【摘要】 电动汽车(electricvehicle, EV)的大规模发展，使得交通网转变为电动汽车和燃油车(gasolinevehicle, GV)随机混合出行的复杂网络；配电网也转变为供需双侧不确定、“源-网-站-储”高效互动的低碳型电网。在新型交通-配电网耦合系统下，亟需研究交通和配电网的联合规划方法，以满足EV时空充电需求，保障交通和配电网的安全可靠运行。为此，基于EV和GV的实时能耗特性差异，建立了混合交通流分配模型，以充分反映GV对EV出行和充电行为的影响，进而建立了混合交通流下的交通网多阶段规划模型。此外，考虑储能型柔性开关(energy storage integrated soft open points, E-SOP)的运行特性，协同“源-网-站-储”，建立了E-SOP影响的配电网多阶段规划模型。结合交通-配电网物理和“流量-功率”耦合约束，实现了交通-配电网的联合规划。根据SiouxFalls交通网和IEEE69节点配电网组成的耦合系统算例测试，验证了所提联合规划模型比独立规划的总成本减少了7.21%，并且E-SOP的接入能减少系统无功出力和电压波动。更多还原

【Abstract】 The large-scale development of electric vehicles(EVs) has transformed the transportation network into a complex network with random and mixed travel of EVs and gasoline vehicles(GVs), and the distribution network has also been a low-carbon grid with uncertain supply and demand, including the interaction of source-grid-station-storage. In the transportation-distribution coupling system(TDCS), it is urgent to develop a coordinated planning method to meet the spatiotemporal charging needs of EVs and ensure the safe operation of the TDCS. Therefore, based on the real-time energy consumption characteristics of EVs and GVs, a mixed traffic flow assignment model is established to better reflect the influence of GVs on the travel and charging behavior of EVs. Then, a multistage planning model of the transportation network in mixed traffic flow is established. Considering the operational characteristics of energy storage integrated soft open points(E-SOP), and cooperating with source-grid-station-storage, a multistage planning model of the distribution network affected by E-SOP is established. Combining with the physical and flow-power coupling constraints, a coordinated planning model is proposed. Based on the case studies of the Sioux Falls transportation network and IEEE 69-node distribution network coupling system, it is verified that the coordinated planning method can reduce the total planning cost by 7.21% compared to separate planning, and E-SOP can reduce the reactive power output and voltage fluctuation of the system.更多还原