含风电场的电力系统动态优化调度研究

发布时间：2018-06-05 19:47

本文选题：风电场 + 动态优化　；参考：《燕山大学》2014年硕士论文

【摘要】：电力系统有功优化通过对有功潮流的调整达到对某些目标值的优化，电力系统的无功优化通过对无功潮流的调整实现对相应目标值的优化。这两种优化对电力系统的优化运行都具有重要的意义，但是又都具有片面性。本文对含风电场的电力系统进行了动态有功优化调度、动态无功优化调度、动态有功-无功综合优化调度。主要内容如下：给出了含风电场的电力系统潮流计算方法。在对风电场的处理中，考虑了单台风电机吸收的无功功率与有功出力以及机端电压的关系。并且计及了尾流效应与风电场布局对于整个风电场输出功率的影响。对基本粒子群算法进行改进，并给出了针对动态优化问题的粒子群求解算法。在有功优化中，首先对不含风电场的电力系统进行动态经济调度，然后采用模糊处理的方法，建立含风电场的电力系统节能环保多目标模糊模型，对风电出力进行模糊处理。针对多目标模型中难以进行模糊处理的问题，提出对多目标模糊模型的分步处理策略。采用求解Pareto最优解集的方法求解此多目标优化问题，对含风电场的电力系统进行动态有功优化调度，并仿真验证。由于无功优化模型中含有离散变量，本文采用针对含有离散变量的优化问题的粒子群算法进行求解。相对于静态无功优化问题，动态无功优化问题的难点在于对控制设备投切次数约束的处理，针对此问题采用对控制设备动作时刻动态调整的方法，进而对含风电场的电力系统进行动态无功优化调度，并对此进行仿真验证。针对单独进行有功优化和无功优化的片面性、不全面性的问题，提出有功-无功综合优化方法。建立了含风电场的电力系统有功-无功多目标优化数学模型，并给出对有功-无功多目标优化模型的求解方法，通过算例对此模型进行仿真验证。
[Abstract]:The active power optimization of power system achieves the optimization of some target values through the adjustment of the active power flow, and the reactive power optimization of the power system realizes the optimization of the corresponding target value by adjusting the reactive power flow. These two kinds of optimization are of great significance to the optimal operation of power system, but both have one-sidedness. In this paper, dynamic active power optimal scheduling, dynamic reactive power optimal scheduling and dynamic active and reactive power comprehensive optimal scheduling are carried out for the power system with wind farm. The main contents are as follows: The power flow calculation method of power system with wind farm is presented. In the treatment of wind farm, the relationship between reactive power absorbed by single typhoon motor and active power output as well as terminal voltage is considered. The effects of wake effect and wind farm layout on the output power of the wind farm are also taken into account. The basic particle swarm optimization algorithm is improved, and the particle swarm optimization algorithm for dynamic optimization problem is presented. In the active power optimization, the dynamic economic dispatch of the power system without wind farm is first carried out, and then the fuzzy processing method is adopted to establish the multi-objective fuzzy model of energy saving and environmental protection of the power system with wind farm, and the fuzzy treatment of wind power output is carried out. Aiming at the difficulty of fuzzy processing in multi-objective model, a step by step strategy for multi-objective fuzzy model is proposed. The multi-objective optimization problem is solved by solving the Pareto optimal solution set. The dynamic active power optimal scheduling of the power system with wind farm is carried out and verified by simulation. Because the reactive power optimization model contains discrete variables, particle swarm optimization (PSO) algorithm is used to solve the optimization problem with discrete variables. Compared with the static reactive power optimization problem, the difficulty of the dynamic reactive power optimization problem is to deal with the control equipment switching times constraint. Then the dynamic reactive power optimal dispatching of the power system with wind farm is carried out, and the simulation is carried out. Aiming at the one-sidedness and incompleteness of active power optimization and reactive power optimization, a comprehensive method of active and reactive power optimization is proposed. The mathematical model of active and reactive power multi-objective optimization of power system with wind farm is established, and the method of solving the multi-objective optimization model of active and reactive power is given. The simulation results of the model are verified by an example.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614;TM73

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