Multi-objective Optimization Dispatching Of Cascade Hydropower Station Under Power Market

The new round of electric power system reform has brought great changes to the production and operation of power generation enterprises,and brought new development opportunities for cascade hydropower station.With the continuous advancement of the new electric power system reform,the dispatching objectives and criteria of cascade hydropower station have also changed.The complicated market environment has made it more difficult to solve the optimal dispatching problem of cascade hydropower station with multiple scales,high dimensions and large scales.In the face of complex hydraulic and market constraints,how to take into account multiple targets and how to make transaction decisions and hydropower bidding in the multi-scale power market environment for cascade hydropower station is a serious and difficult problem that deserves attention and needs to be solved urgently.Aiming at the multi-objective optimal dispatching problem of cascade hydropower station under the electricity market environment,this paper studies the long-term and medium-term multi-objective optimal dispatching of cascade hydropower station under the power market respectively,based on the trading and settlement rules of Yunnan power market and taking Lancang River cascade hydropower station as an example.The main research results are as follows:(1)Aiming at the two competitive objectives of cascade hydropower station to obtain trading income and increase the value of energy storage,the income and storage hedging rule is introduced.Compared with the standard operating policy,the income and storage hedging rule,which is optimized by the adaptive and self-adjustment genetic algorithm and then collated and drawn,can reserve a higher energy storage and make the system’s comprehensive loss smaller when the annual water quantity is insufficient,which can provide the decision makers with a safe and reliable basis for trading and energy storage decisions.According to the optimization results of three different decision-making concepts of the income and storage hedging model,standard operating policy model and comprehensive income model,the decision made under income and storage hedging model is more conservative and can assume greater risks in the case of insufficient water.The results of the scheduling process of the income and storage hedging model can provide a basis for decision makers to make trading decisions in the annual(multi-month)market and monthly market.(2)Aiming at the multi-objective optimal dispatching problem of price-maker cascade hydropower station participating in day ahead market,a multi-objective optimization model was established to maximize the settlement income,maximize the energy storage and minimize the deviation electric quantity.By using the relative target proximity,the multi-objective problem is transformed into a single objective,and then the adaptive and self-adjustment genetic algorithm is integrated to search for the optimal problem,which provides decision-maker with abundant optimal information and help decision-maker make the decision quickly according to the weight of targets.Through the research on the price-maker type of cascade hydropower station participating in the day-ahead market,the bidding strategy can be provided for large-scale cascade hydropower station participating in the power market,and offer the basis for how to arrange generation scheduling and day ahead Market trading plan.