微网中基于储能的能量管理研究

发布时间：2018-03-24 22:15

本文选题：微网　切入点：光伏　出处：《华北电力大学(北京)》2017年硕士论文

【摘要】：微网利用光伏、风机等可再生能源发电并与储能系统配合向本地负荷供电是解决能源危机和环境污染问题的方法之一。然而,光伏、风机等电源的出力具有间歇性,且与用户负荷需求呈不对等分布,难以被本地用户直接利用。因此,通过能量管控实现能源就地高效利用,避免大量过剩功率入网,对负荷起到削峰效果是当前微网研究重点之一。目前,已有不少微网能量管控策略,然而大部分控制策略依赖于精确的负荷需求和分布式电源出力预测数据或通过短时的预测修正来减小对预测数据的依赖,但精准预测和反复预测修正的过程受到现有预测技术和软件计算能力的限制。此外,随着电动汽车的快速发展,其充电随机性高、瞬时充电功率较大且难以精确预测的特性会降低依赖精确预测数据的能量管控策略的控制效果。针对上述问题,论文对包含光伏、风机和微型燃气轮机分布式电源的小区微网提出了冷/热电联产和储能系统联合运行的能量管控策略,实现了对各类能源的高效利用和对用户冷/热、电负荷的分类削减,改善能源供给和负荷需求分布不对等的现状。其中,考虑小区内电动汽车充电负荷不断增长的情况,论文对储能系统的充放电控制提出了一种基于预测数据的实时修正算法。该算法利用预测数据但不依赖于预测数据的精确性,也不需要对数据预测部分进行反复计算修正,直接通过对储能系统充放电功率的修正计算实现最大程度的冲击负荷削减。论文利用实测和模拟数据,对提出的微型燃气轮机冷/热电联产和储能系统联合运行的能量管控策略进行编程实现,并与储能系统充放电控制采用固定阈值算法和自适应控算法的控制策略进行结果比较。结果表明,论文设计的能量管控策略较好的实现了各类能源的本地利用,并在保证运行最优经济性的基础上实现最大程度的冲击负荷削减效果。
[Abstract]:One of the ways to solve the problem of energy crisis and environmental pollution is to use photovoltaic, blower and other renewable energy sources to generate electricity and cooperate with energy storage system to supply local load. However, the output of photovoltaic, blower and other power sources is intermittent. And the distribution is not equal to the demand of user load, so it is difficult to be directly utilized by local users. Therefore, energy can be efficiently utilized in place through energy control, and a large amount of excess power can be avoided. Peak-cutting effect on load is one of the key points in microgrid research. At present, there are many microgrid energy control strategies. However, most control strategies rely on accurate load demand and distributed power generation prediction data or reduce the dependence on prediction data by short-term forecasting correction. But the process of accurate prediction and repeated prediction correction is limited by existing prediction techniques and software computing capabilities. In addition, with the rapid development of electric vehicles, their charging randomness is high. The characteristics of high instantaneous charge power and difficult to predict accurately will reduce the control effect of energy control strategy which depends on accurate predictive data. In this paper, the microgrid of distributed power system of fan and micro gas turbine has put forward the energy control strategy of combined operation of cold / heat power generation and energy storage system, which realizes the efficient utilization of all kinds of energy and the classification and reduction of user's cold / heat and electric load. Improving the unequal distribution of energy supply and load demand. Among them, considering the increasing charge load of electric vehicles in the district, In this paper, a real-time correction algorithm based on predictive data is proposed for charge and discharge control of energy storage system, which utilizes the prediction data but does not depend on the accuracy of the prediction data, nor does it need to calculate and modify the prediction part repeatedly. The maximum impact load reduction is realized by modifying the charge and discharge power of the energy storage system. The proposed energy control strategy for the combined operation of cooling / heat and power generation and energy storage system of micro gas turbine is realized by programming. The results are compared with the control strategies of fixed threshold algorithm and adaptive control algorithm in charge and discharge control of energy storage system. The results show that the energy control strategy designed in this paper can achieve the local utilization of all kinds of energy. The maximum impact load reduction effect is realized on the basis of ensuring the optimal operation economy.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM73

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