Research On Generation Scheduling Optimization Of Cascade Hydropower System And Its Application

With the deregulation of China electric power industry, hydropower system breaks away from the conventional hydrothermal power system, which leads to significant changes of the operation objective and constraints compared to the traditional hydrothermal scheduling. Power companies pay more attention to their own generation interests while meeting the security, stability and economic operation demand of power grid. The progressive development of cascade hydropower stations makes ever larger scale hydropower systems in China, brings about new challenges for hydropower scheduling, and necessitates the unified scheduling to achieve the optimization development of cascade hydropower systems, and to improve the efficiency and benefits of power grid.Optimal scheduling of cascade hydropower systems is a complicated optimization problem affected by the hydraulic and electric coupling and the uncertainties of natural inflow, the conventional operation method based on dispatcher's experience has no longer been able to fulfill the requirements of co-scheduling of the ever larger scale hydropower systems. Based on the project "Hydropower Optimal Scheduling System Development for Cascade Hydroplants on Yuan River Basin", the optimization model and solution algorithm for solving cascade hydropower system generation scheduling are studied, the research work mainly includes the following aspects:(1) First of all, the research field is introduced by reviewing the domestic and international state-of-the-art and advances in hydro scheduling optimization, the comments on optimization algorithms' applications to this field are summarized, then the research focus is established.(2) Accounting for uncertainty, the natural inflow is described as a stochastic forecast-dependent white noise process. With the influence of the errors in estimating the end-of-study water value diminished by extending the study horizon long enough, the randomness of the standardized natural inflow reaches a stable status, and the constraints and probability distribution of inflow during each time interval tends to be the same every year, the assumption that the optimal reservoir storage trajectory will repeat annually when the study horizon is long enough is proposed. A stochastic model consists of two sub models, an annually cycling model and a real-time operation model, is established for the long-term operation optimization of hydropower system. The optimal annually cycling trajectories that serve as the boundary limits on the real-time operation model are derived for offline use by solving the annually cycling model only once. A real-time period (RTP) that covers a transition period (TP) influenced by real-time information is structured. The real-time operation model is to determine the reservoir storage trajectories, transferring from the observed water level at the beginning of a RTP to the annually cycling trajectories at the end of the RTP. Only the optimal storage derived at the end of the first time interval is used as the target to operate the reservoir, then the operation scheme is obtained to guide the reservoir operation by rolling computation. And the solution method to the model is also presented.(3) Inspired by the hierarchical optimization control mechanism, a comprehensive model for short-term generation scheduling of hydropower system is established. The involved constraints include the water mass conservation, the power balance, limits on reservoir storage and release, expansion of pumped-storage hydroplant, nonlinear plant-based power generation characteristics, limits on plant-based power and ramp, limits on plant-based discharge, limits on reservoir release ramp, limits on plant-based operational region, limits on plant-based start-up and shutdown frequency and duration. The nonlinear objective and constraints are successively approximated by first order Taylor series expansion, and p-decomposition-based algorithm is used to decompose the original problem into several sub ones by decomposing the coupling power balance, constraints with upper bounds are simplified so as to decrease the variable number in the coefficient matrix, a constraint violation priority is defined to deal with the situation that the artificial variables associated with the constraints are non-zero to ensure a feasible active solution is always derived. When the reservoir release and plant-based power are determined, the plant-based operation region schedule is obtained by solving a recursive Dynamic Programming process constrained by the requirements for the plant-based start-up and shutdown frequency and duration. The specific solution algorithm is described as well.(4) The coordination between long-term and short-term operation is studied. The storage boundary limits of the short-term optimal scheduling are derived from the long-term scheduling results by linear interpolation, then transferring from the observed water level, the coordination is implemented by rolling computation to attain the optimization operation of the cascade hydropower system.Finally, with application to the optimal co-scheduling of cascade hydroplants on Yuan River basin in Hunan, the models and methods proposed in this dissertation are practically verified to be suitable for generation scheduling of cascade hydropower systems, and the numerical results demonstrate the feasibility and effectiveness of the presented optimization models and solution algorithms.