计及风电场的大电网可靠性模型算法研究
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摘要
随着能源问题和环境问题的日益严峻,世界各国竞相大力发展可再生能源。风电是无需燃料费用的可再生绿色能源,由于其利用成本的低廉和技术的成熟,风电已成为可再生能源中发展最快的、最具有发展前景的一种发电力式。但是与其他常规的火电厂、水电厂不同,风电场的输出功率不断波动,大规模风电并网后会对电力系统的安全稳定运行带来一定的影响。为研究风电场并网对电力系统可靠性的影响,本文建立了基于蒙特卡洛仿真的计及风电场的大电网系统可靠性分析模型,充分考虑了风速的随机性及风电机组强迫停运率,对计及风电场的大电网系统进行可靠性评估。本文所作工作如下:
①本文简单介绍了风力发电可靠性评估的发展概况、方法和国内外研究现状,认识到对计及风电场大电网系统进行可靠性评估的重要性。
②大电网可靠性评估方法可分为解析法和模拟法,其中模拟法由于方法的灵活性和实用性已日益得到重视和应用。模拟法按随机抽样方法的不同而分为非序贯蒙特卡洛仿真、序贯蒙特卡洛仿真和状态转移抽样。本文详细介绍了三种蒙特卡洛仿真方法的基本原理,分析了它们的优缺点。同时,基于序贯蒙特卡洛仿真得到的年可靠性指标样本和非参数概率密度估计技术,论文实现了可靠性指标的概率密度估计,探索了从可靠性指标内在分布规律和结构特征出发深刻揭示电网风险特性的新思路。通过对RBTS和IEEE-RTS79可靠性测试系统的评估分析,验证了所提方法的正确性和有效性。
③风速预测是风电场规划设计中的重要工作。考虑风速时序性和自相关性的特点,采用时间序列法建立了风速序列预测模型,在算例中,将预测风速的分布特性与实际风速分布特性相比较,验证了自回归移动平均模型用于风电场风速预测的可行性。
④根据风速序列预测模型,结合常规机组、线路和变压器等的状态模型,建立了基于序贯蒙特卡洛仿真的风电场可靠性模型,该模型充分考虑了风能随机性和风电机组强迫停运率等不确定因素,将该模型应用于计及风电场的大电网系统,按照在满足系统安全约束条件的前提下充分利用风电的原则,对计及风电场的大电网系统进行可靠性评估。
⑤将风电场的可靠性模型与电力系统模型相结合,提出基于序贯蒙特卡洛方法评估计及风电场的大电网系统可靠性,研究了风电场并网、风电场穿透功率、风电场选址以及风速变化对电网可靠性的影响,为风电场的规划与运行奠定理论基础;另外,基于核密度估计技术得到了可靠性指标的概率密度分布,对几种方案可靠性指标的概率密度分布进行了比较,实现了对计及风电场的大电网风险更深入和完整的认知。
With the increasing severity of energy and environment problems, renewable energy is competitively developed all over the world. The wind energy was developing fastest among all kinds of renewable resources due to its a kind of renewable green power resources, its low cost and technical maturity. Unlike the other power plants, the active power from wind farms varies all the time, which may influence the operation and stability of power network after connection. To study the impact of the wind farm on the system reliability, this thesis presents a reliability assessment model of wind power integration in power systems based on the Monte Carlo simulation approach, which considers the randomicity of the wind and wind power generation forced outage rate. The main work has been done as follows:
①At first the thesis introduces the development, method, significance and research progress of reliability assessment of wind power integration in Bulk Power Systems at home and abroad.
②The reliability evaluation methods are usually divided into two kinds, that are analytical and simulation methods, and the simulation approach has been received consideration attention for its flexibility and practicality. Based on different sampling techniques, there are three kinds of simulation methods which are nonsequential Monte Carlo simulation, sequential Monte Carlo simulation and state transition sampling. This thesis details their fundamental principles and analyzes their merits and drawbacks. Moreover, utilizing the annual reliability indices samples and nonparametric kernel estimation technique, this thesis realizes the probability density estimation for reliability indices. This probability density information can facilitate us to discover system risks from the internal distribution laws and structural features of reliability indices. The proposed methods are verified using RBST and IEEE-RTS79 systems.
③Wind speed forecast is an important task of wind farms planning. Based on time series analysis, the thesis presents a wind speed forecast model, which considers timing and auto-correlation characteristic of wind speed. The distribution characteristic of the forecasted wind speed are compared with those of measured wind speed in a calculative example, which shows that the auto-regressive and moving average (ARMA) model is feasible in wind speed forecast for wind farms.
④This thesis presents a wind farm reliability assessment model based on the sequential Monte Carlo simulation using the reliability models of the conventional generators, lines and the transforms, which considers the randomicity of the wind and wind power generation forced outage rate. The reliability of Bulk Power Systems contain wind farms is evaluated in term of the principle that wind power is employed sufficiently, according to meeting system security constraints.
⑤Combining the wind farm reliability assessment model with the Bulk Power Systems, the reliability of wind power integration in Bulk Power Systems is evaluated. The impacts of adding wind farms to system, changing of penetration and wind speed on reliability of power system is analysed. The study provides the important reference value for wind farm operation and planning. Moreover, the probability density estimation of the five casesare given and compared based on kernel density estimation technique.
①本文简单介绍了风力发电可靠性评估的发展概况、方法和国内外研究现状,认识到对计及风电场大电网系统进行可靠性评估的重要性。
②大电网可靠性评估方法可分为解析法和模拟法,其中模拟法由于方法的灵活性和实用性已日益得到重视和应用。模拟法按随机抽样方法的不同而分为非序贯蒙特卡洛仿真、序贯蒙特卡洛仿真和状态转移抽样。本文详细介绍了三种蒙特卡洛仿真方法的基本原理,分析了它们的优缺点。同时,基于序贯蒙特卡洛仿真得到的年可靠性指标样本和非参数概率密度估计技术,论文实现了可靠性指标的概率密度估计,探索了从可靠性指标内在分布规律和结构特征出发深刻揭示电网风险特性的新思路。通过对RBTS和IEEE-RTS79可靠性测试系统的评估分析,验证了所提方法的正确性和有效性。
③风速预测是风电场规划设计中的重要工作。考虑风速时序性和自相关性的特点,采用时间序列法建立了风速序列预测模型,在算例中,将预测风速的分布特性与实际风速分布特性相比较,验证了自回归移动平均模型用于风电场风速预测的可行性。
④根据风速序列预测模型,结合常规机组、线路和变压器等的状态模型,建立了基于序贯蒙特卡洛仿真的风电场可靠性模型,该模型充分考虑了风能随机性和风电机组强迫停运率等不确定因素,将该模型应用于计及风电场的大电网系统,按照在满足系统安全约束条件的前提下充分利用风电的原则,对计及风电场的大电网系统进行可靠性评估。
⑤将风电场的可靠性模型与电力系统模型相结合,提出基于序贯蒙特卡洛方法评估计及风电场的大电网系统可靠性,研究了风电场并网、风电场穿透功率、风电场选址以及风速变化对电网可靠性的影响,为风电场的规划与运行奠定理论基础;另外,基于核密度估计技术得到了可靠性指标的概率密度分布,对几种方案可靠性指标的概率密度分布进行了比较,实现了对计及风电场的大电网风险更深入和完整的认知。
With the increasing severity of energy and environment problems, renewable energy is competitively developed all over the world. The wind energy was developing fastest among all kinds of renewable resources due to its a kind of renewable green power resources, its low cost and technical maturity. Unlike the other power plants, the active power from wind farms varies all the time, which may influence the operation and stability of power network after connection. To study the impact of the wind farm on the system reliability, this thesis presents a reliability assessment model of wind power integration in power systems based on the Monte Carlo simulation approach, which considers the randomicity of the wind and wind power generation forced outage rate. The main work has been done as follows:
①At first the thesis introduces the development, method, significance and research progress of reliability assessment of wind power integration in Bulk Power Systems at home and abroad.
②The reliability evaluation methods are usually divided into two kinds, that are analytical and simulation methods, and the simulation approach has been received consideration attention for its flexibility and practicality. Based on different sampling techniques, there are three kinds of simulation methods which are nonsequential Monte Carlo simulation, sequential Monte Carlo simulation and state transition sampling. This thesis details their fundamental principles and analyzes their merits and drawbacks. Moreover, utilizing the annual reliability indices samples and nonparametric kernel estimation technique, this thesis realizes the probability density estimation for reliability indices. This probability density information can facilitate us to discover system risks from the internal distribution laws and structural features of reliability indices. The proposed methods are verified using RBST and IEEE-RTS79 systems.
③Wind speed forecast is an important task of wind farms planning. Based on time series analysis, the thesis presents a wind speed forecast model, which considers timing and auto-correlation characteristic of wind speed. The distribution characteristic of the forecasted wind speed are compared with those of measured wind speed in a calculative example, which shows that the auto-regressive and moving average (ARMA) model is feasible in wind speed forecast for wind farms.
④This thesis presents a wind farm reliability assessment model based on the sequential Monte Carlo simulation using the reliability models of the conventional generators, lines and the transforms, which considers the randomicity of the wind and wind power generation forced outage rate. The reliability of Bulk Power Systems contain wind farms is evaluated in term of the principle that wind power is employed sufficiently, according to meeting system security constraints.
⑤Combining the wind farm reliability assessment model with the Bulk Power Systems, the reliability of wind power integration in Bulk Power Systems is evaluated. The impacts of adding wind farms to system, changing of penetration and wind speed on reliability of power system is analysed. The study provides the important reference value for wind farm operation and planning. Moreover, the probability density estimation of the five casesare given and compared based on kernel density estimation technique.
引文
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