KIEE International Transactions on Power Engineering

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

Profit-based Thermal Unit Maintenance Scheduling under Price Volatility by Reactive Tabu Search

  • Sugimoto Junjiro (Graduate School of Science and Technology, Tokyo Metropolitan University) ;
  • Yokoyama Ryuichi (Graduate School of Science and Technology, Tokyo Metropolitan University)
  • 발행 : 2005.12.01
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초록

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 the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

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참고문헌

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