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Modified Shuffled Frog Leaping Algorithm for Solving Economic Load Dispatch Problem  [PDF]
Priyanka Roy, A. Chakrabarti
Energy and Power Engineering (EPE) , 2011, DOI: 10.4236/epe.2011.34068
Abstract: In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem which accounts for minimization of both generation cost and power loss is itself a multiple conflicting objective function problem. In this paper, a modified shuffled frog-leaping algorithm (MSFLA), which is an improved version of memetic algorithm, is proposed for solving the ELD problem. It is a relatively new evolutionary method where local search is applied during the evolutionary cycle. The idea of memetic algorithm comes from memes, which unlike genes can adapt themselves. The performance of MSFLA has been shown more efficient than traditional evolutionary algorithms for such type of ELD problem. The application and validity of the proposed algorithm are demonstrated for IEEE 30 bus test system as well as a practical power network of 203 bus 264 lines 23 machines system.
Solving Economic Load Dispatch Problem Using Particle Swarm Optimization Technique  [cached]
Hardiansyah,Junaidi,Yohannes MS
International Journal of Intelligent Systems and Applications , 2012,
Abstract: Economic load dispatch (ELD) problem is a common task in the operational planning of a power system, which requires to be optimized. This paper presents an effective and reliable particle swarm optimization (PSO) technique for the economic load dispatch problem. The results have been demonstrated for ELD of standard 3-generator and 6-generator systems with and without consideration of transmission losses. The final results obtained using PSO are compared with conventional quadratic programming and found to be encouraging.
Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem  [PDF]
Theofanis Apostolopoulos,Aristidis Vlachos
International Journal of Combinatorics , 2011, DOI: 10.1155/2011/523806
Abstract: Efficient and reliable power production is necessary to meet both the profitability of power systems operations and the electricity demand, taking also into account the environmental concerns about the emissions produced by fossil-fuelled power plants. The economic emission load dispatch problem has been defined and applied in order to deal with the optimization of these two conflicting objectives, that is, the minimization of both fuel cost and emission of generating units. This paper introduces and describes a solution to this famous problem using a new metaheuristic nature-inspired algorithm, called firefly algorithm, which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of this algorithm is presented together with an analytical mathematical modeling to solve this problem by a single equivalent objective function. The results are compared with those obtained by alternative techniques proposed by the literature in order to show that it is capable of yielding good optimal solutions with proper selection of control parameters.
Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem  [PDF]
Theofanis Apostolopoulos,Aristidis Vlachos
International Journal of Combinatorics , 2011, DOI: 10.1155/2011/523806
Abstract: Efficient and reliable power production is necessary to meet both the profitability of power systems operations and the electricity demand, taking also into account the environmental concerns about the emissions produced by fossil-fuelled power plants. The economic emission load dispatch problem has been defined and applied in order to deal with the optimization of these two conflicting objectives, that is, the minimization of both fuel cost and emission of generating units. This paper introduces and describes a solution to this famous problem using a new metaheuristic nature-inspired algorithm, called firefly algorithm, which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of this algorithm is presented together with an analytical mathematical modeling to solve this problem by a single equivalent objective function. The results are compared with those obtained by alternative techniques proposed by the literature in order to show that it is capable of yielding good optimal solutions with proper selection of control parameters. 1. Introduction Biology-inspired metaheuristic algorithms have recently become the forefront of the current research as an efficient way to deal with many NP-hard combinatorial optimization problems and non-linear optimization constrained problems in general. These algorithms are based on a particular successful mechanism of a biological phenomenon of Mother Nature in order to achieve optimization, such as the family of honey-bee algorithms, where the finding of an optimal solution is based on the foraging and storing the maximum amount of flowers’ nectar [1]. A new algorithm that belongs in this category of the so-called nature inspired algorithms is the firefly algorithm which is based on the flashing light of fireflies. Although the real purpose and the details of this complex biochemical process of producing this flashing light is still a debating issue in the scientific community, many researchers believe that it helps fireflies for finding mates, protecting themselves from their predators and attracting their potential prey [1–4]. In the firefly algorithm, the objective function of a given optimization problem is associated with this flashing light or light intensity which helps the swarm of fireflies to move to brighter and more attractive locations in order to obtain efficient optimal solutions. In this research paper we will show how the recently developed firefly algorithm can be used to solve the famous economic emissions load dispatch optimization problem. This hard optimization
Differential Evolution Immunized Ant Colony Optimization Technique in Solving Economic Load Dispatch Problem  [PDF]
N. A. Rahmat, I. Musirin
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.51B029
Abstract: Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) and cloning process. This paper presents Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic load dispatch problem. The combination creates a new algorithm that will be termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT). DEIANT was utilized to optimize economic load dispatch problem. A comparison was made between DEIANT and classical ACO to evaluate the performance of the new algorithm. In realizing the effectiveness of the proposed technique, IEEE 57-Bus Reliable Test System (RTS) has been used as the test specimen. Results obtained from the study revealed that the proposed DEIANT has superior computation time.
Simulated annealing approach for solving economic load dispatch problems with valve point loading effects
KK Vishwakarma, HM Dubey, M Pandit, BK Panigrahi
International Journal of Engineering, Science and Technology , 2012,
Abstract: This paper presents Simulated Annealing (SA) algorithm for optimization inspired by the process of annealing in thermodynamics to solve economic load dispatch (ELD) problems. The proposed approach is found to provide optimal results while working with operating constraints in the ELD and valve point loadings effects. In order to prove the robustness of the algorithm it is investigated on four different standard test cases consisting of 3, 13, 40 generating unit system with valve point effect and a Crete Island system of 18 thermal generating units having convex fuel cost characteristics. The proposed method has been compared with other existing relevant approaches available in literatures. Experimental results support to justify superiority of the approach over other reported techniques in terms of fast convergence, robustness and most significantly its optimal search behavior.
A Social Spider Algorithm for Solving the Non-convex Economic Load Dispatch Problem  [PDF]
James J. Q. Yu,Victor O. K. Li
Computer Science , 2015, DOI: 10.1016/j.neucom.2015.07.037
Abstract: Economic Load Dispatch (ELD) is one of the essential components in power system control and operation. Although conventional ELD formulation can be solved using mathematical programming techniques, modern power system introduces new models of the power units which are non-convex, non-differentiable, and sometimes non-continuous. In order to solve such non-convex ELD problems, in this paper we propose a new approach based on the Social Spider Algorithm (SSA). The classical SSA is modified and enhanced to adapt to the unique characteristics of ELD problems, e.g., valve-point effects, multi-fuel operations, prohibited operating zones, and line losses. To demonstrate the superiority of our proposed approach, five widely-adopted test systems are employed and the simulation results are compared with the state-of-the-art algorithms. In addition, the parameter sensitivity is illustrated by a series of simulations. The simulation results show that SSA can solve ELD problems effectively and efficiently.
A Novel Heuristic Algorithm for Solving Non-Convex Economic Load Dispatch Problem with Non-smooth Cost Function  [cached]
Mir Mahmood Hosseini,Hamidreza Ghorbani,A. Rabii,S. Mobaieen
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: In this study, a novel heuristic algorithm is presented for solving Economic Load Dispatch (ELD) problems in power systems. The implemented method is a hybrid method, called Hybrid Immune Genetic Algorithm (HIGA). ELD problems are complicated and nonlinear in nature with equality and inequality constraints. Two benchmark ELD problems of different characteristics were used to investigate the effectiveness of the proposed algorithm. The proposed methodology easily takes care of valve-point effects, Prohibited Operation Zones (POZs), ramp-rate constraints and transmission losses. Comparing of the obtained numerical results with other available methods affirm the proficiency of proposed algorithm over other existing methods. It shows that the HIGA method has good convergence property. Furthermore, the generation costs of the HIGA approach are lower than other optimization algorithms reported in recent literature.
Using Evolutionary Computation to Solve the Economic Load Dispatch Problem  [PDF]
Samir SAYAH,Khaled ZEHAR
Leonardo Journal of Sciences , 2008,
Abstract: This paper reports on an evolutionary algorithm based method for solving the economic load dispatch (ELD) problem. The objective is to minimize the nonlinear function, which is the total fuel cost of thermal generating units, subject to the usual constraints.The IEEE 30 bus test system was used for testing and validation purposes. The results obtained demonstrate the effectiveness of the proposed method for solving the economic load dispatch problem.
Dynamic Economic Load Dispatch of Thermal Power System Genetic Algorithm
W.M. Mansour,M.M. Salama,S.M. Abdelmaksoud,H.A. Henry
International Journal of Electrical and Power Engineering , 2012, DOI: 10.3923/ijepe.2012.140.148
Abstract: Economic Load Dispatch (ELD) problem is one of the most important problems to be solved in the operation and planning of a power system. The main objective of the economic load dispatch problem is to determine the optimal schedule of output powers of all generating units so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints. This study presents an application of Genetic Algorithm (GA) for solving the ELD problem to find the global or near global optimum dispatch solution. The proposed approach has been evaluated on 26-bus, 6-unit system with considering the generator constraints, ramp rate limits and transmission line losses. The obtained results of the proposed method are compared with those obtained from the Conventional Lambda Iteration Method and Particle Swarm Optimization (PSO) Technique. The results show that the proposed approach is feasible and efficient.
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