, we address the risk of hidden N-k line contingencies in power systems by proposing a preventive mitigation strategy to mitigate these hidden contingencies. The strategy comprises a screening model, an evaluation model, and a mitigation cut generating mechanism. Using this strategy, we first screen out the high-risk hidden N-k line contingencies using the screening model, and then mitigate them by iteratively reducing their hidden probabilities assessed in the evaluation model. This is achieved by incorporating mitigation cuts into an enhanced security constrained economic dispatch module, while taking into consideration both reliability and economic criteria. This mitigation strategy can be employed as a preventive action by the system operators. The simulations on the IEEE 118-bus system demonstrate that the proposed approach can reduce the hidden probabilities of these high-risk contingencies below a given threshold with a reasonable increase in the generation cost, and, thus, verify the approach as an effective tool to address the risk of these contingencies.

Preventive Mitigation Strategy for the Hidden N-k Line Contingencies in Power Systems

The loss of load probability (LOLP) represents an important index in the reliability evaluation of electric power systems. The LOLP denotes the probability of customer demand curtailments due to random outages of various system components. A combined optimization/reliability technique is presented in which the system control parameters are optimized. This simulates practical contingency situations where suitable controls are invoked in order to preserve, as much as possible, the continuity of supply. A DC representation of the power network is used and the optimization problem is solved by linear programming. The active component of the net injected power and the voltage angles at all buses represent the optimization variables of the problem. The optimal solution maximizes the load power supplied subject to the power flow equations as well as upper and lower bounds on the optimization variables. A description of the computerized algorithm developed and numerical results for a test power system are also included.

M. A. El-Kady

Papers

Reliability Evaluation for Optimally Operated, Large, Electric Power Systems

Loss of load probability evaluation based on real-time emergency dispatch