• DocumentCode
    3101857
  • Title

    Profit-oriented Thermal Unit Maintenance Scheduling under Competitive Environment

  • Author

    Sugimoto, Junjiro ; Isa, Aishah Mohd ; Yokoyama, Ryuichi

  • Author_Institution
    Electr. Eng. Dept., Tokyo Metropolitan Univ., Tokyo
  • fYear
    2007
  • fDate
    24-28 June 2007
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS) In competitive power markets, electricity prices are determined by balance between demand and supply in electric power exchanges or bilateral contracts. Therefore it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling method, firstly, electricity prices are forecasted for the targeted period using proposed aggregated bidding model. Secondly, the optimal combinatorial maintenance-scheduling problem is solved by using Reactive Tabu Search in the light of the electricity prices forecasted. This method proposes a new objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss of Maintenance (OLM) is adopted to maximize the profit of Generation Companies (GENCOS). Finally, the proposed maintenance scheduling is applied to a practical power system test model to verify the advantages and effectiveness of the method.
  • Keywords
    power generation scheduling; power markets; power system economics; power system management; Reactive Tabu search; bilateral contracts; competitive environment; demand and supply; electric power exchanges; electricity prices; maintenance scheduling; objective function; opportunity loss of maintenance; power markets; profit oriented; thermal unit; Economic forecasting; Electricity supply industry; Fuels; Job shop scheduling; Power generation; Power markets; Power system modeling; Power system planning; Predictive models; Preventive maintenance; Artificial Neural Network; Electricity Market; Electricity Price Forecasting; Power Generation Maintenance; Tabu Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2007. IEEE
  • Conference_Location
    Tampa, FL
  • ISSN
    1932-5517
  • Print_ISBN
    1-4244-1296-X
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2007.386099
  • Filename
    4275865