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Proceedings ArticleDOI

An evolutionary algorithm for consumer welfare optimisation of a contingent power network

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.
Citations
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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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Book ChapterDOI
01 Jan 2005
TL;DR: An overview of differential evolution is provided and it is presented as an alternative to evolutionary algorithms with two application examples in power systems.
Abstract: As a relatively new population based optimization technique, differential evolution has been attracting increasing attention for a wide variety of engineering applications including power engineering Unlike the conventional evolutionary algorithms which depend on predefined probability distribution function for mutation process, differential evolution uses the differences of randomly sampled pairs of objective vectors for its mutation process Consequently, the object vectors' differences will pass the objective functions topographical information toward the optimization process, and therefore provide more efficient global optimization capability This paper aims at providing an overview of differential evolution and presenting it as an alternative to evolutionary algorithms with two application examples in power systems

86 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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Journal ArticleDOI
TL;DR: In this paper, the authors presented a methodology based on ac power transfer distribution factors to allocate the MW load- ing on transmission lines, which has been derived using sensitivity properties of Newton Raphson load flow Jacobian at a base case load flow result.
Abstract: The ability to allocate the MW loading on transmission lines and group of lines is the basis of NERC's "flow-based" transmis- sion allocation system (1) In such a system, MW flows must be allo- cated to each line or group of lines in proportion to MWs being transmitted by each transaction This letter presents a methodology based on ac power transfer distribution factors to allocate the MW load- ing on transmission lines The ac power transfer distribution factors have been derived using sensitivity properties of Newton Raphson load flow Jacobian at a base case load flow result A 75-bus Indian power system network has been used to demonstrate the effectiveness of the proposed method

59 citations

Journal ArticleDOI
TL;DR: In this article, the authors presented a methodology based on AC power transfer distribution factors to allocate the MW loading on transmission lines and group of lines is the basis of NERC's "flow-based" transmission allocation system.
Abstract: The ability to allocate the MW loading on transmission lines and group of lines is the basis of NERC's "flow-based" transmission allocation system. In such a system, MW flows must be allocated to each line or group of lines in proportion to MWs being transmitted by each transaction. This letter presents a methodology based on AC power transfer distribution factors to allocate the MW loading on transmission lines. The AC power transfer distribution factors have been derived using sensitivity properties of Newton Raphson load flow Jacobian at a base case load flow result. A 75-bus Indian power system network has been used to demonstrate the effectiveness of the proposed method.

53 citations

Proceedings ArticleDOI
11 Dec 2005
TL;DR: The aim of the proposed work is to minimize deviations from transaction schedules and hence the congestion cost, using the Cluster based congestion management method.
Abstract: In this Paper, a Cluster based congestion management has been presented. The Paper is concerned with the Real and Reactive power rescheduling problem in a deregulated market environment. The aim of the proposed work is to minimize deviations from transaction schedules and hence the congestion cost. The TCSC maximizes the power transfer capability between a specific power seller and a power buyer in a network. The TCSC is installed in the most congested lines and analyzed. The method is formulated as a stochastic optimization problem and is solved by Particle Swarm Optimization. The algorithm is illustrated using New England 39-bus system.

22 citations

Journal ArticleDOI
TL;DR: The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.
Abstract: In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. This paper proposes an algorithm for congestion management in a pool based electricity market based on differential evolution (DE). The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost. Numerical results on test system namely IEEE 30 Bus System is presented for illustration purpose and the results are compared with Particle swarm optimization (PSO) in terms of solution quality. The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.

18 citations


"An evolutionary algorithm for consu..." refers background in this paper

  • ...Hence management of dispatch and determination of price of electricity are among important control activities in a power system [1]....

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