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Proceedings ArticleDOI

Solving optimum power flow in dynamic environments to minimize tracking errors using dynamic bacterial foraging algorithm

01 Dec 2013-pp 1-8
TL;DR: A new optimization algorithm is presented for solving an optimal power flow problem with dynamic condition and results show that modified DBFA can adapt to various environmental changes which occur in different scenario, than using BFA and PSO.
Abstract: In this paper, a new optimization algorithm is presented for solving an optimal power flow problem with dynamic condition. Many artificial intelligence techniques have been developed for solving steady state environment of power system problems. In that, Bacterial Foraging Algorithm is one of the evolutionary algorithms which can be used to tackle the OPF problem for static environment. In real time scenario, the power flow in a power system has never been in a static state, as there always are changes in loads and system topology. Hence results using static environment cannot be trusted for dynamic environments. Based on the original BFA, Dynamic Bacterial Foraging Algorithm has been studied for the problem of OPF with dynamic loads and some modifications have been done to make this modified DBFA technique simple and efficient. This approach has been examined and evaluated on standard IEEE 30 Bus Test system. The simulation studies offer a range of changes in dynamic environment and results show that modified DBFA can adapt to various environmental changes which occur in different scenario, than using BFA and PSO.
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Journal ArticleDOI
TL;DR: In order to meet power needs, with concern for economics and environment, wind energy conversion is gradually gaining interest as a suitable source of renewable energy to maximize the power extraction from the wind, optimization techniques are used at the various module of a wind farm starting from wind farm design for siting, sizing, optimal placement and sizing of distributed generation (DG) sources, generation scheduling, tuning of PID controller, control of WECS etc as mentioned in this paper.
Abstract: In order to meet power needs, with concern for economics and environment, wind energy conversion is gradually gaining interest as a suitable source of renewable energy To maximize the power extraction from the wind, optimization techniques are used at the various module of a wind farm starting from wind farm design for siting, sizing, optimal placement and sizing of distributed generation (DG) sources, generation scheduling, tuning of PID controller, control of wind energy conversion system (WECS) etc This paper mainly focuses on the optimization algorithms (mostly the swarm based) in relation to integration of the wind farm with the grid The paper here gives a precise idea about different optimization techniques, their advantage and disadvantage with respect to a wind farm This review will enable the researchers to open the mind to explore possible applications in this field as well as beyond this area

85 citations

References
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Book
01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Abstract: From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields Major concepts are illustrated with running examples, and major algorithms are illustrated by Pascal computer programs No prior knowledge of GAs or genetics is assumed, and only a minimum of computer programming and mathematics background is required

52,797 citations

Book
01 Jan 2002

17,039 citations

Journal ArticleDOI
TL;DR: In this paper, an evolutionary-based approach to solve the optimal power flow (OPF) problem is presented. And the proposed approach has been examined and tested on the standard IEEE 30bus test system with different objectives that reflect fuel cost minimization, voltage profile improvement, and voltage stability enhancement.

1,209 citations


"Solving optimum power flow in dynam..." refers methods in this paper

  • ...5.3 Load Variation on Single Bus BFA, DBFA and PSO are evaluated using MATLAB....

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  • ...In our case, the ideal cost is obtained using PSO which calculates the optimal objective function as a static optimization problem in the new environment in which the values of load changes have been updated....

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  • ...978-1-4799-3506-2/13/$31.00 ©2013 IEEE] The simulation results, obtained by evaluating DBFA in comparison with BFA and PSO under the scenarios mentioned above, have been presented and discussed....

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  • ...In this case, PSO fails to respond to the changes most of the time, with a constantly decreasing performance....

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  • ...The simulation studies offer a range of changes in dynamic environment and results show that modified DBFA can adapt to various environmental changes which occur in different scenario, than using BFA and PSO....

    [...]

Journal ArticleDOI
01 Feb 2000
TL;DR: Three very different methods of accomplishing the same task-managing the operation of the transmission system in the deregulated power system operating environment-have been implemented as deregulated market structures have been created around the world.
Abstract: Three very different methods of accomplishing the same task-managing the operation of the transmission system in the deregulated power system operating environment-have been implemented as deregulated market structures have been created around the world. They are first, the optimal power flow (OPF) model found in various implementations in the United Kingdom, parts of the United States, and in Australia and New Zealand. Second, the point tariff, price area congestion control model used in the Nordpool market area in Norway and Sweden. Third, the US transaction-based model. All are pragmatic solutions implemented in advance of complete theoretical understanding. Each has strengths and flaws, and there are some surprising inter-relationships. Each maintains power system security but differs in its impact on the economics of the energy market. No clearly superior method has so far emerged. In the future, methods of combining decentralized market solutions with operational use of optimal power flow may provide better solutions to existing and emerging problems.

852 citations

Journal ArticleDOI
TL;DR: In this paper, a direct simultaneous solution for all of the unknowns in the Lagrangian function on each iteration is proposed, where each iteration minimizes a quadratic approximation of the Lagrangeian.
Abstract: The classical optimal power flow problem with a nonseparable objective function can be solved by an explicit Newton approach. Efficient, robust solutions can be obtained for problems of any practical size or kind. Solution effort is approximately proportional to network size, and is relatively independent of the number of controls or binding inequalities. The key idea is a direct simultaneous solution for all of the unknowns in the Lagrangian function on each iteration. Each iteration minimizes a quadratic approximation of the Lagrangian. For any given set of binding constraints the process converges to the Kuhn-Tucker conditions in a few iterations. The challenge in algorithm development is to efficiently identify the binding inequalities.

817 citations