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Power Engineering Conference, 2007. IPEC 2007. International

Date 3-6 Dec. 2007

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Displaying Results 1 - 25 of 258
  • Impact of generators’ different bidding strategies on system nash equilibrium point

    Page(s): 1 - 5
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (126 KB) |  | HTML iconHTML  

    Unlike to perfect competitive markets, in electricity oligopoly markets due to strategic producers and transmission constraints Gencos may increase their own profit through strategic biddings. This paper investigates the problem of developing optimal bidding strategies of generators in two cases when they all bid strategically and when some of them alter their biddings in order to exercise market power. The problem is modeled as a bi-level optimization that at the first level each generator maximizes its payoff through strategic bidding and at the second level a system dispatch is accomplished through an OPF problem. The AC power flow model is used for proposed OPF that considers ancillary services as well. Using proposed model optimal bidding strategies of generators in order to achieve to the most profit while considering system constraints are presented and impact of of generators' different bidding strategies on system Nash equilibrium point is studied. Finally IEEE-30 bus test system is used for case study to demonstrate simulation results. View full abstract»

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  • Identification of source to sink relationship in deregulated power systems using artificial neural network

    Page(s): 6 - 11
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (384 KB) |  | HTML iconHTML  

    This paper suggests a method to identify the relationship of real power transfer between source and sink using artificial neural network (ANN). The basic idea is to use supervised learning paradigm to train the ANN. For that a conventional power flow tracing method is used as a teacher. Based on solved load flow and followed by power tracing procedure, the description of inputs and outputs of the training data for the ANN is easily obtained. An artificial neural network is developed to assess which generators are supplying a specific load. Most commonly used feedforward architecture has been chosen for the proposed ANN power transfer allocation technique. Almost all system variables obtained from load flow solutions are utilised as an input to the neural network. Moreover, log-sigmoid activation functions are incorporated in the hidden layer to realise the non linear nature of the power flow allocation. The proposed ANN provides promising results in terms of accuracy and computation time. The IEEE 14-bus network is utilised as a test system to illustrate the effectiveness of the ANN output compared to that of conventional methods. View full abstract»

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  • Factoring the price elasticity of demand in the optimal power flow

    Page(s): 12 - 17
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (398 KB) |  | HTML iconHTML  

    In the traditional optimal power flow, demand sensitivity to price changes is assumed zero but in the new competitive environment, it is necessary to assume that demand is elastic and will vary as a function of price. In this paper, inclusion of price elasticity of demand into the optimal power flow is investigated. It analyzes the effect that the price responsive loads can have on the market operation. These loads can be modeled in the MATPOWER environment. The paper evaluates price elasticity effects on the consumers, generating companies, merchandising surplus, power system security and system operation cost. It shows that the consumers participation in the electricity market can reduce the electricity price that results in enhancing social welfare. These concepts are illustrated using a six-bus system, and numerical results obtained with the IEEE 14- bus system are used to verify the benefits of price responsive loads. View full abstract»

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  • Optimal price bidding strategy for competitive electricity market in Singapore

    Page(s): 18 - 23
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (429 KB) |  | HTML iconHTML  

    With the deregulation and restructuring of electricity industry, different techniques have been evolved to minimize operation costs and optimize profits of Gencos, Transcos and even Retailcos. This paper presents an appropriate bidding price strategy implemented to maximize Genco's profits in Singapore. The methodology considers integration of vesting contract demand and customer demands into the system demand. It makes use of statistical methods such as lognormal distribution, conjointly computed with a statistical quality control method, the acceptance function, to formulate an objective function. The proposed method is capable of generating the best price offer to customers, in order to optimize Gencos profits in this competitive electricity environment. View full abstract»

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  • Experimental analysis of uniform price and PAB auctions in electricity markets

    Page(s): 24 - 29
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    The method of experimental economics is applied to research of Genco bidding strategy and market behavior of uniform price and pay-as-bid (PAB) auction mechanisms under different demand side response conditions with the multi-unit simultaneous auction model. The basic theories of experimental economics are introduced first. Then the experimental design is presented. Both qualitative analysis and quantitative analysis with strict statistic approaches are carried out on the experimental results. Several important conclusions are reached and can be used as reference to design of auction mechanisms in electricity markets. The research presented in this paper shows that experimental method has many advantages over traditional microeconomics and game theory in research of electricity markets and has many merits in modeling realistic electricity markets. View full abstract»

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  • A stochastic model to analyze the economic competitiveness of wind power projects within a restructured electricity industry

    Page(s): 30 - 35
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (760 KB) |  | HTML iconHTML  

    This paper describes a Net Present Value (NPV) model based on probability distributions to assess the financial returns of the small wind power projects with special emphasis in homeowner projects. The probability distributions were employed to reproduce the stochastic behavior of wind power generation, spot market, retail prices, household energy consumption and CO2 allowances trading. The proposed model was built in crystal ball software and the simulations were performed using Monte Carlo techniques. In our model, we applied two different mechanisms to support renewable energy development: the environmental benefits associated to the sale of the carbon credits and the incentives derived from the governmental grants. In windy locations or high wind turbine capacity, the simulation results revealed that the use of the environmental benefits in the NPV calculation is more profitable than the governmental grants, allowing renewable energy technologies to compete with conventional power production. Nonetheless, it has been shown that in less windy location, the small wind power projects are still depending on the governmental support. Moreover, the sensitivity analysis demonstrated the importance of the clear and consistent mechanisms to compensate the customers who sell and deliver their excess generation to the electric grid. View full abstract»

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  • Unit commitment by selective self-adaptive ACO with Relativity Pheromone Updating approach

    Page(s): 36 - 41
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (252 KB) |  | HTML iconHTML  

    This paper presents a novel approach to solve the constrained unit commitment problem using the Selective Self- Adaptive Ant Colony Optimization (SSACO) for improving search performance by automatically adapting ant populations and their transition probability parameters, which cooperates with the Candidate Path Management Module (CPMM) and the Effective Repairing Heuristic Module (ERHM) in reducing search space and recovering a feasible optimality region so that a high quality solution can be acquired in a very early iterative. A new concept of the Relativity Pheromone Updating (RPU) is also introduced to provide a reasonable evaluation of the pheromone trail intensity among the agents. The proposed SSACO method not only enhances the convergence of search process, but also provides a suitable number of the population sharing which conducts a good guidance for trading-off between the importance of the visibility and the pheromone trail intensity. The proposed method has been performed on a test system up to 100 generating units with a scheduling time horizon of 24 hours. The numerical results show the most economical saving in the total operating cost when compared to the previous literature results. Moreover, the proposed SSACO topology can remarkably speed up the computational time of ant colony optimization, which is favorable for a large-scale UC problem implementation. View full abstract»

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  • High accurate fault classification of power transmission lines using fuzzy logic

    Page(s): 42 - 46
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (599 KB) |  | HTML iconHTML  

    In this paper, a very successful performance fuzzy logic-based fault classification scheme has been realized. To achieve high accurate classification of all ten types of shunt faults from this approach, an improved technique has been presented in this work. The proposed technique is able to identify all ten types of shunt faults with high accurate performance in wide variety of system conditions. The faults that occurred in high fault resistances, high system loading level and high distances from relaying point are identified correctly as well as. To illustrate the performance of proposed improved technique a large numbers of test cases was generated. The simulation studies have been carried out using PSCAD/EMTDC and MATLAB fuzzy-logic toolbox. View full abstract»

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  • Short-term load forecasting using wavelet transform and support vector machines

    Page(s): 47 - 52
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (519 KB) |  | HTML iconHTML  

    This paper presents a new technique in short-term load forecasting (STLF.) The proposed method consists of the discrete wavelet transform (DWT) and support vector machines (SVMs.) The DWT splits up load time series into low and high frequency components to be the features for the SVMs. The SVMs then forecast each component separately. At the end we sum up all forecasted components to produce a final forecasted load. The data from Bangkok-Noi area in Bangkok, Thailand, is used to verify on the one-day ahead load forecasting. The performance of the algorithm is compared with that of the SVM without DWT, and neural networks with and without DWT. The experimental results show that the proposed algorithm yields more accuracy in the STLF than the others. View full abstract»

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  • Optimization of Unified Power Flow Controllers (UPFC) using GEA

    Page(s): 53 - 58
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (292 KB) |  | HTML iconHTML  

    This paper deals with the development of dynamic model of a power system with UPFC in synchronously rotating d- q axes reference frame. A comprehensive approach for designing the optimum UPFC controllers using Genetic and Evolutionary Algorithms (GEA) is presented. Investigations reveal that the real and reactive power flows on the line are controlled in a decoupled manner. Studies also show that the dynamic response for DC bus voltage is somewhat superior with pre-control signal based DC voltage regulator as compared to that obtained with conventional P-I type DC bus voltage regulator. View full abstract»

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  • Determining voltage unstable area in power systems using kohonen neural network

    Page(s): 59 - 63
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (289 KB) |  | HTML iconHTML  

    This paper presents a new method to determine voltage unstable area in power systems using Kohonen neural network (KNN) from dynamic voltage stability viewpoint. Using KNN, the buses in a power system are classified as critical and non critical buses based on the power transfer stability index values. The critical buses are then clustered to form the voltage unstable area in a power system. The proposed method was implemented on the IEEE 39-bus test system in which for dynamic simulation of voltage collapse, two contingencies such as load increase and line outage were considered. The dynamic voltage collapse simulation results were used for generating training and testing data sets of the KNN. The results on the determination of voltage unstable area by using the KNN were also compared with the learning vector quantization technique. The results showed that the proposed method using KNN is more accurate than the linear vector quantization technique in forming the voltage unstable area in power systems. View full abstract»

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  • A study of electric vehicle battery charging demand in the context of Singapore

    Page(s): 64 - 69
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (241 KB) |  | HTML iconHTML  

    Continuing environmental concerns are moving electric vehicles into high gear of development. Plug-in type electric and hybrid vehicles are expected in the market anytime. The EV battery-charging load can potentially increase the demand on the utility distribution systems considerably. It is desirable that the EV battery charging load be contained during system off-peak hours without affecting the peak demand, thus utilizing the low cost electricity for charging EV. However, a sizable EV load can introduce a new peak in the early off-peak period. Optimization of the EV charging during the low cost off peak period is formulated to minimize the cost of EV charging in the context of Singapore system. The case studies presented show that significant saving is possible even at reasonable low levels of EV penetrations. View full abstract»

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  • Application of a new hybrid optimization method for optimum distribution capacitor planning

    Page(s): 70 - 74
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (204 KB) |  | HTML iconHTML  

    This work presents a new algorithm based on a combination of fuzzy (FUZ), dynamic programming (DP), and genetic algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem. View full abstract»

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  • Implementation of telecontrol protocols in SCADA systems based on FSM

    Page(s): 75 - 79
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (415 KB) |  | HTML iconHTML  

    In China power systems began to carry out the international standard protocol-IEC60870-5-101 as the communication protocol for telecontrol, teleprotection, and associated telecommunications in 1998. For the sake of the generalization of IEC60870-5-101 standard and the development of the high quality software, this paper introduces the finite state machine (FSM) theory for design of the communication software of the master station in SCADA systems. And this paper also presents a new framework of implementation of FSM according to the OO method. The introduction of this framework can not only make the software more reusable and flexible, but also can improve the maintenance and robustness. With the development of communication software, a more convenient and universal design pattern is introduced. View full abstract»

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  • Probabilistic load flow solution considering reactive power and voltage control

    Page(s): 80 - 85
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    Voltage and Var control (VVC) schemes (i.e., centralized and decentralized controls) are discussed. Probabilistic load flow (PLF) method is applied on a real distribution system; the results from Monte Carlo simulations of both control schemes are compared. Models of WC element (on load tap changer, shunt capacitor and automatic voltage regulator of generator) are discussed. Voltage and reactive power in a decentralized control scheme are regulated independently through WC elements. The centralized VVC control scheme is accomplished by utilizing a genetic algorithm (GA) to minimize the number of buses in which voltage violation occurs. Advantages and disadvantages from both control schemes are discussed. Numerical results from a real distribution system are applied as a test bed. View full abstract»

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  • Investigation of solar energy for photovoltaic application in Singapore

    Page(s): 86 - 89
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (219 KB) |  | HTML iconHTML  

    This paper addresses the availability of solar energy resources for photovoltaic applications in Singapore, a typical tropical country. The paper analyzes the two years solar radiation data in Singapore, studies on the impact of unique tropical weather conditions on solar radiation and performs a case study of grid-tied PV system. The solar radiation data in 2002 and 2003 are collected from Singapore Meteorological Authority. The study on the radiation data will help work out the yearly variation of solar net radiation, diffuse and irradiation in the tropical area. The PV system for case study is a 19.2 kWp grid-tied PV system installed in Singapore Polytechnic. The PV system is composed of the 256 times 75 Wp mono-crystalline PV modules and installed on the rooftop of one teaching block in the Polytechnic campus. The analytic results in the paper help understand the variation of solar radiations in Singapore and the impact of tropical weather conditions on the operation of a photovoltaic system. View full abstract»

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  • Voltage sag source location based on instantaneous energy detection

    Page(s): 90 - 94
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (239 KB) |  | HTML iconHTML  

    Voltage sag is the major power quality problem, which could disrupt the operation of sensitive equipment. This paper presents the applications of instantaneous energy direction for voltage sag source detection. Simulations have been performed to provide the analysis for system with distributed generation units. The studies show that the presented method can effectively detect the location of the voltage sag source. View full abstract»

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  • Inter-area damping controller design based on mode controllability and observability

    Page(s): 95 - 99
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (270 KB) |  | HTML iconHTML  

    This paper proposes a new method of controller design for damping inter-area oscillations in power system. The concepts of the mode controllability index and mode observability index are introduced into the modal analysis at the operating point in damping controller design. The controller is located according to mode controllability index, and the input signals of controller are selected according to mode observability index. Then a method is presented to obtain the optimal global signals combination under the constraints of the amount of signals. The parameters tuning of the controller is based on phase compensation information. The proposed schemes are validated by eigenvalue analysis of a two-area system. Simulations results also demonstrate the advantage of designed damping controller. View full abstract»

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  • A practical design of fuzzy SMES controller based on synchronized phasor measurement for interconnected power system

    Page(s): 100 - 105
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (413 KB) |  | HTML iconHTML  

    Recently, fuzzy logic control has widely received attention in various power system applications, despite difficulties of obtaining its control rules and membership functions. Nowadays, power system consists of multiple areas where load variations with abrupt changes always exist, and proper control rules and membership functions could be hardly achieved. This paper proposes a practical design of fuzzy logic controllers for superconducting magnetic energy storage (SMES) based on wide area synchronized phasor measurement for improving stability of interconnected power system. Moreover, a heuristic method is applied for determining control rules and membership functions. The estimated model is determined via a coupled vibration model for detection and assessment of an approximated inter-area oscillation mode. Finally, some simulation studies based on a two-area four-machine power system are carried out to examine the performance and effectiveness of the designed fuzzy SMES controller. View full abstract»

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  • An energy approach to optimal selection of controllers/sensors in power system

    Page(s): 106 - 111
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (263 KB) |  | HTML iconHTML  

    The paper presents an energy approach based on controllability and observability gramians for the optimal selection of controllers/sensors in large-scale power systems. This approach consists in solving a stochastic optimization problem based on scenarios reflecting various operational situations (load changes, line tripping ...). This approach may be regarded as part of a structural optimization procedure aiming at defining some new control systems in the context of security improvements of large-scale power systems. Applications to both "two-area system" and "118 bus system" give very promising results. View full abstract»

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  • Utility applications of a RTDS® Simulator

    Page(s): 112 - 117
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (199 KB) |  | HTML iconHTML  

    The RTDS Simulator is a fully digital, real time power system simulator widely used in the industry. The system provides continuous real time electromagnetic transient simulations based on the Dommel algorithm. The simulator hardware and software have both undergone many improvements since the simulator was first introduced in the early 1990's. The improvements have increased the performance of the simulator and widened its scope of application. In particular, electric power utilities have used the system for closed-loop testing and training on controllers for HVDC, SVC and generators, closed-loop protective relay testing, and large scale real time simulation. The paper describes the simulator design and its utility applications in greater detail. View full abstract»

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  • A data mining technique based on pattern discovery and k-nearest neighbor classifier for transient stability assessment

    Page(s): 118 - 123
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    This paper presents a novel strategy based on pattern discovery algorithm and extended A-Nearest Neighbor (k- NN) classifier to design the power system transient stability assessment (TSA) scheme. A pattern discovery algorithm based on residual analysis and recursive partitioning is employed to identify the latent structure (called pattern) of data samples. An extended A-NN classifier is then designed to label the input sample with stability levels where the identified patterns are applied as initial classified data set. In order to improve the pattern discovery efficiency, a feature selection process is introduced in the first stage to extract kernel-feature subset from the pre-contingency steady state parameters as the input features for the TSA scheme. Applications of the proposed scheme on two IEEE test systems prove its feasibility and show good performance in stability level classifications. View full abstract»

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  • ATC evaluation with consideration of load changes and participation factors- A sensitivity analysis approach

    Page(s): 124 - 129
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    While allowing the open access to the market participants, one or more lines may operate beyond their limits thereby causing the network congestion. It can be detected by evaluation of available transfer capability (ATC) of the network for various applied power transactions. ATC refers to the available limit of the network that can support a particular bilateral transaction. Due to flexible operating policies of a restructured power system, load at a bus may be required to be met by more than one generator. Which means ATC must be determined from different aspects such as of the maximum allowable load at a bus, which a network can support without causing any insecurity. When the load at a bus is subjected to change, participation factors of generators can decide the ATC of the network. This paper describes the method of ATC determination when the load applied at a bus, is of main concern. Similar approach of ATC computation as in case of bilateral transaction is used except for the fact that the total change in load is split into different bilateral transactions. Sensitivity analysis and power transfer distribution factor is used for the determination of ATC for individual transaction. The algorithm can be suitable for hour-ahead markets. View full abstract»

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  • A mathematic model and its iterative algorithm on obtaining optimal capacity of P-S station

    Page(s): 130 - 133
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    With rising electricity loading in developing country, measuring capacity of pumped-storage station (P-S station) is becoming more critical. This paper tries to establish mathematic model on obtaining capacity of P-S station for maximum cost savings. The paper first deducts the relationship between capacity of P-S station, peak load and the vale load by simulating cost curve of thermoelectric unit, and then deducts the formula for calculating optimal capacity of P-S station. Based upon these findings and the load curve, the paper then develops the curve to describe the relationship between volume of generated electricity and capacity of the P-S station and provides the solution for obtaining optimal capacity of the P-S station. Finally, the paper discusses the impact of selecting initial solution or certain iterative solution on iterative speed and suggests the direction for further research. View full abstract»

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  • Optimization of combined economic and emission dispatch problem — A comparative study

    Page(s): 134 - 139
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (437 KB) |  | HTML iconHTML  

    This paper presents an evolutionary computation (EC) method called genetic algorithm (GA) and a metaheuristic algorithm called ant colony search algorithm (ACSA) to solve the combined economic and emission dispatch (EED) problem with transmission losses. Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. A real coded GA has been implemented to minimize both the dispatch cost as well as emission while satisfying all the equality and inequality constraints. ACSA is also developed to provide a means of comparison and it is a new cooperative agents approach, which is inspired by the observation of the behaviors of real ant colonies on the topic of ant trail formation and foraging methods. In the ACSA, a set of cooperating agents called "ants" cooperates to find a good solution for economic dispatch problem. The merits of ACSA are parallel search and optimization capabilities. The feasibility of the proposed method is tested on a power system network and the experimental results of both GA and ACSA are compared with the solutions of conventional Lamda iteration method. View full abstract»

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