TY - GEN
T1 - Profit-oriented thermal unit maintenance scheduling under competitive environment
AU - Sugimoto, Junjiro
AU - Isa, Aishah Mohd
AU - Yokoyama, Ryuichi
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
KW - Artificial neural network
KW - Electricity market
KW - Electricity price forecasting
KW - Power generation maintenance
KW - Tabu search
UR - http://www.scopus.com/inward/record.url?scp=42549157907&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=42549157907&partnerID=8YFLogxK
U2 - 10.1109/PES.2007.386099
DO - 10.1109/PES.2007.386099
M3 - Conference contribution
AN - SCOPUS:42549157907
SN - 1424412986
SN - 9781424412983
BT - 2007 IEEE Power Engineering Society General Meeting, PES
T2 - 2007 IEEE Power Engineering Society General Meeting, PES
Y2 - 24 June 2007 through 28 June 2007
ER -