Research On The Optimal Scheduling Models And Methods For Hydropower System

As the large-scale basin cascade hydropower stations are developing rapidly in our country and the electricity market reform is promoting, the fine modeling of the optimal scheduling of the hydropower station reservoirs and the modeling considering the competition mechanism in the market environment will bring about more economic benefits. Under the planned scheduling mode, the optimization of the scheduling of the hydropower need to be improved so as to promote the utilization efficiency of the water resource and show the advantage of the hydropower in the the energy saving and environmental protection, which is of practical importance. As the electricity marketization reform is clear, the scheduling should be optimized combining the electricity price mechanism and the load scheduling mechanism in order to realize the objective of the maximization of the generation profits. So under the market condition, the research on the mid-long term water level optimization scheme for the hydropower scheduling, the meticulous modeling for the short-term scheduling, and the integration of the power generation and consumption scheduling for the hydropower-domain power system will not only possess academic value, but will also provide the theoretical analyzing methods for the power generation enterprises participating the market competition and giving full play to the value of hydropower resources.(1) Under the planned scheduling mode, based on the economic concept, the dependable inflow in the first scheduling period under the given confidence level is proposed, second, a full-scenario biennial stochastic scheduling model of cascade hydropower plant was proposed to maximize the generation profits which will adapt the optimized water level to the constraints under different scenarios in the following year. The conditional value at risk (CVaR) was applied to illustrate the risk of the generation profit, and the bi-level programming combing the economy and the risk of the generation profit was constructed. At last, as for the solution of the proposed mixed-integer linear programming model, the optimal Benders decomposition with the integrated control of the master problem and the subproblems was proposed to solve the model.(2) Under the market environment, an integrated decision-making framework of end-year water level optimization and short-term market clearing is proposed to acquire the maximization of the profits of the power generation companies. Within this framework, a bi-level programming with the upper objective of maximizing the hydro power profits and the lower objective of maximizing the social welfare is constructed to optimize the water end-year water level in the upper problem and the market clearing prices in the lower problem. An optimal Benders decomposition approach with the master and subproblems is proposed with the application of the KKT conditions and the Strong Duality Theory. And then, the two-stage stochastic linear programming model is constructed aiming at the maximization of the power generation companies and the energy allocation problem of the spot market and the bilateral transactions market. The energy traded in the bilateral transactions market is optimized in the first stage considering the demand price elasticity, and the power generation is adjusted in order to compensate the energy traded in the second stage. Meanwhile, considering the stochastic nature of the spot market prices and the inflow water, the CVaR is utilized to measure the profits risk. Finally, the linear programming method is utilized to solve the model.(3) As for the short-term scheduling problem of the hydropower under the market environment, the conversion relationship between the water head and the power generated is subtly modeled in order to fully excavate the profits of the hydropower. Second, the spot market price is simulated. The short-term hydropower dispatching model is constructed satisfying the operational constraints in order to maximize the generation profits. Meanwhile, considering the market risks, the stochastic process is reasonably modeled and the risks are measured by CVaR. At last the mixed integral linear programming is utilized to solve the model.(4) The load dispatching is studied first. A two-stage load management scheme is proposed:1)The yardstick competition is applied in the optima? electricity energy rationing model to realize the maximum energy efficiency. The load dispatching order is optimized and the load dispatching amount is obtained.2)The stochastic characteristics is analyzed by means of two-state Markov Process, and the decision-making model considering the rate of load dispatching accopmplishment is constructed in order to obtain the optimized stochastic amount of the load control scheme. The price-responsive load is modeled combining the optimal power flow under the market environment, and from the systematic prospective, the price-responsive load and the interruptible load are separatedly integrated into the positive spinning reserve and the negative spinning reserve. Finally the primal-dual interior method is utilized to solve the proposed integrated dispatching model of the power generation and demand side.Finally, the feasibility and correctness of the proposed optimal scheduling models and solving methods are proved through the calculation of the case study, which will lay theoretical foundation for the practical use of the scheduling scheme.