Multi-Fuel Allocation for Power Generation Using Genetic Algorithms

Authors

  • Anurak Choeichum College of Innovative Technology and Engineering, Dhurakij Pundit University, Bangkok, Thailand
  • Narongdech Keeratipranon College of Innovative Technology and Engineering, Dhurakij Pundit University, Bangkok, Thailand
  • Chaiyaporn Khemapatapan College of Innovative Technology and Engineering, Dhurakij Pundit University, Bangkok, Thailand

DOI:

https://doi.org/10.6000/1929-7092.2017.06.25

Keywords:

Multi-fuel Allocation, Power Generation, Genetic Algorithms, Power Energy

Abstract

The ever increasing growth of energy consumption has stimulated an energy crisis, not only in terms of energy demand, but also the impact of climate change from greenhouse gas (GHG) emissions. Renewable energy sources (RES) have high potential toward sustainable development, with a wide variety of socioeconomic benefits, including diversification of energy supply and creation of domestic industry. This paper presents a solution to optimal multi-fuel allocation for the electric power generation planning problem via genetic algorithms (GA). The objective is to maximize the electric power energy output and minimize generation cost. This is a difficult problem because of its data variation and volatility. GA can provide an appropriate heuristic search method and return an actual or near optimal solution. This paper uses some heuristics during crossover and mutation for tuning the system to obtain a better candidate solution. An experimental result showed significantly improved results compared with other techniques. The results in this paper should be useful for connecting power generation with economic growth.

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Published

2017-06-09

Issue

Section

Special Issue - Recent Topical Research on Global, Energy, Health & Medical, and Tourism Economics, and Global Software