Solving economic emission load dispatch problems using hybrid differential evolution

This paper presents the combination of differential evolution (DE) and Biogeography-based Optimization (BBO) algorithm to solve complex economic emission load dispatch (EELD) problems of thermal generators of power systems. Emission substances like NO"X, SO"X, CO"X, power demand equality constraint and operating limit constraint are considered here. Differential evolution (DE) is one of the very fast and robust, accurate evolutionary algorithms for global optimization and solution of EELD problems. Biogeography-based Optimization (BBO) is another new biogeography inspired algorithm. Biogeography deals with the geographical distribution of different biological species. This algorithm searches for the global optimum mainly through two steps: migration and mutation. In this paper the combination of DE and BBO (DE/BBO) is proposed to accelerate the convergence speed of both the algorithm and to improve solution quality. To show the advantages of the proposed algorithm, it has been applied for solving multi-objective EELD problems in a 3 generator system with NO"X and SO"X emission, in a 6 generators system considering NO"X emission, in a 6 generator system addressing both valve-point loading and NO"X emission. The current proposal is found better in terms of quality of the compromising and individual solution obtained.

[1]  Manjaree Pandit,et al.  Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch , 2008, Appl. Soft Comput..

[2]  P. K. Chattopadhyay,et al.  Hybrid Differential Evolution With Biogeography-Based Optimization for Solution of Economic Load Dispatch , 2010, IEEE Transactions on Power Systems.

[3]  A. T. Johns,et al.  Environmental/economic dispatch using fuzzy logic controlled genetic algorithms , 1997 .

[4]  Prakash Kumar Hota,et al.  Economic emission load dispatch through fuzzy based bacterial foraging algorithm , 2010 .

[5]  Mohamed E. El-Hawary,et al.  Emission-Economic Dispatch using a Novel Constraint Handling Particle Swarm Optimization Strategy , 2006, 2006 Canadian Conference on Electrical and Computer Engineering.

[6]  M.S. Osman,et al.  Epsilon-dominance based multiobjective genetic algorithm for economic emission load dispatch optimization problem , 2006, 2006 Eleventh International Middle East Power Systems Conference.

[7]  M. A. Abido.  Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003 .

[8]  Malabika Basu,et al.  Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II , 2008 .

[9]  H.C.S. Rughooputh,et al.  Elitist multiobjective evolutionary algorithm for environmental/economic dispatch , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[10]  Yaonan Wang,et al.  Environmental/economic power dispatch problem using multi-objective differential evolution algorithm , 2010 .

[11]  G. P. Granelli,et al.  Emission constrained dynamic dispatch , 1992 .

[12]  Ryuichi Yokoyama,et al.  Environmental marginal cost evaluation by non-inferiority surface (power systems) , 1990 .

[13]  H. Sasaki,et al.  Multiobjective optimal generation dispatch based on probability security criteria , 1988 .

[14]  S. Hemamalini,et al.  Emission constrained economic dispatch with valve-point effect using particle swarm optimization , 2008, TENCON 2008 - 2008 IEEE Region 10 Conference.

[15]  T. Thakur,et al.  A Particle Swarm Optimization Solution to NO2 and SO2 Emissions for Environmentally Constrained Economic Dispatch Problem , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[16]  M. A. Abido,et al.  Differential evolution algorithm for emission constrained economic power dispatch problem , 2010 .

[17]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[18]  Wenyin Gong,et al.  DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization , 2010, Soft Comput..

[19]  Halis Altun,et al.  Environmentally constrained economic dispatch via a genetic algorithm with arithmetic crossover , 2002, IEEE AFRICON. 6th Africon Conference in Africa,.

[20]  M. A. Abido,et al.  A niched Pareto genetic algorithm for multiobjective environmental/economic dispatch , 2003 .

[21]  H.C.S. Rughooputh,et al.  Environmental/economic dispatch of thermal units using an elitist multiobjective evolutionary algorithm , 2003, IEEE International Conference on Industrial Technology, 2003.

[22]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[23]  A. C. Liew,et al.  Dynamic-security-constrained multiobjective generation dispatch of longitudinally interconnected power systems using bicriterion global optimization , 1996 .

[24]  D. P. Kothari,et al.  Stochastic economic emission load dispatch , 1993 .

[25]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[26]  J. S. Dhillon,et al.  Economic-emission load dispatch using binary successive approximation-based evolutionary search , 2009 .

[27]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[28]  Lixiang Li,et al.  A multi-objective chaotic ant swarm optimization for environmental/economic dispatch , 2010 .

[29]  P. K. Chattopadhyay,et al.  Biogeography-Based Optimization for Different Economic Load Dispatch Problems , 2010, IEEE Transactions on Power Systems.

[30]  P. K. Chattopadhyay,et al.  Application of Biogeography-based Optimization for Solving Multi-objective Economic Emission Load Dispatch Problems , 2010 .

[31]  J. Nanda,et al.  ECONOMIC-EMISSION LOAD DISPHTCH THROUGH GOAL PROGRAMMING TECHNIIJUES , 1988 .