含风电场的电力系统可靠性与规划问题的研究
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摘要
随着能源需求增长与化石燃料资源日趋枯竭的矛盾日益突出,洁净的可再生能源越来越受到人们的欢迎和重视,风力发电是新能源中最具有经济发展前景的一种发电形式。但风能具有间歇性和随机性的特点,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。本文采用蒙特卡罗仿真方法,深入研究了风能的随机性和电力系统运行中的不确定性,建立了含风电场的发输电系统概率分析模型,研究风电的特性和评估其对电力系统的可靠性与规划影响。
主要完成的研究内容有:
(1)研究风能资源特性,建立风能的概率统计模型和预测模型。
用Weibull分布作为风电场风速概率统计模型,根据实测的风速数据提出应用极大似然法求解风速概率分布参数,由此估算出能直接体现风能资源状况的风能特征指标值,为风电场风能资源评估提供重要参考价值。
风速是一个典型的时间序列,采用时间序列法建立的风速序列预测模型,算例说明利用ARMA模型预测得到的风速序列能反映风电场风速分布特性。
(2)基于蒙特卡罗方法研究风力发电机组的可靠性模型。
在风能的概率统计模型和预测模型基础上,充分考虑风能的随机特性和风力发电机组强迫停运率等不确定因素,结合负荷模型,分别提出基于序贯和非序贯两种蒙特卡罗方法实现风电机组的可靠性评估,并研究风电机组的投资及其动态经济性评价。
(3)研究风电场的稳态模型和含风电场的电力系统可靠性模型。
提出了风电场的稳态分析模型,该模型考虑了风电场的尾流效应、风电机组输出功率与尖速比和滑差等之间的函数关系;应用该模型计算含风电场的电力系统的潮流分布,通过算例说明其有效性。
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罗方法评估含风电场的发输电系统可靠性,计算了风电容量可信度、风电场对电量不足期望值贡献系数等风电可靠性指标,研究风电场对电网可靠性的贡献和经济效益评价,为评估风电的经济价值和风电场的规划设计、风电场接入电网方案奠定理论基础。
(4)基于遗传算法分别研究离网型和并网型风力发电系统的容量扩展规划。
提出基于改进遗传算法的风力—柴油联合发电系统容量扩展规划模型,在满足系统规划和运行等非线性约束条件下,寻求总成本最小的容量扩展方案。在模型中采用蒙特卡罗方法计算系统的概率性发电成本,不仅考虑了风速随机性、机组随机停运、风速序列和负荷序列相关性,而且考虑了风电穿透功率极限的约束。
在风电场的可靠性模型基础上,采用概率性方法对含风电场的发电系统进行随机生产模拟,通过采用改进遗传算法实现优化电源决策,实现含风电场的电力系统电源发展规划。
Renewable energy has been increasingly embraced due to dwindling fuel reserves, and wind generation is one of the most prospective new energy. However, the large-scale wind generation connected to grid has adverse effect on the safety of power systems. Based on Monte Carlo simulation method, the paper studies wind randomicity and power systems indefinite characteristic, establishes the probabilistic model of power systems containing wind generation, and studies the characteristics of wind energy and evaluate its effect on the reliability and planning of power systems.This paper mainly contributes the following aspects:(1) To study the wind speed probability statistical model and forecast model.A new method is presented that Weibull distribution parameters of wind speed are calculated with the indices measured based on maximum likelihood estimation. The wind energy characteristic indices are calculated with the probabilistic distribution parameters and help to evaluate wind energy resources.Wind speed forecast model is presented based on time series method that carries on the medium and long-term forecast of wind speed sequence. According to historical wind speed data, the model is utilized to perform the tendency extrapolation forecast.(2) To study the reliability model of wind turbine generation.A reliability model of wind power is presented based on the sequential and not-sequential Monte-Carlo simulation respectively, which considers adequately the random feature of wind energy and the forced outage of wind units. The models are applied to simulate wind generation and evaluate correspondence reliability and economic indices.(3) To research the steady-state model and the reliability model of wind farms.The steady-state model of wind farm is introduced in the paper, which considers weak effect of wind farm and output power function of wind turbine generator. This model is applied to analyse power flow in power networks including wind farms. The example indicates the presented model is reasonable.The reliability model of wind power based on the sequential Monte-Carlo simulation approach is introduced to calculate such reliability indices as wind power capacity credit and wind generation EENS benefit, study reliability benefits of adding wind farms to power system and provide the important reference value for wind farm operation and planning.(4) To study capacity expansion plan of wind power generation system.This paper proposes the model of the optimal expansion planning of wind-diesel energy system based on improved genetic algorithm that the minimum overall cost capacity expansion scheme is sought meeting the non-linear constraints of planning. The evaluation of probability cost and reliability in the model is performed by using Monte-Carlo method.Probability method is applied to stochastic production simulation of generation system including wind farms based on the reliability model of wind farms. Genetic algorithm is employed to realize optimization expansion planning of generation system including wind farms.
主要完成的研究内容有:
(1)研究风能资源特性,建立风能的概率统计模型和预测模型。
用Weibull分布作为风电场风速概率统计模型,根据实测的风速数据提出应用极大似然法求解风速概率分布参数,由此估算出能直接体现风能资源状况的风能特征指标值,为风电场风能资源评估提供重要参考价值。
风速是一个典型的时间序列,采用时间序列法建立的风速序列预测模型,算例说明利用ARMA模型预测得到的风速序列能反映风电场风速分布特性。
(2)基于蒙特卡罗方法研究风力发电机组的可靠性模型。
在风能的概率统计模型和预测模型基础上,充分考虑风能的随机特性和风力发电机组强迫停运率等不确定因素,结合负荷模型,分别提出基于序贯和非序贯两种蒙特卡罗方法实现风电机组的可靠性评估,并研究风电机组的投资及其动态经济性评价。
(3)研究风电场的稳态模型和含风电场的电力系统可靠性模型。
提出了风电场的稳态分析模型,该模型考虑了风电场的尾流效应、风电机组输出功率与尖速比和滑差等之间的函数关系;应用该模型计算含风电场的电力系统的潮流分布,通过算例说明其有效性。
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罗方法评估含风电场的发输电系统可靠性,计算了风电容量可信度、风电场对电量不足期望值贡献系数等风电可靠性指标,研究风电场对电网可靠性的贡献和经济效益评价,为评估风电的经济价值和风电场的规划设计、风电场接入电网方案奠定理论基础。
(4)基于遗传算法分别研究离网型和并网型风力发电系统的容量扩展规划。
提出基于改进遗传算法的风力—柴油联合发电系统容量扩展规划模型,在满足系统规划和运行等非线性约束条件下,寻求总成本最小的容量扩展方案。在模型中采用蒙特卡罗方法计算系统的概率性发电成本,不仅考虑了风速随机性、机组随机停运、风速序列和负荷序列相关性,而且考虑了风电穿透功率极限的约束。
在风电场的可靠性模型基础上,采用概率性方法对含风电场的发电系统进行随机生产模拟,通过采用改进遗传算法实现优化电源决策,实现含风电场的电力系统电源发展规划。
Renewable energy has been increasingly embraced due to dwindling fuel reserves, and wind generation is one of the most prospective new energy. However, the large-scale wind generation connected to grid has adverse effect on the safety of power systems. Based on Monte Carlo simulation method, the paper studies wind randomicity and power systems indefinite characteristic, establishes the probabilistic model of power systems containing wind generation, and studies the characteristics of wind energy and evaluate its effect on the reliability and planning of power systems.This paper mainly contributes the following aspects:(1) To study the wind speed probability statistical model and forecast model.A new method is presented that Weibull distribution parameters of wind speed are calculated with the indices measured based on maximum likelihood estimation. The wind energy characteristic indices are calculated with the probabilistic distribution parameters and help to evaluate wind energy resources.Wind speed forecast model is presented based on time series method that carries on the medium and long-term forecast of wind speed sequence. According to historical wind speed data, the model is utilized to perform the tendency extrapolation forecast.(2) To study the reliability model of wind turbine generation.A reliability model of wind power is presented based on the sequential and not-sequential Monte-Carlo simulation respectively, which considers adequately the random feature of wind energy and the forced outage of wind units. The models are applied to simulate wind generation and evaluate correspondence reliability and economic indices.(3) To research the steady-state model and the reliability model of wind farms.The steady-state model of wind farm is introduced in the paper, which considers weak effect of wind farm and output power function of wind turbine generator. This model is applied to analyse power flow in power networks including wind farms. The example indicates the presented model is reasonable.The reliability model of wind power based on the sequential Monte-Carlo simulation approach is introduced to calculate such reliability indices as wind power capacity credit and wind generation EENS benefit, study reliability benefits of adding wind farms to power system and provide the important reference value for wind farm operation and planning.(4) To study capacity expansion plan of wind power generation system.This paper proposes the model of the optimal expansion planning of wind-diesel energy system based on improved genetic algorithm that the minimum overall cost capacity expansion scheme is sought meeting the non-linear constraints of planning. The evaluation of probability cost and reliability in the model is performed by using Monte-Carlo method.Probability method is applied to stochastic production simulation of generation system including wind farms based on the reliability model of wind farms. Genetic algorithm is employed to realize optimization expansion planning of generation system including wind farms.
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