TY - GEN
T1 - Conditional value-at-risk based mid-term generation operation planning in electricity market environment
AU - Lu, Gang
AU - Wen, Fushuan
AU - Chung, C. Y.
AU - Wong, K. P.
PY - 2007/9
Y1 - 2007/9
N2 - In the electricity market environment, it is very important for generation companies (GENCOs) to make the optimal mid-term generation operation planning (MTGOP) which includes the trading strategies in the spot market and the contract market as well as the suitable unit maintenance scheduling (UMS). In making the decision of MTGOP, GENCOs are subject to risk due to uncertain factors, and hence should manage the inevitable risk rationally. Given this background, a new MTGOP model is first developed for a GENCO as a price taker so as to maximize its profit and minimize its risk measured by the Conditional Value-at-Risk (CVaR). In this model, the bilateral physical contracts are taken into consideration, together with the transmission congestion and the operation constraints of generating units. Then, a solving method is given by integrating the Genetic Algorithm and the Monte Carlo method. Finally, a numerical example is used to show the features of the proposed method.
AB - In the electricity market environment, it is very important for generation companies (GENCOs) to make the optimal mid-term generation operation planning (MTGOP) which includes the trading strategies in the spot market and the contract market as well as the suitable unit maintenance scheduling (UMS). In making the decision of MTGOP, GENCOs are subject to risk due to uncertain factors, and hence should manage the inevitable risk rationally. Given this background, a new MTGOP model is first developed for a GENCO as a price taker so as to maximize its profit and minimize its risk measured by the Conditional Value-at-Risk (CVaR). In this model, the bilateral physical contracts are taken into consideration, together with the transmission congestion and the operation constraints of generating units. Then, a solving method is given by integrating the Genetic Algorithm and the Monte Carlo method. Finally, a numerical example is used to show the features of the proposed method.
KW - Conditional value-at-risk
KW - Contract market
KW - Mid-term generation operation planning
KW - Spot market
KW - Unit maintenance scheduling
UR - http://www.scopus.com/inward/record.url?scp=79955306449&partnerID=8YFLogxK
U2 - 10.1109/CEC.2007.4424818
DO - 10.1109/CEC.2007.4424818
M3 - Conference article published in proceeding or book
AN - SCOPUS:79955306449
SN - 1424413400
SN - 9781424413409
T3 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
SP - 2745
EP - 2750
BT - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
T2 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
Y2 - 25 September 2007 through 28 September 2007
ER -