CN114187137A - Charging pile power capacity distribution method and device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a charging pile power capacity distribution method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side; acquiring current power load data of the building power utilization unit, and predicting the building power utilization load of the building power utilization unit at a target time according to the current power load data and a pre-established power load prediction model; and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value. By adopting the method, the utilization rate of the power resources in the whole target area can be improved.
Description
Technical Field
The application relates to the technical field of electric power regulation and control, in particular to a charging pile power capacity distribution method and device, computer equipment and a storage medium.
Background
With the rapid development of economy, new energy vehicles are continuously increasing, and charging equipment meeting the charging requirements of the new energy vehicles is added in communities such as residential areas or office areas, so that the infrastructure construction project is greatly promoted in China and places. The increase of intermittent energy supply equipment such as a charging pile of a new energy automobile inevitably increases the difficulty of power grid dispatching operation, and the increase also provides a new important challenge for the electric power regulation and control capability of a power utilization system.
However, a large amount of new energy vehicles charge loads and building-side user power utilization loads are superposed, so that stress is applied to the power distribution network of the community, and the existing community power distribution network is difficult to bear. At present, the traditional community new energy automobile charging scheme is that the planning construction of charging piles is carried out according to the fixed residual capacity after the community power distribution planning, but the residual capacity is limited, the electric quantity distributed to the charging pile side for use is little, the charging demand of the new energy automobile increasing day by day is hardly met, and the electric power resource utilization rate of the whole community is very low.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a charging pile power consumption capacity allocation method, device, computer device, and storage medium, which can improve utilization rate of community power consumption resources.
A method for distributing power capacity of charging piles comprises the following steps:
acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side;
acquiring current power load data of the building power utilization unit, and predicting the building power utilization load of the building power utilization unit at a target time according to the current power load data and a pre-established power load prediction model;
and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
In one embodiment, the method for constructing the power load prediction model comprises the following steps: collecting historical electricity load data of building electricity utilization units within a certain time period; and according to a deep learning algorithm, taking historical power load data as model training data to obtain a trained power load prediction model.
In one embodiment, calculating an allocable electricity capacity threshold value allocable to the charging post electricity unit at a target time according to the building electricity load and the transformer capacity threshold value comprises: acquiring a power consumption demand value of a power consumption unit of a charging pile at a target time; and calculating the allocable power consumption capacity threshold value of the power consumption unit of the charging pile at the target time according to the building power consumption load, the transformer capacity threshold value and the power consumption demand value.
In one embodiment, the method further comprises: and adjusting the output power of the charging unit of the charging pile at the target time according to the threshold value of the allocable power utilization capacity.
In one embodiment, a charging pile electricity consumption unit comprises a plurality of power gears, and the output power of the charging pile electricity consumption unit at a target time is adjusted according to a threshold value of allocable electricity consumption capacity, and the method comprises the following steps: the output power of the electric unit for charging is adjusted by switching the power gear of the electric unit for charging.
In one embodiment, adjusting the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity comprises: and uniformly adjusting the output power of each charging pile electricity utilization unit in the target time according to the distributable electricity utilization capacity threshold.
In one embodiment, adjusting the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity comprises: and acquiring the priority of each charging pile electricity utilization unit, and adjusting the output power of one or more charging pile electricity utilization units at the target time according to the allocable electricity utilization capacity threshold and the priority.
In one embodiment, the method further comprises: and when the actual power load value of the building power utilization unit exceeds the building power load value is monitored at the target time, controlling the charging pile power utilization unit to reduce the actual output power.
A capacity distribution device for a charging pile, the device comprising:
the total power load acquisition module is used for acquiring a transformer capacity threshold value of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side;
the building side electricity utilization prediction module is used for acquiring current electricity utilization load data of the building electricity utilization units and predicting the building electricity utilization loads of the building electricity utilization units at the target time according to the current electricity utilization load data and a pre-established electricity utilization load prediction model;
and the charging pile electricity utilization distribution module is used for calculating a distributable electricity utilization capacity threshold value which can be distributed to the charging pile electricity utilization units at the target time according to the building electricity utilization load and the transformer capacity threshold value.
A computer device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the steps of the charging pile power consumption capacity distribution method.
A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the charging pile power capacity allocation method described above.
According to the charging pile power consumption capacity distribution method, device, computer equipment and storage medium, a power consumption load prediction model is constructed in advance, the power consumption load threshold value of the building power unit on the building side at the target time is predicted based on the power consumption load prediction model, and the power consumption capacity threshold value which can be used by the charging pile power unit on the charging pile side at the target time is calculated by combining the transformer capacity threshold value of the whole target area. Because the electricity consumption of the building electricity utilization units is not fixed and unchanged, and the maximum value of the electricity utilization load of the building electricity utilization units at different times is different, the electricity utilization capacity which can be distributed to the electricity utilization units of the charging piles can be dynamically calculated according to the predicted change of the building electricity utilization load, so that the flexible regulation and control of the electricity utilization capacity in the whole target area can be realized, and the utilization rate of the electricity resources in the whole target area is improved.
Drawings
Fig. 1 is an application environment diagram of a charging pile power consumption capacity allocation method in an embodiment;
FIG. 2 is a schematic flow chart illustrating a charging pile power consumption capacity allocation method according to an embodiment;
FIG. 3 is a schematic diagram illustrating a daily and annual electrical load trend curve for air conditioning power units in a residential area, according to one embodiment;
FIG. 4 is a schematic diagram illustrating a daily and annual power load trend curve of air conditioning power units in an office building area according to an embodiment;
fig. 5 is a schematic diagram illustrating a comparison between a conventional charging pile power capacity allocation method and a power capacity allocation method according to an embodiment of the present application;
FIG. 6 is a schematic diagram illustrating uniform adjustment of output power of power consumption units of charging piles in one embodiment;
FIG. 7 is a schematic diagram of adjusting the output power of the charging post power consumption unit according to priority in one embodiment;
fig. 8 is a block diagram showing the structure of a charging-pile electricity capacity distribution apparatus according to an embodiment;
FIG. 9 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, the charging pile power consumption capacity allocation method provided by the application can be applied to an application environment as shown in fig. 1. Specifically, the server 100 may obtain a transformer capacity threshold value of a target area, where the target area may include a building power unit on a building side and a charging pile power unit on a charging pile side, the server 100 may obtain current power load data of the building power unit through a power distribution system, predict building power loads of the building power unit at a target time according to the current power load data and a pre-established power load prediction model, and calculate an allocable power capacity threshold value allocable for the charging pile power unit at the target time according to the building power loads and the transformer capacity threshold value.
Further, the server 100 may further adjust the power consumption capacity of the charging pile power consumption unit by communicating with the charging pile platform according to the calculated threshold value of the allocable power consumption capacity. Further, the server 100 may further obtain actual power load data of the charging pile power consumption units through the power distribution system to calculate power consumption demand values of the charging pile power consumption units, and the like.
The server 100 may be any one or more physical servers or cloud servers of an EMS (Energy Management System) platform, where the EMS platform is a modern integrated automation System for power utilization supported by a computer technology and a power utilization System application software technology, and is also an integrated System of an Energy System and an information System. The target area may include areas of a community, a shopping mall complex, an office building, a hotel, etc. The power load data of the building power utilization units can be monitored through the power distribution system, and the server 100 can communicate with the power distribution system. The regulation and control of the power consumption capacity of the charging pile power consumption unit can be carried out through the charging pile platform, and the server 100 can be communicated with the charging pile platform. The above communication may be performed through a network, or may be realized by calling a hardware interface.
In an embodiment, as shown in fig. 2, a method for allocating power capacity for a charging pile is provided, which is described by taking the method as an example applied to the server in fig. 1, and may include the following steps:
step S202: acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit on the building side and a charging pile power utilization unit on the charging pile side.
The target area refers to a selected area, and may be any community in which the new energy charging apparatus is disposed, for example, various residential areas, office areas, business areas, or the like. The target area may be divided into a power consumption area on the building side and a power consumption area on the charging pile side. The transformer capacity threshold value is an upper limit value of the total available power capacity in the target region.
Wherein, can include at least one building power consumption unit in the power consumption region of building side, exemplarily, building power consumption unit can include building illumination power consumption unit, public district illumination power consumption unit, garage district power consumption unit, power elevator (owner) power consumption unit, power elevator (reserve) power consumption unit, fan power consumption unit, total pump house power consumption unit, boiler room power consumption unit, spray pump power consumption unit, fire pump power (owner) power consumption unit, fire pump power (reserve) power consumption unit, heat source pump power consumption unit, underground garage fan power consumption unit, air conditioner power consumption unit, at least one among bottom shop power consumption unit and the regional power consumption unit of afforestation. The electric power utilization area of the charging pile side can include at least one charging pile electric power utilization unit, one charging pile electric power utilization unit can be formed by one charging pile, and the charging pile area can also be formed by a plurality of charging pile clusters including the charging piles.
In this step, the upper limit value of the total power capacity allocated to the target area including the building power consumption unit and the charging pile power consumption unit may be acquired by one or more servers allocated to the EMS platform, and the upper limit value may be used as the transformer capacity threshold value of the target area.
Step S204: the method comprises the steps of obtaining current power load data of the building power utilization unit, and predicting the building power utilization load of the building power utilization unit at a target time according to the current power load data and a pre-established power utilization load prediction model.
The power load prediction model is a prediction model for predicting a power load trend curve of a building power unit on a building side in a certain future time range. The power load prediction model may be generated based on historical power load data for building power units and a deep learning algorithm. The deep learning algorithm may include a convolutional neural network algorithm, a cyclic neural network algorithm, a generative confrontation network algorithm, or a deep reinforcement learning algorithm. The target time refers to a certain time period or time point within a certain time range in the future. The building electrical load is an upper limit value of an expected electrical load of the building electrical unit on the building side at the target time outputted by the electrical load prediction model.
In this step, the current power load data of the building power consumption unit acquired by the power distribution system may be acquired by communicating with the power distribution system through any one or more servers disposed on the EMS platform, and the acquired current power load data may be used as an input parameter of a power load prediction model established in advance to perform prediction calculation, so as to obtain an upper limit value of a predicted power load of the building power consumption unit on the building side at a target time output by the power load prediction model, and the upper limit value may be used as the building power load.
In an embodiment, the method for constructing the power load prediction model may include: historical power load data of the building power utilization units in a certain time period are collected, and the historical power load data are used as model training data according to a deep learning algorithm to obtain a trained power load prediction model.
In this embodiment, data precipitation processing may be performed on historical electrical load data of each building electrical unit on the building side in advance, and when the data precipitation time sequence satisfies a preset period, an electrical load prediction model is established by using a deep learning algorithm and a simulation algorithm. The preset period can be set by a user, for example, one day, one month, one year, and the like.
Wherein, the historical electrical load data may include: the power utilization value range for illumination of each building in a certain preset period of history, the power utilization value range for illumination of each public area, the power utilization value range of each garage area, the power utilization value range of each power elevator (main use), the power utilization value range of each power elevator (standby use), the power utilization value range of each set of fan, the power utilization value range of a master pump house, the power utilization value range of a boiler house, the power utilization value range of a spray pump, the power utilization value range of a fire pump (main use), the power utilization value range of a fire pump (standby use), the power utilization value range of a heat source pump power supply, the power utilization value range of a fan in an underground garage, the power utilization value range of an air conditioner, and other power utilization value ranges (including bottom merchants, greening and the like). The value range refers to a threshold region, i.e., a region between an upper limit value and a lower limit value of the power load trend curve.
For example, for the same building electricity utilization unit, if the state, project or data collection time of the area where the building electricity utilization unit is located is different, different electricity utilization value ranges are obtained. Taking an air conditioning electric unit as an example, referring to fig. 3 in the state of a residential area, fig. 3 shows a schematic diagram of a daily and annual electric load trend curve of the air conditioning electric unit in the residential area in one embodiment. Fig. 3 (a) is a trend curve of the daily power load of the air-conditioning power unit in the residential area, and fig. 3 (b) is a trend curve of the annual power load of the air-conditioning power unit in the residential area. Referring to fig. 4, fig. 4 is a schematic diagram illustrating a daily and annual power load trend curve of an air conditioning power unit in an office building area according to another embodiment. Fig. 4 (a) is a trend curve of the daily power load of the air conditioning power units in the office building area, and fig. 4 (b) is a trend curve of the annual power load of the air conditioning power units in the office building area.
As can be seen from fig. 3 to 4, for the same building electricity consumption unit, if the state, project or data collection time of the area where the building electricity consumption unit is located is different, different electricity consumption value ranges are obtained. Therefore, the power load prediction model can be respectively constructed according to historical power load data of building power units collected in different regional statuses, projects or different time intervals. For example, the power load and the prediction model of the target area can be subjected to data acquisition and model construction according to the state, project, power utilization characteristics and the like of the target area. The building power load prediction accuracy can be improved by respectively constructing the power load prediction models, so that the prediction accuracy of the distributable power consumption capacity of the power consumption unit of the charging pile can be improved.
Step S206: and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
In this step, the server may perform, through the building electrical load of the building electrical unit at the target time output by the electrical load prediction model and the acquired transformer capacity threshold of the entire target area, a difference calculation or other correlation calculation between the transformer capacity threshold and the building electrical load, and the like, to obtain an allocable electrical capacity threshold that the charging pile electrical unit of the target area may be allocated for use.
For example, the server may use the following relation according to the predicted sum of the electricity loads of the building electricity utilization units: the sum of the power loads of all power utilization units (including all building power utilization units and charging pile power utilization units) is a preset coefficient (which can be 0.2-0.3, and can also be set according to business requirements) and less than or equal to a transformer capacity threshold value by a preset percentage (for example, 80%), so that an allocable power utilization capacity threshold value which can be allocated for use is determined.
According to the charging pile power consumption capacity distribution method, a power consumption load prediction model is constructed in advance, a power consumption load threshold value of a building power unit on a building side at a target time is predicted based on the power consumption load prediction model, and the power consumption capacity threshold value which can be used by the charging pile power unit on the charging pile side at the target time is calculated by combining a transformer capacity threshold value of the whole target area. Because the electricity consumption of the building electricity utilization units is not fixed and unchanged, and the maximum value of the electricity utilization load of the building electricity utilization units at different times is different, the electricity utilization capacity which can be distributed to the electricity utilization units of the charging piles can be dynamically calculated according to the predicted change of the building electricity utilization load, so that the flexible regulation and control of the electricity utilization capacity in the whole target area can be realized, and the utilization rate of the electricity resources in the whole target area is improved.
The beneficial effects of the embodiments of the present application are described in detail with reference to fig. 5, and referring to fig. 5, fig. 5 is a schematic diagram illustrating a comparison between a conventional charging pile power capacity allocation method and a power capacity allocation method according to an embodiment of the present application. The traditional charging pile power capacity distribution method only uses fixed residual capacity outside the building side available capacity planned for a building during community construction to plan the charging pile, and the capacity which can be distributed by the charging pile is only the part of the residual capacity, so that the quantity of the charging piles which can be constructed is small, and the charging requirement of new energy vehicles which are growing day by day cannot be met. However, according to the power consumption capacity allocation method, as the power consumption load threshold value used by the building side is predicted, the predicted building power consumption load can change between the upper limit value of the safe reserved capacity and the upper limit value of the available capacity of the building side along with different time, namely, the predicted building power consumption load changes between the value range of the flexible capacity, so that the flexible capacity can be fully utilized, and part or all of the flexible capacity can be correspondingly allocated to the charging pile side for use according to the predicted building power consumption load, so that the utilization rate of power resources in a community is improved, more charging piles can be planned and constructed, and the charging requirements are met.
In one embodiment, calculating an allocable electricity capacity threshold value allocable to the charging post electricity unit at a target time according to the building electricity load and the transformer capacity threshold value comprises: acquiring a power consumption demand value of a power consumption unit of a charging pile at a target time; and calculating the allocable power consumption capacity threshold value of the power consumption unit of the charging pile at the target time according to the building power consumption load, the transformer capacity threshold value and the power consumption demand value.
In this embodiment, the calculation of the allocable capacitance threshold may be further performed in combination with the power demand of the charging pile power consumption unit at the target time. More specifically, the power demand value of the power unit of the charging pile at a target time can be predicted by acquiring the power load data of the power unit of the charging pile in real time and establishing a demand prediction model for predicting the power demand of the charging pile, and if the power demand value is larger than the difference value between the transformer capacity threshold value and the building power load, the allocable power capacity threshold value can be determined based on the difference value; if the power demand value is less than the difference between the transformer capacity threshold value and the building power load, the distributable power capacity threshold value can be determined according to the power demand value.
In the embodiment, the distributable power consumption capacity threshold value is calculated by combining the power consumption demand value of the charging pile power consumption unit, so that the power consumption demand of the charging pile power consumption unit can be better matched, and when the power consumption demand of the charging pile power consumption unit is smaller, the power consumption capacity exceeding the demand can be distributed to other power consumption units needing more power, so that the utilization rate of power consumption resources in the whole area is further improved.
In one embodiment, the method further comprises: and adjusting the output power of the charging unit of the charging pile at the target time according to the threshold value of the allocable power utilization capacity.
In this embodiment, according to the predicted threshold value of the allocable power consumption capacity, when the threshold value of the allocable power consumption capacity is not exceeded, the output power of the charging pile power consumption unit at the target time is controlled to control the power consumption load at the target time, so that the purpose of flexibly and accurately allocating the power consumption capacity to the charging pile power consumption unit is achieved. For example, when the calculated threshold value of the allocable electricity utilization capacity is increased, the output power of the charging pile electricity utilization unit can be correspondingly increased; and when the calculated threshold value of the allocable electricity utilization capacity is reduced, the output power of the electricity utilization unit of the charging pile can be correspondingly reduced. That is, when the total output power of the charging pile electricity utilization unit on the charging pile side does not exceed the allocable capacitance threshold value, the adjustment can be performed according to any pre-configured adjustment strategy.
For example, the manner in which the server adjusts the output power of the charging pile power consumption unit may include: and generating a control instruction, and sending the control instruction to the charging pile platform, so that the charging pile platform adjusts the output power of the charging pile electricity utilization unit according to the received control instruction.
In one embodiment, a charging pile electricity consumption unit comprises a plurality of power gears, and the output power of the charging pile electricity consumption unit at a target time is adjusted according to a threshold value of allocable electricity consumption capacity, and the method comprises the following steps: the output power of the electric unit for charging is adjusted by switching the power gear of the electric unit for charging.
In this embodiment, one charging pile power consumption unit includes a plurality of power gears, for example, may include 4 gears, and the output power from 1 gear to 4 gears may be increased in sequence. Because can adjust the output that fills electric pile electricity unit through gear shifting, consequently, under limited allocable power consumption capacity threshold value, can start more and fill electric pile units. For example, when the calculated allocable electric capacity threshold is 21kW, if each charging pile unit is not provided with a gear, 3 charging piles with maximum power of 7kW may be started at most, whereas if the charging pile unit is provided with 4 gears (1.75kW, 3.5kW, 5.25kW, 7kW), the number of charging pile power units that can be started may be quadrupled at most when the total output power of the charging pile power units does not exceed 21 kW.
In one embodiment, adjusting the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity comprises: and uniformly adjusting the output power of each charging pile electricity utilization unit in the target time according to the distributable electricity utilization capacity threshold.
Illustratively, referring to fig. 6, fig. 6 shows a schematic diagram of uniformly adjusting the output power of each charging pile electricity consumption unit in one embodiment. Specifically, if 4 charging pile power consumption units (charging piles) are included in the target area, the maximum output power of each charging pile power consumption unit is 7kW, the calculated distributable electric capacity threshold value is 21kW, and under the condition that the total output power of the 4 charging pile power consumption units does not exceed 21kW, the output power of each charging pile power consumption unit can be uniformly adjusted. For example, the output power of 21kW may be equally distributed to 4 charging pile power consumption units, and each charging pile power consumption unit may control the output power to 75% of the maximum output power of 7kW, that is, 5.25 kW.
In one embodiment, adjusting the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity comprises: and acquiring the priority of each charging pile electricity utilization unit, and adjusting the output power of one or more charging pile electricity utilization units at the target time according to the allocable electricity utilization capacity threshold and the priority.
Illustratively, referring to fig. 7, fig. 7 is a diagram illustrating the output power of the charging post power consumption unit according to the priority in one embodiment. Specifically, if 4 charging pile electricity consumption units (charging piles) are included in the target area, the maximum output power of each charging pile electricity consumption unit is 7kW, the allocable capacity threshold value is calculated to be 21kW, in the case where the total output power of the 4 charging pile electricity consumption units does not exceed 21kW, the priorities of the 4 charging pile electricity consumption units are obtained, for example, according to the priority, the charging piles 2 and 4 are judged to have higher priority than the charging piles 1 and 3, under the condition that the threshold value of the allocable electricity utilization capacity is not changed, the output power of the electricity utilization unit of the charging pile with higher priority can be ensured according to the priority of the priority, for example, the output power of the charging pile 1 and the charging pile 3 is adjusted to 50% of the maximum output power of 7kW, i.e. 3.5kW, whereas the unit output of charging piles 2 and 4 can be kept constant at a maximum output of 7 kW.
The priority of the charging pile can be set in a user-defined mode according to business requirements, for example, the priority of the charging pile which is being used at a target time can be set to be higher by monitoring the use condition of the charging pile; or, the reservation data of the charging pile can be collected, and the priority of the reserved charging pile at the target time is set to be higher. The adjustment strategy of the output power of the charging pile can also be set by self according to the requirement as long as the total output power does not exceed the calculated threshold value of the allocable power utilization capacity.
In one embodiment, the method further comprises: and when the actual power load value of the building power utilization unit exceeds the building power load value is monitored at the target time, controlling the charging pile power utilization unit to reduce the actual output power.
In this embodiment, the actual power load value of the building power unit can be monitored in real time, and the allocable power capacity in the scheme is obtained based on the building power load predicted by the power load prediction model, so that in individual cases, the actual power load value of the building power unit may have unexpected abnormal change, in such cases, the actual output power of the charging pile power unit can be controlled and reduced, on one hand, the power demand of the building power unit at the building side in the target area can be preferentially ensured without capacity expansion of the total power capacity, the power failure of the building power unit at the building side due to power distribution overload can be avoided, on the other hand, the charging safety of the charging pile power unit can be improved, and the scheme is used as a backup protection mechanism for charging safety protection of the charging pile except for the charging pile platform, safety risk and economic loss brought to the electric unit of charging stake are avoided transshipping.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 8, there is provided a charging pile power capacity distribution apparatus including: general power load obtains module 810, building side power consumption prediction module 820 and fills electric pile power consumption distribution module 830, wherein:
a total power load obtaining module 810, configured to obtain a transformer capacity threshold of a target area; the target area comprises a building power utilization unit on the building side and a charging pile power utilization unit on the charging pile side.
And the building side electricity utilization prediction module 820 is used for acquiring the current electricity utilization load data of the building electricity utilization unit and predicting the building electricity utilization load of the building electricity utilization unit at the target time according to the current electricity utilization load data and a pre-established electricity utilization load prediction model.
And the charging pile electricity utilization distribution module 830 is configured to calculate an allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
In one embodiment, the building side electricity consumption prediction module 820 is further configured to construct an electricity consumption load prediction model, and specifically, the building side electricity consumption prediction module 820 collects historical electricity consumption load data of the building electricity consumption units within a certain time period; and according to a deep learning algorithm, taking historical power load data as model training data to obtain a trained power load prediction model.
In one embodiment, the charging pile power distribution module 830 obtains a power demand value for the charging pile power unit at a target time; and calculating the allocable power consumption capacity threshold value of the power consumption unit of the charging pile at the target time according to the building power consumption load, the transformer capacity threshold value and the power consumption demand value.
In one embodiment, the charging pile electricity distribution module 830 is further configured to adjust the output power of the charging pile electricity consumption unit at the target time according to the threshold value of the allocable electricity consumption capacity.
In one embodiment, one charging pile power consumption unit includes a plurality of power gears, and the charging pile power consumption distribution module 830 adjusts the output power of the charging pile power consumption unit by switching the power gears of the charging pile power consumption unit.
In one embodiment, the charging pile electricity distribution module 830 uniformly adjusts the output power of each charging pile electricity unit at the target time according to the distributable electricity consumption capacity threshold.
In one embodiment, the charging pile power distribution module 830 obtains the priority of each charging pile power consumption unit, and adjusts the output power of one or more charging pile power consumption units at the target time according to the allocable power consumption capacity threshold and the priority.
In one embodiment, the charging pile electricity distribution module 830 is configured to control the charging pile electricity consuming units to reduce the actual output power when the actual electricity load value of the building electricity consuming units exceeds the building electricity load at the target time.
For specific limitations of the charging pile power consumption capacity distribution device, reference may be made to the above limitations on the charging pile power consumption capacity distribution method, and details are not repeated here. All modules in the charging pile power utilization capacity distribution device can be completely or partially realized through software, hardware and a combination of the software and the hardware. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 9. The computer device comprises a processor, a memory and a network interface which are connected through a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a charging pile power capacity allocation method.
Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program: acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side; acquiring current power load data of the building power utilization unit, and predicting the building power utilization load of the building power utilization unit at a target time according to the current power load data and a pre-established power load prediction model; and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
In one embodiment, the processor, when executing the computer program, further performs the steps of: collecting historical electricity load data of building electricity utilization units within a certain time period; and according to a deep learning algorithm, taking historical power load data as model training data to obtain a trained power load prediction model.
In one embodiment, when the processor executes the computer program to calculate the threshold value of the allocable electricity consumption capacity allocable to the charging pile electricity consumption unit at the target time according to the building electricity load and the threshold value of the transformer capacity, the following steps are specifically implemented: acquiring a power consumption demand value of a power consumption unit of a charging pile at a target time; and calculating the allocable power consumption capacity threshold value of the power consumption unit of the charging pile at the target time according to the building power consumption load, the transformer capacity threshold value and the power consumption demand value.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and adjusting the output power of the charging unit of the charging pile at the target time according to the threshold value of the allocable power utilization capacity. In one embodiment, when the processor executes the computer program to adjust the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically implemented: the output power of the electric unit for charging is adjusted by switching the power gear of the electric unit for charging.
In one embodiment, when the processor executes the computer program to adjust the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically implemented: and uniformly adjusting the output power of each charging pile electricity utilization unit in the target time according to the distributable electricity utilization capacity threshold. In one embodiment, when the processor executes the computer program to adjust the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically implemented: and acquiring the priority of each charging pile electricity utilization unit, and adjusting the output power of one or more charging pile electricity utilization units at the target time according to the allocable electricity utilization capacity threshold and the priority.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and when the actual power load value of the building power utilization unit exceeds the building power load value is monitored at the target time, controlling the charging pile power utilization unit to reduce the actual output power. In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side; acquiring current power load data of the building power utilization unit, and predicting the building power utilization load of the building power utilization unit at a target time according to the current power load data and a pre-established power load prediction model; and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
In one embodiment, the computer program when executed by the processor further performs the steps of: collecting historical electricity load data of building electricity utilization units within a certain time period; and according to a deep learning algorithm, taking historical power load data as model training data to obtain a trained power load prediction model.
In one embodiment, when the computer program is executed by the processor to realize the calculation of the threshold value of the allocable electricity consumption capacity which can be allocated to the charging pile electricity consumption unit at the target time according to the building electricity consumption load and the threshold value of the transformer capacity, the following steps are specifically realized: acquiring a power consumption demand value of a power consumption unit of a charging pile at a target time; and calculating the allocable power consumption capacity threshold value of the power consumption unit of the charging pile at the target time according to the building power consumption load, the transformer capacity threshold value and the power consumption demand value.
In one embodiment, the computer program when executed by the processor further performs the steps of: and adjusting the output power of the charging unit of the charging pile at the target time according to the threshold value of the allocable power utilization capacity. In one embodiment, when the computer program is executed by the processor to realize the adjustment of the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically realized: the output power of the electric unit for charging is adjusted by switching the power gear of the electric unit for charging.
In one embodiment, when the computer program is executed by the processor to realize the adjustment of the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically realized: and uniformly adjusting the output power of each charging pile electricity utilization unit in the target time according to the distributable electricity utilization capacity threshold. In one embodiment, when the computer program is executed by the processor to realize the adjustment of the output power of the charging pile electricity utilization unit at the target time according to the threshold value of the allocable electricity utilization capacity, the following steps are specifically realized: and acquiring the priority of each charging pile electricity utilization unit, and adjusting the output power of one or more charging pile electricity utilization units at the target time according to the allocable electricity utilization capacity threshold and the priority.
In one embodiment, the computer program when executed by the processor further performs the steps of: and when the actual power load value of the building power utilization unit exceeds the building power load value is monitored at the target time, controlling the charging pile power utilization unit to reduce the actual output power.
It will be understood by those skilled in the art that all or part of the processes of the methods for implementing the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, the computer program can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A charging pile power capacity allocation method, the method comprising:
acquiring a transformer capacity threshold of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side;
acquiring current power load data of the building power consumption unit, and predicting the building power consumption load of the building power consumption unit at the target time according to the current power consumption load data and a pre-established power consumption load prediction model;
and calculating the allocable electricity utilization capacity threshold value allocable to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
2. The method according to claim 1, wherein the method for constructing the power load prediction model comprises:
collecting historical electricity load data of the building electricity utilization units within a certain time period;
and according to a deep learning algorithm, taking the historical power load data as model training data to obtain the trained power load prediction model.
3. The method of claim 1, wherein calculating the allocable electricity usage capacity threshold allocable to the charging post electricity usage unit at the target time based on the building electricity load and the transformer capacity threshold comprises:
acquiring a power consumption demand value of the power consumption unit of the charging pile at the target time;
and calculating the allocable electricity utilization capacity threshold value of the electricity utilization unit of the charging pile at the target time according to the building electricity utilization load, the transformer capacity threshold value and the electricity utilization demand value.
4. The method of claim 1, further comprising:
and adjusting the output power of the charging pile electricity utilization unit in the target time according to the allocable electricity utilization capacity threshold.
5. The method of claim 4, wherein one of the charging post power units comprises a plurality of power ranges, and wherein adjusting the output power of the charging post power unit at the target time based on the allocable capacity threshold comprises:
through switching the power that fills electric pile power consumption unit keeps off the position in order to adjust fill electric pile power consumption unit's output.
6. The method of claim 4, wherein adjusting the output power of the charging post power cell at the target time based on the allocable capacitance threshold comprises:
uniformly adjusting the output power of each charging pile electricity unit in the target time according to the allocable capacitance threshold; and/or the presence of a gas in the gas,
and acquiring the priority of each charging pile electricity utilization unit, and adjusting the output power of one or more charging pile electricity utilization units in the target time according to the allocable electricity utilization capacity threshold and the priority.
7. The method of claim 1, further comprising:
and if the actual power load value of the building power utilization unit exceeds the building power load value is monitored in the target time, controlling the charging pile power utilization unit to reduce the actual output power.
8. A charging pile power consumption capacity distribution device, characterized in that the device comprises:
the total power load acquisition module is used for acquiring a transformer capacity threshold value of a target area; the target area comprises a building power utilization unit at the building side and a charging pile power utilization unit at the charging pile side;
the building side electricity utilization prediction module is used for acquiring current electricity utilization load data of the building electricity utilization units and predicting the building electricity utilization loads of the building electricity utilization units at the target time according to the current electricity utilization load data and a pre-established electricity utilization load prediction model;
and the charging pile electricity utilization distribution module is used for calculating a distributable electricity utilization capacity threshold value which can be distributed to the charging pile electricity utilization unit at the target time according to the building electricity utilization load and the transformer capacity threshold value.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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