考虑用户响应的动态尖峰电价优化决策模型研究

发布时间：2018-01-10 13:34

本文关键词：考虑用户响应的动态尖峰电价优化决策模型研究　出处：《华北电力大学(北京)》2016年硕士论文　论文类型：学位论文

【摘要】：随着我国电力需求的持续增长,一些经济发达省市夏季高峰负荷不断升高,解决电力供应不平衡问题仅依赖发电侧资源调节是不经济,不安全的。如果利用需求响应措施则可以更好地引导用户,调动需求侧资源例如电动汽车、大规模空调及蓄热蓄冰设备等与电网互动,缓解资源与环境的压力。电价机制作为需求响应的重要组成部分,可以利用价格杠杆起到削峰填谷的作用,其扮演的角色也将越来越重要。现阶段我国普遍实行的是分时电价,但是分时电价是费率相对固定的静态电价,已试点的尖峰电价实质也为尖-峰-平-谷分时电价,动态性较差。因此,设计合理的动态尖峰电价机制有针对性地引导用户减少或者转移尖峰负荷有着重要的理论和实际意义。本文在借鉴国内外经验的基础上,提出了一种考虑用户响应的动态尖峰电价优化决策模型。在所提出的尖峰电价中,首先给出了利用阈值和模糊隶属度动态确定尖峰日和尖峰时段的方法,接着基于用户对尖峰电价的响应,建立了尖峰电价优化决策模型,兼顾了电网公司和用户的利益,并综合考虑了用户满意度、月平均电价不变和防止“尖峰漂移”等问题。仿真结果表明尖峰电价能明显起到减少尖峰负荷,改善负荷特性的效果,同时也能减少用户的电费支出。其次,本文探讨了所提尖峰电价对于电动汽车这种重要需求侧资源的影响。在本文的研究中,根据相关数据统计利用蒙特卡洛方法对无序随机充电模式、有序充电模式和V2G模式等三种充电情景的充放电负荷曲线进行模拟,分析尖峰电价优化前后的变化。通过仿真可知,尖峰电价可以明显改善电动汽车充放电负荷“峰上加峰”的问题,同时电动汽车与电网的双向互动也可进一步提高电网可靠性。最后,为了更好地促进尖峰电价的推广实施,建立了相关的评价体系。在本文的综合评价体系中,对尖峰电价实施效果进行了梳理,建立了合适的框架,并定义了评价指标,采用模糊层次分析法进行评价。此评价机制可以提供恰当的反馈信息,给电力公司、用户及政府相关部门提出有效的配套意见,对进一步完善尖峰电价机制有着重要意义。
[Abstract]:With the continuous growth of power demand in China, the peak load of some economically developed provinces and cities is increasing in summer. It is not economical to solve the problem of power supply imbalance only relying on generation side resource regulation. Unsafe. If you use demand response measures, you can better guide users, mobilize demand-side resources such as electric vehicles, large-scale air conditioning and ice storage equipment to interact with the grid. As an important part of demand response, electricity price mechanism can use price lever to cut the peak and fill the valley. Its role will also be more and more important. At this stage, China generally implements the time-sharing price, but the time-sharing price is the static price with relatively fixed rate. The peak-peak price is also peak-peak-equal-valley time-sharing price, which is less dynamic. It is of great theoretical and practical significance to design a reasonable dynamic peak-price mechanism to guide customers to reduce or transfer peak load. In this paper, a dynamic peak-price optimization decision model considering user response is proposed. In the proposed peak-price, the method of dynamically determining peak day and peak time by using threshold and fuzzy membership degree is given. Then, based on the response of customers to peak price, a decision model of peak price optimization is established, which takes into account the interests of power grid companies and users, and comprehensive consideration of customer satisfaction. The simulation results show that the peak price can obviously reduce the peak load, improve the load characteristics, but also reduce the user's electricity expenditure. Secondly, the simulation results show that the peak price can obviously reduce the peak load and improve the load characteristics. In this paper, the effect of peak price on the demand side resource of electric vehicle is discussed. In this paper, the random charging mode is analyzed by Monte Carlo method according to the relevant data. The charge and discharge load curves of three charging scenarios, such as orderly charging mode and V2G mode, were simulated to analyze the changes of peak price before and after optimization. The peak price can obviously improve the charge and discharge load of electric vehicle. At the same time, the two-way interaction between electric vehicle and power grid can also further improve the reliability of power grid. In order to promote the promotion and implementation of peak-peak electricity price, a related evaluation system is established. In the comprehensive evaluation system of this paper, the implementation effect of peak-peak electricity price is combed, and a suitable framework is established. The evaluation index is defined and the fuzzy analytic hierarchy process is used to evaluate. This evaluation mechanism can provide appropriate feedback information and provide effective supporting opinions to power companies, users and relevant government departments. It is of great significance to further improve the peak-peak price mechanism.
【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】：F426.61

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