CN111489009B - An optimization calculation method and device for the operation mode of an electric vehicle charging station - Google Patents
An optimization calculation method and device for the operation mode of an electric vehicle charging station Download PDFInfo
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Abstract
本发明涉及电力系统技术领域，特别是一种电动汽车充电站运行方式的优化计算方法。本发明包括：电动汽车充电站柔性控制方式建模；考虑电动汽车充电站与可再生能源消纳的电力系统优化建模；电动汽车电池充放电功率及补偿成本优化计算。本发明在保证调度周期内用电量不变的前提下，通过充放电功率转移，实现对电动汽车充电站的优化控制，有效减少可再生能源弃电量。本发明综合考虑电动汽车充电站用电量约束、用电功率爬坡约束建模、储能荷电状态SOC约束、电力系统负荷平衡约束和联络线注入功率约束等因素，计算结果更加符合实际电力系统调度情况，能够为调度员提供最直观的判断依据。
The invention relates to the technical field of power systems, in particular to an optimization calculation method for the operation mode of an electric vehicle charging station. The invention includes: modeling of the flexible control mode of the electric vehicle charging station; power system optimization modeling considering the electric vehicle charging station and renewable energy consumption; electric vehicle battery charging and discharging power and compensation cost optimization calculation. Under the premise of ensuring that the power consumption in the dispatching period remains unchanged, the invention realizes the optimal control of the electric vehicle charging station through the transfer of charging and discharging power, and effectively reduces the power waste of renewable energy sources. The invention comprehensively considers factors such as electric vehicle charging station power consumption constraints, electric power climbing constraint modeling, energy storage state of charge SOC constraints, power system load balance constraints, tie line injection power constraints and other factors, and the calculation results are more in line with the actual power system scheduling situation, and can provide the most intuitive judgment basis for dispatchers.
Description
Technical Field
The invention relates to the technical field of electric power systems, in particular to an optimization calculation method and device for an electric vehicle charging station operation mode.
Background
Under the double crisis of fossil energy and environmental pollution, the powerful development and utilization of renewable energy is an effective way to solve this problem. The invention mainly refers to wind power and solar power generation, and the dispatching operation of a traditional distribution network can be greatly influenced under the condition of large-scale renewable energy power generation grid connection. With the improvement of battery energy storage technology, electric vehicles are widely popularized, and the load side can also show flexible characteristics to participate in power system dispatching, so that the electric vehicles become an important means for promoting renewable energy consumption, realizing peak clipping and valley filling and improving flexibility adjustment of a power distribution network.
In the current stage, the popularization of electric vehicles is greatly promoted by China, the sales of electric vehicles in China continuously increase from 2012 to 2016, the sales of electric vehicles in 2016 reach 23.32 ten thousand, and the pure electric vehicles use electric power as driving force, so that the dependence of the traditional fuel oil vehicles on fossil energy is reduced. It is found that the electric vehicles of users are in a parked state 90% of the time, and the mobile distributed energy storage potential of the electric vehicles is very large. The charging power of a single electric automobile is smaller, and the electric automobile charging station is generally adopted for unified management of charging and discharging of the electric automobile, so that ordered charging and discharging of the electric automobile are realized. After the electric vehicle charging station receives a control command issued by the power grid, the number of the current electric vehicle charging stations and the SOC value of each electric vehicle are collected, and the charging power of each electric vehicle is obtained through optimization calculation, so that the load power is increased and reduced.
The related researches on the running mode of the current electric vehicle charging station mainly focus on the control mode research as the controllable flexible load, and the research result does not accord with the actual power system scheduling condition, so that effective basis can not be provided for power system scheduling operators.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an optimization calculation method and device for the operation mode of an electric vehicle charging station, wherein the electric vehicle charging station is used as a controllable flexible load to participate in power grid optimization scheduling, the operation scheme of the electric vehicle charging station is determined and coordinated under the constraint conditions of operation safety of an electric power system and stable operation of the electric vehicle charging station on the premise of knowing renewable energy sources and load predicted values, and the aim of the maximum consumption of renewable energy sources is achieved by actively matching the controllable flexible load with the power grid on the basis of meeting the load power requirements. The invention quantifies the relation between the overall charge and discharge power of the electric vehicle charging station and the charge and discharge power of a single electric vehicle, and realizes the optimization calculation of the charge and discharge power of the electric vehicle battery and the compensation cost.
Based on the above object, the present invention is achieved by the following technical scheme:
in a first aspect, the present invention provides a method for optimizing the operation mode of an electric vehicle charging station, comprising the following steps:
determining an electric vehicle SOC value which is expected to be reached when the electric vehicle charging is finished according to a predetermined charge-discharge power relation in a preset period of the electric vehicle charging station, an electric power climbing constraint for the electric vehicle charging station and an energy storage charge state SOC relation between the electric vehicle charging station and the electric vehicle;
calculating to obtain the charging power of the electric vehicle charging station of each time section according to the expected electric vehicle SOC value and a power system model of the electric vehicle charging station and renewable energy source consumption, which is constructed in advance; the electric system model for the electric vehicle charging station and the renewable energy source absorption aims at taking the electric vehicle charging station as a controllable flexible load and maximizing the renewable energy source generating capacity;
and calculating the charging and discharging power of the electric vehicle battery and the compensation cost according to the charging power of the electric vehicle charging station of each time section.
The determining the charge-discharge power relationship in the preset period of the electric vehicle charging station comprises the following steps: modeling the electricity consumption of an electric vehicle charging station, wherein the electric vehicle charging station is used as a transferable load model, and the total electricity consumption of the electric vehicle charging station before and after transferring the charging power is consistent, and the electricity consumption is shown in a formula (1):
in the method, in the process of the invention,representing a charging power of the electric vehicle charging station in response to the previous t moment;Electric steam for indicating t moment after responseThe electric power of the vehicle charging station;The charging power of the electric vehicle charging station at the time t;The discharge power of the electric vehicle charging station at the time t; t is the calculated period length.
The determining an electric power ramp constraint for an electric vehicle charging station includes: modeling an electric vehicle charging station by using electric power climbing constraint, wherein the fluctuation of charging power of the electric vehicle charging station is kept in an acceptance range, and the formula (2):
in the method, in the process of the invention,the maximum value of the power that can be used for climbing up and down in 1 scheduling period is represented as the transferable load of the electric vehicle charging station.
The determining the energy storage state of charge (SOC) relationship between the electric vehicle charging station and the electric vehicle includes:
electric vehicle charging station energy storage state of charge SOC modeling, an electric vehicle charging station SOC calculation formula is shown as a formula (3) and is expressed as a current energy storage electric quantity E rem Can store the maximum electric quantity E with the energy storage battery max Ratio of; the charging and discharging power and the SOC of the electric automobile which are flexibly controlled in the charging period meet the formula (4); the relation between the SOC of the electric vehicle charging station and the SOC of each electric vehicle at the time 0 and the time T is shown in formulas (5) and (6):
wherein, SOC (0) is the SOC value of initial charge of the electric automobile; SOC (T) is the SOC value that the user is expected to reach at the end of charging; Δt is 1 scheduling period; SOC (State of Charge) i The energy storage charge state of the ith electric automobile;the battery for the i-th electric automobile can store the maximum amount of electricity.
The establishment process of the electric vehicle charging station and the renewable energy source-consumed electric power system model comprises the following steps:
establishing an electric power system optimization calculation objective function considering electric vehicle charging station and renewable energy consumption;
determining constraints of the objective function, the constraints comprising: load balancing constraints and tie injection power upper and lower limits constraints.
The objective function is shown in formula (7):
wherein P is w (t) wind power output at time t, P pv And (t) is the power generated by solar energy at the moment t.
The load balancing constraint is shown in formula (8):
wherein P is PCC (t) active power is injected into the contact line at the moment t, P l (t) is the load electric power at time t;charging power for an electric vehicle charging station for each time section;
the tie line is injected with upper and lower limit constraints of power, and the upper and lower limit constraints are shown in a formula (9):
P PCC,min ≤P PCC (t)≤P PCC,max (9)。
according to the charging power of the electric vehicle charging station of each time section, the charging and discharging power of the electric vehicle battery and the compensation cost are calculated, and the method comprises the following steps:
according to the expected electric automobile SOC value, the calling power of the ith electric automobile at the time t is shown in a formula (10):
in the above formula:for the energy storage charge state before the i-th electric automobile t moment is called,/or%>The energy storage charge state after the i-th electric automobile t time is called is +.>The battery of the ith electric automobile can store the maximum electric quantity;The power is called at the t moment of the ith electric automobile;
calculating the call compensation cost of the ith electric automobile according to the following formulaSee (11):
in the method, in the process of the invention,the cost is compensated for the unit capacity of the ith electric car.
In a second aspect, the present invention provides an optimization computing device for an electric vehicle charging station operation mode, including:
a memory for storing a computer program;
the method for executing the computer program for implementing the optimized calculation of the electric vehicle charging station operating mode described above.
In a third aspect, the present invention provides a computer storage medium having a computer program stored thereon, which when executed by a processor, implements the steps of the method for optimizing the operation of an electric vehicle charging station as described above.
The invention has the following advantages and beneficial effects:
1. the invention provides an optimal calculation method, device and computer storage medium for an operation mode of an electric vehicle charging station, which are used for optimally modeling the schedulability of the electric vehicle charging station, and realizing optimal control of the electric vehicle charging station through charge and discharge power transfer on the premise of ensuring that the power consumption is unchanged in a scheduling period, so that the renewable energy waste power is effectively reduced.
2. In the process of optimally calculating the combined operation of the electric vehicle charging station and the renewable energy power generation, the factors such as the electric quantity constraint of the electric vehicle charging station, the power consumption climbing constraint modeling, the energy storage charge state SOC constraint, the power system load balance constraint and the tie line injection power constraint are comprehensively considered, the calculation result is more in line with the actual power system scheduling condition, and the most visual judgment basis can be provided for power system scheduling operators.
Drawings
In order to facilitate the understanding and practice of the invention, those of ordinary skill in the art will now make further details with reference to the drawings and detailed description, it being understood that the scope of the invention is not limited to the specific description.
Fig. 1 is a flowchart of the optimization calculation of the operation mode of the electric vehicle charging station according to the invention.
Detailed Description
The invention relates to an optimization calculation method, a device and a computer storage medium for an operation mode of an electric vehicle charging station. The constraint condition of the control model of the electric vehicle charging station comprises electricity consumption constraint, climbing power constraint and energy storage charge state constraint, and the single electric vehicle invoking compensation cost is calculated based on invoking power every moment.
Example 1
The method specifically comprises the following steps:
step 1: determining an electric vehicle SOC value which is expected to be reached when the electric vehicle charging is finished according to a predetermined charge-discharge power relation in a preset period of the electric vehicle charging station, an electric power climbing constraint for the electric vehicle charging station and an energy storage charge state SOC relation between the electric vehicle charging station and the electric vehicle;
step 2: calculating to obtain the charging power of the electric vehicle charging station of each time section according to the expected electric vehicle SOC value and a power system model of the electric vehicle charging station and renewable energy source consumption, which is constructed in advance; the electric system model for the electric vehicle charging station and the renewable energy source absorption aims at taking the electric vehicle charging station as a controllable flexible load and maximizing the renewable energy source generating capacity;
step 3: and calculating the charging and discharging power of the electric vehicle battery and the compensation cost according to the charging power of the electric vehicle charging station of each time section.
Example 2
The following describes a specific implementation procedure of the present invention in conjunction with the optimization calculation flowchart of the electric vehicle charging station operation mode of fig. 1.
In the step 1, determining a charging and discharging power relationship in a preset period of the electric vehicle charging station includes:
step 1-1: modeling the electricity consumption of an electric vehicle charging station, wherein the electric vehicle charging station is used as a transferable load model, and the total electricity consumption of the electric vehicle charging station before and after transferring the charging power is consistent, and the electricity consumption is shown in a formula (1):
in the method, in the process of the invention,representing a charging power of the electric vehicle charging station in response to the previous t moment;Representing the electric power of the electric vehicle charging station at the time t after the response;The charging power of the electric vehicle charging station at the time t;The discharge power of the electric vehicle charging station at the time t; t is the calculated period length.
Step 1-2: determining an electric power hill climbing constraint for an electric vehicle charging station, comprising: modeling an electric vehicle charging station with an electric power climbing constraint, wherein the electric vehicle charging station charging power fluctuation is kept within an acceptable range, as shown in formula (2):
in the method, in the process of the invention,the maximum value of the power that can be used for ascending and descending the slope in 1 scheduling period is respectively indicated as the transferable load of the electric vehicle charging station, and the time length of 1 scheduling period is usually 15 minutes.
Step 1-3: determining an energy storage state of charge, SOC, relationship of an electric vehicle charging station to an electric vehicle, comprising: electric vehicle charging station energy storage state of charge SOC modeling, an electric vehicle charging station SOC calculation formula is shown as a formula (3) and is expressed as a current energy storage electric quantity E rem Can store the maximum electric quantity E with the energy storage battery max Ratio of the two components. And (3) the charging and discharging power and the SOC of the electric automobile which are flexibly controlled in the charging period meet the formula (4). The relation between the SOC of the electric vehicle charging station and the SOC of each electric vehicle at the time 0 and the time T is shown in formulas (5) and (6).
Wherein, SOC (0) is the SOC value of initial charge of the electric automobile; SOC (T) is the SOC value that the user is expected to reach at the end of charging; Δt is 1 scheduling period; SOC (State of Charge) i The energy storage charge state of the ith electric automobile;the battery for the i-th electric automobile can store the maximum amount of electricity.
The establishing process of the electric vehicle charging station and the renewable energy source consumption electric power system model in the step 2 comprises the following steps: establishing an electric power system optimization calculation objective function considering electric vehicle charging station and renewable energy consumption; determining constraints of the objective function, the constraints comprising: load balancing constraint and tie line injection power upper and lower limit constraint; and calculating the charging power of the electric vehicle charging station of each time section.
Step 2-1: establishing an electric power system optimization calculation objective function considering electric vehicle charging stations and renewable energy consumption, and determining constraint conditions of the objective function, wherein the constraint conditions comprise: load balancing constraints and tie injection power upper and lower limits constraints.
Electric vehicle charging station charging power calculation for each time sectionMaximizing the energy generation capacity of renewable energy sources in a calculation period, wherein the objective function is shown in a formula (7).
Wherein P is w (t) wind power output at time t, P pv And (t) is the power generated by solar energy at the moment t.
Step 2-2: the load balance constraint is shown in the formula (8).
Wherein P is PCC (t) active power is injected into the contact line at the moment t, P l (t) is the load electric power at time t,charging power for electric vehicle charging stations for each time section.
Step 2-3: the upper and lower limits of the power of the tie line injection are restricted, and the tie line injection is shown in a formula (9).
P PCC,min ≤P PCC (t)≤P PCC,max (9)
Step 2-4: finally, optimizing and calculating to obtain the charging power of the electric vehicle charging station of each time section by adopting the mathematical model established by the novel methodAt the moment, the optimal operation of renewable energy power generation and charging and discharging of the electric vehicle charging station is realized, and the maximum renewable energy power generation is realized.
The step 3: according to the electric vehicle charging station charging power of each time section, electric vehicle battery charging and discharging power and compensation cost are calculated, including:
step 3-1: and (3) calculating the call power of the ith electric vehicle at the time t according to the SOC value of the electric vehicle calculated in the step (1), wherein the call power is shown in a formula (10).
In the above formula:for the energy storage charge state before the i-th electric automobile t moment is called,/or%>The energy storage charge state after the i-th electric automobile t time is called is +.>The battery of the ith electric automobile can store the maximum electric quantity;and (5) calling power at the t moment of the ith electric automobile.
Step 3-2: calculating the call compensation cost of the ith electric automobile according to the following formulaSee formula (11).
In the method, in the process of the invention,the cost is compensated for the unit capacity of the ith electric car.
Example 3
Based on the same inventive concept, the embodiment of the invention also provides an optimization computing device of the running mode of the electric vehicle charging station, the principle of solving the technical problem is similar to that of the optimization computing method of the running mode of the electric vehicle charging station, and the repetition is omitted.
The optimization computing device of the operation mode of the electric vehicle charging station comprises:
a memory for storing a computer program;
the computer program is used for executing the optimization calculation method for the operation mode of the electric vehicle charging station in the embodiment 1 or 2.
Example 4
Based on the same inventive concept, the embodiment of the present invention further provides a computer storage medium, where a computer program is stored, where the computer program when executed by a processor implements the steps of the method for optimizing the operation mode of the electric vehicle charging station described in embodiment 1 or 2.
Embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to imply that the scope of the disclosure, including the claims, is limited to such examples; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the invention, the steps may be implemented in any order and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the present invention should be included in the scope of the present invention.
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| CN114759580B (en) * | 2022-05-17 | 2026-02-03 | 河海大学 | Method, system and storage medium for handling tight balance of power system |
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| GB0823447D0 (en) * | 2007-12-24 | 2009-01-28 | Mayer Yaron | System and method for improved electric cars and/or electric car batteries and/or improved infrastructures for recharging electric cars |
| CN108133285A (en) * | 2017-12-21 | 2018-06-08 | 南京工程学院 | A kind of energy mix system real-time scheduling method for accessing extensive regenerative resource |
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