含电动汽车及换电站的微网优化调度研究
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摘要
随着经济的发展,能源需求不断增长,构建稳定、经济、清洁、安全的能源供应体系面临一系列重大挑战；机动车保有量增长迅速,尾气成为城市大气的主要污染源。应对能源与环境的双重压力,应积极优化能源结构、推动能源生产和利用方式变革。分布式发电与电动汽车的推广应用有助于减少石油依赖、降低环境污染、控制温室气体排放。如何提高电动汽车的保有量,提高能源供给设施的利用率,同时降低可能对电网产生的不利影响,发挥电动汽车接入的优势,使电网与电动汽车用户效益最大化是目前急需解决的问题。在这样的背景下,本文对含电动汽车与换电站的微网优化调度问题进行了研究,取得一些创新性的研究成果。
首先,介绍了电动汽车及其能源供给的发展背景、发展现状,概括了电动汽车产业发展与智能电网建设间的关系以及面临的挑战与机遇。电动汽车成本、里程、用户体验等方面的问题一定程度上可以通过加强能源供给基础设施建设来解决。综述了电动汽车充放电对电力系统的影响、电动汽车相关优化调度研究,概括了微网在利用可再生能源解决电动汽车能源供给方面的优势,以及优化调度的重要意义。为避免含大规模电动汽车的优化调度计算出现“维数灾”问题,以及分布式电源与电动汽车直接接入配电网可能带来的不利影响,并考虑到国家电网公司发布的指导意见,利用分层分区运行管理结构,考虑将问题转化为含电动汽车及换电站的微网优化调度问题。
其次,在电动汽车行驶统计规律的基础上,提出了电动汽车智能接入模式下的微网优化调度模型。微网调度机构根据不同电动汽车用户需求、可再生能源功率、其他负荷功率以及电动汽车充放电过程需满足的约束,给出包括每辆电动汽车在内的微网内所有设备的运行策略。所建立的混合整数线性规划模型可利用现有成熟商业软件(如CPLEX)求解。优化结果表明,智能接入模式下的电动汽车作为分散式储能单元,与微网内集中式储能元件协调配合,可发挥移峰填谷的作用,具有很好的经济性。
第三,提出了一种基于微网的电动汽车换电站运营模式,建立了换电站充放电模型。根据换电站内充放电装置和电池组的约束,考虑了含有风电、光伏、燃料电池、微型燃气轮机、柴油发电机等电源的微网,提出了含电动汽车换电站的微网优化调度策略,并将换电站接入模式与传统储能电站接入模式进行了对比。算例表明换电站也可以发挥削峰填谷的作用,且更具经济性。随后,对市场容量、换电池价格及可再生能源渗透率等因素对经济性的影响进行了分析,提出的激励指数可为换电池价格、电池租赁价格的制定提供参考。随着可再生能源渗透率提高,电动汽车换电站接入微网模式的节能减排效益将更加明显。
第四,对微电网内重要单元,如电池储能电站、电动汽车换电站、可中断负荷等分别进行了分析并建模,结合系统功率平衡、备用需求等约束,建立微电网独立运行优化模型。优化结果表明,相比传统电池储能电站,电动汽车换电站作为储能装置,通过协调优化,可以提高微电网的可再生能源接纳能力,提高微电网可靠性,并更具经济性。
如前所述,第二部分研究电动汽车分散式接入微网的优化调度问题,第三、四部分分别在微网并网、孤岛运行方式下,研究采用集中换电方式的优化调度问题,由于问题侧重于经济性、可行性的分析,所以对可再生能源功率、负荷等采用典型日曲线来描述,没有考虑不确定性。
第五,在微网并网运行方式下,同时考虑电动汽车分散式充放电和集中换电站模式,针对风电、光伏、负荷、电动汽车充放电功率等多种不确定因素,在预测值与概率分布统计规律的基础上,应用区间系数规划与机会约束规划建立了考虑电动汽车、可再生能源和换电站的微网随机调度模型,推导出随机变量线性组合的分布函数,并将含不确定性因素的约束转化成等价的确定性约束,有利于问题的快速求解,优化后的调度方案在满足备用约束的前提下更具经济性。
最后,对全文工作进行了总结,概括了本文主要研究成果,并指出了今后有待进一步开展的工作。
With the rapid economic development, energy demand is growing quickly y ear-by-year. Construction of stable energy supply system is likely to face severe challenges. Exhaust gas from automobile engine is one of the main air pollution sources. The utilization efficiency of energy production and end use should be promoted. Electric vehicles and renewable energy can effectively relieve the burden of energy supply and environment. there are some urgent issues to be settled, such as increasing the quantity of electric vehicles, improving the utilization rate of energy supply facility, reducing the possible adverse effects on power system, exploiting advantages of electric vehicles plugging and maximizing the benefit of investors. Under such background, this thesis conducts research on optimal dispatch for microgrid with electric vehicles and battery swap station, and obtains some innovative research results.
Firstly, the development background of electric vehicles and energy supply infrastructure. The challenges and opportunities of electric vehicle industry and smart grid are summarized, as well as the relationship between them. Problems such as cost, mileage, user experience of electric vehicles can be solved by enhancing energy supply infrastructure. The research status of impacts of electric vehicle charging and discharging on power system and optimal dispatch methods are reviewed. The superiorities of microgrid for electric vehicles and renewable resource integration are concluded, as well as the importance of optimal dispatch. Microgrid can help decrease communications and computational burden, and alleviate the adverse effects. Instruction released by state grid corporation of China should be considered carefully. A centralized hierarchical management and control structure is proposed, which makes microgrid independent from distributed network. The main problem is then transformed into research on optimal dispatch for microgrid with electric vehicles and battery swap station (BSS).
Secondly, significant uncertainty arising from a large amount of EV's disordered integration should be considered while dispatching. A smart connecting mode for EV is proposed on the basis of statistical regularities. The optimal dispatch model of microgrid is presented according to EV owners'needs, renewable energy power, load and other constraints of EV when charging or discharging. The operation strategy of all components in microgrid including each electric vehicle is given. The model of mixed integer linear programming can be solved by CPLEX. The stochastic simulation is used to create a large number of scenarios. Smart connecting mode is compared with random charging mode and off-peak charging mode after thousands of times optimization. The results indicate that in smart connecting mode electric vehicles play the role of distributed energy storage devices, coordinating with centralized energy storage station. Thus, load shifting is realized in smart connecting mode, which will bring more profit in electricity market than other two modes.
Thirdly, a business model of microgrid based battery swap station for electric vehicles is proposed. Analysis and evaluation of charging and discharging performance modeling is presented. According to battery and charger/discharger constraints, a new optimal dispatching strategy of microgrid containing BSS, wind generators, photovoltaic systems, fuel cells, micro turbines and diesel generators is given. Economic indices of BSS mode and traditional energy storage station (ESS) mode are also compared, and the simulation results indicate that BSS can bring more benefits than ESS. Furthermore, the economic impacts of battery renting market capacity, price of batteries and penetration of renewable energy are also discussed. A pricing method for battery swapping and renting is also put forward.
Fourthly, the intermittence of renewable power supply may result in power surplus or shortfall in islanded microgrid. The important components of microgrid such as interruptible load and energy storage station are analyzed and modeled. Case study is carried out respectively for microgrid with BSS and that with ESS, which shows that, through coordinated optimization, the islanded microgrid with BSS as the energy storage device is cheaper and more reliable, and integrates more renewable energy sources.
Fifthly, stochastic dispatch is a difficult problem because of high penetration of renewable energy and electric vehicles. The uncertainties caused by renewable energy resources, load, electric vehicles charging and V2G are all considered. An interval coefficients and chance constrained programming combined stochastic dispatch model is proposed based on power forecasts and probability distribution. Case studies are carried out to illustrate the feasibility and efficiency of the proposed model comparing with traditional model.
At last, the main findings of the paper are summarized, and the future research directions are pointed out.
首先,介绍了电动汽车及其能源供给的发展背景、发展现状,概括了电动汽车产业发展与智能电网建设间的关系以及面临的挑战与机遇。电动汽车成本、里程、用户体验等方面的问题一定程度上可以通过加强能源供给基础设施建设来解决。综述了电动汽车充放电对电力系统的影响、电动汽车相关优化调度研究,概括了微网在利用可再生能源解决电动汽车能源供给方面的优势,以及优化调度的重要意义。为避免含大规模电动汽车的优化调度计算出现“维数灾”问题,以及分布式电源与电动汽车直接接入配电网可能带来的不利影响,并考虑到国家电网公司发布的指导意见,利用分层分区运行管理结构,考虑将问题转化为含电动汽车及换电站的微网优化调度问题。
其次,在电动汽车行驶统计规律的基础上,提出了电动汽车智能接入模式下的微网优化调度模型。微网调度机构根据不同电动汽车用户需求、可再生能源功率、其他负荷功率以及电动汽车充放电过程需满足的约束,给出包括每辆电动汽车在内的微网内所有设备的运行策略。所建立的混合整数线性规划模型可利用现有成熟商业软件(如CPLEX)求解。优化结果表明,智能接入模式下的电动汽车作为分散式储能单元,与微网内集中式储能元件协调配合,可发挥移峰填谷的作用,具有很好的经济性。
第三,提出了一种基于微网的电动汽车换电站运营模式,建立了换电站充放电模型。根据换电站内充放电装置和电池组的约束,考虑了含有风电、光伏、燃料电池、微型燃气轮机、柴油发电机等电源的微网,提出了含电动汽车换电站的微网优化调度策略,并将换电站接入模式与传统储能电站接入模式进行了对比。算例表明换电站也可以发挥削峰填谷的作用,且更具经济性。随后,对市场容量、换电池价格及可再生能源渗透率等因素对经济性的影响进行了分析,提出的激励指数可为换电池价格、电池租赁价格的制定提供参考。随着可再生能源渗透率提高,电动汽车换电站接入微网模式的节能减排效益将更加明显。
第四,对微电网内重要单元,如电池储能电站、电动汽车换电站、可中断负荷等分别进行了分析并建模,结合系统功率平衡、备用需求等约束,建立微电网独立运行优化模型。优化结果表明,相比传统电池储能电站,电动汽车换电站作为储能装置,通过协调优化,可以提高微电网的可再生能源接纳能力,提高微电网可靠性,并更具经济性。
如前所述,第二部分研究电动汽车分散式接入微网的优化调度问题,第三、四部分分别在微网并网、孤岛运行方式下,研究采用集中换电方式的优化调度问题,由于问题侧重于经济性、可行性的分析,所以对可再生能源功率、负荷等采用典型日曲线来描述,没有考虑不确定性。
第五,在微网并网运行方式下,同时考虑电动汽车分散式充放电和集中换电站模式,针对风电、光伏、负荷、电动汽车充放电功率等多种不确定因素,在预测值与概率分布统计规律的基础上,应用区间系数规划与机会约束规划建立了考虑电动汽车、可再生能源和换电站的微网随机调度模型,推导出随机变量线性组合的分布函数,并将含不确定性因素的约束转化成等价的确定性约束,有利于问题的快速求解,优化后的调度方案在满足备用约束的前提下更具经济性。
最后,对全文工作进行了总结,概括了本文主要研究成果,并指出了今后有待进一步开展的工作。
With the rapid economic development, energy demand is growing quickly y ear-by-year. Construction of stable energy supply system is likely to face severe challenges. Exhaust gas from automobile engine is one of the main air pollution sources. The utilization efficiency of energy production and end use should be promoted. Electric vehicles and renewable energy can effectively relieve the burden of energy supply and environment. there are some urgent issues to be settled, such as increasing the quantity of electric vehicles, improving the utilization rate of energy supply facility, reducing the possible adverse effects on power system, exploiting advantages of electric vehicles plugging and maximizing the benefit of investors. Under such background, this thesis conducts research on optimal dispatch for microgrid with electric vehicles and battery swap station, and obtains some innovative research results.
Firstly, the development background of electric vehicles and energy supply infrastructure. The challenges and opportunities of electric vehicle industry and smart grid are summarized, as well as the relationship between them. Problems such as cost, mileage, user experience of electric vehicles can be solved by enhancing energy supply infrastructure. The research status of impacts of electric vehicle charging and discharging on power system and optimal dispatch methods are reviewed. The superiorities of microgrid for electric vehicles and renewable resource integration are concluded, as well as the importance of optimal dispatch. Microgrid can help decrease communications and computational burden, and alleviate the adverse effects. Instruction released by state grid corporation of China should be considered carefully. A centralized hierarchical management and control structure is proposed, which makes microgrid independent from distributed network. The main problem is then transformed into research on optimal dispatch for microgrid with electric vehicles and battery swap station (BSS).
Secondly, significant uncertainty arising from a large amount of EV's disordered integration should be considered while dispatching. A smart connecting mode for EV is proposed on the basis of statistical regularities. The optimal dispatch model of microgrid is presented according to EV owners'needs, renewable energy power, load and other constraints of EV when charging or discharging. The operation strategy of all components in microgrid including each electric vehicle is given. The model of mixed integer linear programming can be solved by CPLEX. The stochastic simulation is used to create a large number of scenarios. Smart connecting mode is compared with random charging mode and off-peak charging mode after thousands of times optimization. The results indicate that in smart connecting mode electric vehicles play the role of distributed energy storage devices, coordinating with centralized energy storage station. Thus, load shifting is realized in smart connecting mode, which will bring more profit in electricity market than other two modes.
Thirdly, a business model of microgrid based battery swap station for electric vehicles is proposed. Analysis and evaluation of charging and discharging performance modeling is presented. According to battery and charger/discharger constraints, a new optimal dispatching strategy of microgrid containing BSS, wind generators, photovoltaic systems, fuel cells, micro turbines and diesel generators is given. Economic indices of BSS mode and traditional energy storage station (ESS) mode are also compared, and the simulation results indicate that BSS can bring more benefits than ESS. Furthermore, the economic impacts of battery renting market capacity, price of batteries and penetration of renewable energy are also discussed. A pricing method for battery swapping and renting is also put forward.
Fourthly, the intermittence of renewable power supply may result in power surplus or shortfall in islanded microgrid. The important components of microgrid such as interruptible load and energy storage station are analyzed and modeled. Case study is carried out respectively for microgrid with BSS and that with ESS, which shows that, through coordinated optimization, the islanded microgrid with BSS as the energy storage device is cheaper and more reliable, and integrates more renewable energy sources.
Fifthly, stochastic dispatch is a difficult problem because of high penetration of renewable energy and electric vehicles. The uncertainties caused by renewable energy resources, load, electric vehicles charging and V2G are all considered. An interval coefficients and chance constrained programming combined stochastic dispatch model is proposed based on power forecasts and probability distribution. Case studies are carried out to illustrate the feasibility and efficiency of the proposed model comparing with traditional model.
At last, the main findings of the paper are summarized, and the future research directions are pointed out.
引文
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