【作者】 王茜；

【导师】 张粒子；

【作者基本信息】 华北电力大学（北京） ， 电力系统及其自动化， 2011， 博士

【摘要】 风电场的地点选择和容量确定、输电网发展规划等都将对电力系统的可靠性和投资经济性产生重要的影响。为充分发挥风力发电的节能减排效益,促进系统可靠性、投资经济性、环保效果的整体优化,论文分别从风电场对发输电系统可靠性的影响及其容量优化、含风电场的输电网规划与投资经济性评价、风电场与输电网协调规划的模型和方法等三个方面开展理论研究,取得了如下主要研究成果：风电场对发输电系统可靠性的影响及其容量优化方面：(1)在发输电系统可靠性评估理论的基础上,针对蒙特卡洛模拟方法中最优乘子确定方法计算精度与速度难以协调的不足,基于聚类最优乘子向量提出了一种改进的发输电系统可靠性评估快速抽样方法。(2)针对现有可靠性评估中没有考虑不同故障持续时间下单位负荷损失不同的问题,构建了基于停电持续时间的负荷损失费用模型,并应用于风电场对电力系统可靠性的影响分析中。(3)考虑到不同地点风况的差异性以及电网拓扑结构和线路传输能力的制约,针对不同地点分散接入风电机组的效果可能会优于在同一个地点集中接入的情况,构建了最大化风电场容量的多个风电场规划模型,并应用蒙特卡洛模拟提出了求解该模型的概率方法。含风电场的输电网规划与投资容量优化方面：(1)在考虑风电场出力波动对电力系统影响的基础上,以电网投资成本和网损费用之和最小化为目标,建立了含风电场的输电网规划模型；针对风电波动性可能会增加规划模型复杂度的不足,采用风电场出力的分段线性化策略简化了上述模型,并综合运用混合蛙跳算法、离散化处理方法和阈值选择策略等进行了求解。(2)针对跨省区联络线或输电断面的投资决策问题,在考虑风电场弃风的效益损失基础上,以跨省区输电投资前后的阻塞成本减少与输电投资成本之差(即综合效益)最大化为目标,建立了跨省区输电投资容量优化模型,应用确定性方法和概率性方法进行了对比分析。风电场与输电网协调发展的模型和方法方面：(1)针对风电场并网地点的选择问题,以线路投资成本和负荷损失费用等之和(即综合费用)最小化为目标,构建了风电场接入系统方案与输电网扩展规划的协调优化模型；采用奔德斯分解算法将优化模型分解为投资决策主问题和运行模拟子问题,结合蒙特卡洛模拟和样本均值算法提出了一种提高算法收敛速度的改进奔德斯分解算法。(2)为促进投资经济性、系统可靠性、环保效果的整体优化,同时以风电场和线路投资成本等之和(即综合成本)、负荷损失费用、污染物排放量最小化为子目标,构建了风电场与输电网协调发展的多目标规划模型；针对因帕累托最优解较多而无法合理决策的问题,采用方差最大化决策和分类逼近理想解的排序方法缩小最优解的范围,提出了模拟、神经元网络和改进非劣分类遗传算法相结合的混合智能算法。论文针对电力系统规划所面临的新问题,系统地开展了含风电的发输电系统可靠性评估与规划问题研究,从全社会效益最大化角度探讨风电规划与输电网规划协调优化的模型和方法,具有理论价值和现实意义。更多还原

【Abstract】 Wind farms’sites and capacities, transmission development planning and other aspects would affect power system’s reliability and investment economy. In order to embody wind farms energy saving and emission reduction benefits, it is necessary to maximize integration result of power system reliability, investment efficiency, and environmental effects. This paper does theory research on composite generation and transmission reliability with wind farms, decides wind farms sites and capacities, evaluates transmission planning and investment economy, and promotes coordinated planning between wind farms and transmission network. The following research achievements are obtained:In aspect of composite generation and transmission reliability with wind farms and its capacity optimization, firstly, on the basis of composite generation and transmission reliability theory-and Monte Carlo simulation method, this paper proposes an improved composite generation and transmission reliability assessment fast sampling method based on clustering optimal multiplier vector, which can coordinates optimal multiplier method’s results precision and computing time. Secondly, in order to embody diffenence of unit load loss in different fault duration in power system reliability assessment, the load loss cost model based on outage duration is established, which can be applied to power system reliability impact analysis with wind farms. Thirdly, this paper can reasonably simulates the wind speed in different regions and considers transmission network structure and capability, and establishes a optimal model of maximizing wind turbine capacity with several wind farms, which can reflect that benefits of wind turbine integrated in different locations are better than the same location, then the probability method to solve above model based on Monte Carlo simulation is presented.In aspect of evaluating transmission planning and investment capacity optimization with wind farms, firstly, this paper establishes a transmission planning model with wind farms aiming at minimizing transmission investment cost and network loss cost, which could consider wind farm output volatility’s influence on power system. In order to solve planning model complexity difficulty caused by wind volatility, piecewise linear strategy is used to simplify wind power output. Then shuffled frog leaping algorithm, discretization processing method and threshold selection strategy are comprehensively used to solve the above model. Secondly, for cross-regional and trans-provincial power transmission investment decision problems, this paper proposes a transmission capacity optimal model considering wind energy benefit, whose objective is to maximize difference value between congestion cost reduced value and transmission investment cost, then analyzes application results of deterministic method and probabilistic method. In aspect of promoting coordinated development between wind farms and transmission network, firstly, this paper proposes a coordinated optimal model between grid-connected wind farms program and transmission planning, whose objective is to minimize transmission investment, load loss cost, et al. Then the above model is decomposed by Benders decomposition algorithm into two parts, which are investment decision main-problem and operation simulation sub-problem. The modified Benders decomposition algorithm combined with Monte Carlo simulation method and sample average approximation is used to improve the convergence behavior. Secondly, in order to maximize integration result of investment efficiency, power system reliability, and environmental effects, this paper proposes the multi-objective coordinated optimal model between wind farms planning and transmission planning, whose objective is to minimize power system investment and operation cost, load loss cost and pollutant emission. Aiming at solving decision rationality difficulties, the hybrid intelligent algorithm combined with simulation, neural network, and non-dominated sorting genetic algorithmⅡis proposed, which could narrow the optimal solution scope by deviations maximization method and technique for order preference by similarity to an ideal solution.In order to solve some new problems appeared in power system planning, this paper systematically carries out research on composite generation and transmission reliability assessemnt and planning with wind farms, and explores models and methods of coordinated optimization planning between wind farms and transmission network based on the biggest social benefits, which has larger theory value and practical significance.更多还原