CN113285464B - 一种电动公交车与分布式光伏协调控制系统 - Google Patents

一种电动公交车与分布式光伏协调控制系统 Download PDF

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CN113285464B
CN113285464B CN202110516406.5A CN202110516406A CN113285464B CN 113285464 B CN113285464 B CN 113285464B CN 202110516406 A CN202110516406 A CN 202110516406A CN 113285464 B CN113285464 B CN 113285464B
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charging
power
bus
power generation
electric bus
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CN113285464A (zh
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张海波
李云鹏
吴晓燕
范春阳
吴凡
陈笑梅
张可
刘潇逸
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Nantong Power Supply Co Of State Grid Jiangsu Electric Power Co
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/62—The condition being non-electrical, e.g. temperature
    • H02J2310/64—The condition being economic, e.g. tariff based load management
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles
    • Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
    • Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
    • Y04S30/12—Remote or cooperative charging
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
    • Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
    • Y04S30/14—Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

本发明公开了一种电动公交车与分布式光伏协调控制系统，由充电排班模块，发电预测模块、功率优化模块三部分组成；充电排班模块主要根据公交排班情况制定各电动公交车的充电任务计划；发电预测模块采用深度神经网络模型，利用光伏的发电历史数据集，训练得到光伏发电预测模型。对未来的光伏发电功率进行预测，获取光伏发电功率预测曲线；功率优化模块依据光伏发电功率预测曲线，制定电动公交车充电功率曲线。本发明利用有限的充电桩资源，合理规划电动公交车充电秩序，在满足公交车运营的前提下，降低公交站充电成本，提高用能质量为目标，优化公交车充电功率。

Description

一种电动公交车与分布式光伏协调控制系统
技术领域
本申请 涉及一种电动公交车与分布式光伏协调控制系统。
背景技术
电动汽车(Electric Vehicle，EV)作为一种环保、低碳的交通工具，近年来得到快速发展。配套充电设施的建设和完善受到我们政府的高度重视。在充电站中融合分布式光伏、储能等系统，有助于降低充电站运营成本，促进城市低碳化发展。一方面，集中式充电站在电动汽车充电时，电网侧会承受负荷波动冲击；另一方面，光伏发电受气象影响而波动，出力具有时序上的不确定性，对配电网的电能质量，电压稳定等产生一系列的影响。
相对于私人电动汽车而言，纯电动公交车有固定的发车时间和较强的出行规律，为保证正常运营普遍采用“间歇充电”的模式，日间频繁充电。公交充电站基本采用专用集中充电模式，充电桩资源有限。合理规划公交车充电秩序，优化公交车充电功率有助于降低公交站充电成本，提高用能质量。
发明内容
本发明的目的在于提供一种利用有限的充电桩资源，合理规划电动公交车充电秩序，优化公交车充电功率的电动公交车与分布式光伏协调控制系统。
本发明的技术解决方案是：
一种电动公交车与分布式光伏协调控制系统，其特征在于：
由充电排班模块，发电预测模块、功率优化模块三部分组成；
充电排班模块主要根据公交排班情况制定各电动公交车的充电任务计划；发电预测模块采用深度神经网络模型，利用光伏的发电历史数据集，训练得到光伏发电预测模型。对未来的光伏发电功率进行预测，获取光伏发电功率预测曲线；功率优化模块依据光伏发电功率预测曲线，制定电动公交车充电功率曲线。
所述充电排班模块以为充电裕度最大优化目标，制定公交充电任务计划；
定义第n辆电动公交车的充电裕度ηnj为：
Figure BDA0003062429470000021
Cnj为电动公交车n行驶时段j消耗产生的新增充电需求，充电需求具体指电动汽车从当前电池状态至电池充满所需要的电量；
Figure BDA0003062429470000022
Figure BDA0003062429470000023
分别为电动公交n的充电任务j起始、结束时刻；充电裕度代表用于满足营运充电需求的可用充电时长，充电裕度越大则公交车充电抗干扰的能力越强；
具体的，充电排班模块以充电裕度最高为目标，求解电动公交车的充放电任务计划。
obj＝max(min(ηnj))。
所述发电预测模块综合考虑多种气象因素预测光伏发电功率；神经网络的模型的输入层包括光照、湿度、温度、上时刻发电功率。
所述功率优化模块以充电费用最低和电网波动最小为多优化目标，求解公交站最优充电功率曲线；优化过程采用多阶段优化方式：第一阶段，以充电费用最低为目标，获取经济优化充电功率。第二阶段，以电网波动最小为目标，获取曲线优化充电功率。
所述充电排班模块，其优化过程需要考虑三方面的约束因素：
1)充电时段约束：电动公交车仅能够在充电站内，即间歇时段才可以进行充电；
Figure BDA0003062429470000031
式中
Figure BDA0003062429470000032
分别为间歇时段的起始、结束时间；
2)公交运营电量约束：分配给电动公交车的充电时长，采用额度功率pne充电，需要满足电动公交车的行驶耗电；
3)充电桩约束：每一个充电任务只能够在一个充电桩执行；
定义zmj为充电任务所采用的充电桩，当zmj＝1时代表任务j 在充电桩m上充电，当zmj＝0时代表任务j不在充电桩m上充电。每一个充电任务只能够在一个充电桩执行：
∑zmj＝1。
所述功率优化模块，其优化过程需要考虑三方面的约束因素：
1)充电功率约束：电动公交车充电功率必须满足充电功率约束；
Figure BDA0003062429470000033
式中
Figure BDA0003062429470000034
为t时刻最小、最大充电功率；
2)充电需求约束：电动公交车充电需求是连续的，定义Rnj为电动公交车n第j个充电任务的起始充电需求；充电任务j+1的起始充电需求等于任务j运行时段结束时的充电需求；
Figure BDA0003062429470000041
电动公交车的充电结束时的充电需求最小为0；
Figure BDA0003062429470000042
为保证电动公交车每日均能够正常的运行；全日总充电电量应等于总消耗电量；
Figure BDA0003062429470000043
3)分时充电量约束，为保证充电站充电费用最小，需要保证不同电价时段总体充放电电量保持不变；
Figure BDA0003062429470000044
本发明利用有限的充电桩资源，合理规划电动公交车充电秩序，在满足公交车运营的前提下，降低公交站充电成本，提高用能质量为目标，优化公交车充电功率。
附图说明
下面结合附图和实施例对本发明作进一步说明。
图1一种电动公交车与分布式光伏协调控制系统架构图。
图2公交车间歇充电示意图。
图3光伏预测模块功能示意图。
图4功率优化模块功能示意图。
图5电动汽车充放电功率控制曲线。
具体实施方式
如图1所示协调控制系统主要由充电排班模块、发电预测模块、功率优化模块三部分组成。
电动公交车由日间营运时段和夜间停运时段两部分组成。夜间停运时段电动公交车处于停驶状态，且光伏发电量为零，基于分时电价以公交站充电成本最低为目标，将电池充满供次日电动公交车营运使用。营运期间采用“间歇充电”的模式，电动公交车行驶结束返回充电站，针对每个间歇时段电动公交车均可进行一次短时充电任务，补充电池电量降低充电需求。
如图2所示，电动公交车由一组间歇时段和行驶时段构成。
充电排班模块主要根据公交排班情况制定各电动公交车的充电任务计划；发电预测模块采用深度神经网络模型，利用光伏的发电历史数据集，训练得到光伏发电预测模型。对未来的光伏发电功率进行预测，获取光伏发电功率预测曲线；功率优化模块依据光伏发电功率预测曲线，制定电动公交车充电功率曲线。
所述充电排班模块以为充电裕度最大优化目标，制定公交充电任务计划；
定义第n辆电动公交车的充电裕度ηnj为：
Figure BDA0003062429470000061
Cnj为电动公交车n行驶时段j消耗产生的新增充电需求，充电需求具体指电动汽车从当前电池状态至电池充满所需要的电量；
Figure BDA0003062429470000062
Figure BDA0003062429470000063
分别为电动公交n的充电任务j起始、结束时刻；充电裕度代表用于满足营运充电需求的可用充电时长，充电裕度越大则公交车充电抗干扰的能力越强；
具体的，充电排班模块以充电裕度最高为目标，求解电动公交车的充放电任务计划。
obj＝maX(min(ηnj))
如图3所示，光伏电站的实时发电波动主要受气象因素影响。所述发电预测模块综合考虑多种气象因素预测光伏发电功率；神经网络的模型的输入层包括光照、湿度、温度、上时刻发电功率。
如图4所示，功率优化模块以充电费用最低和电网波动最小为多优化目标。公交充电站的投资运营主体为公交公司或者其他充电站建设公司，应优先考虑充电费用最低。在费用最低的基础上调整相同电价时段充放电功率，降低用电功率波动，优化用电曲线，有助于提高电网稳定。为保证充电站充电费用最小，需要保证不同电价时段总体充放电电量保持不变。
所述功率优化模块以充电费用最低和电网波动最小为多优化目标，求解公交站最优充电功率曲线；优化过程采用多阶段优化方式：第一阶段，以充电费用最低为目标，获取经济优化充电功率。第二阶段，以电网波动最小为目标，获取曲线优化充电功率。
所述充电排班模块，其优化过程需要考虑三方面的约束因素：
1)充电时段约束：电动公交车仅能够在充电站内，即间歇时段才可以进行充电；
Figure BDA0003062429470000071
式中
Figure BDA0003062429470000072
分别为间歇时段的起始、结束时间；
2)公交运营电量约束：分配给电动公交车的充电时长，采用额度功率pne充电，需要满足电动公交车的行驶耗电；
3)充电桩约束：每一个充电任务只能够在一个充电桩执行；
定义zmj为充电任务所采用的充电桩，当zmj＝1时代表任务j 在充电桩m上充电，当zmj＝0时代表任务j不在充电桩m上充电。每一个充电任务只能够在一个充电桩执行：
∑zmj＝1。
所述功率优化模块，其优化过程需要考虑三方面的约束因素：
1)充电功率约束：电动公交车充电功率必须满足充电功率约束；
Figure BDA0003062429470000073
式中
Figure BDA0003062429470000074
为t时刻最小、最大充电功率；
2)充电需求约束：电动公交车充电需求是连续的，定义Rnj为电动公交车n第j个充电任务的起始充电需求；充电任务j+1的起始充电需求等于任务j运行时段结束时的充电需求；
Figure BDA0003062429470000081
电动公交车的充电结束时的充电需求最小为0；
Figure BDA0003062429470000082
为保证电动公交车每日均能够正常的运行；全日总充电电量应等于总消耗电量；
Figure BDA0003062429470000083
3)分时充电量约束，为保证充电站充电费用最小，需要保证不同电价时段总体充放电电量保持不变；
Figure BDA0003062429470000084
如图5所示，基于本专利所提协调控制系统0:00-8:00低谷时段，公交充电站从电网购买电量，使得电动公交车运营时段开始时基本处于电池充满状态；运营时段，公交车采用间歇充电的方式补充电量，为达到充电费用最小的目的，充电站优先消纳光伏发电，8:00-12:00 峰值时段，购电电量基本为0；12:00-17:00平价时段，电动公交车补充电池电量，保障公交运营，避免后续17:00-21:00峰值时段购买电量。
另一方面，充电站不同时段的用电功率基本保持恒定的状态，且基本不受光伏波动影响，有助于电网稳定。

Claims (4)

1.一种电动公交车与分布式光伏协调控制系统，其特征在于：
由充电排班模块，发电预测模块、功率优化模块三部分组成；
充电排班模块主要根据公交排班情况制定各电动公交车的充电任务计划；发电预测模块采用深度神经网络模型，利用光伏的发电历史数据集，训练得到光伏发电预测模型， 对未来的光伏发电功率进行预测，获取光伏发电功率预测曲线；功率优化模块依据光伏发电功率预测曲线，制定电动公交车充电功率曲线；
所述充电排班模块以为充电裕度最大优化目标，制定公交充电任务计划；
定义第n辆电动公交车的充电裕度ηnj为：
Figure FDA0003470054780000011
Cnj为电动公交车n行驶时段j消耗产生的新增充电需求，充电需求具体指电动汽车从当前电池状态至电池充满所需要的电量；
Figure FDA0003470054780000012
Figure FDA0003470054780000013
分别为电动公交n的充电任务j起始、结束时刻；充电裕度代表用于满足营运充电需求的可用充电时长，充电裕度越大则公交车充电抗干扰的能力越强；
具体的，充电排班模块以充电裕度最高为目标，求解电动公交车的充放电任务计划；
obj＝max(min(ηnj))。
2.根据权利要求1所述的一种电动公交车与分布式光伏协调控制系统，其特征在于：
所述发电预测模块综合考虑多种气象因素预测光伏发电功率；神经网络的模型的输入层包括光照、湿度、温度、上时刻发电功率。
3.根据权利要求1所述的一种电动公交车与分布式光伏协调控制系统，其特征在于：
所述功率优化模块以充电费用最低和电网波动最小为多优化目标，求解公交站最优充电功率曲线；优化过程采用多阶段优化方式：第一阶段，以充电费用最低为目标，获取经济优化充电功率， 第二阶段，以电网波动最小为目标，获取曲线优化充电功率。
4.根据权利要求1所述的一种电动公交车与分布式光伏协调控制系统，其特征在于：
所述充电排班模块，其优化过程需要考虑三方面的约束因素：
1)充电时段约束：电动公交车仅能够在充电站内，即间歇时段才可以进行充电；
Figure FDA0003470054780000021
式中
Figure FDA0003470054780000022
分别为间歇时段的起始、结束时间；
2)公交运营电量约束：分配给电动公交车的充电时长，采用额度功率pne充电，需要满足电动公交车的行驶耗电；
3)充电桩约束：每一个充电任务只能够在一个充电桩执行；
定义zmj为充电任务所采用的充电桩，当zmj＝1时代表任务j在充电桩m上充电，当zmj＝0时代表任务j不在充电桩m上充电， 每一个充电任务只能够在一个充电桩执行：
∑zmj＝1。
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