An enhanced differential evolution algorithm application to economic dispatch with valve-point effects and system losses considerations

This paper presents an enhanced differential evolution algorithm (EnDEA) to solve economic dispatch (ED) problem of generating units considering valve-point effects and system losses. The aim of ED problem is to achieve optimal generation scheduling of power plants, which has minimum total production cost associated with technical and economical constraints. The efficiency and effectiveness of the proposed method is initially demonstrated via the analysis of 10-unit test system considering valve-point loading and system losses constraints. Furthermore, multiple fuels of thermal power plant are included and investigated in this ED problem. A detailed comparative study between a conventional differential evolution algorithm (CDEA) and the proposed EnDEA method is presented. Regarding the experimental results, the proposed technique obtained solutions with good accuracy, stable convergence characteristics, and satisfactory calculation time.

[1]  M. Abido.  Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[2]  Chao-Lung Chiang,et al.  Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels , 2005, IEEE Transactions on Power Systems.

[3]  Malcolm Irving,et al.  Differential evolution algorithm for static and multistage transmission expansion planning , 2009 .

[4]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[5]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[6]  L. Lakshminarasimman,et al.  Short-term scheduling of hydrothermal power system with cascaded reservoirs by using modified differential evolution , 2006 .

[7]  R. Balamurugan,et al.  Differential Evolution-based Dynamic Economic Dispatch of Generating Units with Valve-point Effects , 2008 .

[8]  Kit Po Wong,et al.  A Differential Evolution Based Method for Power System Planning , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[9]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[10]  Xianzhong Duan,et al.  Study of differential evolution for optimal reactive power flow , 2007 .

[11]  Thanathip Sum-Im,et al.  Self-adaptive differential evolution algorithm for economic dispatch with transmission losses consideration , 2010, TENCON 2010 - 2010 IEEE Region 10 Conference.

[12]  K.P. Wong,et al.  Parallel Optimal Reactive Power Flow Based on Cooperative Co-Evolutionary Differential Evolution and Power System Decomposition , 2007, IEEE Transactions on Power Systems.

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

[14]  P. K. Chattopadhyay,et al.  Evolutionary programming techniques for economic load dispatch , 2003, IEEE Trans. Evol. Comput..

[15]  K.P. Wong,et al.  Application of Differential Evolution Algorithm for Transient Stability Constrained Optimal Power Flow , 2008, IEEE Transactions on Power Systems.

[16]  P. Attaviriyanupap,et al.  A Hybrid EP and SQP for Dynamic Economic Dispatch with Nonsmooth Fuel Cost Function , 2002, IEEE Power Engineering Review.

[17]  A. Ebenezer Jeyakumar,et al.  A modified hybrid EP–SQP approach for dynamic dispatch with valve-point effect , 2005 .