Nature of Computation and Communication. Second International Conference, ICTCC 2016, Rach Gia, Vietnam, March 17-18, 2016, Revised Selected Papers

Research Article

Hybrid Mean-Variance Mapping Optimization for Economic Dispatch with Multiple Fuels Considering Valve-Point Effects

Download
294 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-46909-6_19,
        author={Khoa Truong and Pandian Vasant and M. Balbir Singh and Dieu Vo},
        title={Hybrid Mean-Variance Mapping Optimization for Economic Dispatch with Multiple Fuels Considering Valve-Point Effects},
        proceedings={Nature of Computation and Communication. Second International Conference, ICTCC 2016, Rach Gia, Vietnam, March 17-18, 2016, Revised Selected Papers},
        proceedings_a={ICTCC},
        year={2017},
        month={1},
        keywords={Economic dispatch Multiple fuels Valve-point effects Mean-variance mapping optimization MVMO MVMO-SH},
        doi={10.1007/978-3-319-46909-6_19}
    }
    
  • Khoa Truong
    Pandian Vasant
    M. Balbir Singh
    Dieu Vo
    Year: 2017
    Hybrid Mean-Variance Mapping Optimization for Economic Dispatch with Multiple Fuels Considering Valve-Point Effects
    ICTCC
    Springer
    DOI: 10.1007/978-3-319-46909-6_19
Khoa Truong1,*, Pandian Vasant1,*, M. Balbir Singh1,*, Dieu Vo2,*
  • 1: Universiti Teknologi Petronas
  • 2: HCMC University of Technology
*Contact email: trhkhoa89@gmail.com, pvasant@gmail.com, balbir@petronas.com.my, vndieu@gmail.com

Abstract

Many thermal generating units of an electric power system are supplied with multi-fuel sources such as coal, natural gas and oil. These fuels represent irreplaceable natural resources and conservation is used as a way to increase energy efficiency. Economic dispatch (ED) is one of the significance optimization problems in power system operation for fuel cost savings. This paper proposes a new approach which is hybrid variant of mean-variance mapping optimization (MVMO-SH) for solving this problem. The MVMO-SH is the improvement of original mean-variance mapping optimization algorithm (MVMO). This method adopts a swarm scheme of MVMO and incorporates local search and multi-parent crossover strategies to enhance its global search ability and improve solution quality for optimization problems. The proposed MVMO-SH is tested on 10-unit and large-scale systems with multiple fuels and valve-point effects. The obtained results are compared to those from other optimization methods available in the literature. The comparisons show that the proposed method provides higher quality solutions than the others. Therefore, the MVMO-SH is a promising method for solving the complex ED problems in electric power system.