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Joint International Conference on Power Systems Technology (POWERCON)/IEEE Power India Conference

作者： Vaisakh, K. Srinivas, L. R. Andhra Univ Dept Elect Engn Autonomous Coll Engn Visakhapatnam 530003 Andhra Pradesh India SRKR Engn Dept Elect Engn Bhimavaram 534204 AP India

ISBN: (纸本)9781424417636

An efficient evolutionary-based approach, termed as Differential Evolution (DE), is presented for the solution of Optimal Power Flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary, programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.

关键词： Conventional and non-conventional cost characteristics differential evolution evolutionary programming optimal power flow

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Comparison of Intelligent Techniques to Solve Economic Load Dispatch with Bilateral and Multilateral Transactions

Comparison of Intelligent Techniques to Solve Economic Load ...

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IEEE Region 10 Conference (TENCON 2008)

作者： Raglend, I. Jacob Karthikeyan, P. Sudheera Sailaja Sowjanya Kothari, D. P. Vellore Inst Technol Sch Elect Sci Vellore 632014 Tamil Nadu India Vellore Inst Technol FNAE FNASC SMIEEE Vellore 632014 Tamil Nadu India

ISBN: (纸本)9781424424085

One of the most challenging operational aspects in restructured systems with open transmission access is the power management of the grid. With the trend of an increasing number of bilateral and multilateral transactions submitted to the Independent System Operator (ISO), the possibility of insufficient resources in the transmission system may be unavoidable. In this paper, evolutionary computation techniques such as Genetic Algorithm (GA), evolutionary programming (EP), Particle Swarm Optimization (PSO), Differential Evolution (DE), are applied to solve the economic load dispatch problem with bilateral and multilateral transactions. Different evolutionary Computation methods are applied to obtain ELD solutions for IEEE 30-bus system. The results obtained by this approaches are compared with respect to solution time, production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic environment. The algorithm and simulation are carried using Matlab software.

关键词： Economic Load Dispatch Genetic Algorithm evolutionary programming Particle Swarm Optimization and Differential Evolution Bilateral Multilateral Transactions

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evolutionary programming using mutations based on the Levy probability distribution

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IEEE TRANSACTIONS ON evolutionary COMPUTATION 2004年第1期8卷 1-13页

作者： Lee, CY Yao, X Kongju Natl Univ Dept Ind Informat Chungnam 340802 South Korea Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

\This paper studies evolutionary programming with mutations based on the Levy probability distribution. The Levy probability distribution has an infinite second moment and is, therefore, more likely to generate an offspring that is farther away from its parent than the commonly employed Gaussian mutation. Such likelihood depends on a parameter alpha in the Levy distribution. We propose an evolutionary,programming algorithm using adaptive as well as nonadaptive Levy mutations. The proposed algorithm was applied to multivariate functional optimization. Empirical evidence shows that, in the case of functions having many local optima, the performance of the proposed algorithm was better than that of classical evolutionary programming using Gaussian mutation.

关键词： evolutionary optimization evolutionary programming Levy mutation Levy probability distribution mean-square displacement

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evolutionary programming based security constrained optimal power flow

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ELECTRIC POWER SYSTEMS RESEARCH 2004年第2期72卷 137-145页

作者： Somasundaram, P Kuppusamy, K Devi, RPK Anna Univ Dept Elect & Elect Engn Madras 600025 Tamil Nadu India

This paper presents an algorithm for solving security constrained optimal power flow problem through the application of evolutionary programming (EP). The controllable system quantities in the base-case state are optimised to minimize some defined objective function subject to the base-case operating constraints as well as the contingency-case security constraints. An IEEE 30-bus system is taken for investigation. The security constrained optimal power flow results obtained using EP are compared with those obtained using conventional security constrained optimal power flow. The investigations reveal that the proposed algorithm is relatively simple, reliable and efficient and suitable for on-line applications. (C) 2004 Elsevier B.V. All rights reserved.

关键词： optimal power flow evolutionary programming security constraints

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Design of Grid-Connected Induction Generators for Variable Speed Wind Power Generation

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INTERNATIONAL ENERGY JOURNAL 2008年第1期9卷 59-64页

作者： Balamurugan, K. Slochanal, S. M. R. Amutha, N. BMC Acad Bukit Merah Town Ctr Block 16203-03555 Singapore 150162 Singapore Thiagarajar Coll Engn Madurai 15 Tamil Nadu India PSR Engn Coll Sivakasi 626140 Tamil Nadu India

Commonly standard induction machines are used for both constant speed (CS) and variable speed (VS) wind power generation. But the operational conditions of an induction machine for VS wind power generation are different from CS wind power generation and motor applications. This paper considers the operating condition of VS wind energy conversion system (WECS) in maximum power tracking mode for the exclusive design of squirre-cage induction generator for VSWECS. In such a case, the induction machine always operate at a point close to the maximum torque and maximum efficiency. As a result, these maximums can be introduced to the sizing equations in place of conventionally defined rated efficiency, power factor and starting torque. This design strategy leads to downsizing of induction machine without sacrificing its capacity and performance. evolutionary programming in MATLAB 6.5 platform was used as a design optimization tool.

关键词： evolutionary programming grid-connected squirrel-cage induction generators no-load losses optimum slip reactive power size

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Multiobjective generation scheduling of fixed head hydrothermal power systems through an interactive fuzzy satisfying method and evolutionary programming technique

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2004年第12期32卷 1287-1299页

作者： Basu, A Jadavpur Univ Dept Power Plant Engn Kolkata 700032 W Bengal India

This article presents evolutionary programming based on interactive fuzzy satisfying method for multiobjective generation scheduling of fixed head hydro plants and thermal plants with nonsmooth fuel cost and emission level functions. The multiobjective problem is formulated considering two objectives;(1) economy, and (2) emission. These two objectives are mutually conflicting and equally important. Assuming that the decision maker (DM) has imprecise or fuzzy goals for each of the objective functions, the multiobjective problem is transformed into a minimax problem, which is then handled by the evolutionary programming technique. The solution methodology can offer a global or near-global noninferior solution for the DM. Numerical results for a sample test system have been presented to demonstrate the performance and applicability of the proposed method. The results obtained from the proposed method are compared to those found by interactive fuzzy satisfying method based on simulated annealing technique.

关键词： decision maker evolutionary programming fixed head fuzzy satisfying method hydrothermal system membership function multiobjective

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An evolutionary programming-based tabu search method for solving the unit commitment problem

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IEEE TRANSACTIONS ON POWER SYSTEMS 2004年第1期19卷 577-585页

作者： Rajan, CCA Mohan, MR Pondicherry Engn Coll Dept Elect & Elect Engn Pondicherry 605014 India Anna Univ Sch Elect Engn Madras 600025 Tamil Nadu India

This paper presents a new approach to solving the short-term unit commitment problem using an evolutionary programming-based tabu search (TS) method. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next H hours. evolutionary programming, which happens to be a global optimization technique for solving unit commitment problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all of the units according to their initial status ("flat start"). Here, the parents are obtained from a predefined set of solutions (i.e., each and every solution is adjusted to meet the requirements). Then, a random decommitment is carried out with respect to the unit's minimum downtimes, and TS improves the status by avoiding entrapment in local minima. The best population is selected by evolutionary strategy. The Neyveli Thermal Power Station (NTPS) Unit-II in India demonstrates the effectiveness of the proposed approach;extensive studies have also been performed for different power systems consisting of 10, 26, and 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using the evolutionary programming method and other conventional methods like dynamic programming, Lagrangian relaxation, and simulated annealing and tabu search in reaching proper unit commitment.

关键词： dynamic programming evolutionary programming Lagrangian relaxation Tabu search unit commitment

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Long-period fiber grating filter synthesis using evolutionary programming

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FIBER AND INTEGRATED OPTICS 2004年第4期23卷 249-261页

作者： Lee, CL Lai, YC Natl Chiao Tung Univ Inst Electroopt Engn Hsinchu Taiwan Natl United Univ Dept Electroopt Engn Miaoli Taiwan

An innovative algorithm based on the evolutionary programming (EP) method is developed for the synthesis of long-period fiber gratings (LPGs). The proposed method exhibits a number of attractive features that prove to be effective for solving the inverse design problems of LPGs. The basics of EP are reviewed and the detailed programming procedures of the proposed algorithm are presented. A new mutation process using the concepts of leveled adjustment and adaptive weighting factor is proposed and verified. Comprehensive numerical results on designing practical LPG filters are presented to demonstrate the feasibility and the effectiveness of the proposed algorithm.

关键词： long-period fiber gratings inverse design evolutionary programming

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Economic dispatch with prohibited operating zones using fast computation evolutionary programming algorithm

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ELECTRIC POWER SYSTEMS RESEARCH 2004年第3期70卷 245-252页

作者： Somasundaram, P Kuppusamy, K Devi, RPK Anna Univ Sch Elect & Elect Engn Power Syst Engn Div Madras 600025 Tamil Nadu India

This paper presents an efficient and simple approach for solving the economic dispatch (ED) problem with units having prohibited operating zones. The operating region of the units having prohibited zones is broken into isolated feasible sub-regions which results in multiple decision spaces for the economic dispatch problem. The optimal solution will lie in one of the feasible decision spaces and can be found using the conventional lambda-delta iterative method in each of the feasible decision spaces. But, this elaborate search procedure is time consuming and not acceptable for on-line application. In this paper, a simple and novel approach is proposed. In this approach, the optimal solution and the corresponding optimum system lambda are determined using an efficient fast computation evolutionary programming algorithm (FCEPA) without considering the prohibited operating zones. Then, a small set of advantageous decision spaces is formed by combining the feasible sub-re-ions of the fuel cost curve intervening the prohibited zones in the neighbourhood of the optimal system lambda. A penalty cost for each advantageous decision space is judiciously computed using participation factor. The most advantageous decision space is found out by comparing the penalty cost of the decision spaces. The optimal solution in the most advantageous decision space is obtained using the FCEPA. The proposed algorithm is tested on a number of sample systems with units possessing prohibited zones. The study results reveal that the proposed approach is computationally efficient and would be a competent method for solving economic dispatch problem with units having prohibited operating zones. (C) 2004 Elsevier B.V. All rights reserved.

关键词： prohibited operating zones decision space economic dispatch evolutionary programming

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A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique

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IEEE TRANSACTIONS ON POWER SYSTEMS 2004年第2期19卷 913-918页

作者： Yan, W Lu, S Yu, DC Chongqing Univ Elect Power Dept Elect Engn Coll Chongqing 400044 Peoples R China Univ Wisconsin Dept Elect Engn Milwaukee WI 53211 USA

This paper proposes an improved evolutionary programming (IEP) and its hybrid version combined with the nonlinear interior point (IP) technique to solve the optimal reactive power dispatch (ORPD) problems. In an IEP method, the common practices in regulating reactive power are followed in adjusting the mutation direction of control variables in order to increase the possibility of keeping state variables within bounds. The IEP is also hybridized with the IP method to obtain a fast initial solution, which is then used as a highly evolved individual in the initial population of the improved EP method. Numerical tests of the proposed algorithm on the IEEE 118-bus system and a realistic power system in Western China are very encouraging compared with the existing ORPD algorithms in term of computational efficiency and optimality.

关键词： evolutionary programming interior point method optimal power flow optimal reactive power dispatch

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