WO2021110146A1 - 电动汽车充电与新能源发电的协同调度方法及装置 - Google Patents

电动汽车充电与新能源发电的协同调度方法及装置 Download PDF

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WO2021110146A1
WO2021110146A1 PCT/CN2020/133959 CN2020133959W WO2021110146A1 WO 2021110146 A1 WO2021110146 A1 WO 2021110146A1 CN 2020133959 W CN2020133959 W CN 2020133959W WO 2021110146 A1 WO2021110146 A1 WO 2021110146A1
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electric vehicle
new energy
electric vehicles
power generation
charged
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French (fr)
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吴俊杰
贾庆山
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清华大学
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
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    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • 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
    • Y02T90/14—Plug-in electric vehicles

Definitions

  • the invention relates to the technical field of electric vehicle charging scheduling, in particular to a method and device for cooperative scheduling of electric vehicle charging and new energy power generation based on index sorting.
  • a double-layer optimized scheduling method for electric vehicles and wind power cooperative charging A double-layer optimized scheduling method for electric vehicles and wind power cooperative charging based on a multi-objective particle swarm algorithm is disclosed.
  • the multi-objective particle swarm algorithm is used for electric vehicles.
  • the optimization of charging scheduling includes an upper-level scheduling method for electric vehicle charging from a time perspective and a lower-level scheduling method for electric vehicle charging from a spatial perspective.
  • the upper-level scheduling of electric vehicle charging specifically includes the following steps: (1) When the electric vehicle needs to be charged, read the initial SOC and target SOC of the electric vehicle, and predict the load of the electric vehicle based on the read information; (2) According to The load forecasting information aims at the lowest carbon emissions, the lowest power generation cost, and the smallest system equivalent load variance.
  • the particle swarm algorithm is used to optimize the upper-level scheduling model to generate the upper-level strategy for electric vehicle charging scheduling; the lower-level scheduling for electric vehicle charging specifically includes The steps are as follows: (1) Calculate the charging price of the time-sharing zone according to the degree of congestion of different charging stations; (2) Calculate the number of electric vehicles to be charged in each period according to the results of the upper-level scheduling model; (3) Use electric vehicles The user's charging cost is the minimum and the charging queuing time is the shortest as the goal.
  • the multi-objective particle swarm algorithm is used to optimize the lower-level scheduling model to obtain the optimal charging strategy.
  • the above solution steps are too complicated.
  • the upper-level scheduling needs to be optimized first, and the prediction model also needs to be used to predict the electric vehicle compliance, and then the lower-level scheduling optimization is performed. It is also necessary to indirectly optimize the use of new energy power generation.
  • This method indirectly considers the supply-demand matching relationship between new energy power generation and electric vehicle charging through the electricity price. Since the electricity price is related to the transaction behavior in the electricity market, the response of the electricity price to the fluctuation of the new energy generation supply is lagging.
  • the proposed LLLP rule uses two characteristic factors of charging flexibility and remaining charging time as ranking indicators. When the two factors are incomparable, an effective ranking cannot be obtained.
  • the document also indirectly considers the supply-demand matching relationship between new energy power generation and electric vehicle charging through electricity prices, and there is also a lag in the response of electricity prices to fluctuations in the supply of new energy power generation.
  • the present invention aims to solve one of the technical problems in the related art at least to a certain extent.
  • an object of the present invention is to propose a method for coordinated scheduling of electric vehicle charging and new energy power generation.
  • the method is simple to solve and only needs to calculate the index value and sort to obtain a clear charging strategy.
  • Another object of the present invention is to provide a coordinated scheduling device for electric vehicle charging and new energy power generation.
  • Step S1 obtain the current time period of new energy power generation information and electric vehicle charging power to determine the utilization The number of electric vehicles charged by new energy power generation; step S2, obtain electric vehicle index factors, sort the electric vehicle index factors, obtain the electric vehicle charging priority sequence, and determine the number of electric vehicles that must be charged in the current period; step S3 , Determine whether the number of electric vehicles that use new energy generation for charging is not less than the number of electric vehicles that must be charged, and if so, charge the electric vehicles according to the electric vehicle charging priority sequence until the new energy generation is exhausted, If not, then purchase city electricity to charge the electric vehicle that must be charged; step S4, determine whether the current time period exceeds the preset time period, if not, skip to step S1, until the end of the preset time period exceeds cycle.
  • the coordinated scheduling method for electric vehicle charging and new energy power generation in the embodiment of the present invention is simple to solve and can meet the requirements of large-scale and real-time; the new energy power generation information can be directly used as decision-making information, and the new energy power generation can be better realized.
  • the use of; the index value is sorted in total order, which can ensure that the solution strategy is obtained, and the incomparable situation is avoided.
  • the coordinated dispatch method for electric vehicle charging and new energy power generation according to the above-mentioned embodiment of the present invention may also have the following additional technical features:
  • the electric vehicle index factors include power, remaining charging time, and remaining parking time.
  • the step S2 further includes: constructing a sorting index value equation according to the power of the electric vehicle, the remaining charging time and the remaining parking time, and calculating the calculated index value of the electric vehicle in the parking state;
  • the calculated index values of the electric vehicles in the parking state are arranged to obtain the electric vehicle charging priority sequence.
  • arranging the calculated index values of the electric vehicles in the parking state includes but is not limited to the following methods: bubble sorting method, selection sorting method, insertion sorting method, and merge sorting method.
  • the charging electric vehicles according to the electric vehicle charging priority sequence includes: first using new energy to generate electricity to charge the electric vehicles that must be charged; when the electric vehicles that must be charged After the vehicle is fully charged, if the new energy generation capacity still remains, the remaining electric vehicles are charged according to the electric vehicle charging priority sequence until the new energy generation is exhausted.
  • another embodiment of the present invention proposes a coordinated dispatching device for electric vehicle charging and new energy power generation, including: a determining module, used to obtain current period energy generation information and electric vehicle charging power, and determine the use of new energy The number of electric vehicles charged by energy generation; the acquisition sequence module is used to acquire the index factors of electric vehicles, sort the index factors of electric vehicles, obtain the priority sequence of electric vehicles, and determine the number of electric vehicles that must be charged in the current period Judgment module, used to determine whether the number of electric vehicles charged by new energy generation is not less than the number of electric vehicles that must be charged, and if so, the electric vehicles are charged according to the electric vehicle charging priority sequence until the new Energy generation is exhausted.
  • a determining module used to obtain current period energy generation information and electric vehicle charging power, and determine the use of new energy The number of electric vehicles charged by energy generation
  • the acquisition sequence module is used to acquire the index factors of electric vehicles, sort the index factors of electric vehicles, obtain the priority sequence of electric vehicles, and determine the number of electric vehicles that must be charged in the current period
  • the cycle module is used to determine whether the current period exceeds the preset period of time, if it does not exceed, then jump to the determination module to reschedule, The loop ends until the preset time period is exceeded.
  • the coordinated scheduling device for electric vehicle charging and new energy power generation in the embodiment of the present invention is simple to solve and can meet the requirements of large-scale and real-time; the new energy power generation information can be directly used as decision information, which can better realize the power generation of new energy.
  • the use of; the index value is sorted in total order, which can ensure that the solution strategy is obtained, and the incomparable situation is avoided.
  • the coordinated scheduling device for electric vehicle charging and new energy power generation may also have the following additional technical features:
  • the electric vehicle index factors include power, remaining charging time, and remaining parking time.
  • the acquiring sequence module includes:
  • the index calculation module is used to construct a sorting index value equation according to the electric vehicle's power, remaining charging time and remaining parking time, and calculate the calculated index value of the electric vehicle in the parking state;
  • the sorting module is used to sort the calculated index values of the electric vehicles in the parking state to obtain the electric vehicle charging priority sequence.
  • arranging the calculated index values of the electric vehicles in the parking state includes but is not limited to the following methods: bubble sorting method, selection sorting method, insertion sorting method, and merge sorting method.
  • the judgment module is specifically used to: first use new energy to generate electricity to charge an electric vehicle that must be charged; when the electric vehicle that must be charged is fully charged, the new energy generating capacity still remains The remaining electric vehicles are charged according to the electric vehicle charging priority sequence until the new energy generation is exhausted.
  • Fig. 1 is a flowchart of a coordinated dispatch method for electric vehicle charging and new energy power generation according to an embodiment of the present invention
  • Fig. 2 is a schematic structural diagram of a coordinated scheduling device for electric vehicle charging and new energy power generation according to an embodiment of the present invention.
  • Fig. 1 is a flowchart of a method for coordinated dispatching of electric vehicle charging and new energy power generation according to an embodiment of the present invention.
  • the coordinated scheduling method for electric vehicle charging and new energy power generation includes the following steps:
  • step S1 the new energy power generation information of the current period and the charging power of the electric vehicles are obtained to determine the number of electric vehicles that use the new energy power generation for charging.
  • step S2 the electric vehicle index factors are obtained, the electric vehicle index factors are sorted, the electric vehicle charging priority sequence is obtained, and the number of electric vehicles that must be charged in the current period is determined.
  • the electric vehicle index factors may include indicators such as power, remaining charging time, and remaining parking time.
  • step S2 further includes:
  • the index value is calculated for the electric vehicle in the parking state.
  • a, b, c, d are weighting factors.
  • the sorting method can also use the same index and different sorting methods, such as bubbling sorting, selection sorting, insertion sorting, merge sorting and other sorting methods, to obtain the sorting, or use different indexes or weights for calculation, It is also possible to obtain the same sorting.
  • step S3 it is judged whether the number of electric vehicles charged by new energy generation is not less than the number of electric vehicles that must be charged. If so, the electric vehicles are charged according to the priority sequence of electric vehicle charging until the new energy generation is exhausted, if not , Then purchase city electricity to charge electric vehicles that must be charged.
  • charging the electric vehicle according to the electric vehicle charging priority sequence includes:
  • step S2 a judgment is made, when K ⁇
  • represents the size of the ⁇ set, that is, the number of electric cars that must be charged), first use new energy to generate electricity to charge the electric cars in ⁇ ; if If there is still remaining new energy power generation, the remaining electric vehicles will be charged according to the priority sequence of electric vehicle charging Prio [[1],[2],...[N]] until the new energy generation is used up.
  • in addition to using new energy to generate electricity to charge electric vehicles, it is necessary to supplement the purchase of city electricity to meet all electric vehicle charging requirements within ⁇ .
  • step S4 it is determined whether the current time period exceeds the preset time period, and if it does not exceed, then jump to step S1 until the preset time period is exceeded to end the loop.
  • the solution is simple, and can meet the requirements of large-scale and real-time performance. Only by calculating the index value and sorting, a clear charging strategy can be obtained.
  • the complexity is N log N, the steps are simple, and the solution efficiency is high; the new energy power generation information can be directly used as decision-making information, which can better realize the utilization of new energy power generation.
  • the electricity price is used as a Decision-making information can effectively avoid the delay of electricity prices to changes in power generation; to avoid incomparable situations, the index values are sorted in total order.
  • this method can guarantee the solution Strategy to avoid incomparable situations.
  • Fig. 2 is a schematic structural diagram of a coordinated scheduling device for electric vehicle charging and new energy power generation according to an embodiment of the present invention.
  • the device 10 includes: a determination module 100, an acquisition sequence module 200, a judgment module 300, and a circulation module 400.
  • the determining module 100 is used to obtain new energy power generation information and electric vehicle charging power in the current period, and determine the number of electric vehicles that use new energy power generation for charging.
  • the sequence acquiring module 200 is used to acquire the index factors of electric vehicles, sort the index factors of electric vehicles, obtain the electric vehicle charging priority sequence, and determine the number of electric vehicles that must be charged in the current period.
  • the judging module 300 is used to judge whether the number of partially charged electric vehicles is not less than the number of electric vehicles that must be charged. If so, the electric vehicles are charged according to the electric vehicle charging priority sequence until the new energy generation is exhausted. If not, the purchase market Electricity charges electric cars that must be charged.
  • the cycle module 400 is used to determine whether the current time period exceeds a preset time period, and if it does not exceed, then jump to the determination module to reschedule until the preset time period is exceeded to end the cycle.
  • the electric vehicle index factors include: power, remaining charging time, and remaining parking time.
  • the acquiring sequence module further includes:
  • the index calculation module is used to construct the sorting index value equation according to the electric vehicle's power, remaining charging time and remaining parking time, and calculate the calculated index value of the electric vehicle in the parking state;
  • the sorting module is used to sort the calculated index values of the electric vehicles in the parking state to obtain the charging priority sequence.
  • arranging the calculated index values of the electric vehicles in the parking state includes: bubbling sorting method, selection sorting method, insertion sorting method, merge sorting method and other sorting methods.
  • the electric vehicle charging priority sequence is applied to the electric vehicles.
  • Charging specifically includes: first use new energy to generate electricity to charge the electric vehicles that must be charged; when the electric vehicles that must be charged are fully charged and the new energy generation capacity is still left, the remaining electric vehicles are charged according to the priority sequence of electric vehicle charging until the new Energy generation is exhausted.
  • the coordinated scheduling device for electric vehicle charging and new energy power generation proposed according to the embodiment of the present invention is simple to solve and can meet the requirements of large-scale and real-time; the new energy power generation information can be directly used as decision-making information, which can better realize the new energy generation Utilization of energy generation; the index values are sorted in full order, which can ensure that the solution strategy is obtained, and the incomparable situation is avoided.
  • first and second are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with “first” and “second” may explicitly or implicitly include at least one of the features. In the description of the present invention, “plurality” means at least two, such as two, three, etc., unless otherwise specifically defined.

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Abstract

一种电动汽车充电与新能源发电的协同调度方法及装置，其中，该方法包括以下步骤：获取当前时段的新能源发电信息和电动汽车的充电功率，确定利用新能源发电进行充电的电动汽车数量；获取电动汽车指标因子，对电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量；判断利用新能源发电进行充电的电动汽车数量是否不小于必须充电的电动汽车数量，若是，则依据电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电。该方法求解简单，只需计算指标值并排序，即可得出明确的充电策略，且能够直接利用新能源发电信息作为决策信息，更好地实现对新能源发电的利用。

Description

电动汽车充电与新能源发电的协同调度方法及装置 技术领域
本发明涉及电动汽车充电调度技术领域，特别涉及一种基于指标排序的电动汽车充电与新能源发电的协同调度方法及装置。
背景技术
随着新能源发电(太阳能、风电、潮汐能等等)技术的发展和新能源汽车的迅速普及，电动汽车特别是纯电动汽车的充电调度问题日益成为学界和产业界关注的话题。
电动汽车充电与新能源发电供需匹配协同优化的现有方案中以智能优化算法为主，比如：
相关技术一，一种电动汽车与风电协同充电双层优化调度方法，公开了一种基于多目标粒子群算法的电动汽车与风电协同充电双层优化调度方法，利用多目标粒子群算法对电动汽车充电调度进行优化，包括从时间角度出发的电动汽车充电上层调度方法和从空间角度出发的电动汽车充电下层调度方法。其中，电动汽车充电上层调度具体包括如下步骤：(1)当电动汽车需要充电时，对电动汽车的初始SOC以及目标SOC进行读取，根据读取信息对电动汽车负荷进行预测；(2)根据负荷预测的信息，以碳排放量最低、发电成本最低和系统等效负荷方差最小为目标，使用粒子群算法对上层调度模型进行优化，生成电动汽车充电调度上层策略；电动汽车充电下层调度具体包括如下步骤：(1)根据不同充电站的拥挤程度，计算出分时分区的充电电价；(2)根据上层调度模型结果，计算出每个时段待充电的电动汽车数量；(3)以电动汽车用户充电费用最少以及充电排队时间最短为目标，使用多目标粒子群算法对下层调度模型进行优化求解，得到最优的充电策略。
显然，上述求解步骤过于复杂，提出分层调度优化结构，需要首先对上层调度进行优化，其中还需要利用预测模型对电动汽车符合进行预测，再进行下层调度优化。还需要对新能源发电使用量进行间接优化。该方法通过电价间接考虑了新能源发电与电动汽车充电之间的供需匹配关系，由于电价与电力市场中的交易行为有关，故电价对于新能源发电供给波动的反应存在滞后。
相关技术二，提出了一种基于充电弹性和剩余充电时间的优先级方法，即最小充电弹性-最长剩余充电时间优先(LLLP，Less Laxity and Longer Remaining Processing  Time)：当一辆电动汽车A相对于另外一辆车B同时满足两个条件时，(1)充电弹性较小；(2)剩余充电时间较长，则A车相对于B车有更高的充电优先级。在未按时完成充电时，若惩罚函数为剩余充电量的凸函数，基于该方法可以得到惩罚最小的充电策略。
但其提出的LLLP规则，利用充电弹性和剩余充电时间两个特征因子作为排序指标，在出现两个因子不可比的情况时，无法得出一个有效的排序。另外，该文献也是通过电价间接考虑了新能源发电与电动汽车充电之间的供需匹配关系，也存在电价对于新能源发电供给波动的反应存在滞后。
相关技术三，针对共享电动汽车充电调度优化问题，提出了一种基于剩余电量排序的充电调度优化方法：剩余电量越低的电动汽车优先安排充电，剩余电量越高的电动汽车优先安排载客，在每个决策时刻通过枚举的方式确定具体的电动汽车充电数量和载客车数量。利用上述方式减小求解问题的难度，实现对电动汽车充电调度的优化。
但其提出了利用电动汽车的剩余电量作为排序指标，需要通过枚举的方式确定具体的充电及载客车的数量，且未利用新能源发电信息作为决策辅助，使得该方法不能很好地实现电动汽车充电与新能源发电之间的供需匹配。
发明内容
本发明旨在至少在一定程度上解决相关技术中的技术问题之一。
为此，本发明的一个目的在于提出一种电动汽车充电与新能源发电的协同调度方法，该方法求解简单，只需计算指标值并排序，即可得出明确的充电策略。
本发明的另一个目的在于提出一种电动汽车充电与新能源发电的协同调度装置。
为达到上述目的，本发明一方面实施例提出了电动汽车充电与新能源发电的协同调度方法，包括以下步骤：步骤S1，获取当前时段的新能源发电信息和电动汽车的充电功率，以确定利用新能源发电进行充电的电动汽车数量；步骤S2，获取电动汽车指标因子，对所述电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量；步骤S3，判断所述利用新能源发电进行充电的电动汽车数量是否不小于所述必须充电的电动汽车数量，若是，则依据所述电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车 充电；步骤S4，判断所述当前时段是否超过预设时间段，若不超过，则跳转至步骤S1，直至超过所述预设时间段结束循环。
本发明实施例的电动汽车充电与新能源发电的协同调度方法，求解简单，能够满足大规模和实时性的要求；可直接利用新能源发电信息作为决策信息，能够更好地实现对新能源发电的利用；对指标值进行全序排序，能够保证获得求解策略，避免了不可比的情况。
另外，根据本发明上述实施例的电动汽车充电与新能源发电的协同调度方法还可以具有以下附加的技术特征：
进一步地，在本发明的一个实施例中，所述电动汽车指标因子包括电量、剩余充电时间和剩余停车时间。
进一步地，在本发明的一个实施例中，所述步骤S2进一步包括：根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；将所述处于停车状态的电动汽车计算指标值进行排列，得到电动汽车充电优先级序列。
进一步地，在本发明的一个实施例中，将所述处于停车状态的电动汽车计算指标值进行排列包括但不限于如下方法：冒泡排序法、选择排序法、插入排序法和归并排序法。
进一步地，在本发明的一个实施例中，所述依据所述电动汽车充电优先级序列对电动汽车充电，包括：先利用新能源发电给必须充电的电动汽车充电；当所述必须充电的电动汽车充电完成后，若新能源发电量仍有剩余，则依据所述电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
为达到上述目的，本发明另一方面实施例提出了电动汽车充电与新能源发电的协同调度装置，包括：确定模块，用于获取当前时段的能源发电信息和电动汽车的充电功率，确定利用新能源发电进行充电的电动汽车数量；获取序列模块，用于获取电动汽车指标因子，并对所述电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量；判断模块，用于判断所述利用新能源发电进行充电的电动汽车数量是否不小于所述必须充电的电动汽车数量，若是，则依据所述电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电；循环模块，用于判断所述当前时段是否超过预设时间段，若不超过，则跳转至确定模块重新调度，直至超过所述预设时间段结束循环。
本发明实施例的电动汽车充电与新能源发电的协同调度装置，求解简单，能够满足大规模和实时性的要求；可直接利用新能源发电信息作为决策信息，能够更好地实现对新能源发电的利用；对指标值进行全序排序，能够保证获得求解策略，避免了不可比的情况。
另外，根据本发明上述实施例的电动汽车充电与新能源发电的协同调度装置还可以具有以下附加的技术特征：
进一步地，在本发明的一个实施例中，所述电动汽车指标因子包括电量、剩余充电时间和剩余停车时间。
进一步地，在本发明的一个实施例中，所述获取序列模块包括：
指标计算模块，用于根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；
排序模块，用于将所述处于停车状态的电动汽车计算指标值进行排列，得到电动汽车充电优先级序列。
进一步地，在本发明的一个实施例中，将所述处于停车状态的电动汽车计算指标值进行排列包括但不限于如下方法：冒泡排序法、选择排序法、插入排序法和归并排序法。
进一步地，在本发明的一个实施例中，所述判断模块具体用于：先利用新能源发电给必须充电的电动汽车充电；当所述必须充电的电动汽车充电完成，新能源发电量仍有剩余，则依据所述电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
本发明附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实践了解到。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。在附图中：
图1为根据本发明一个实施例的电动汽车充电与新能源发电的协同调度方法流程图；
图2为根据本发明一个实施例的电动汽车充电与新能源发电的协同调度装置结构示意图。
具体实施方式
下面详细描述本发明的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本发明，而不能理解为对本发明的限制。
下面参照附图描述根据本发明实施例提出的电动汽车充电与新能源发电的协同调度方法及装置，首先将参照附图描述根据本发明实施例提出的电动汽车充电与新能源发电的协同调度方法。
图1是本发明一个实施例的电动汽车充电与新能源发电的协同调度方法流程图。
如图1所示，该电动汽车充电与新能源发电的协同调度方法包括以下步骤：
在步骤S1中，获取当前时段的新能源发电信息和电动汽车的充电功率，以确定利用新能源发电进行充电的电动汽车数量。
例如，从t＝0时段开始，优化t∈[0,T]时段内的充电调度策略，对当前时段t，获得实时新能源发电信息，结合电动汽车的充电功率P e确定可以利用新能源发电进行充电的电动汽车数量K。
在步骤S2中，获取电动汽车指标因子，对电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量。
其中，电动汽车指标因子可以包括电量、剩余充电时间和剩余停车时间等指标。
具体而言，获取电动汽车的电量B i、剩余充电时间β i、剩余停车时间α i，i＝1,2,...,N(其中，i表示电动汽车的编号，N是处于停车状态的电动汽车总数量)等指标。
进一步地，在本发明的一个实施例中，步骤S2进一步包括：
根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；
将处于停车状态的电动汽车计算指标值进行排列，得到电动汽车充电优先级序列。
也就是说，依据排序指标值方程R(B i,β i,α i)，i＝1,2,...,N，对处于停车状态的电动汽车计算指标值。
I i＝R(B i,β i,α i)＝aB i+bβ i+cα i+d
其中，a,b,c,d是权重因子。
同时，确定当前时段必须充电的电动汽车集合Φ＝{i|β i＞α i,i＝1,2,...,N}。
再将I i，i＝1,2,...,N从大到小排序，得到序列S＝[I [1],I [2],L,I [N]]，其中，I [j]表示排名第j大的指标值，[j]表示该辆电动汽车的编号。由此得到充电优先级序列Prio＝[[1],[2],…[N]]。
需要说明的是，排序方式还可以利用相同的指标，利用不同排序方法，比如冒泡排序、选择排序、插入排序、归并排序等排序方法，获得排序，或是利用由不同指标或权重进行计算，也可能获得同样的排序。
在步骤S3中，判断利用新能源发电进行充电的电动汽车数量是否不小于必须充电的电动汽车数量，若是，则依据电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电。
进一步地，在本发明的一个实施例中，依据电动汽车充电优先级序列对电动汽车充电，包括：
先利用新能源发电给必须充电的电动汽车充电；
当必须充电的电动汽车充电完成后，若新能源发电量仍有剩余，则依据电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
具体而言，步骤S2之后进行判断，当K≥|Φ|(|Φ|表示Φ集合的大小，即必须充电的电动汽车数量)时，先利用新能源发电给Φ内的电动汽车充电；若新能源发电量仍有剩余，则依据电动汽充电优先级序列Prio＝[[1],[2],…[N]]对剩余电动汽车充电，直至新能源发电用完为止。当K＜|Φ|时，则除利用新能源发电对电动汽车充电外，需补充购买市电以满足所有Φ内的电动汽车充电需求。
在步骤S4中，判断当前时段是否超过预设时间段，若不超过，则跳转至步骤S1，直至超过预设时间段结束循环。
最后，令t＝t+1，到下一时段，若t＞T，结束；否则，跳转至步骤S1。
根据本发明实施例提出的电动汽车充电与新能源发电的协同调度方法，求解简单，能够满足大规模和实时性的要求，只需计算指标值并排序，即可得出明确的充电策略，求解复杂度为N log N，步骤简单，求解效率高；可直接利用新能源发电信息作为决策信息，能够更好地实现对新能源发电的利用，相比于相关技术一和相关技术二利用电价作为决策信息，能够有效避免电价对于发电量变化的延迟性；避免不可比的情 况，对指标值进行全序排序，相比于相关技术二中所提出的偏序排序方法，该方法能够保证获得求解策略，避免了不可比的情况。
其次参照附图描述根据本发明实施例提出的电动汽车充电与新能源发电的协同调度装置。
图2是本发明一个实施例的电动汽车充电与新能源发电的协同调度装置结构示意图。
如图2所示，该装置10包括：确定模块100、获取序列模块200、判断模块300和循环模块400。
其中，确定模块100用于获取当前时段的新能源发电信息和电动汽车的充电功率，确定利用新能源发电进行充电的电动汽车数量。获取序列模块200用于获取电动汽车指标因子，对电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量。判断模块300用于判断偏充电的电动汽车数量是否不小于必须充电的电动汽车数量，若是，则依据电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电。循环模块400用于判断当前时段是否超过预设时间段，若不超过，则跳转至确定模块重新调度，直至超过预设时间段结束循环。
进一步地，在本发明的一个实施例中，电动汽车指标因子包括：电量、剩余充电时间和剩余停车时间。
进一步地，在本发明的一个实施例中，获取序列模块进一步包括：
指标计算模块，用于根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；
排序模块，用于将处于停车状态的电动汽车计算指标值进行排列，得到充电优先级序列。
进一步地，在本发明的一个实施例中，将所述处于停车状态的电动汽车计算指标值进行排列包括：冒泡排序法、选择排序法、插入排序法和归并排序法等排序方法。
进一步地，在本发明的一个实施例中，若判断模块判断所述利用新能源发电进行充电的电动汽车数量不小于所述必须充电的电动汽车数量，则依据电动汽车充电优先级序列对电动汽车充电具体包括：先利用新能源发电给必须充电的电动汽车充电；当必须充电的电动汽车充电完成，新能源发电量仍有剩余，则依据电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
根据本发明实施例提出的电动汽车充电与新能源发电的协同调度装置，求解简单，能够满足大规模和实时性的要求；可直接利用新能源发电信息作为决策信息，能够更好地实现对新能源发电的利用；对指标值进行全序排序，能够保证获得求解策略，避免了不可比的情况。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本发明的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (10)

  1. 一种电动汽车充电与新能源发电的协同调度方法，其特征在于，包括以下步骤：
    步骤S1，获取当前时段的新能源发电信息和电动汽车的充电功率，以确定利用新能源发电进行充电的电动汽车数量；
    步骤S2，获取电动汽车指标因子，对所述电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量；
    步骤S3，判断所述利用新能源发电进行充电的电动汽车数量是否不小于所述必须充电的电动汽车数量，若是，则依据所述电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电；
    步骤S4，判断所述当前时段是否超过预设时间段，若不超过，则跳转至步骤S1，直至超过所述预设时间段结束循环。
  2. 根据权利要求1所述的电动汽车充电与新能源发电的协同调度方法，其特征在于，所述电动汽车指标因子包括：电量、剩余充电时间和剩余停车时间。
  3. 根据权利要求1所述的电动汽车充电与新能源发电的协同调度方法，其特征在于，所述步骤S2进一步包括：
    根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；
    将所述处于停车状态的电动汽车计算指标值进行排列，得到电动汽车充电优先级序列。
  4. 根据权利要求3所述的电动汽车充电与新能源发电的协同调度方法，其特征在于，将所述处于停车状态的电动汽车计算指标值进行排列包括但不限于如下方法：冒泡排序法、选择排序法、插入排序法和归并排序法。
  5. 根据权利要求1所述的电动汽车充电与新能源发电的协同调度方法，其特征在于，所述依据所述电动汽车充电优先级序列对电动汽车充电，包括：
    先利用新能源发电给必须充电的电动汽车充电；
    当所述必须充电的电动汽车充电完成后，若新能源发电量仍有剩余，则依据所述电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
  6. 一种电动汽车充电与新能源发电的协同调度装置，其特征在于，包括：
    确定模块，用于获取当前时段的新能源发电信息和电动汽车的充电功率，确定利用新能源发电进行充电的电动汽车数量；
    获取序列模块，用于获取电动汽车指标因子，对所述电动汽车指标因子进行排序，获得电动汽车充电优先级序列，并确定当前时段必须充电的电动汽车数量；
    判断模块，用于判断所述利用新能源发电进行充电的电动汽车数量是否不小于所述必须充电的电动汽车数量，若是，则依据所述电动汽车充电优先级序列对电动汽车充电，直至新能源发电用尽，若不是，则购买市电为必须充电的电动汽车充电；
    循环模块，用于判断所述当前时段是否超过预设时间段，若不超过，则跳转至确定模块重新调度，直至超过所述预设时间段结束循环。
  7. 根据权利要求6所述的电动汽车充电与新能源发电的协同调度装置，其特征在于，所述电动汽车指标因子包括：电量、剩余充电时间和剩余停车时间。
  8. 根据权利要求6所述的电动汽车充电与新能源发电的协同调度装置，其特征在于，所述获取序列模块包括：
    指标计算模块，用于根据电动汽车的电量、剩余充电时间和剩余停车时间构建排序指标值方程，计算得到处于停车状态的电动汽车计算指标值；
    排序模块，用于将所述处于停车状态的电动汽车计算指标值进行排列，得到电动汽车充电优先级序列。
  9. 根据权利要求8所述的电动汽车充电与新能源发电的协同调度装置，其特征在于，将所述处于停车状态的电动汽车计算指标值进行排列包括但不限于如下方法：冒泡排序法、选择排序法、插入排序法和归并排序法。
  10. 根据权利要求6所述的电动汽车充电与新能源发电的协同调度装置，其特征在于，所述判断模块具体用于：先利用新能源发电给必须充电的电动汽车充电；当所述必须充电的电动汽车充电完成，新能源发电量仍有剩余，则依据所述电动汽车充电优先级序列对剩余电动汽车充电，直至新能源发电用尽。
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