Research On Multi-objective Optimization Scheduling And System Design Of Cascade Hydropower Stations

Hydropower energy is a clean,low-carbon and convenient renewable energy with comprehensive utilization efficiency.By the end of 2017,China's hydropower capacity was 341 million kW,which was a year-on-year increase of 2.7%,accounting for 19.2% of total installed power generation capacity.Strengthening the overall planning and scientific management of hydropower energy is a key measure to advance the structural reform of the energy supply side.In recent years,under the guidance of the principle of “basin,cascade,rolling,and comprehensive”,China's hydropower construction has gradually formed a number of hydropower bases.With the succession of river basins and inter-basin hydropower stations,the joint optimal operation of cascade hydropower stations in the river basin has large-scale,nonlinear,strong coupling,and multi-target characteristics,and must consider the effects of hydrometeorology,water demand,and power grid security.Traditional single-objective optimization scheduling method is difficult to solve the multi-objective optimization scheduling problem under the new situation.It is urgent to seek new theories,models,methods and technical means to carry out research.Therefore,Xiluodu-Xiangjiaba and Qingjiang cascade hydropower stations are studied respectively in this paper.Long-term and short-term multi-objective models are established,which are solved by the multi-objective evolutionary algorithm based on decomposition and the improved multi-objective particle swarm optimization algorithm,respectively.The dispatching system is designed to provide technical support and decision support for multi-objective optimal dispatching of cascaded hydropower stations.The main work and achievements are as follows:(1)In order to increase the minimum output during the dry season and improve the power supply reliability of the power system,the power generation and capacity benefits of the cascade hydropower stations are coordinated.A multi-objective optimization model is established with the minimum output of the period and the total power generation of all periods.Using a constrained "corridor" approach to randomly generate initial solutions in a feasible space and correcting the infeasible solutions to the boundary through a repair strategy,an improved MOEA/D combined with differential evolution and polynomial mutation operators is proposed to solve the model.The case studies of cascade stations show that MOEA/D can effectively deal with the complex constraints of the medium and long-term scheduling and the convergence speed is fast.The Pareto front can be distributed uniformly,providing data support for actual decision-making optimization.(2)Focusing on the preparation of short-term power generation plans for cascade hydropower stations on the Qingjiang River,a comprehensive multi-objetive power generation planning model with the largest total power generation and the least load variance on the power grid is established.Based on the constraint processing method of multi-objective optimization scheduling in long-term,the optimal flow distribution technology is adopted to improve the accuracy of power generation planning.The above model is solved by using SMPSO.The results show that the improved algorithm can effectively overcome the shortcomings of slow convergence speed and easy convergence to local optimum.It can improve the power generation efficiency of the whole cascade while responding to the peaking demand of the power grid and provide a new solution to the short-term power generation planning ideas.(3)Aiming at the deficiencies of chaotic front-end logic and unclear responsibilities in the traditional MVC model,this paper proposes a REST-based front-end and back-end separation architecture model for the development and integration of reservoir group optimization scheduling system.The back-end is based on the Spring Boot micro framework and focuses on model solving and data processing.The front-end uses React,Dva,and Ant Design's technology stack,focusing on data interaction and user experience.At the same time,with the object-oriented programming as a guide,the abstraction of the power plants and model algorithms involved in the optimization scheduling is abstracted,and a set of core class libraries for optimal operation of the reservoir group is designed to improve the system's standardization and scalability.