电动汽车和风电并网条件下的热电联合经济调度

发布时间：2018-08-10 07:25

【摘要】：在化石能源日渐枯竭和环境问题日益凸显的全球大环境下,电动汽车和风电由于其良好的环境和经济效益而得到国家的大力发展,而高渗透率的电动汽车和风电给电力系统调度带来了新的挑战。在热电机组比重较高的“三北地区”,大量热电联产机组在供暖期采取“以热定电”方式运行,不利于电网高效经济运行,同时也导致电网调峰能力不足,这也是“三北”地区冬季大量弃风的重要原因之一。为了更好地消纳风电以及达到电力系统经济运行的目的,电网需要积极调动电力系统充裕性资源,充分利用常规机组、热电机组和电动汽车可控负荷的灵活调节能力,在满足热负荷和电负荷的同时,通过热电联合调度提高系统风电消纳能力,改善机组运行经济性的同时减少电动汽车无序充电对电力系统的不利影响。本文针对规模化电动汽车可控负荷和风电参与的热电联合调度问题开展研究,主要工作包括：首先,对不同类型的热电机组特性和电动汽车集中充电可控负荷特性进行研究,分析其对于消纳风电和提高机组运行经济性的作用,从而为热电联合调度模型的建立提供理论基础。在此基础上,在满足热负荷平衡等约束条件下,以抽汽式热电机组有功出力可调范围最大和热电机组总运行成本最小为目标函数,建立了热电机组多目标优化模型,采用非支配排序遗传算法(NSGA-Ⅱ)进行求解,探索热电机组运行经济性与抽汽式热电机组有功出力可调范围之间的关系,并设置不同单目标优化模型进行计算,比较分析优化结果从而得出相关结论。而后,研究电动汽车有序充电控制模型,考虑充电机充电功率约束等约束条件,以叠加电动汽车充电负荷后的总等效负荷方差最小为目标函数,采用YALMIP工具包进行建模并求解,并通过仿真算例分析了优化模型的有效性。在此基础上,通过热电机组最小出力模型计算出系统等效负荷,从而使基于等效负荷的电动汽车可控负荷参与到热电联合调度中。最后,基于上述电动汽车有序充电控制模型得到的电动汽车充电负荷信息,电网调度中心在冬季供暖期,对常规火电机组、热电机组和风电进行联合调度。热电机组承担供暖任务,电负荷则由热电机组、火电机组和风电共同承担,以机组总运行成本最小为目标函数,建立了含规模化电动汽车和风电的热电联合经济调度模型。本文所提出的优化调度模型在MATLAB中采用YALMIP进行建模并求解,仿真算例验证了优化调度模型的可行性和有效性,并研究了不同因素对调度结果的影响。
[Abstract]:In the global environment where fossil energy is exhausted and environmental problems are becoming increasingly prominent, electric vehicles and wind power have been greatly developed by the state because of their good environmental and economic benefits. High permeability electric vehicles and wind power bring new challenges to the dispatching of power systems. In the heating period, a large number of cogeneration units operate in the heating period, which is not conducive to the efficient economic operation of the power grid, and also leads to the lack of power grid peak regulation ability. It is also one of the important reasons for the large number of discarded winds in the "Three North" areas in winter. Actively mobilize the abundant resources of the power system, make full use of the conventional unit, the power plant and the electric vehicle controllable load flexibly. While meeting the heat load and electric load, the power system can be improved by combined heat and power dispatching, and the economy of the unit is improved and the electric vehicle disordered charging is reduced to the electric power system. The main work includes: first, the characteristics of different types of thermoelectric units and the controllable load characteristics of the centralized charging of electric vehicles are studied, and the economy of the wind power and the operation of the units are analyzed. In order to provide a theoretical basis for the establishment of a combined thermoelectric scheduling model, the multi-objective optimization model of a thermoelectric unit is established on the basis of satisfying the constraint conditions such as the balance of heat load and so on. The order genetic algorithm (NSGA- II) is used to solve the relationship between the operation economy of the thermoelectric unit and the adjustable range of the active power output of the steam turbine, and the different single target optimization models are set up to calculate, and the results of the optimization are compared and analyzed, and then the related conclusions are obtained. Then, the order charging control model of the electric vehicle is studied and the charger is considered. The constraint conditions such as charging power constraints are used to stack the minimum variance of the total equivalent load after the charging load of the electric vehicle as the objective function. The model is modeled and solved by the YALMIP toolkit. The effectiveness of the optimized model is analyzed by a simulation example. On this basis, the equivalent load of the system is calculated by the minimum force model of the thermal motor group. The control load of electric vehicle based on the equivalent load is involved in the combined power and power dispatching. Finally, the charging load information of the electric vehicle is obtained based on the model of the electric vehicle ordered charging control. The power grid dispatching center jointly scheduls the conventional thermal power unit, the thermal electric motor group and the wind power in the winter heating period. The electric load is jointly undertaken by the thermoelectric unit, the thermal power unit and the wind power, with the minimum total operating cost of the unit as the objective function, the combined economic dispatch model of the scale electric vehicle and the wind power is established. The optimal scheduling model proposed in this paper is modeled and solved by using YALMIP in MATLAB. The simulation example is proved to be an example. The feasibility and validity of the optimal scheduling model are studied, and the effects of different factors on the scheduling results are studied.
【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】：2016
【分类号】：TM73

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