【作者】 张婷；

【导师】 包哲静；

【作者基本信息】 浙江大学 ， 系统分析与集成， 2015， 硕士

【摘要】 随着风力发电技术的发展以及绿色能源的推广,全球风电总装机容量不断增大,风电渗透率水平也不断提高。但是,由于风电功率具有较强的随机性与波动性,会给大电网电能质量带来不可忽视的影响,同时也给电网调度规划带来了巨大的挑战。对此,各国都针对风电场并网问题制定了相关标准。本文采用由储能电池和超级电容组成的混合储能系统作为功率补偿装置,平抑风电功率波动,使其分别在一分钟和半小时两个时间尺度上均满足相应的并网要求。主要研究内容包括：1.提出了一种基于月平均风速的超短期风速合成方法。首先根据威布尔分布与风速日形状曲线,由月平均风速生成十分钟平均风速；再根据湍流模型与Vor-karman功率谱密度,由十分钟平均风速生成秒级风速。2.提出了一种基于自适应滤波的实时平抑控制策略。首先,根据两个时间尺度上风电功率波动的关系,自适应调整低通滤波算法的滤波系数,确定使风电并网功率波动在两个时间尺度上均满足要求的混合储能功率；然后,考虑到储能电池能量密度大、充放电持续时间长,而超级电容功率密度大、充放电迅速的特点,根据储能电池荷电状态和充放电改变次数,自适应调整低通滤波算法的滤波系数,协调控制储能电池吸收低频功率波动,超级电容吸收高频波动。3.提出了考虑实际平抑控制策略的、能够连续对风电波动进行平抑的储能系统最小容量确定方法。以典型日为研究对象,以最小化储能系统一天的荷电变化量以及储能系统容量为优化目标,以电池与超级电容荷电状态的限制为约束,建立混合储能系统容量配置优化模型,将实时平抑控制策略融入改进的PSO算法中进行求解。更多还原

【Abstract】 With the development of wind power generation technology and renewable energy utilization, total installed capacity of wind turbines around the world, as well as the penetration of wind power, is increasing. However, wind power could bring remarkable influence to the power quality of main grid, and challenge its scheduling and planning at the same time, due to the intermittency and uncertainty of wind power. Therefore, many countries have set up standards to guide the connections of wind power to main grid. In this paper, the hybrid energy storage system (HESS) composed of energy storage battery and super capacitor is used as the power compensation device to mitigate the wind power fluctuations and make it meet the fluctuation requirements in any1-min and30-min time window, respectively. Main research work is illustrated as follows:1. With the monthly average wind speed, the synthesis method of generating super-short-term wind speed is proposed. Firstly, the monthly average speed is applied to synthesize10-minute average wind speed based on the Wei-bull distribution and diurnal pattern in a day. Then, with10-minute average wind speed, the wind speed in the time-scale of1second is produced according to the model of turbulence and Vor-karman power spectrum.2. A real-time smoothing strategy based on the self-adaptive filtering algorithm is presented. First, the expected HESS output power to make the wind power connected to the main grid satisfy the fluctuation requirements is determined by the low-pass filtering algorithm where the filtering constant is self-adapting according to the relationship between the two time-scale power fluctuations. Secondly, since the battery has large energy density and long lasting time of charge and discharge, and on the contrary the super capacitor has large power density and rapid transition between charge and discharge, the low-pass filtering algorithm is performed where the filtering constant is self-tuning by considering the state of charging (SOC) and switching frequency between charge and discharge of the battery, to coordinately assign the fluctuations with low frequency to the battery and those with high frequency to the super capacitor.3. An approach for determining the HESS capacity is proposed to make it continuously smooth the wind power fluctuations, in which the real-time smoothing strategy is integrated. For a typical day, HESS capacity optimization model is established, with the objective of minimizing the weighted sum of the SOC change at the beginning and ending of the day and the HESS capacity, and the constraints of battery and super-capacitor SOC are considered. The optimization is solved by the improved particle swarm optimization (PSO) algorithm with the integrated real-time smoothing strategy.更多还原