含电动汽车的风光储微网容量配置与运行调度策略

发布时间：2018-03-08 08:46

本文选题：微网　切入点：容量优化配置　出处：《北京交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着风力发电和光伏发电等可再生能源在电网中渗透率的不断提升,电动汽车充电负荷的大量接入,电网的安全稳定运行将面临又一次挑战。风能、太阳能发电的随机波动性和电动汽车充电负荷的随机性,将对电网形成巨大冲击,微网作为平抑电网波动、消纳清洁能源的一种重要方式,对传统电网向清洁能源转型具有重要意义。微网的容量优化配置作为系统前期规划阶段的重要一环,是保证系统供电可靠性和运行经济性的重要前提;采用运行优化调度策略对于提高系统的稳定运行与合理制订微网调度计划有着重要影响。本文针对含电动汽车的微网中风光储容量配置和优化调度策略进行了研究,主要研究内容如下:(1)采用依据季节性变化的随机抽样方法,基于北京地区的实际气象数据建立了微网中风力发电和光伏发电功率模型,对常规负荷和电动汽车充电负荷功率曲线进行了建模,为微网中风光储容量的优化配置和微网运行调度策略研究奠定了基础。(2)针对含有电动汽车的风光储微网,提出了基于改进差分进化算法的容量优化配置计算方法。首先通过考虑气象数据的季节性变化,对输入数据进行拟合,以风光-负荷偏差率、储能投资成本、风光投资成本、从电网购电费用等作为优化目标,以储能电池充放电约束、并网点功率波动率约束等作为约束条件,建立了微网风、光、储容量优化配置模型,并给出了在两种不同负荷类型应用场景下的容量配置方案,验证了所提方法的灵活性和有效性。(3)对含电动汽车的风光储微网日前调度策略进行了研究,以削峰填谷和减小系统功率波动为目标进行优化,并在负荷类型为居民负荷的微网模型中进行了仿真验证,结果表明在满足用户侧电动汽车充电需求的基础上,通过日前调度策略优化可以实现网侧减小负荷峰谷差的需求。(4)提出了基于滤波系数自适应的低通滤波算法的实时调度策略,并与定滤波系数的低通滤波算法进行了对比分析,仿真结果表明:在实时调度策略的优化下,可以跟踪日前调度计划并平抑风光发电的随机性波动,验证了所提方法的有效性。
[Abstract]:With the increasing permeability of renewable energy, such as wind power generation and photovoltaic power generation, and the massive access of electric vehicle charging load, the safe and stable operation of the power grid will face another challenge. The random fluctuation of solar power generation and the randomness of charging load of electric vehicles will have a huge impact on the power grid. Microgrid is an important way to calm the fluctuation of power grid and absorb clean energy. It is of great significance for the transformation of traditional power grid to clean energy. As an important part of the early planning stage of the system, the optimal configuration of the capacity of the microgrid is an important prerequisite to ensure the reliability of the power supply and the operation economy of the system. It is very important to adopt the optimal scheduling strategy to improve the stable operation of the system and to make the scheduling plan of microgrid reasonably. This paper studies the configuration of the wind-storage capacity and the optimal scheduling strategy of the micro-grid with electric vehicles. The main research contents are as follows: (1) based on the actual meteorological data in Beijing, the power models of wind power generation and photovoltaic power generation in the microgrid are established by using the random sampling method based on seasonal variation. In this paper, the power curve of conventional load and electric vehicle charging load is modeled, which lays a foundation for the optimal configuration of wind storage capacity in microgrid and the study of micro-grid operation scheduling strategy. Based on the improved differential evolution algorithm, a capacity optimal allocation method is proposed. Firstly, the input data are fitted by considering the seasonal variation of meteorological data, and then the wind-load deviation rate, the investment cost of energy storage and the cost of wind investment are calculated. The optimal configuration model of wind, light and storage capacity of microgrid is established by taking the charge and discharge constraints of energy storage cells and the network power fluctuation constraints as the optimization objectives from the power purchase cost of the power grid. The capacity configuration scheme under two different load application scenarios is given, and the flexibility and effectiveness of the proposed method are verified. The pre-day scheduling strategy of the solar microgrid with electric vehicles is studied. With the aim of cutting peak and filling valley and reducing the power fluctuation of the system, the simulation is carried out in the micro-grid model with load type as the resident load. The results show that, on the basis of satisfying the charging demand of the electric vehicle on the user side, the simulation results show that, By optimizing the scheduling strategy before day, the demand of reducing load peak and valley difference on network side can be realized. (4) A real-time scheduling strategy based on filter coefficient adaptive low-pass filtering algorithm is proposed, and compared with low-pass filtering algorithm with fixed filtering coefficient. The simulation results show that under the optimization of real-time scheduling strategy, the scheduling plan before the day can be tracked and the random fluctuation of wind power generation can be stabilized. The effectiveness of the proposed method is verified.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727;TM73

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