Multi-objective Optimal Operation And Multi-attribute Risk Decision Making Of Cascaded Hydropower Stations

With the constraints of hydrological cycle, generation control, network power flow and water supply, the optimal operation of cascade hydroelectric stations is a high-dimension, multi-objective, strong-coupling, nonlinear optimal problem, and it is also a hot interdisciplinary research field of hydroelectric science and complexity science. Nowadays, with the continued fast exploitation of river basin hydroelectric energy, the scope and topology of cascade hydroelectric stations increases day by day, which bring great challenges to the joint operation of cascade hydroelectric stations. The traditional optimization theories and methods can not satisfy the demands of joint optimal operation of large-scale hydroelectric energy systems and high efficient utilization of river basin water resources. Therefore, it is quite necessary to study interrelated new optimal theories and decision-making methods. In this thesis, concering on the joint optimal operation problems of cascade hydroelectric stations, we deeply study the joint optimal operation theories and decision-making methods, by adopting the system engineering theory, modern optimization methods based on swarm intelligence, and multi-objective decision-making theory. Some conclusions with theoretical and practical value are obtained. The main conclusions of research and innovation are as follows:(1) Considering that the joint optimal operation problems of cascade hydroelectric stations have a large number of variables and these variables are usually coupled, we present a cultural differential evolution (CDE), which is suited for the optimal problems with multiple coupled variables. CDE consistes of two parts:population space and belief space. In population space, differential evolution (DE) is adopted as the searching engine of the population, and in the belief space, three knowledge structures are defined to guide the evolution process of the population, which can avoid premature convengence and improve the algorithm's global searching ability. CDE is tested by several benchmark functions and applied to the optimal operation problems of a hydropower system with 10 stations and the Three Gorges-Gezhouba cascade stations. The obtained results show that CDE can handle the complex constraints efficiently and has fast convergence rate and high convergence precision, thus it is an efficient method for joint optimal operation of cascade hydroelectric stations.(2) According to the characteristics of multi-objective optimization (MOO), we extend CDE to solve multi-objective problems (MOPs) and present a multi-objective algorithm named multi-objective cultural differential evolution (MOCDE). In MOCDE, the situational knowledge is used as archive set and an update strategy based on iterative "μ+1" selection is presented to improve the diversity of the solutions in archive set. Meanwhile, the select operator of DE is modified to suit for MOPs, according to the Pareto dominace principle. MOCDE is tested by a series of widely used multi-objective benchmark functions and it is compared with several popular multi-objective optimal algorithms, the results show that MOCDE can effectively deal with complex MOPs with the characteristics of non-convex, discontinuous and multi-modal, and it is an efficient solver for MOPs(3) Besed on analyses of the competition and conflict relation among different objectives, a multi-objective flood control operation model and a multi-objective annual power generation model are established, the former considers the flood control demands of upstream and downstream areas, and the latter considers the cascade stations' generation benefit and capacity benefit. Then we use MOCDE to solve these two multi-objective models, the results show that MOCDE can get a set of non-dominated operation schemes in a single run and provice alternatives for decision makers. Furthermore, MOCDE is used to solve multi-objective short-term optimal operation of a hydrothermal power system. A dynamic adjustment strategy is presented to handle power load balance equivalence constraints. The results validate the rationality and availability of MOCDE.(4) Risk analysis and multi-attribute risk decision making theory and methods of cascade reservoir systems are deeply researched. Considering the uncertainty, the natural inflow is described as a stochastic forecast-dependent white noise process, and then we analyse the flood control and power generation risk of cascade stations. The operation objectives, such as the maximum water level, the maximum discharge, the final water level, the annual power production, the minimum power output, and so on, are described as normal distribution stochastic variables. To solve the decision making problems with random variables, a risk decision making method based on superiority possibility and comprehensive weights assignment strategy is presented. This method calculates attribute objective weights according to the deviation of decision variables, and then integrates attribute objective weights and subjective weights to get comprehensive weights. After that, a relative dominance matrix is constructed by comparing each two schemes, and finally we can sort the schemes and pick out the best scheme. Case studies of the Three Gorges Cascade Stations show the validity of the proposed risk analysis and decision making methods.