The Bidding Strategy And Optimal Scheduling Methods Of Hydro-dominated Power Market

The hydropower resources in southwest China are very rich,taking Yunnan and Sichuan province as an example,the installed hydropower capacity has both exceeded 70%of their total installed capacity.With the deepening of the new round of electricity market reform,a typical hydro-dominated power market has formed.The marketization of electricity provides an opportunity for hydropower consumption,but it also brings new challenges.Unlike other electricity markets with small proportion of hydropower installed capacity,the hydro-dominated power market in southwest China has its unique features,such as the hydropower installed capacity is very large and dominated,power generation is susceptible to uncertain runoff,the competitiveness of various market players is greatly different,the relationship between cascade hydropower plants is tightly coupled,the local consumption ability is insufficient and the hydropower is need to be sending out,and so on.These characteristics have greatly increased the difficulty in dispatching and trading of hydro-dominated power market,the power market is faced with new problems including the complexity of the complex formation mechanism of electricity price,the marketization consumption of hydropower under the influence of uncertainties,the coordination of market transactions and energy conservation,etc.However,whether domestic or foreign,there are relatively few researches that can be referred for the hydro-dominated power market.Given the fact that China's electricity market reform is still in its infancy,this dissertation carries out the studies including market clearing price forecasting,power grid scheduling in transition and hydropower market transactions,respectively from three different perspectives,namely,market,power grid and hydropower companies.The main achievements can be wrapped up by the following points:(1)In view of the fact that few data are available for mid-term electricity market clearing price(MCP)forecasting at the early stage of market reform,a novel grey prediction model(defined as interval GM(0,N)model)is proposed.Based on the power market reform in Yunnan province,also a pilot province of China power market reform,the main influence factors of MCP is firstly analyzed from supply side and demand side,which are used as input data.Then,the upper and lower points of the forecasting point in the MCP sequence are regarded as two virtual values to construct two new MCP sequences,which are respectively used as input for two improved GM(0,N)models,obtaining the forecasting interval.Finally,based on the forecasting interval,a novel whitenization method,taking correlation coefficient weighted gaps of factor sequences into consideration,is established to determine the definite forecasting value.For evaluating the accuracy of the proposed model,the after-test residue checking method,mean absolute error(MAE),mean squares error(MSE)and mean absolute percentage error(MAPE)are used.Besides,a statistical evaluation method named modified Diebold-Mariano(MDM)test is also proposed to further judge the forecasting performances of different forecasting models.Compared with the multiple linear regression(MLR)model,the traditional GM(O,N)model and the artificial neural network(ANN)model,the proposed model gives a better performance,suggesting that it is suitable for mid-term electricity MCP forecasting in a data-sparse electricity market and can provide supervision for market bidding,power generation,maintenance planning,risk control,and so on.(2)For the issues during the cross-provincial and cross-regional market trading of large-scale hydropower,this section proposed a new optimization model of trading strategy portfolio for cascade hydropower plants,aiming to achieve maximum benefits for cascade hydropower plants in various markets.Considering the uncertainty of market price and coupling correlation between multiple markets,the Copula function is firstly introduced to describe the correlation of price fluctuation among different markets,obtaining the joint distribution function of market price.Then.the market price scenarios are reduced by Hierarchical clustering method and Inconsistent Coefficient,and based on these scenarios,the optimization model is constructed in consideration of hydraulic connection,electrical interaction and market transaction constraints.Finally,the LINGO 17.0 software is used as the solution tool.which includes a nonlinear global optimization method(named Global Solver)based on branch and bound algorithm.Take the Wujiang cascades as a study case,and the proposed model is also compared with the traditional operation method.Simulation results shown that,the proposed model performs better in following the market prices changes,and can obtain optimization strategy between different time periods and different markets,so as to gain greater market benefit for hydropower cascades.(3)For the competition issues among different hydropower plants in market environment,a sampling stochastic dynamic programming game(SSDP-Game)model is proposed in this section to study the changes in hydropower operation modes,power outputs,benefits,etc.and their influence factors in the market environment.Respectively with the goal of maximum benefits for single-and multi-stakeholders,both non-cooperative and cooperative SSDP-Game models are constructed.The equilibrium status of the various entities in market under the non-cooperative and cooperative mode are respectively described by Nash-Cournot model and Nash-Harsanyi Bargaining model,and further solved by one-and multi-dimensional solving methods based on the fastest rise search.Hydropower plants including Longtan on Hongshuihe river,Xiao wan on Lancang river and Goupitan on Wujing river are selected for case studies,and the results show that the SSDP-Game results are affected by four characters of hydropower plants,the regulation ability affecting the average price,the falling degree changing of reservoir level before flood season affecting total energy losing,and the installed capacity and inflow stability of refill months affecting the market energy decreasing.The simulation results provide scientific basis for hydropower plants generation decision-making and reservoir level control in market environment.(4)Considering the particularity of power generation scheduling during the transition period of the electricity market reform,a novel power grid dispatchling model for the transition period of electricity market reform is built.In this model,the generation schedule of different types of units(e.x.bidding and non-bidding,hydro and thermal)are optimized in harmony according to the electricity purchasing cost,emission reduction and scheduling fairness objectives.By the decomposition algorithm of mid-and long-term contract energy,the scheduling fairness of units those participate in market is ensured,and the decomposed contract quantity are considered as a constraint in the established model.The multi-objective model is converted to a single objective model by fuzzy optimization method,and further solved by adaptive particle swarm optimization algorithm with feasible initial solution(FIS-APSO)and adaptive parameters,so as to improve the drawback of local convergence in the traditional PSO.The IEEE(Institu:te of Electrical and Electronics Engineers)simulation systems are combined with the power source structure of Yunnan and Guizhou province respectively.The simulation results show that the proposed model can achieve the nested optimization of day-ahead generation scheduling and mid-to long-term market transaction in markets with different power source structure,considering not only the completion of the market transaction contract,but also the coordination of dispatch economy,environmental protection and fairness,which provides effective guidance for power system dispatching in the market transition periods.Finally,summarize the content of the whole study and some problems to be further studied are discussed.