混合储能系统对风电功率波动的平抑作用研究

发布时间：2018-02-28 22:01

本文关键词： 混合储能系统(HESS) 粒子群优化(PSO)算法低通滤波算法目标功率功率分配　出处：《浙江大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着环境问题日益严重,世界各国对清洁能源、可再生能源发电的关注度也日益提高。近年来,我国风能发电产业获得了飞速的发展。然而,风力发电具有随机性和波动性,所以风电并网会对电网产生冲击,一旦超出了电网的承受范围,就会严重破坏电网的安全性和稳定性。利用储能技术能够较好的平抑风电波动,使输出功率满足一定指标。近年来储能技术也取得了飞速的发展,将几种储能技术组合起来,取长补短,发挥各自优势,能够在提高功率输出能力的同时,延长使用寿命,降低设备成本等。研究混合储能系统(HESS)的功率分配问题,具有十分重要的意义。本文主要研究以下内容： (1)基于风速预测计算风电场平抑目标功率。在能够较精确的预测风电场输出功率的前提下,利用PSO算法或者其他优化算法来寻求平抑目标功率的最优解,既能够满足两个时间尺度的波动指标,又考虑尽可能地接近预测功率从而降低对设备的需求。 (2)利用PSO算法配置混合储能系统的输出功率。平抑目标功率和实际输出功率的差值就是混合储能系统的期望出力。由于蓄电池能量密度大的特性,优先考虑蓄电池来平抑波动,蓄电池无法平抑的高频波动,则由超级电容来平抑。根据蓄电池的基本特性,总结归纳出蓄电池工作状态下的约束条件,从而计算出蓄电池期望功率的最优解。还进一步定义了蓄电池的充放电状态方程和24小时内的状态转换总量,并将其加到目标函数中,从仿真结果能够看到蓄电池的充放电转换次数有明显地减少,有效地延长了蓄电池使用寿命。 (3)利用一种滤波系数可变的低通滤波算法来实时计算平抑目标功率,再利用PSO算法实时分配超级电容和蓄电池的功率。为了延长蓄电池寿命,同时减少环境污染,我们把超级电容作为优先吸收或释放能量的设备,在超级电容的容量不足时,蓄电池也参与工作。在仿真中可以发现超级电容就可以完成大部分充放电任务,蓄电池的使用率相对较低。这样就可以减少储能设备的负担,降低成本。而且,随着超级电容的荷电状态SOC的变化,功率分配策略也会有实时的调整。这样让超级电容和蓄电池协调工作,取长补短,对于整个系统而言,既最大程度地发挥了设备的优势,又提高了平抑质量。
[Abstract]:With the increasingly serious environmental problems, countries in the world pay more and more attention to clean energy and renewable energy power generation. In recent years, wind power generation industry in China has made rapid development. However, wind power generation has randomness and volatility. Therefore, wind power grid connection will have an impact on the power grid. Once the wind power grid is beyond its bearing range, it will seriously damage the security and stability of the power grid. The use of energy storage technology can better calm the fluctuation of wind power. In recent years, energy storage technology has also made rapid development. Combining several energy storage technologies to complement each other and give full play to their respective advantages can improve the power output capacity and prolong the service life at the same time. It is of great significance to study the power allocation of hybrid energy storage system (HESS). The main contents of this paper are as follows:. Based on wind speed prediction, wind power is calculated. On the premise that wind farm output power can be accurately predicted, PSO algorithm or other optimization algorithms are used to find the optimal solution of stabilizing target power. It can not only satisfy the fluctuation index of two time scales, but also consider getting as close as possible to the predicted power so as to reduce the demand for equipment. PSO algorithm is used to configure the output power of the hybrid energy storage system. The difference between the target power and the actual output power is the expected output force of the hybrid energy storage system. Due to the high energy density of the battery, priority is given to the storage battery to stabilize the fluctuation. The high frequency fluctuation of the battery can not be calmed down by the super capacitor. According to the basic characteristics of the battery, the constraints under the working state of the battery are summarized and summarized. The state equation of charge and discharge and the total amount of state conversion within 24 hours are further defined and added to the objective function. From the simulation results, it can be seen that the battery charge and discharge conversion times are obviously reduced, and the battery service life is effectively prolonged. In order to prolong the battery life and reduce environmental pollution, a low pass filter algorithm with variable filter coefficient is used to calculate the power of the stabilized target in real time, and then the PSO algorithm is used to distribute the power of super capacitor and battery in real time. We use super capacitors as a priority device to absorb or release energy, and batteries work when the capacity of super capacitors is low. In the simulation, we can find that super capacitors can accomplish most of the charge and discharge tasks. Battery usage is relatively low. This reduces the load on energy storage equipment and reduces costs. And, as the charging state of the supercapacitor changes, The power allocation strategy will also be adjusted in real time so that the super capacitor and the battery can work harmoniously to complement each other. For the whole system the advantages of the equipment are maximized and the quality of stabilization is improved.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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