Research On Optimal Dispatching Of Generating Units In Wind Power Integrated System

Wind energy is a renewable green clean energy without consuming fuel. Due to its lost cost, it has broad prospects for development. In recent years, China's making great efforts to the development of energy-saving society, and paying more attention to the development and utilization of clean energy, which promotes the development of China's wind power business. However, due to the randomness of wind speed and wind power output forecast error, wind power has brought new demands to the stable operation of the power system. Especially when large-scale wind farm grid, because of the random nature of wind farm output, the scheduling problem in wind power integrated system become the research topic that needs to be solved.Scheduling power unit is a high-dimensional,non-convex,multi-constrained optimization problem. Taking the randomness of the wind farm output into account, chance-constrained programming and stochastic simulation techniques are introduced, and mathematical model of the scheduling problem in wind power integrated system based on chance constrained programming is established. It describes the related constrained conditions by the form of probability,and Stochastic simulation techniques is introduced to evaluate the constraints, to obtain a reliability program considering the characteristics of randomness and volatility of wind farm.Hybrid intelligent algorithm of ant colony-particle swarm is introduced. UC problem is divided into outer and inner optimization sub-problems. The outer layer is unit commitment, solved by VC algorithm considering of unit rules. The inner layer is the economic distribution of the load solved by PSO algorithm. The specific solution steps of the algorithm is discussed through the 10-machine system example to solve unit commitment optimization and load distribution before and after integrating the wind farm, and under different degree of confidence. The calculation results show that the algorithm is effective and feasible, giving consideration to economy and reliability in wind power integrated system In the case of wind farm output uncertainty.Based on chance co strained programming, a multi-objective unit commitment model for the total cost of dispatching saving and emission of atmospheric pollutants in wind power integrated system is presented. The problem is divided into outer and inner layers. The inner layer is the economic distribution of the load solved by MOPSO algorithm, considering Pareto optimal solution set of concepts and the overall coordination of decision-making method. Through the 10-machine system example, unit commitment optimization and load distribution are solved before and after integrating the wind farm, and under different degree of confidence. The calculation results show that the algorithm is effective and feasible, providing a new way of thinking to optimal scheduling of the multi-objective unit containing the wind farm power system.