CN115239065A - Operation planning method, system and equipment for multi-type charging and discharging piles in area - Google Patents
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Abstract
An operation planning method, a system and equipment for multi-type charging and discharging piles in an area comprise the following steps: respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the area at the appointed time into a pre-constructed quantity and time and power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at the set time; obtaining an operation planning scheme of each type of charging pile at a set moment based on the relation between the number and power of the charging piles at the set moment and a set minimum limiting condition; the quantity and time and power and time logistic models are constructed based on the quantity of the charging piles of various types with fitting correlation at each moment, and the maximum growth rate of the quantity and the power obtained by fitting the charging power by using an exponential model respectively and combining with a logistic equation. The invention adopts a logistic model of quantity and time and power and time to carry out charging operation planning, and can realize dynamic charging planning of various charging piles.
Description
Technical Field
The invention relates to the field of new energy charging, in particular to a method, a system and equipment for planning the operation of various types of charging and discharging piles in an area.
Background
The assistance force achieves the aim of 'double carbon', the new energy automobile becomes an important means for green and clean travel of the country, and the charging infrastructure becomes one of important contents of new national infrastructure. Charging facilities are an important foundation for the development of new energy automobiles, and in recent years, with the rapid increase of the sales volume of new energy automobiles, matched charging facilities are also invested and built on a large scale. In order to improve charging safety, improve loading capacity of a power grid and slow down investment speed of upgrading and reconstruction of the power grid, a new mode comprising ordered charging and vehicle-grid interactive charging (V2G) is advocated vigorously by China. The orderly charging control of the electric automobile guides a user to charge at the valley price time period of a non-power grid load peak, and the charging control system can guide the charging time period of the electric automobile to be reasonably arranged to charge at the non-load peak time period through charging effective regulation and guidance, so that the charging cost of the user can be greatly saved, the number of the vehicles which can be connected into a platform area can be effectively increased, and the charging requirements of more vehicles can be met. The V2G charging technology is characterized in that an electric automobile is used as a mobile energy storage device, the idle time of the electric automobile is fully utilized, electric quantity is stored in the electricity consumption valley period, and then electric power is transmitted to a power grid in the electricity consumption peak period, so that not only can the charging cost of a user be saved, but also a certain discharging benefit can be obtained, and meanwhile, a power is contributed to the safe and reliable operation of the power grid.
The Logistic function is a theoretical model evolved from the ecological population growth problem, and is then developed into a basic principle for more widely describing the dynamic property of a nonlinear system. The model may be used to describe the logical relationship of the study living space to the available resources. In nature, the development of organisms, including individuals and populations, goes through a process from slow to fast and then from prosperous to smooth or decaying, the middle stage is the peak stage of development, the growth speed is the most rapid, and then the growth speed is changed from fast to slow due to the limitation of environmental pressure, so that an S-shaped change curve of the density of the biological populations along with time is formed, and the change curve also exists for the volume and weight changes of the organisms.
According to the current technical scheme and documents, a logistic model is mainly used for planning the construction of charging facilities and the prediction of charging behaviors, and aiming at the operation of a charging pile, the 'electric vehicle charging behavior prediction method based on internet data' in the patent predicts the probability situation of the charging behaviors by adopting the logistic model, however, for the problem of dynamic charging planning, no relevant model is applied to the multi-type and multi-mode charging operation planning.
Disclosure of Invention
In order to solve the problem that the operation of charging piles in the prior art is only limited to the probability condition of predicting charging behaviors and cannot solve the dynamic charging planning, the invention provides an operation planning method for various types of charging and discharging piles in an area, which comprises the following steps:
respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the area at a specified time into a pre-constructed quantity and time logistic model and a power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at a set time;
obtaining an operation planning scheme of each type of charging pile at a set moment based on the relation between the number and power of the charging piles at the set moment and a set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively.
Optionally, the constructing of the pre-constructed quantity and time logistic model and the power and time logistic model includes:
the method comprises the steps that the using quantity and power of charging piles of various types with fitting correlation at each moment in a set time period are fitted respectively by an exponential model to obtain the maximum increasing rate of quantity and the maximum increasing rate of power;
and respectively substituting the maximum growth rate of the quantity and the maximum growth rate of the power into a logistic equation to obtain a logistic model of the quantity and the time and a logistic model of the power and the time.
Optionally, the logistic model of the quantity and time is shown as the following formula:
N i (t)＝K i N 0 e at /(K i +N 0 (1+e at ))；
wherein a is the maximum growth rate of the quantity; k i A maximum environmental capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of hydrogen i (t) the using quantity of the charging piles at the moment t; n is a radical of hydrogen 0 Is t 0 The quantity of the used charging piles at all times.
Optionally, the logistic model of power versus time is shown as follows:
P j (t)＝K j P 0 e bt /(K j +P 0 (1+e bt ))；
wherein b is the maximum rate of increase of power; k j A maximum environmental capacity value for power; p j (t) is the power at time t; p 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
Optionally, before the step of fitting the maximum increase rate of the number and the maximum increase rate of the power obtained by respectively adopting an exponential model to fit the usage number and the power of the charging piles of each type having the fitting correlation at each time within a set time period, the method further includes:
and judging the use quantity and time of the charging piles at each moment in a set time period and the fitting correlation between the power and the time.
Optionally, the determining of the number of charging piles and the time of charging piles at each moment in the set time period and the fitting correlation between power and time includes:
acquiring the using quantity and charging power of each type of charging pile at each moment in a set time period;
taking the maximum value of the using quantity of the electric piles in a set time period as the environmental capacity of the quantity, and taking the maximum value of the charging power in the set time period as the environmental capacity of the power;
combining the environmental capacity of the quantity and the charging pile usage quantity at the initial moment in a set time period with a decision coefficient calculation formula to obtain a decision coefficient of the quantity and the time, wherein when the decision coefficient of the quantity and the time is larger than a set threshold value, the charging pile usage quantity and the time at each moment have fitting correlation;
and combining the environmental capacity of the power and the power value of the initial moment in the set time period with a decision coefficient calculation formula to obtain a decision coefficient of the power and the time, wherein when the decision coefficient of the power and the time is greater than a set threshold value, the charging pile has fitting correlation between the power value and the time at each moment.
Optionally, the decision coefficient calculation formula is as follows:
in the formula, R 2 To determine the coefficients; x is K and 2N 0 The natural logarithm of the ratio; k is the maximum environmental capacity; n is a radical of 0 Is t 0 Number of objects at the moment.
Optionally, the set minimum limiting condition includes a minimum time of use.
Optionally, the obtaining of the operation planning scheme of each type of charging pile at the set time based on the relationship between the number and power of the charging piles at the set time and the set minimum limiting condition includes:
calculating an inverse function of the using quantity of each type of charging pile at a set moment and an inverse function of power, and selecting a minimum value from the inverse functions;
judging that the minimum value meets the minimum time, and if the minimum value meets the minimum time, taking the use quantity and power of all types of charging piles at a set time as an operation planning scheme of each type of charging pile at the set time;
otherwise, adjusting the charging mode of each type of charging pile to enable the using quantity and the power of each type of charging pile at the set moment to meet the set minimum time;
wherein all types of charging piles at least comprise one or more of the following: fill electric pile, unordered electric pile and the electric pile of V2G in order.
Optionally, the charging mode of each type of charging pile includes: independent operation and cooperative operation of various types of charging piles;
the cooperative operation of the charging piles of various types comprises the following steps: unordered electric pile and the orderly electric pile that fills move in coordination, fill electric pile and V2G in coordination and unordered electric pile and V2G fill electric pile in coordination.
In another aspect, the present invention further provides a system for planning operations of multiple types of charging and discharging piles in an area, including:
the calculation module is used for respectively inputting the acquired charging pile usage number and charging power of each type of charging pile in the area at the specified time into a pre-constructed quantity and time logistic model and a pre-constructed power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at the set time;
the planning module is used for obtaining an operation planning scheme of each type of charging pile at the set time based on the relation between the number and power of the charging piles at the set time and the set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively.
Optionally, the system further comprises a building module for:
the method comprises the steps that the number and power of charging piles of various types with fitting correlation at each moment in a set time period are fitted respectively by an exponential model to obtain the maximum increase rate of the number and the maximum increase rate of the power;
and respectively substituting the maximum growth rate of the quantity and the maximum growth rate of the power into a logistic equation to obtain a logistic model of the quantity and the time and a logistic model of the power and the time.
Optionally, the logistic model of the number and time in the building block is shown as follows:
N i (t)＝K i N 0 e at /(K i +N 0 (1+e at ))；
wherein a is the maximum growth rate of the quantity; k i A maximum environment capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of i (t) the using quantity of the charging piles at the moment t; n is a radical of 0 Is t 0 The quantity of the used charging piles at all times.
Optionally, the logistic model of power and time in the building block is shown as follows:
P j (t)＝K j P 0 e bt /(K j +P 0 (1+e bt ))；
wherein b is the maximum rate of increase of power; k j A maximum environmental capacity value for power; p j (t) is the power at time t; p 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
In yet another aspect, the present invention provides a computer apparatus, including: one or more processors;
the processor to store one or more programs;
when the one or more programs are executed by the one or more processors, the operation planning method for the multi-type charging and discharging piles in the area is realized.
In still another aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed, implements the method for planning operations of multiple types of charging and discharging piles in an area as described above.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an operation planning method for various types of charging and discharging piles in a region, which comprises the following steps: respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the area at a specified time into a pre-constructed quantity and time logistic model and a power and time logistic model to obtain the charging pile usage number and power of the type of charging pile to be planned at a set time; obtaining an operation planning scheme of each type of charging pile at a set moment based on the relation between the number and power of the charging piles at the set moment and a set minimum limiting condition; the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively. The method adopts the quantity and time logistic model and the power and time logistic model to carry out the charging operation planning method, and can realize the dynamic charging planning of the multi-type charging piles.
According to the method, the charging pile usage quantity and power of the type of charging pile to be planned at the set time are obtained based on the quantity and time logistic model and the power and time logistic model, and the operation planning scheme of each type of charging pile at the set time is obtained by combining the set minimum limiting condition, so that the problems that the charging modes of multiple types of charging piles are not effectively operated and planned, the operation cost of operators is generally high, and the operation planning of the vehicle pile network is unreasonable are solved.
According to the method, the number and the power of the charging piles at each moment in the set time period are used by the various types of charging piles with fitting correlation, the exponential models are respectively adopted for fitting to obtain the maximum increase rate of the number and the maximum increase rate of the power, firstly, the number and the power of the various types of charging piles at each moment in the set time period are only adopted, the fitting accuracy is guaranteed, secondly, the exponential models are adopted for fitting, and the calculation process is simplified.
Drawings
FIG. 1 is a flow chart of a method for planning the operation of a plurality of types of charging and discharging piles in an area according to the present invention;
FIG. 2 is a graph of the decision coefficient of the present invention;
fig. 3 is a flow chart of the collaborative operation planning of ordered charging and V2G charging of the present invention.
Detailed Description
For a better understanding of the present invention, reference is made to the following description taken in conjunction with the accompanying drawings and examples.
According to the method, the relation model of the research object and the environmental capacity is utilized, the operation planning is carried out by adopting the logistic relation, the planning of the cooperative operation of the vehicle pile network is realized, the utilization rate of the charging piles can be improved, the cooperative operation of various types of charging piles can be realized, the innovation of the operation mode is realized, and the reliability of the operation of the power grid in the region is also ensured.
Example 1
The invention provides an operation planning method for multi-type charging and discharging piles in a region, which comprises the following steps as shown in figure 1:
s1: respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the region at a specified time into a pre-constructed quantity and time logistic model and a power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at a set time;
s2: obtaining an operation planning scheme of each type of charging pile at a set moment based on the relation between the number and power of the charging piles at the set moment and a set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively.
The present invention is described in detail below:
the invention belongs to a planning method for the operation of a plurality of types of charging piles, and comprises a constraint condition for charging operation planning, a logistic planning method, a logistic collaborative planning method under the condition of multi-factor coupling, and a collaborative planning method for the operation of the plurality of types of charging piles and a charging mode.
The operation planning of the charging pile is generally directed at a certain area, the range of the area is based on the power distribution range of a power distribution station area of a power grid, the area also determines that the operation of the power grid is adjustable and controllable, and when a given area needs to be processed across the power distribution station area, the area range can be defined into a plurality of planning areas, or the range of the power distribution station area is subjected to operation planning of a larger area. The constraints of the region include: the capacity of the distribution station area of the area is measured by the maximum operation power P _ max, and the maximum power P _ EVmax which can be used for charging is measured; the number No _ make of the charging piles running in the region is a fixed resource, the number types of the charging piles are known after the construction of the charging piles in the region is completed, when different types of charging piles are distinguished, the number of the disordered charging piles is recorded as No _ V0G, the number of the ordered charging piles is recorded as No _ V1G, and the number of the V2G charging piles is recorded as No _ V2G; when different types of charging piles are distinguished, the power of the unordered charging pile is recorded as P _ V0G, the power of the ordered charging pile is recorded as P _ V1G, and the power of the V2G charging pile is recorded as P _ V2G (charging is positive and discharging is negative); no _ EV of the running quantity of the electric vehicles in the area is counted as No _ EVV0G after disorderly charging when different types of charging modes are distinguished, no _ EVV1G after orderly charging is counted as No _ EVV1G, no _ EVV2G of charging pile quantity is counted as No _ EVV2G: when charging power P _ EV of the electric automobile in the area is different in charging modes, the disordered charging number is recorded as P _ EVV0G, the ordered charging number is recorded as P _ EVV1G, and the V2G charging number is recorded as P _ EVV2G.
Before S1, the present invention further comprises: the construction of the logistic model of quantity and time and the logistic model of power and time, the construction process is described in detail as follows:
the logistic planning method is based on a basic rule exhibited by charging power of the electric vehicle in a charging operation process, and takes an object maximum value (K) allowed by environmental capacity as a regulating parameter, wherein the determined constraint conditions such as the maximum power P _ max of the power distribution area are respectively the maximum environmental capacity value K under each scene.
The method is adopted for regulation and control, firstly, a logistic model fitting is carried out on the charging operation process, and according to a logistic differential equation, the relative growth rate of the usage amount (N) of a certain resource meets an expression:
dN/dt＝rN(1-N/K) (1)
wherein r is the maximum growth rate when the resources are not limited, N is the number of the objects at the moment t, integral transformation is carried out on the equation, and the expression of the logistic model is determined as follows:
N 1 (t)＝KN 0 e rt (K+N 0 (1+e rt )) (2)
wherein N is 0 Is t 0 The number of objects at the moment, the moment of starting operation planning under default condition is t 0 Time point of =0, where the number of objects at that time is N 0 The value is obtained.
The next step is to calculate the maximum growth rate r of the logistic model. In some cases, because a certain research object, in this embodiment, the number of charging piles used at a certain time and the power of the charging piles are used as the research object, the maximum growth rate r and the environmental capacity K are not determined, and an expression of a logistic model, that is, formula (2), is directly used to perform curve fitting, so that the calculation process is relatively complex, in order to simplify the calculation process, the invention uses an exponential growth model with unlimited resources to perform fitting, so as to obtain the maximum growth rate r, the relative F growth rate satisfies a differential equation:
dN/dt＝rN (3)
the form of the integral is:
N 2 (t)＝N 0 e rt (4)
for the logistic model, the point where the relative growth rate is fastest is N = K/2, beyond which the relative growth rate gradually decreases and is oriented to zero. For the exponential growth model, N is from N 0 Increases to K/2, the time t is (0,ln) (K/(2N) 0 ))。
The next step is to perform a fit analysis on the fitted curve. The exponential model is adopted to fit the logistic model, the decision coefficient of linear regression can be calculated, the fitting degree of numerical values is analyzed, and the calculation formula is as follows:
wherein the content of the first and second substances,
is ln (N) 1 (t)) is in (0,ln (K/(2N)) 0 ) Mean value in the interval, when K is much greater than N 0 In this case, the calculation of the determination coefficient can be simplifiedThe calculation formula is as follows:
wherein x = ln (K/(2N) 0 ) (t ≠ 0), it is known that the environmental capacity K must be greater than N 0 The value interval of x is (ln 0.5, + ∞), where x is not equal to 0, and 6x 4 -36x 2 +64x-18 is not equal to 0. The graph is shown in FIG. 2 according to the formula (6).
Next, determining an application range of the fitting formula, where the application range of the fitting formula is subject to actual operating condition requirements, and this embodiment is described by taking the current specification as an example:
according to the formula, the simplified decision coefficient is meaningfully 1 ≧ R 2 The value of not less than 0,x should not be less than 0.462, and K is not less than 3.17N 0 (ii) a To have a linear dependence of the fitted function, R 2 More than or equal to 0.8, x should be selected to be not less than 2.28, and K is more than or equal to 19.55N 0 (ii) a To have a good linear correlation of the fitted function, R 2 More than or equal to 0.95, x is not less than 3.45, and K is more than or equal to 63N 0 (ii) a In the application process, the corresponding decision coefficient can be selected according to the actual situation to carry out operation planning decision.
Coefficient of determination R of the subject 2 And when the research object meets the fitting correlation at least 0.8, substituting the maximum growth rate of the research object meeting the fitting correlation into a logistic equation to obtain a logistic model of the research object.
A logistic collaborative planning under the condition of multi-factor coupling firstly extracts K, N of the multi-factor 0 And (4) judging the value, and judging whether the fitting formula established by the method is in the application range. If R is 2 And the coefficient correlation requirement is met, and the maximum growth rate is obtained by adopting exponential model fitting. In view of the fact that the research object of the embodiment is the usage number and power of the charging piles at each time in the set time period, the usage number N of the charging piles is the research object i (t), quantity versus time, the complex logistic equation:
N i (t)＝K i N 0 e at /(K i +N 0 (1+e at )) (7)
wherein a is the maximum growth rate of the quantity; k i A maximum environment capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of i (t) the using quantity of the charging piles at the moment t; n is a radical of 0 Is t 0 The quantity of the used charging piles at all times.
When the research object is the power P of the charging pile j (t), the power versus time relationship is compounded by the logistic equation:
P j (t)＝K j P 0 e bt /(K j +P 0 (1+e bt )) (8)
wherein b is the maximum rate of increase of power; k j A maximum environmental capacity value for power; p is j (t) is the power at time t; p 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
S1: and respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the area at the appointed time into a pre-constructed quantity and time logistic model and a pre-constructed power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at the set time.
S2: obtaining an operation planning scheme of each type of charging pile at the set time based on the relation between the number and power of the charging piles at the set time and the set minimum limiting condition, and specifically comprising the following steps:
setting the minimum limit condition includes:
minimum time of use.
In the operation planning, according to actual needs, the minimum limiting conditions which can be selected include the maximum power P used by a regional power grid for charging, the number N of charging piles, the maximum output power of all charging piles and the like, the maximum power for charging, the number of charging piles and the maximum output power of all charging piles, function models related to t can be obtained according to a logistic formula in the invention, whether the limiting conditions are exceeded or not is judged according to the minimum time delta t during operation, and the output power and the operation mode of the charging piles are adjusted when the limiting conditions are exceeded. For example, when 12 days 10 months 6, the charging power of a distribution network in a certain area exceeds the allowable power of the area, and the charging output power of the area is adjusted to be reduced or the operation mode is adjusted to add the discharging pile power.
Calculating the inverse functions of the use quantity and the inverse functions of the power of the charging piles of all types at the set moment according to the formula (9), and selecting the minimum value from the inverse functions;
judging whether the minimum value meets the minimum time, and if so, taking the use quantity and power of all types of charging piles at the set time as the operation planning scheme of each type of charging pile at the set time;
otherwise, adjusting the charging mode of each type of charging pile to enable the using quantity and the power of each type of charging pile at the set moment to meet the set minimum time;
wherein all types of charging piles comprise at least one or more of the following: fill electric pile, unordered electric pile and the electric pile of filling of V2G in order.
When a logistic model is adopted, the limit value K is in an infinite approaching state, K/2 is a point with the fastest growth rate, a certain point is selected as the limit value of the limiting condition in the interval (K/2,K) according to the requirement of operation planning, and in the area, all the limiting conditions have a minimum time of use Deltat:
according to the time delta t, whether the current charging running state meets the requirements of the high efficiency of the charging pile and the safety of the power grid or not can be analyzed, if not, the running mode of the charging pile can be adjusted, and the high efficiency and the reliable running of the system are guaranteed.
And adjusting the operation mode implementation mode of the charging pile, including reducing the output power of the charging pile and using the discharging pile discharging mode.
And performing operation planning on the multi-type charging pile and the charging mode by adopting a logistic model, namely performing collaborative planning by adopting the logistic model coupled by multiple factors, wherein research objects comprise a new energy automobile, the charging pile and a regional power grid. Because the unordered electric pile that fills does not possess the regulating power, in order to make it satisfy operation regulation and control ability, can will stop to charge as the regulation mode that unordered charges.
The charging mode of each type of charging pile comprises independent operation and cooperative operation of various charging piles, for example, modes such as the cooperative operation of an unordered charging pile and an ordered charging pile, the cooperative operation of an ordered charging pile and a V2G charging pile, and the like.
Cooperative operation also means that as the charging vehicle increases, the power of the charge is adjusted and the discharging vehicle is called to discharge through the discharging pile to provide additional charge. And calculating the total power of the charging piles at the time t according to a logistics formula by taking the charging power allowed by the power distribution network as a limiting condition, and switching the charging mode if the calculated total power exceeds the limiting condition at a certain time.
Example 2
Based on the same invention concept, the invention also provides an operation planning system for the multi-type charging and discharging piles in the region, which comprises the following steps:
the calculation module is used for respectively inputting the acquired charging pile usage number and charging power of each type of charging pile in the area at the specified time into a pre-constructed quantity and time logistic model and a pre-constructed power and time logistic model to obtain the charging pile usage number and power of the type of charging pile to be planned at the set time;
the planning module is used for obtaining an operation planning scheme of each type of charging pile at the set time based on the relation between the number and power of the charging piles at the set time and the set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively.
Optionally, the system further comprises a building module for:
the method comprises the steps that the using quantity and power of charging piles of various types with fitting correlation at each moment in a set time period are fitted respectively by an exponential model to obtain the maximum increasing rate of quantity and the maximum increasing rate of power;
and respectively substituting the maximum growth rate of the quantity and the maximum growth rate of the power into a logistic equation to obtain a logistic model of the quantity and the time and a logistic model of the power and the time.
Optionally, the logistic model of the number and time in the building block is shown as follows:
N i (t)＝K i N 0 e at /(K i +N 0 (1+e at ))；
wherein a is the maximum growth rate of the quantity; k is i A maximum environmental capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of i (t) the using quantity of the charging piles at the moment t; n is a radical of 0 Is t 0 The quantity of the used charging piles at all times.
Optionally, the logistic model of power and time in the building block is shown as follows:
P j (t)＝K j P 0 e bt /(K j +P 0 (1+e bt ))；
wherein b is the maximum rate of increase of power; k j A maximum environmental capacity value for power; p j (t) is the power at time t; p 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
An operation planning system of stake of polymorphic type charge-discharge in the region still includes: and the correlation judgment module is used for judging the use quantity and time of the charging piles at each moment in a set time period and the fitting correlation between the power and the time.
The correlation judgment module comprises:
the acquisition submodule is used for acquiring the using quantity and charging power of the charging piles at each moment in a set time period;
the capacity determination submodule is used for taking the maximum value of the using quantity of the charging piles in a set time period as the environmental capacity of the quantity and taking the maximum value of the charging electric power in the set time period as the environmental capacity of the power;
the fitting calculation submodule is used for combining the environmental capacity of the quantity and the charging pile usage quantity at the initial moment in a set time period with a decision coefficient calculation formula to obtain a decision coefficient of the quantity and the time, and when the decision coefficient of the quantity and the time is larger than a set threshold value, the charging pile usage quantity at each moment has fitting correlation with the time; and combining the environmental capacity of the power and the power value of the initial moment in the set time period with a decision coefficient calculation formula to obtain a decision coefficient of the power and the time, wherein when the decision coefficient of the power and the time is greater than a set threshold value, the charging pile has fitting correlation between the power value and the time at each moment.
The calculation of the decision coefficient in the fitting calculation submodule is shown as follows:
in the formula, R 2 To determine the coefficients; x is K and 2N 0 The natural logarithm of the ratio; k is the maximum environmental capacity; n is a radical of 0 Is t 0 Number of objects at a time.
Example 3
The following describes in detail a specific implementation process of the operation planning method for multiple types of charging and discharging piles in an area according to the present invention with reference to fig. 3:
And 2, setting limit values Ki of all research objects according to operation planning requirements, wherein the limit values Ki include charging power P _ EVi of a power grid in an area, the number of the orderly charging piles is No _ V1Gi, the number of the V2G charging piles is No _ V2Gi, the power of the orderly charging piles is P _ V1Gi, and the power of the V2G charging piles is P _ V2Gi.
And 6, if the current operation does not meet the actual requirement, the reliability of the operation of the power grid can be influenced. According to the time t, the operation state of the charging piles is adjusted, firstly, the charging power of the orderly charging piles and the power of the V2G charging piles are reduced, when the reduced power is insufficient to support the maximum power which can be provided by the power grid, the charging and discharging modes of the V2G charging piles are adjusted, the V2G charging piles are set to discharge to the power grid, other orderly charging piles are fed back, and the chargeable maximum power P _ Evmax and the charging power limit value P _ EVi of the power grid in the mode are changed. The maximum growth rate and the minimum elapsed time Δ t are readjusted to meet the operational requirements of the system.
The specific implementation process is as follows:
| t/time | Number of V1G charges | Number of |
| 0 | 1 | 1 |
| 1 | 2 | 1 |
| 2 | 3 | 2 |
| 3 | 4 | 3 |
| 4 | 7 | 4 |
| 5 | 10 | 5 |
| 6 | 17 | 7 |
| 7 | 27 | 10 |
| 8 | 43 | 14 |
| 9 | 69 | 19 |
| 10 | 110 | 27 |
| 11 | 176 | 38 |
| 12 | 52 | |
| 13 | 73 |
TABLE 1 quantity of ordered charging and V2G charging at time t
Example 4
Based on the same inventive concept, the present invention also provides a computer apparatus comprising a processor and a memory, the memory being configured to store a computer program comprising program instructions, the processor being configured to execute the program instructions stored by the computer storage medium. The Processor may be a Central Processing Unit (CPU), or may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable gate array (FPGA) or other Programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., which is a computing core and a control core of the terminal, and is specifically adapted to implement one or more instructions, and to load and execute one or more instructions in a computer storage medium, so as to implement a corresponding method flow or a corresponding function, so as to implement the step of the operation planning method for the intra-area multi-type charge and discharge peg in the foregoing embodiments.
Example 5
Based on the same inventive concept, the present invention further provides a storage medium, in particular, a computer-readable storage medium (Memory), which is a Memory device in a computer device and is used for storing programs and data. It is understood that the computer readable storage medium herein can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space storing an operating system of the terminal. Also, one or more instructions, which may be one or more computer programs (including program code), are stored in the memory space and are adapted to be loaded and executed by the processor. It should be noted that the computer-readable storage medium may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in the computer-readable storage medium may be loaded and executed by the processor to implement the steps of the method for planning operations of the multi-type charging and discharging piles in the area in the foregoing embodiments.
It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, 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.
The present invention is not limited to the above embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention are included in the scope of the claims of the present invention as filed.
Claims (16)
1. An operation planning method for multi-type charging and discharging piles in an area is characterized by comprising the following steps:
respectively inputting the obtained charging pile usage number and charging power of each type of charging pile in the area at a specified time into a pre-constructed quantity and time logistic model and a power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at a set time;
obtaining an operation planning scheme of each type of charging pile at a set moment based on the relation between the number and power of the charging piles at the set moment and a set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed based on the fact that the quantity of the charging piles of various types with fitting correlation are used at all times, and the maximum quantity growth rate and the maximum power growth rate obtained by respectively fitting the charging power through an exponential model are respectively combined with a logistic equation.
2. The method of claim 1, wherein the building of the pre-built quantity-versus-time and power-versus-time logistic models comprises:
the method comprises the steps that the using quantity and power of charging piles of various types with fitting correlation at each moment in a set time period are fitted respectively by an exponential model to obtain the maximum increasing rate of quantity and the maximum increasing rate of power;
and respectively substituting the maximum growth rate of the quantity and the maximum growth rate of the power into a logistic equation to obtain a logistic model of the quantity and the time and a logistic model of the power and the time.
3. The method of claim 2, wherein the quantity versus time logistic model is as follows:
wherein a is the maximum growth rate of the quantity; k i A maximum environmental capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of i (t) the using quantity of the charging piles at the moment t; n is a radical of hydrogen 0 Is t 0 The quantity of the used charging piles at all times.
4. The method of claim 2, wherein the power versus time logistic model is as follows:
wherein b is the maximum rate of increase of power; k is j A maximum environmental capacity value for power; p is j (t) is the power at time t; p 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
5. The method of claim 2, wherein the step of respectively fitting the number of charging piles and the power of each type of charging pile with the fitting correlation at each moment in the set time period by using an exponential model to obtain the maximum increase rate of the number and the maximum increase rate of the power further comprises the following steps:
and judging the use quantity and time of the charging piles at each moment in a set time period and the fitting correlation between the power and the time.
6. The method of claim 5, wherein the determining of the fitted correlation between the number of charging post uses and the time, and the power and the time at each moment in the set period of time comprises:
acquiring the using quantity and charging power of each type of charging pile at each moment in a set time period;
taking the maximum value of the using quantity of the electric piles in a set time period as the environmental capacity of the quantity, and taking the maximum value of the charging power in the set time period as the environmental capacity of the power;
combining the environmental capacity of the quantity and the charging pile usage quantity at the initial moment in a set time period with a decision coefficient calculation formula to obtain a decision coefficient of the quantity and the time, wherein when the decision coefficient of the quantity and the time is larger than a set threshold value, the charging pile usage quantity and the time at each moment have fitting correlation;
and combining the environmental capacity of the power and the power value of the initial moment in the set time period with a decision coefficient calculation formula to obtain a decision coefficient of the power and the time, wherein when the decision coefficient of the power and the time is greater than a set threshold value, the charging pile has fitting correlation between the power value and the time at each moment.
7. The method of claim 6, wherein the decision coefficient is calculated as follows:
in the formula, R 2 To determine the coefficients; x is K and 2N 0 The natural logarithm of the ratio; k is the maximum environmental capacity; n is a radical of 0 Is t 0 Number of objects at a time.
8. The method of claim 1, wherein the set minimum limit condition comprises a minimum time-to-use.
9. The method of claim 8, wherein the step of obtaining an operation planning scheme for each type of charging pile at a set time based on the number and power of the charging piles at the set time and the relationship between the set minimum limit conditions comprises:
calculating an inverse function of the using quantity of each type of charging pile at a set moment and an inverse function of power, and selecting a minimum value from the inverse functions;
judging that the minimum value meets the minimum time, and if the minimum value meets the minimum time, taking the use quantity and power of all types of charging piles at a set time as an operation planning scheme of each type of charging pile at the set time;
otherwise, adjusting the charging mode of each type of charging pile to enable the using quantity and the power of each type of charging pile at the set moment to meet the set minimum time;
wherein all types of charging piles at least comprise one or more of the following: fill electric pile, unordered electric pile and the electric pile of filling of V2G in order.
10. The method of claim 9, wherein the charging mode of each type of charging post comprises: independent operation and cooperative operation of various types of charging piles;
the cooperative operation of the charging piles of various types comprises the following steps: unordered electric pile and the orderly electric pile that fills move in coordination, fill electric pile and V2G in coordination and unordered electric pile and V2G fill electric pile in coordination.
11. The utility model provides an operation planning system of stake of polymorphic type charge-discharge in area which characterized in that includes:
the calculation module is used for respectively inputting the acquired charging pile usage number and charging power of each type of charging pile in the area at the specified time into a pre-constructed quantity and time logistic model and a pre-constructed power and time logistic model to obtain the charging pile usage number and power of each type of charging pile at the set time;
the planning module is used for obtaining an operation planning scheme of each type of charging pile at the set moment based on the relation between the number and the power of the charging piles at the set moment and the set minimum limiting condition;
the pre-constructed quantity and time logistic model and the power and time logistic model are constructed on the basis that the quantity of the charging piles of each type with fitting correlation are used at each moment, and the maximum quantity growth rate and the maximum power growth rate are obtained by fitting the charging power by using exponential models respectively and are combined with a logistic equation respectively.
12. The system of claim 11, further comprising a build module to:
the method comprises the steps that the using quantity and power of charging piles of various types with fitting correlation at each moment in a set time period are fitted respectively by an exponential model to obtain the maximum increasing rate of quantity and the maximum increasing rate of power;
and respectively substituting the maximum growth rate of the quantity and the maximum growth rate of the power into a logistic equation to obtain a logistic model of the quantity and the time and a logistic model of the power and the time.
13. The system of claim 12, wherein the logistic model of quantity versus time in the building blocks is represented by the following equation:
wherein a is the maximum growth rate of the quantity; k i A maximum environment capacity value that is a quantity; e is an exponential function of a natural base number; n is a radical of i (t) the using quantity of the charging piles at the moment t; n is a radical of 0 Is t 0 The quantity of the used charging piles at all times.
14. The system of claim 12, wherein the logistic model of power versus time in the building block is represented by the following equation:
wherein b is the maximum rate of increase of power; k j A maximum environmental capacity value for power; p j (t) is the power at time t; p is 0 Is t 0 The power value of (d); t is t 0 Is the initial time.
15. A computer device, comprising: one or more processors;
the processor to store one or more programs;
the one or more programs, when executed by the one or more processors, implement the method for planning operations of the intra-area multi-type charge-discharge peg of any one of claims 1-10.
16. A computer-readable storage medium having stored thereon a computer program which, when executed, implements a method of planning operation of a multi-type charge-discharge peg in an area according to any one of claims 1 to 10.
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