计及系统可靠性与收益风险的峰谷分时电价模型研究

发布时间：2018-05-18 20:00

本文选题：峰谷分时电价 + 多时段响应　；参考：《重庆大学》2014年硕士论文

【摘要】：立足于需求响应的初衷—提高系统可靠性与降低市场交易风险，研究计及系统可靠性与收益风险的峰谷分时电价模型，对于切实保证电力系统的供电可靠性和电网经营企业的收益，并提高社会经济效益具有重要的现实意义。本文对峰谷分时电价制定的基础、计及因素与定价优化模型进行如下研究： ①用户的电价响应评估与峰谷时段划分是峰谷分时电价制定的基础。目前，鲜有文献给出电量电价弹性矩阵的解析求解方法，且现有的统计方法难以体现不同负荷水平下弹性需求的差异与时段之间的相互影响。为此，，本文基于电力供给与电力弹性需求的平衡关系及用户的多时段电价响应，推导峰谷分时电价下电量电价弹性矩阵及解析求解方法，准确、全面地刻画用户对电价变化的响应过程，并在算例中分析自弹性系数与交叉弹性系数的数字特征。根据半梯形隶属函数，采用基于F等价矩阵模糊聚类进行峰谷时段划分，并依据电价施行的需要进行时段修正。通过算例对比，表明该方法简单，且能较好地反映各负荷点的峰谷特性。 ②电网经营企业的收益风险与系统可靠性是峰谷分时电价制定须计及的重要因素。采用多时段潮流计算线路损耗及根据我国“厂网分开”的市场背景，确定电网经营企业需承担的线损成本；通过电力市场风险分析，基于现货市场电价与负荷的函数关系，提出计及线损成本与购电风险的电网经营企业收益模型。算例中分析了线损成本与购电风险对电网经营企业收益的影响，表明电价的制定应充分考虑线损成本与购电风险。大电网可靠性评估非常复杂、耗时，采用三次样条插值建立系统可靠性随负荷变化的函数关系模型，简化峰谷分时电价定价优化模型的求解过程。 ③立足需求响应的初衷，从提高系统可靠性与降低市场交易风险出发，以计及线损成本与购电风险的电网经营企业收益最大化为目标函数，考虑可靠性约束、用户利益及其电量调整能力等，建立峰谷分时电价的定价优化模型，并采用基于系统可靠性与负荷的三次样条函数关系的自适应遗传算法求解模型。算例表明，该电价模型通过激励用户积极参与电价响应，采用电价调节即可达到提高供电可靠性、减少用户停电损失以及降低企业收益风险的目的。此外，不同的可靠性的约束条件会影响模型的优化结果，并随着用户需求弹性的减小，电价的调整力度逐渐增大，才能保证用户所期望的供电可靠性。
[Abstract]:Based on the original intention of demand response-to improve system reliability and reduce market transaction risk, the peak-valley time-sharing pricing model considering system reliability and revenue risk is studied. It is of great practical significance to ensure the reliability of power supply and the income of power grid management enterprises, and to improve the social and economic benefits. In this paper, the basis, factors and pricing optimization model of peak-valley time-sharing pricing are studied as follows: The pricing response evaluation and peak-valley time division are the basis of peak-valley time-sharing pricing. At present, there are few literatures on the analytical solution of the electricity price elasticity matrix, and the existing statistical methods are difficult to reflect the interaction between the elastic demand and the period of time under different load levels. Therefore, based on the balance between power supply and elastic demand of power and the price response of customers in multiple time periods, the elastic matrix and analytical solution of electricity price under time-sharing price of peak and valley are derived, and the method is accurate. The response process of the user to the change of electricity price is described comprehensively, and the numerical characteristics of the self-elastic coefficient and the cross-elastic coefficient are analyzed in a numerical example. According to the semi-trapezoidal membership function, the peak-valley period is divided by fuzzy clustering based on F equivalent matrix, and the time period is modified according to the demand of electricity price implementation. The comparison of examples shows that the method is simple and can well reflect the peak and valley characteristics of each load point. The profit risk and system reliability of power grid management enterprises are the important factors to be taken into account in the pricing of peak and valley time-sharing electricity. This paper adopts multi-period power flow to calculate line loss and according to the market background of "separation of power plant and power network" in our country, determines the line loss cost to be borne by power network management enterprises, and through power market risk analysis, based on the functional relationship between electricity price and load in spot market, This paper presents a revenue model of power grid enterprises considering the cost of line loss and the risk of purchasing electricity. The influence of line loss cost and power purchase risk on the income of power grid management enterprises is analyzed, which indicates that the line loss cost and power purchase risk should be fully taken into account in the formulation of electricity price. The reliability evaluation of large power grid is very complex and time-consuming. The cubic spline interpolation is used to establish the functional model of system reliability varying with load, which simplifies the solution process of peak-valley time-sharing pricing optimization model. (3) based on the original intention of demand response, starting from improving system reliability and reducing market transaction risk, taking line loss cost and power purchase risk as objective function, considering reliability constraint. The pricing optimization model of peak-valley time-sharing price is established, and the adaptive genetic algorithm based on cubic spline function relationship between system reliability and load is used to solve the model. The example shows that the electricity price model can improve the reliability of power supply, reduce the loss of power outage and reduce the risk of enterprise income by encouraging users to actively participate in the price response. In addition, different reliability constraints will affect the optimization results of the model, and with the decrease of demand elasticity, the adjustment of electricity price will gradually increase, which can ensure the reliability of power supply expected by users.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.61;F726

【参考文献】