【作者】 刘鹏；

【导师】 于继来；

【作者基本信息】 哈尔滨工业大学 ， 电力系统及其自动化， 2019， 博士

【摘要】 随着我国经济与社会的发展,节能减排与大气污染防治的压力与日俱增。一方面,大气污染物排放频繁超过重点人居地区的环境承载能力,显著增加了雾霾天气的爆发概率;另一方面,虽然我国风电装机已达较高比例,但弃风问题依然严重,大量风电急需被消纳利用。在此背景下,国家提出了发展电动车(Electric Vehicle,EV)产业,实施以电代油的能源发展规划。在各类EV中,私家插电式EV(Plug-in EV,PEV)预计占有相当比重。因此,通过调控管理手段,提高PEV用能中的风电比重和电源-电网-电动车(简称源-网-车)系统应对空气重污染预警的响应力度,对落实电能替代发展规划具有重要意义。本文针对源-网-车系统协联调控(简称协控)涉及的基础建模、协控机制、决策方法与安全校核问题展开深入研究,以帮助消纳电网过剩风电,提升系统对重点人居环境的大气减污效能,并切实达到降低充电负荷管控的技术难度与实施成本、提高系统可靠性与扩展性、避免泄露车主隐私的目的。针对我国供电调度自动化系统尚未监测PEV个体充电行为信息的技术现状,本文沿着数据挖掘-理论建模-参数辨识的思路,研究了实际PEV集群自然充电负荷特征参数的辨识方法和疏导弹性的统计与评估技术。针对自然充电负荷,提出了大数据挖掘方法,建立了解析计算模型,构建了特征参数辨识模型,并将其疏导弹性分为两类,分别给出了统计与评估方法。基于居民负荷实际数据,验证了数据挖掘方法和参数辨识模型的有效性,分析了疏导弹性的统计与评估结果。所提方法不依赖对PEV个体充电行为信息的采集,能节约相关信息采集与数据传输系统的投资与运维成本,并保护车主充电行为隐私。辨识的特征参数可用于整定充电负荷疏导信号,疏导弹性指标评估结果可反映充电负荷参与有序化调控的潜力。为降低有序化调控充电负荷资源的技术难度和实施成本,提出一种源-网-车系统单向协控模式,并从吸收过剩风电和避免充电同步化角度,设计了一种有序化疏导充电负荷时空分布的单向协控机制。充电桩只需从电网侧单向接收分群错时充电的复合随机型分时电价(Time-of-Use Pricing,TOUP)信号、利用事先设计的本地响应算法自主决策PEV起充时间,容易纳入我国现有电力调控体系。构建了集群充电负荷响应模型,提出了一种面向冬季弃风消纳的季节性复合随机型TOUP参数整定模型,探讨了TOUP低谷电价的取值范围。该机制有助于充电负荷与过剩风电形成平稳互补的协同态势,可有效避免馈线负荷短时陡升效应,能产生较大安全与经济收益。为提升PEV吸收过剩风电的灵活性并兼顾配电馈线的调节需求,基于充电桩单向接收复合随机型TOUP信号、自主决策PEV起充时间的协控模式,研究了有序化疏导充电负荷时空分布的短期协控方法。设计了协控系统基本框架,通过精细化处理车主计划离家时间信息,改进了本地充电响应算法和集群充电响应负荷模型。在此基础上,提出了复合随机型TOUP参数的日前整定模型和安全校核与校正算法。所提方法可帮助充电负荷与过剩风电形成灵活互补的短期协同态势,并能满足馈线调节需求,不依赖电网对PEV个体信息的监测,可避免车主隐私泄露,具有良好技术经济性、较高的可靠性和扩展性。为针对性地提升PEV充电负荷资源和燃煤机组应对重污染天气预警的响应力度,在源-网-车系统单向协控模式下,研究了PEV-电热联合系统的短期协控方法。设计了一种基于荷电状态的阶梯电价(State of Charge Tired Pricing,SOCTP)方案,以引导PEV在重污染天气下自动适当减少源自高边际影响燃煤机组的充电量。提出一种依据空气质量指数时空分布信息计缴燃煤机组排污税的新思路,以提升环境容量裕度资源的使用效能。在此基础上,构建了一种集成SOCTP、复合随机型TOUP和新型排污计税方案的PEV-电热联合系统日前协控模型。算例表明:SOCTP、复合随机型TOUP和新型排污税计缴方案的协同作用,可提升PEV-电热联合系统对重点人居环境的大气减污效能。更多还原

【Abstract】 With developments of economy and society,pressures on energy-saving,emission reduction and prevention and control of air pollution are increasing day by day.On one hand,emissions of air pollutant frequently exceed the environmental capacities of key human settlements,which greatly increases occurring probabilities of fog and haze events;on the other hand,although wind penetrations have reached up to a relative ly high level in China,the wind curtailment issue remains serious.Large amounts of wind energy require to be absorbed.In these backgrounds,the Chinese government has proposed an energy development plan of replacing oil with electricity by developing electric vehicle(EV)industry.Among all kinds of EVs,private plug-in EVs(PEVs)will possess considerable proportions in future.Thus,through dispatch and control managements,promoting ratios of energy generated from wind turbines among total volumes of energy used by PEVs and enhancing response capabilities of electric power source-electric power grid-EVs(abbreviated as source-grid-vehicle,SGV)systems to alerts of heavy air pollution are of great significance to implementing the development plan of electric energy substitution.This paper deeply studies the coordinated dispatch and control(abbreviated as co-control)issues of SGV systems(SGVSs)involving basic modelling,co-control mechanis m,decision methodology and security check and correction.The purposes are to absorb surplus wind powers in the grid,enhance efficiencies of SGVSs on mitigating air pollution in key human settlements,reduce technical difficulties and implementation costs of managing PEV charging load,promote SGVSs’ reliability and scalability and avoid exposing PEV owners’ privacies.Considering that distribution dispatch and automation systems in China cannot yet monitor information of individual PEV’s charging behavior,this paper uses the idea of data mining-theoretical modelling-parameter identification to study the method of identifying characteristic parameters and the technique of counting and evaluating dispatch elasticity(DE)for natural aggregated charging loads(ACLs)of actual PEV fleets.For natural ACL,a data-mining method is proposed and an analytical calculation model is derived.Besides,a characteristic parameter identification model is built.DE of natural ACL is divided into two types and corresponding statistics and evaluation methods are separately proposed.Based on actual residential data,feasibilities of the data mining method and the parameter identification model are verified.Statistics and evaluation results of DE are analyzed.The proposed methodology does not rely on the collection of individual PEVs’ charging behavior information.Thus,it will save corresponding costs of investment,operation as well as maintenance on information collection and data transmission systems,and protect privacies of PEV owners’ charging behaviors.Identified characteristic parameters can be used to tune the coordination signal of charging load and evaluation results of DE index are able to reflect the potential capability of charging load taking part in the coordination program.To reduce technical difficulties and imple mentation costs of coordinating charging load resources,a unidirectional co-control mode is proposed for SGVSs.From the perspective of absorbing surplus wind energy and alleviating charging synchrony,a unidirectional co-control mechanism is designed to coordinate the temporal-spatial distribution of PEV charging load.Charging poles only require to receive the multi stochastic time-of-use pricing(MS-TOUP)information via one-way communication from the grid level and use a local response algorithm designed in advance to autonomously decide start charging times for individual PEVs.It is easy to bring the mechanism into the current power dispatch and control system in China.Noted that,the MS-TOUP is designed based on an idea that PEVs are divided into different groups and charging times are staggered among groups.A coordinated ACL model is built.A seasonal MS-TOUP parameter tuning model is proposed to help absorb surplus wind power in winter.The cheap tariff range of TOUP is identified.The mechanis m will help form steady complementary synergy between ACL and surplus wind power,and greatly mitigate the effects yie lded by the short sharp increment in feeder load.It will produce relative ly high benefits of security and economy.To increase flexibilities of absorbing surplus wind energy via PEVs and consider regulation requirements of distribution feeders,a short term co-control method is studied to coordinate the temporal-spatial distribution of PEV charging load.The method is based on the co-control mode that charging poles receive the MS-TOUP information via one-way communication,and autonomously decide PEVs’ start charging times.The basic framework is designed for the co-control system.The local charging response algorithm and the coordinated ACL model are improved by carefully dealing with times when PEV owners schedule to departure home.On this basis,a day-ahead model is proposed to tune MS-TOUP parameters and a day-ahead algorithm is designed to check and correct MS-TOUP parameters.The proposed method will help form flexible complementary synergy in short-term time scale between ACL and surplus wind power,and meanwhile satisfy regulation requirements for feeders.The method will not rely on the power grid monitoring individual PEVs’ information,and will aviod exposing privacy information of PEV owners.It is with well cost-effectiveness,high reliability and scalability.To enhance effic iencies of PEV charging load resources and coal-fired units on responding to the heavy air pollution whether alert in a pointed manner,the short term co-control method of a combined PEV and electric-thermal system is studied under the unidirectional co-control mode of SGVSs.A state of charge tiered pricing(SOCTP)scheme is proposed to lead PEVs to automatically decrease proper volumes of charging energy from coal-fired units that have high margina l effects on heavy air pollution.A novel idea,levying air pollutant tax from coal-fired units according to the spatial and temporal distribution of AQI,is proposed to promote utilization effic iencies of margin resources of environmental capacities.On this basis,a day ahead co-control model of a combined PEV and electric-thermal system is formulated by integrating SOCTP,MS-TOUP and novel emission tax.Case studies show that,the coordinated regulations of SOCTP,MS-TOUP and novel emission tax will enhance efficiencies of the combined PEV and electric-thermal system on mitigating air pollution in key human settleme nts.更多还原