风电—储能联合系统储能容量优化研究

发布时间：2018-03-20 20:56

本文选题：风力发电　切入点：储能容量　出处：《湖北工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：可再生能源中,风能是最具有发展潜力的,而发展风能最有效的途径就是将其转换为电能。受制于风能具有波动性和不连续性,风电也带有极大的波动性和不连续性,这一特点是导致风电无法大规模并入电力系统的主要原因,因为它严重影响了大电网的稳定运行。解决这一问题的理想方案是采用风电储能联合系统的输出功率配合大电网的调度计划,也就是说,将储能技术应用于风力发电,利用储能填平风电场输出电能的功率波动。但是如何最优化配置储能系统、如何将储能系统的输出功率适应规划的电网调度,如何提高电网容纳风电的能力又是几项复杂的大问题。这些问题的解决与否直接关系着风电能否大规模发展,因此解决这些问题具有巨大的理论、工程和现实意义。为风电储能联合系统的储能容量能够被更合理的优化配置,使得风电储能联合发电系统能够稳定输出功率,本文首先详细介绍了风力发电系统和储能系统的模型,并对风力机、风力发电机及储能系统模型的特征做出了总结;然后说明了风电场输出功率的预测,是影响风电储能联合系统储能容量的两个关键因素之一,另一个关键因素是储能容量优化目标。为解决这两个因素,本文采取持续预测的办法,通过获取风电场小时预测出力,提出了以弃风能量、充放电失去量、运营成本的费用最少为设计目的的储能系统优化模型;在这一模型的基础上,本文进一步提出了风电储能联系系统储能容量优化算法,这一算法基于“调度置信度水平”,也结合了历史输出功率和预测调度计划的差值功率分布。该算法也应用了两个函数,即积累分布函数和概率分布函数,这两个函数都运用了非参数估计拟合差值功率。最后,本文以功率型储能系统作为研究对象,结合在上海的某一风电场实地测试数据,进行了仿真分析。这种风电储能联合系统容量优化的仿真结果表明,相比传统的方法,本文所提出的方法能够使储能系统的运行总费用最小,且总费用和“调度置信度水平”成反比例的关系。考虑到风电场的输出功率的预测值与储能容量优化目标是影响风电储能联合系统储能容量的最关键因素,本文采用“调度置信度水平”的方法来优化风电储能联合系统储能容量,它具有储能系统的费用总和与置信度成反比例的规律,置信度越高,费用就越低。因此,本文的研究成果为优化配置风电储能联合系统储能容量提供了一种新的途径。
[Abstract]:Among renewable energy sources, wind energy has the most potential, and the most effective way to develop wind energy is to convert it into electric energy, which is constrained by the volatility and discontinuity of wind energy and the great volatility and discontinuity of wind power. This feature is the main reason why wind power cannot be incorporated into the power system on a large scale. Because it seriously affects the stable operation of large power grid, the ideal solution to this problem is to adopt the output power of wind energy storage joint system to match the dispatching plan of large power grid, that is, to apply energy storage technology to wind power generation. However, how to optimize the configuration of the energy storage system, how to adapt the output power of the energy storage system to the planned power grid scheduling, How to improve the capacity of power grid to hold wind power is also a complex problem. The solution of these problems is directly related to the large-scale development of wind power, so there is a huge theory to solve these problems. Engineering and practical significance. In order to optimize the storage capacity of the combined wind energy storage system, the wind energy storage combined power generation system can output power stably. In this paper, the models of wind power generation system and energy storage system are introduced in detail, and the characteristics of wind turbine, wind turbine and energy storage system are summarized, and the prediction of output power of wind farm is explained. It is one of the two key factors that affect the energy storage capacity of the combined wind power storage system, and the other is the optimization goal of the energy storage capacity. In order to solve these two factors, this paper adopts the method of continuous prediction and obtains the hourly predictive force of the wind farm. In this paper, an optimization model of energy storage system is proposed, which is designed for the purpose of energy dissipation, charge / discharge loss and minimum operating cost, and on the basis of this model, an optimization algorithm for energy storage capacity of wind energy storage associated system is further proposed in this paper. This algorithm is based on the "level of confidence in scheduling" and combines the historical output power with the differential power distribution of the forecast scheduling plan. The algorithm also uses two functions, namely, the cumulative distribution function and the probability distribution function. These two functions use non-parametric estimation to fit the difference power. Finally, the power storage system is taken as the research object, and the field test data of a wind farm in Shanghai are combined. The simulation results show that compared with the traditional method, the proposed method can minimize the total operating cost of the energy storage system. And the total cost is inversely proportional to the "level of confidence in dispatching". Considering that the prediction value of output power of wind farm and the optimization objective of energy storage capacity are the most critical factors affecting the storage capacity of wind power storage combined system, In this paper, the method of "dispatching confidence level" is used to optimize the energy storage capacity of the combined wind energy storage system. It has the rule that the total cost of the energy storage system is inversely proportional to the confidence degree. The higher the confidence level, the lower the cost. The results of this paper provide a new way to optimize the energy storage capacity of wind energy storage system.
【学位授予单位】：湖北工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614;TM73

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