随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分...随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分布鲁棒优化(distributionally robust optimization,DRO)规划模型。可靠性评估通过系统平均中断频率指标(system average interruption frequency index,SAIFI)与预期能源未供应指标(expectation energy not supplied,EENS)量化,给出一种显式可靠性评估模型。利用Wasserstein距离衡量的DRO规划模型来处理可再生能源出力、电与气负荷的随机性。最后经过案例分析得出,投建设施种类的增加不仅能降低总成本,还能提高系统运行可靠性与灵活性,可再生能源出力与气电负荷的不确定性导致总成本提升60%以上。随着可靠性要求提升总成本也随之提高,但得到的方案在实际应用中更具价值与参考性。展开更多
混合储能系统具有储能容量大、调节能力强等优点,有助于提高综合能源系统(integrated energy system,IES)的需求响应能力。首先,构建了一种电-氢-热混合储能系统(electric-hydrogen-thermal hybrid energy storage system,EHT-HESS),其...混合储能系统具有储能容量大、调节能力强等优点,有助于提高综合能源系统(integrated energy system,IES)的需求响应能力。首先,构建了一种电-氢-热混合储能系统(electric-hydrogen-thermal hybrid energy storage system,EHT-HESS),其中采用电解槽(electrolytic cell,EC)、蒸气重整反应(steam methane reforming,SMR)装置、储氢、热电联产氢燃料电池(hydrogen fuel cell,HFC)设备,实现电、气向氢能的转换,以及以氢能作为中间模态的“制氢-储氢-放氢/电/热”功能。其次,建立考虑EHT-HESS的IES需求响应策略优化模型,其中考虑IES响应电价和气价,同时根据富余风电量,进行购电、购气、用电、用热、用氢等策略决策的综合需求响应(integrated demand response,IDR)行为;并采用信息间隙决策理论(information gap decision theory,IGDT)计入概率分布未知的风电严重不确定性,采用基于综合范数的分布鲁棒优化(distributionally robust optimization,DRO)方法计入概率分布不完备的电价严重不确定性。最后,算例验证了模型和方法的合理性及有效性,并表明IES装设热电联产HFC构建EHT-HESS可实现氢能向电能与热能的转换,有助于增加风电消纳量,增加IDR决策的鲁棒性。展开更多
随着可再生能源渗透率的提升,其不确定性给综合能源系统(integrated energy system,IES)的经济性和鲁棒性带来了极大挑战。为了促进可再生能源消纳以及降低碳排放量,提出了一种基于数据驱动的分布鲁棒优化(distributionally robust opti...随着可再生能源渗透率的提升,其不确定性给综合能源系统(integrated energy system,IES)的经济性和鲁棒性带来了极大挑战。为了促进可再生能源消纳以及降低碳排放量,提出了一种基于数据驱动的分布鲁棒优化(distributionally robust optimization,DRO)调度策略。首先,构建了由有机朗肯循环(organic Rankine cycle,ORC)、氢燃料电池和电动汽车等构成的供需灵活响应模型,并引入阶梯碳交易机制来约束系统碳排放量。其次,为了能获取最恶劣情况下的场景概率分布,采用综合范数对风电输出场景的概率分布置信集合进行约束。然后,以在最恶劣场景概率分布下综合能源系统运行总成本最低为目标建立两阶段鲁棒优化模型,并通过列和约束生成(column and constraint generation,CCG)算法对模型进行迭代求解。最后,算例仿真结果表明了所提模型和求解方法的有效性,并分析了阶梯碳交易机制和供需灵活响应模型对提高系统灵活性和低碳经济性的影响。展开更多
With the rapid adoption of electric vehicles(EVs),more charging and battery swapping facilities are needed to meet growing demand.However,a single type of charging or swapping facility cannot simultaneously and effici...With the rapid adoption of electric vehicles(EVs),more charging and battery swapping facilities are needed to meet growing demand.However,a single type of charging or swapping facility cannot simultaneously and efficiently satisfy the power supply requirements of diverse vehicle types.In order to solve this problem,a joint planning method of charging piles and charging-battery swapping stations(CBSSs)is proposed in this paper.In this method,the influence of geospatial constraints on the layout scale of charging piles is considered,and the Monte Carlo simulation method is used to predict the spatiotemporal distribution of charging and battery swapping demands of private electric vehicles(PEVs)and the battery swapping demands of taxi electric vehicles(TEVs)respectively.On this basis,the layout scale of charging piles of each functional area is determined during the maximum charging demand period in a day to meet the demands of PEVs for charging convenience.Then,an operating state model of CBSS is established for calculation of the objective function.At the same time,a planning model of CBSSs is established to minimize the annual social comprehensive cost,which takes into account the economy of CBSSs and the battery swapping convenience of EVs.The planning of CBSSs can meet the demands of TEVs and some PEVs for a rapid power supply.Finally,using the urban transportation network of Changchun and IEEE 33-node system as an example,the planning of charging piles and CCBSs in direct charging mode and peak shifting mode are simulated and analyzed.The simulation results show that the proposed method enables PEVs and TEVs to access convenient and rapid power supply,and the planning result of CBSSs in direct charging mode is more economical,while peak shifting mode is more conducive to the safe operation of distribution networks.展开更多
文摘随着可再生能源占比的提升,气电联合配网(integrated electricity-gas distribution systems,IEGDS)发展迅速,其研究的必要性也随之凸显。为解决IEGDS考虑可再生能源接入后的多设施规划及可靠性评估问题,提出了考虑可靠性约束的IEGDS分布鲁棒优化(distributionally robust optimization,DRO)规划模型。可靠性评估通过系统平均中断频率指标(system average interruption frequency index,SAIFI)与预期能源未供应指标(expectation energy not supplied,EENS)量化,给出一种显式可靠性评估模型。利用Wasserstein距离衡量的DRO规划模型来处理可再生能源出力、电与气负荷的随机性。最后经过案例分析得出,投建设施种类的增加不仅能降低总成本,还能提高系统运行可靠性与灵活性,可再生能源出力与气电负荷的不确定性导致总成本提升60%以上。随着可靠性要求提升总成本也随之提高,但得到的方案在实际应用中更具价值与参考性。
文摘随着可再生能源渗透率的提升,其不确定性给综合能源系统(integrated energy system,IES)的经济性和鲁棒性带来了极大挑战。为了促进可再生能源消纳以及降低碳排放量,提出了一种基于数据驱动的分布鲁棒优化(distributionally robust optimization,DRO)调度策略。首先,构建了由有机朗肯循环(organic Rankine cycle,ORC)、氢燃料电池和电动汽车等构成的供需灵活响应模型,并引入阶梯碳交易机制来约束系统碳排放量。其次,为了能获取最恶劣情况下的场景概率分布,采用综合范数对风电输出场景的概率分布置信集合进行约束。然后,以在最恶劣场景概率分布下综合能源系统运行总成本最低为目标建立两阶段鲁棒优化模型,并通过列和约束生成(column and constraint generation,CCG)算法对模型进行迭代求解。最后,算例仿真结果表明了所提模型和求解方法的有效性,并分析了阶梯碳交易机制和供需灵活响应模型对提高系统灵活性和低碳经济性的影响。
基金supported by the Major Science and Technology Special Project of Jilin Province(No.20240204001SF).
文摘With the rapid adoption of electric vehicles(EVs),more charging and battery swapping facilities are needed to meet growing demand.However,a single type of charging or swapping facility cannot simultaneously and efficiently satisfy the power supply requirements of diverse vehicle types.In order to solve this problem,a joint planning method of charging piles and charging-battery swapping stations(CBSSs)is proposed in this paper.In this method,the influence of geospatial constraints on the layout scale of charging piles is considered,and the Monte Carlo simulation method is used to predict the spatiotemporal distribution of charging and battery swapping demands of private electric vehicles(PEVs)and the battery swapping demands of taxi electric vehicles(TEVs)respectively.On this basis,the layout scale of charging piles of each functional area is determined during the maximum charging demand period in a day to meet the demands of PEVs for charging convenience.Then,an operating state model of CBSS is established for calculation of the objective function.At the same time,a planning model of CBSSs is established to minimize the annual social comprehensive cost,which takes into account the economy of CBSSs and the battery swapping convenience of EVs.The planning of CBSSs can meet the demands of TEVs and some PEVs for a rapid power supply.Finally,using the urban transportation network of Changchun and IEEE 33-node system as an example,the planning of charging piles and CCBSs in direct charging mode and peak shifting mode are simulated and analyzed.The simulation results show that the proposed method enables PEVs and TEVs to access convenient and rapid power supply,and the planning result of CBSSs in direct charging mode is more economical,while peak shifting mode is more conducive to the safe operation of distribution networks.
