摘要风能作为可再生的清洁能源，受到各国青睐。但是风电的不可预测性和波动性给电力系统的研究带来了许多难题。电力系统的经济调度是在系统和负荷一定的条件下使运行成本最小，其模型是非线性的、多约束的。风电并网以后，电力系统的稳定性受到了冲击。本论文针对风电，运用粒子群算法实现电力系统的经济调度。76793

首先，考虑电力系统的经济调度中目标函数和约束条件的确定。风电并网后，系统较之前变得更加复杂。在处理安全约束时，本文采用直流潮流法不考虑无功功率，简化模型。为保持系统的稳定，本文增大旋转备用容量防止因风电的骤减或猛增使系统不能稳定运行。

其次，基于粒子群优化算法的特点，用粒子群算法处理目标函数和约束条件，在电力系统中求得最优解。为实现算法的高效性，在火电机组出力、爬坡、滑坡约束、旋转备用容量约束等约束条件的范围内产生随机数，加速收敛。

最后，通过对电力系统模型的仿真，证明粒子群算法的可行性和风电并网系统的稳定性、经济性和高效性。

该论文有图13幅，表11个，参考文献32篇。

毕业论文关键词： 风电并网  电力系统的经济调度  粒子群优化算法  约束条件

Power System Containing Wind Power Economic Dispatch Model and the Realization of the Swarm Algorithm

Abstract As a renewable clean energy, wind energy has been the favor。 But the unpredictability and volatility of wind power has brought many problems to power system research。 Economic operation of power system minimizes the operating cost under the definite condition of system and load。 The model is nonlinear and multiple constraints。 After wind power grid, the stability of power system is impacted。 For wind power, this paper uses particle swarm algorithm to realize the economic dispatch of power system。

First of all, it should be considered of the identification of the objective function and constraint conditions in the economic dispatch of power system。 After wind power grid, the system becomes more complicated than before。 When dealing with security constraints, this paper uses the dc current method without considering the reactive power in order to simplify the model。 To maintain the stability of system, this paper increases spinning reserve capacity to prevent that the system can not operate stably caused by the sudden increase or decrease of wind power。 

Secondly, based on the superiority of the particle swarm optimization algorithm, the objective function and constraint conditions can be dealt with particle swarm optimization 。And doing like this is in order to gain the optimal solution in the power system。 To achieve the efficiency of the algorithm in the thermal power unit output, it produces random number within the scope of constraint conditions such as climbing and landslides of thermal power generating unit, spinning reserve capacity constraints to speed up the convergence。

Finally, through the simulation of power system model, it can be proved of the feasibility of particle swarm optimization (PSO) algorithm and the stability, economy and efficiency of wind power grid system。

Key Words：wind power grid  the economic dispatch of power system  the particle swarm optimization algorithm  constraint conditions

目  录

摘  要 I

Abstract II

目  录 IV

图清单 VI

表清单 VI

1 绪论 1

1。1 课题的研究背景和意义