【作者】 王东；

【导师】 李春燕；

【作者基本信息】 重庆大学 ， 电气工程， 2017， 硕士

【摘要】 近年来,随着智能电网技术、无线通信技术和高级量测体系等的迅猛发展,为负荷聚合调度的实施提供了条件。大量中小型用户通过负荷聚合商参与市场、大规模电动汽车接入电网和新能源并网将对电网的可靠运行带来威胁。基于此,本文对负荷聚合商、电动汽车需求响应的不确定性和新能源的实时波动功率展开研究,以达到电网稳定运行和用户效益双赢的目的。针对用户用电历史数据和电动汽车出行统计数据,分别建立负荷聚合商聚类和电动汽车无序充放电负荷分布模拟抽样方法。在保证用户未来个性化出行需求的情况下,提出计及行驶路程备用裕量系数的充放电荷电状态期望表征充放电电量需求,建立充电迫切度和放电充裕度指标,量化电动汽车可调控能力并进行排序,进而确定时间序列功率可调控域上下限。基于此,以电网运行成本最小化为目标,建立计及负荷聚合商需求响应和电动汽车有序充放电的优化调度模型,并采用双层粒子群算法求解,以修改后的IEEE9节点算例验证了模型的有效性。建立计及负荷聚合商和电动汽车响应可靠性的时空充放电电价优化调度模型。在空间上,各节点建立计及空间特性最优潮流的节点电价模型,通过实时电价引导电动汽车用户改变充放电习惯,降低运行成本;时间上,考虑电动汽车放电边际成本和供电侧发电成本,确定放电电价的上下边界,引入消费者心理学原理表征电动汽车用户对电价响应的不确定性,制定计及负荷聚合商和电动汽车响应可靠性的充放电电价定价策略,进而建立计及负荷聚合商和电动汽车时间尺度的优化调度模型。以修改后的IEEE33节点算例分析表明,该模型能有效实现电网运行成本、调度策略响应可靠性和用户侧经济效益共赢的目标。提出基于负荷聚合商调度优先权的双层实时调度模型,协调控制多负荷聚合商有效消纳由新能源接入的出力不确定性和电动汽车响应的不确定性带来的实时功率波动。在宏观层,根据负荷聚合商的用电风险特性,建立用电贡献度和用电置信度评价指标量化表征各负荷聚合商消纳实时波动功率的能力和风险;分别从主、客观两个角度结合应用层次分析法和熵权法确定调度优先权,运营商即可制定满足具体要求的各负荷聚合商实时调度计划。在微观层,为降低消纳宏观层实时波动功率时负荷聚合商响应的不确定性,针对负荷聚合商工作时间和用户经济水平的差异,分别提出可中断时间补偿度和消纳分摊权,建立总负荷聚合商利益最大化优化消纳分摊策略。通过修改后的微网算例验证了模型的科学性和有效性。更多还原

【Abstract】 In recent years,with the rapid development of smart grid technology,wireless communication technology and advanced measurement system,conditions have been provided for the implementation of load aggregation scheduling.A large number of small and medium-sized users participating in the market via load aggregators,largescale electric vehicle integrated in power grids and new energy grid connection,will bring threat to the reliable operation of power grid.Based on this problem,the paper studies the response uncertainty of the load aggregators,the electric vehicle and the real-time power fluctuation of the new energy in order to achieve the win-win goal of stable operation and user benefit.According to the users’ electricity consumption history data and electric vehicle travel statistics,the load sampling method of load aggregators clustering and electric vehicle disordered charge and discharge load distribution are established.In the case of guaranteeing users personalized travel demand in the future,expectations for charging and discharging of charge state are proposed considering distance traveled spare margin coefficients,then the charge urgent level and discharging abundance index are built,and electric vehicles regulable capacity are quantified and sorted so that the upper and lower limits of time series power regulable domain could be determined.Based on these,for the minimization of grid operating cost,an optimal scheduling model is proposed to meet the demand response of load aggregators and the orderly charge and discharge of electric vehicle,and a bilayer particle swarm optimization is proposed to solve it.the validity of the model is verified by the modified IEEE 9-bus example.The optimal scheduling model of time-space charge and discharge price considering load aggregators and the response reliability of electric vehicle is established.In space,the node price model is established for each node considering the optimal trend of the spatial characteristic,and guiding the electric vehicle users to change the charge and discharge habits through real-time electricity price,and reducing the running cost.In the terms of time,the marginal cost of electric vehicle discharge and power generation side of the cost of electricity are taken into account to determine the upper and lower boundaries of the discharge price,and the principles of consumer psychology are introduced to characterize the response uncertainty of electric vehicle users to electricity price,and pricing strategies for charge and discharge prices considering load aggregators and electric vehicle response reliability are made,then,the optimal scheduling model is established for the time scales of load aggregators and electric vehicles..The example analysis of the modified IEEE 33-bus verified that the model can achieve a win-win goal of grid operating cost,scheduling strategy response reliability and user economic benefit.The double real-time scheduling model based on priority scheduling is created and it could provide coordination control for load aggregators to consume the real-time power fluctuation caused by the uncertainty of the new energy integrated and the response of the electric vehicle.At the macro layer,the contribution degree and confidence degree of the electricity indexes are defined according to the electrical risk characteristics of load aggregators to quantify the risk.From the perspective of subjective and objective point of view,the comprehensive evaluation of each indexes is calculated using the analytic hierarchy process and entropy weight method to determine the scheduling priority in accordance with the specific requirements.Operators can make the real-time scheduling scheme of the load aggregators based on the scheduling priority.At the micro layer in order to reduce the response uncertainty of the load aggregators when real-time power fluctuations are disposed of at the macro layer,the compensation degree for interruptible time and the consumptive contribution weight are put forward respectively considering the differences of the work time in the load aggregators and users economic level.Finally The example analysis of the modified real micro-grid show the scientific character and effectiveness of the proposed model.更多还原