An evolutionary algorithm for consumer welfare optimisation of a contingent power network
03 Nov 2011-pp 504-508
TL;DR: An evolutionary optimization technique based methodology has been proposed to sustain the total generation cost even in contingent states of a power network for consumer welfare and can improve the operating conditions of the system apart from optimizing the price volatility of electrical power market.
Abstract: An evolutionary optimization technique based methodology has been proposed in this paper to sustain the total generation cost even in contingent states of a power network for consumer welfare. The alteration of generation cost during contingency is quite evident which makes the consumers suffer economically due to rise of the level of congestion and price of electricity. The aim of this proposed methodology is to minimize the deviations of generation cost, during contingency, from a preferred value by re-allocation of generation schedule with a controlled load curtailment technique and hence relieving the lines from overloading for congestion management. It has been demonstrated that, on application, the proposed methodology can improve the operating conditions of the system apart from optimizing the price volatility of electrical power market. The methodology has been tested on a standard benchmark system and the comprehensive simulation results looked promising.
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09 Oct 2016
TL;DR: In this paper, the authors reviewed some congestion management (CM) methods including the nodal pricing method, differential evolution (DE), addition of renewable energy sources, extended quadratic interior point (EQIP) based OPF, mixed integer nonlinear programming, particle swarm optimization (PSO), cost free methods and genetic algorithm (GA).
Abstract: In a deregulated power market, the optimum power flow (OPF) for an interconnected grid system is an important concern as related to transmission loss and operating constraints of power network. The increased power transaction as related to increased demand and satisfaction of those demand to the competition of generation companies (GENCOs) are resulting the stress on power network which further causes the danger to voltage security, violation of limits of line flow, increase in the line losses, large requirement of reactive power, danger to power system stability and over load of the lines i.e. congestion of power in system. It can be managed by rescheduling of generators or optimal location of distributed generation (DG) at minimum cost with minimum loss without disturbing the operating constraints. This paper reviews some of congestion management (CM) methods including the nodal pricing method, differential evolution (DE), addition of renewable energy sources, extended quadratic interior point (EQIP) based OPF, mixed integer nonlinear programming, particle swarm optimization (PSO), cost free methods and Genetic Algorithm (GA). Each technique has its own significance and potential for promotion of rescheduling of generators in a deregulated power system.
4 citations
References
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TL;DR: In this paper, a robust and efficient method for solving TSCOPF problems based on differential evolution (DE) is developed, which is a new branch of evolutionary algorithms with strong ability in searching global optimal solutions of highly nonlinear and nonconvex problems.
Abstract: Consideration of transient stability constraints in optimal power flow (OPF) problems is increasingly important because modern power systems tend to operate closer to stability boundaries due to the rapid increase of electricity demand and the deregulation of electricity markets. Transient stability constrained OPF (TSCOPF) is however a nonlinear optimization problem with both algebraic and differential equations, which is difficult to be solved even for small power systems. This paper develops a robust and efficient method for solving TSCOPF problems based on differential evolution (DE), which is a new branch of evolutionary algorithms with strong ability in searching global optimal solutions of highly nonlinear and nonconvex problems. Due to the flexible properties of DE mechanism, the hybrid method for transient stability assessment, which combines time-domain simulation and transient energy function method, can be employed in DE so that the detailed dynamic models of the system can be incorporated. To reduce the computational burden, several strategies are proposed for the initialization, assessment and selection of solution individuals in evolution process of DE. Numerical tests on the WSCC three-generator, nine-bus system and New England ten-generator, 39-bus system have demonstrated the robustness and effectiveness of the proposed approach. Finally, in order to deal with the large-scale system and speed up the computation, DE is parallelized and implemented on a Beowulf PC-cluster. The effectiveness of the parallel DE approach is demonstrated by simulations on the 17-generator, 162-bus system.
257 citations
"An evolutionary algorithm for consu..." refers background in this paper
...DE has drawn an increasing attention for a wide variety of engineering applications including power engineering applications such as transient stability, economic dispatch etc [12-16]....
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TL;DR: In this paper, a multiobjective particle swarm optimization (MOPSO) method is used to solve the complex nonlinear optimization problem of load flow in power transmission networks, which considers the voltage and frequency dependence of loads and generator regulation characteristics.
Abstract: This paper presents an effective method of congestion management in power systems. Congestions or overloads in transmission network are alleviated by generation rescheduling and/or load shedding of participating generators and loads. The two conflicting objectives 1) alleviation of overload and 2) minimization of cost of operation are optimized to provide pareto-optimal solutions. A multiobjective particle swarm optimization (MOPSO) method is used to solve this complex nonlinear optimization problem. A realistic frequency and voltage dependent load flow method which considers the voltage and frequency dependence of loads and generator regulation characteristics is used to solve this problem. The proposed algorithm is tested on IEEE 30-bus system, IEEE 118-bus system, and Northern Region Electricity Board, India (NREB) 390-bus system with smooth as well as nonsmooth cost functions due to valve point loading effect.
230 citations
"An evolutionary algorithm for consu..." refers methods in this paper
...Different multi-objective PSO based algorithms for congestion management are presented in [7, 8, 9]....
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TL;DR: The results show that the proposed contingency filtering techniques lead to faster solution of the PSCOPF, while being more robust and meaningful, than severity-index based ones.
Abstract: This paper focuses on contingency filtering to accelerate the iterative solution of preventive security-constrained optimal power flow (PSCOPF) problems. To this end, we propose two novel filtering techniques relying on the comparison at an intermediate PSCOPF solution of post-contingency constraint violations among postulated contingencies. We assess these techniques by comparing them with severity index-based filtering schemes, on a 60-and a 118-bus system. Our results show that the proposed contingency filtering techniques lead to faster solution of the PSCOPF, while being more robust and meaningful, than severity-index based ones.
163 citations
"An evolutionary algorithm for consu..." refers background in this paper
...The Security Constraints Optimal Power Flow (SCOPF), however, is capable of managing congestion during contingency but it fails to limit the variations of generation cost in varying conditions of markets [4]....
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TL;DR: In this paper, a method of congestion management by generation rescheduling and load shedding is described, where the sensitivities of the overloaded lines to bus injections and the costs of generation and Load shedding are considered for ranking the generation and load buses.
147 citations
"An evolutionary algorithm for consu..." refers background in this paper
...Congestion management based on optimum generation rescheduling and load shedding schemes are reported in [5], [6]....
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01 Nov 2001
TL;DR: It is shown that the search-space expansion scheme can enhance the possibility of converging to a global optimum in the DE search and the chosen frequency-domain error criterion make the proposed approach quite efficacious for optimally approximating unstable and/or nonmimimum-phase linear systems.
Abstract: The problem of optimally approximating linear systems is solved by a differential evolution algorithm (DEA) incorporating a search-space expansion scheme. The optimal approximate rational model with/without a time delay for a system described by its rational or irrational transfer function is sought such that a frequency-domain L/sup 2/-error criterion is minimized. The distinct feature of the proposed model approximation approach is that the search-space expansion scheme can enhance the possibility of converging to a global optimum in the DE search. This feature and the chosen frequency-domain error criterion make the proposed approach quite efficacious for optimally approximating unstable and/or nonmimimum-phase linear systems. The simplicity and robustness of the modified DEA in terms of easy implementation and minimum assumptions on search space are demonstrated by two numerical examples.
117 citations
"An evolutionary algorithm for consu..." refers background in this paper
...DE has drawn an increasing attention for a wide variety of engineering applications including power engineering applications such as transient stability, economic dispatch etc [12-16]....
[...]