摘要
研究竞价上网环境下的梯级水电厂日优化运行问题 ,建立了电网边际电价预测的线性移动自回归模型 ,在此基础上 ,提出了梯级水电厂日优化运行模型 ,并采用遗传算法求解。计算结果可作为梯级水电厂日前交易市场电价和电量申报的基础 。
The optimal generation problem of cascade hydroelectric plants in a competitive power market is presented in this paper. A linear moving mean auto regression model has been developed to forecast the marginal price of the system. The second model by using genetic algorithms is presented to attain the total day generation of the cascade plants each 15 minutes. These results can be the basis of declaring power price and electric energy. The case study shows that the optimal operation of cascade hydropower plants based on forecasting power price can get considerable economic benefits in a competitive electricity market.
出处
《水力发电学报》
EI
CSCD
北大核心
2004年第4期11-15,共5页
Journal of Hydroelectric Engineering
基金
美国能源基金项目 :TheChinaSustainableEnergyProgram(G 0 2 1 2 0 6633)
关键词
电力市场
电价
遗传算法
power market
hydroelectric power price
genetic algorithms