CN115411725A - Coordination control method and device for virtual power plant, electronic equipment and storage medium - Google Patents
Coordination control method and device for virtual power plant, electronic equipment and storage medium Download PDFInfo
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- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
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Abstract
The application provides a coordination control method and device of a virtual power plant, electronic equipment and a storage medium, wherein a power prediction function of an energy block is obtained according to an edge gateway, so that a master station is prevented from predicting the power of a plurality of energy blocks, a data processing task of the master station is shared through the edge gateway, and the data processing workload of the master station is reduced; by adding the number of the target energy blocks and the number of the users corresponding to the scheduling capacity into the target function of the coordination control model, when the target function takes the minimum value, the minimum target energy blocks and the users are selected according to the scheduling instruction, when the compensation value is constant, the compensation value obtained by distributing the target energy blocks and the users is the maximum, and the positivity of the target energy blocks and the users for responding to the scheduling instruction is increased.
Description
Technical Field
The application relates to the technical field of power system demand side response, in particular to a coordination control method and device for a virtual power plant, electronic equipment and a storage medium.
Background
With the proposal of a double-carbon target, the installed proportion of new energy power generation is continuously improved, and meanwhile, the intelligent level of the load of the power grid terminal is continuously improved, thereby bringing huge challenges and opportunities to the operation and maintenance of the power grid. The virtual power plant is a power supply coordination management system which integrates charging piles, air conditioners, energy storage and other power loads scattered at a user end through an energy internet technology and realizes coordination optimization so as to be used as a special power plant to participate in power grid operation and power market.
Generally, a demand side response function of a virtual power plant can realize real-time response to a scheduling instruction, but in a response process, a corresponding load scheduling strategy is made from the perspective of a power grid, the willingness of a user of an adjusted load to the load scheduling strategy is not considered, and in order to improve the enthusiasm of the user in response to the load scheduling strategy, a load scheduling strategy specifying method with the minimum load influence on the user and the maximum profit needs to be provided.
Disclosure of Invention
In view of the above, an object of the present application is to provide a method, an apparatus, an electronic device and a storage medium for coordinated control of a virtual power plant, so as to solve or partially solve the above technical problems.
In view of the above, a first aspect of the present application provides a coordination control method for a virtual power plant, where the method is applied to a master station of a virtual power plant system, and the virtual power plant system includes: the system comprises a master station, a plurality of edge gateways and a plurality of energy blocks, wherein the master station is in communication connection with the edge gateways, and each edge gateway in the edge gateways is in one-to-one corresponding communication connection with each energy block in the energy blocks; the method comprises the following steps:
in response to determining that a scheduling instruction is received, obtaining, by the edge gateway, a power prediction function for each of the plurality of energy blocks and sending the power prediction function to the master station, wherein the scheduling instruction comprises: target capacity, scheduling start time and scheduling end time;
inputting the scheduling command and the power prediction function into a pre-constructed coordination control model to obtain an energy block scheduling strategy,
wherein, the construction process of the coordination control model comprises the following steps: selecting at least one energy block from the plurality of energy blocks as a target energy block; determining the scheduling capacity of the target energy block through integration according to the power prediction function, wherein the scheduling capacity is greater than or equal to the target capacity; determining a compensation value and compensation capacity corresponding to the target capacity through multiplication according to a pre-stored compensation coefficient and the scheduling instruction; receiving a first weight, a second weight and a third weight;
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number h of the target energy block 0 The number of the users after normalization processing corresponding to the target energy block is obtained; in response to determining that the value of the target function corresponding to the target energy block and the compensation value is minimum, combining the compensation capacity and the target energy block as the energy scheduling policy;
and sending the energy block scheduling strategy to an edge gateway corresponding to a target energy block in the energy block scheduling strategy, wherein the energy block scheduling strategy is used for the edge gateway to control the output power of the corresponding target energy block.
A second aspect of the present application provides a coordinated control device of a virtual power plant, the device is installed in a master station of a virtual power plant system, the virtual power plant system includes: the system comprises a master station, a plurality of edge gateways and a plurality of energy blocks, wherein the master station is in communication connection with the edge gateways, and each edge gateway in the edge gateways is in one-to-one corresponding communication connection with each energy block in the energy blocks; the device comprises:
an obtaining module configured to obtain, by the edge gateway, a power prediction function for each of the plurality of energy blocks in response to determining that a scheduling instruction is received, and to transmit the power prediction function to the primary station, wherein the scheduling instruction includes: target capacity, scheduling start time and scheduling end time;
a coordination module configured to input the scheduling instruction and the power prediction function into a pre-constructed coordination control model to obtain an energy block scheduling policy,
wherein, the construction process of the coordination control model comprises the following steps: selecting at least one energy block from the plurality of energy blocks as a target energy block; determining a scheduling capacity of the target energy block by integration according to the power prediction function, wherein the scheduling capacity is greater than or equal to the target capacity;
determining a compensation value and compensation capacity corresponding to the target capacity through multiplication according to a pre-stored compensation coefficient and the scheduling instruction; receiving a first weight, a second weight and a third weight;
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number h of the target energy block 0 The number of the users after normalization processing corresponding to the target energy block is obtained; in response to determining that the target energy block and the value of the objective function corresponding to the compensation value are minimum, combining the compensation capacity and the target energy block as the energy scheduling policy;
a scheduling module configured to send the energy block scheduling policy to an edge gateway corresponding to a target energy block in the energy block scheduling policy, where the energy block scheduling policy is used for the edge gateway to control output power of the corresponding target energy block.
A third aspect of the application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of the first aspect when executing the program.
A fourth aspect of the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of the first aspect.
From the above, according to the coordination control method, the coordination control device, the electronic device and the storage medium of the virtual power plant, the power prediction function of the energy blocks is obtained according to the edge gateway, so that the power prediction of a master station on a plurality of energy blocks is avoided, the data processing task of the master station is shared through the edge gateway, and the data processing workload of the master station is reduced; by adding the number of the target energy blocks and the number of the users corresponding to the scheduling capacity into the target function of the coordination control model, when the target function takes the minimum value, the minimum target energy blocks and the users are selected according to the scheduling instruction, so that the compensation value obtained by the target energy blocks and the users is the maximum when the compensation value is constant, and the positivity of the target energy blocks and the users for responding to the scheduling instruction is increased.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the related art, the drawings needed to be used in the description of the embodiments or the related art will be briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of a virtual power plant system;
FIG. 2a is a schematic flow chart of a coordination control method of a virtual power plant according to an embodiment of the present application;
FIG. 2b is an expanded view of step 202;
FIG. 3 is a schematic structural diagram of a coordination control device of a virtual power plant according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings in combination with specific embodiments.
It should be noted that technical terms or scientific terms used in the embodiments of the present application should have a general meaning as understood by those having ordinary skill in the art to which the present application belongs, unless otherwise defined. The use of "first," "second," and similar terms in the embodiments of the present application is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
As described in the background, the virtual power plant system 100 is shown in fig. 1, and the virtual power plant system 100 includes a primary station 101, a plurality of edge gateways (e.g., edge gateway 102, edge gateway 103, edge gateway 104), and a plurality of energy blocks (e.g., energy block 105, energy block 106, energy block 107), where the primary station 101 is communicatively coupled to the plurality of energy blocks (e.g., the primary station 101 is communicatively coupled to the edge gateway 102, the edge gateway 103, and the edge gateway 104), and each of the plurality of edge gateways is communicatively coupled to each of the plurality of energy blocks (e.g., the edge gateway 102 is communicatively coupled to the energy block 105, the edge gateway 103 is communicatively coupled to the energy block 106, and the edge gateway 104 is communicatively coupled to the energy block 107).
The master station 101 receives the scheduling instruction, constructs an energy block scheduling strategy according to the scheduling instruction, and sends the energy block scheduling strategy to an edge gateway connected with a target energy block in the energy block scheduling strategy, and the edge gateway controls the output power of the energy block according to the scheduling instruction in the energy scheduling strategy. For example, when the load curve in the power grid has a peak, a part of the load needs to be reduced to ensure the stable operation of the power system. At this time, the master station 101 receives a scheduling instruction sent by the power grid as an instruction in a peak clipping scene, and the master station 101 selects a target energy block from the plurality of energy blocks according to a load power reduction amount within a period of time corresponding to the peak clipping instruction, and sends the load power reduction amount within the period of time to an edge gateway connected to the target energy block. And after the edge gateway controls the target energy block to cut off the corresponding electric load, calculating the compensation electric charge of the energy block given by the power grid according to the electric quantity reduced by the target energy block in the process of responding to the peak clipping instruction.
Therefore, an energy block scheduling strategy with low compensation electricity charge and small target energy block number is needed to complete the response of the scheduling command, the low compensation electricity charge represents that the resource cost needed by the response of the scheduling command is low, the small target energy block number represents that the compensation electricity charge averagely obtained by the target energy block is large under the condition of certain compensation electricity charge, namely the average income obtained by the target energy block is maximum, and the energy block scheduling strategy is favorable for exciting other energy blocks to be added into a virtual power plant system responding to the scheduling command, so that the working efficiency of the virtual power plant system for expanding the schedulable capacity is improved, and the ground application of the virtual power plant system is effectively promoted.
In view of this, embodiments of the present application provide a coordination control method and apparatus for a virtual power plant, an electronic device, and a storage medium, which may be applied to response of a scheduling instruction in a virtual power plant system.
As shown in fig. 2a, the method of the embodiment is applied to a master station of a virtual power plant system, where the virtual power plant system includes: the energy block management system comprises a main station, a plurality of edge gateways and a plurality of energy blocks, wherein the main station is in communication connection with the edge gateways, and each edge gateway in the edge gateways is in one-to-one corresponding communication connection with each energy block in the energy blocks. The method of the embodiment comprises the following steps:
In this step, the scheduling instruction refers to an instruction for power adjustment, and a preferred scheduling instruction in this embodiment may be an instruction for adjusting output power of an energy block, including: the target capacity, the scheduling start time and the scheduling end time can be obtained by integrating the output power with time, so that the output power required to be adjusted can be calculated according to the target capacity, the scheduling start time and the scheduling end time of the scheduling instruction. The edge gateway refers to a gateway device capable of communicating with the master station and controlling the energy block, and the edge gateway in this embodiment may be a gateway device installed on one side of the energy block and capable of communicating with the master station and controlling the energy block.
The energy block refers to an object capable of responding to a scheduling command, and the preferred energy block of the embodiment may be a virtual power plant capable of responding to the scheduling command, for example, the energy block may be an office building including a schedulable load, wherein the schedulable load includes an air conditioner for accumulating cold through a phase change material and an electrically driven air conditioner. When the energy block needs to respond to the peak clipping scheduling instruction, the refrigerating capacity of electrically driven air conditioning equipment in the office building is replaced by the refrigerating capacity of phase change material cold accumulation, so that the electricity consumption of the office building is reduced, and the response of the energy block to the peak clipping scheduling instruction is realized; when the valley filling dispatching instruction needs to be responded, the electric energy is converted into the cold accumulation energy of the phase change material in the cold accumulation equipment.
The power prediction function refers to a function of the change of the power of the energy block in response to the scheduling command with time, and the preferred power prediction function of this embodiment may be a function of the change of the active power of the energy block in response to the scheduling command with time.
as shown in fig. 2b, the process of constructing the coordination control model includes:
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number h of the target energy block 0 The number of the users after normalization processing corresponding to the target energy block is obtained;
In this step, the target energy block refers to an energy block that changes output power according to the scheduling command, and a preferred target energy block in this embodiment may be an energy block that changes output active power according to the scheduling command. The scheduling capacity refers to an upper limit of a capacity of an energy block change in response to a scheduling command, and a preferred scheduling capacity of the present embodiment may be an upper limit of a capacity of a target energy block change in response to a scheduling command. The compensation capacity refers to a value of the target energy block sharing target capacity, and the preferred compensation capacity of the embodiment may be a value of the target energy block sharing target capacity in the virtual power plant system.
The compensation coefficient refers to a coefficient for measuring the loss of the energy block in response to the scheduling command, and the preferred compensation coefficient in this embodiment may be a coefficient for measuring the loss of the energy block in response to the scheduling command by the sender of the scheduling command. The compensation value refers to a value for measuring the loss of the energy block in response to the scheduling command, and the preferred compensation coefficient in this embodiment may be the resource cost of the scheduling command sender for measuring the loss of the energy block in response to the scheduling command.
The first weight, the second weight and the third weight can realize the effect of adjusting the compensation value, the number of target energy blocks and the number of users on the target function, and the preferred first weight, the second weight and the third weight of the embodiment can be 0.2, 0.4 and 0.4, so that the target energy block with the least number can be selected in the energy block scheduling strategy, and therefore when the compensation value is constant, the compensation value distributed by the target energy block and the users is the largest, and the positivity of the target energy block and the users for responding to the scheduling instruction is increased.
The normalization processing refers to converting the compensation value, the number of target energy blocks and the number of users into decimal numbers between (0, 1), so that the influence of different orders of magnitude among the compensation value, the number of target energy blocks and the number of users on the calculation of the target function is avoided.
Specifically, in the process of calculating the energy block scheduling strategy by using the coordination control model, the maximum compensation value C corresponding to the target energy block is obtained max And the minimum compensation value C min Then, the formula for performing normalization processing on the compensation value C of the energy block scheduling policy is: c 0 ＝(C-C min )/(C max -C min ) (ii) a Obtaining the maximum number k of target energy blocks max And a minimum number k min Then, the formula for normalizing the number k of the target energy blocks of the energy block scheduling policy is as follows: k is a radical of formula 0 ＝(k-k min )/(k max -k min ) (ii) a Obtaining the maximum user number h of the target energy block max And a minimum number h of users min Then, the formula for normalizing the number h of users of the energy block scheduling policy is as follows: h is a total of 0 ＝(h-h min )/(h max -h min )。
In this step, the output power refers to the power consumption of the energy block under the control of the edge gateway, and the preferred output power of this embodiment may be the active power of the target energy block under the control of the edge gateway.
According to the scheme, the power prediction function of the energy blocks is obtained according to the edge gateway, so that the power prediction of a master station on a plurality of energy blocks is avoided, the data processing task of the master station is shared through the edge gateway, and the data processing workload of the master station is reduced; by adding the number of the target energy blocks and the number of the users corresponding to the scheduling capacity into the target function of the coordinated control model, when the target function takes the minimum value, the minimum target energy blocks and the users are selected according to the scheduling instruction, so that the compensation value obtained by the target energy blocks and the users is the maximum when the compensation value is fixed, and the positivity of the target energy blocks and the users for responding to the scheduling instruction is increased.
In some embodiments, said determining the scheduling capacity of the target energy block by integration according to the power prediction function comprises:
calculating the scheduling capacity according to:
wherein E is the scheduling capacity, P i (t) is the power prediction function of the ith target energy block, t 0 For scheduling start time, t, in scheduling instructions 1 And k is the scheduling ending time in the scheduling instruction, and the number of the target energy blocks is K.
In the above solution, the power prediction function refers to a function of a change of power of the energy block in response to the scheduling command with time, and the preferred power prediction function in this embodiment may be a function of a change of active power of the energy block in response to the scheduling command with time.
Through the scheme, a basis is provided for the calculation of the compensation value in the subsequent objective function.
In some embodiments, the determining the scheduling capacity of the target energy block by integrating according to the power prediction function further comprises:
in response to determining that the number of target energy blocks is 1, calculating the scheduling capacity according to:
where E is the scheduling capacity, P (t) is the power prediction function of the target energy block, t 0 For the scheduling start time, t, in the scheduling instruction 1 Is the scheduling end time in the scheduling instruction.
In the above scheme, since the number of the target energy blocks is 1, it is necessary to consider the number of users in the energy blocks so that the average compensation value obtained by the users in the energy blocks is the largest. For example, the energy block is a load aggregator, that is, the energy block includes a plurality of loads, each of the plurality of loads corresponds to a user one by one, and in order to increase the enthusiasm of the user for participating in the virtual power plant system, an energy block scheduling strategy making model that maximizes the average compensation value of the user needs to be adopted.
Through the scheme, a basis is provided for the calculation of the compensation value in the subsequent objective function.
In some embodiments, the determining a compensation value and a compensation capacity corresponding to the target capacity by multiplying the pre-stored compensation coefficient and the scheduling instruction includes:
calculating the compensation value according to the following formula:
wherein C is the compensation value, d i Compensation factor for the ith target energy block, D i A compensation capacity allocated for the ith target energy block according to the target capacity,
and is
R is the target capacity.
In the scheme, in order to improve the positivity of the target energy block participating in the response of the scheduling instruction, the scheduling instruction sender stores the compensation coefficients of a plurality of energy blocks in advance, and calculates the compensation value of the target energy block according to the compensation coefficients. For example, the target energy block is reduced by a compensation factor of 0.1 for 1kWh of power usage. The compensation value refers to a value for measuring the loss of the energy block in response to the scheduling command, and the preferred compensation value in this embodiment may be a value for measuring the loss of the energy block in response to the scheduling command by the scheduling command sender, for example, the compensation value for reducing the energy block by 3kWh is 0.3.
For example, the scheduling instruction is 5MW, the scheduling capacity of 3 target energy blocks is 8MW, where the integral of the power prediction function corresponding to the 1 st target energy block is 4MW, the integral of the power prediction function corresponding to the 2 nd target energy block is 3MW, and the integral of the power prediction function corresponding to the 3 rd target energy block is 1MW, then the compensation capacity of the 1 st target energy block is selected to be 2MW, and the compensation capacity of the 2 nd target energy block is selected to be 3MW.
Through the scheme, a basis is provided for the calculation of the subsequent objective function.
In some embodiments, step 2021 specifically comprises:
and selecting at least one energy block as the target energy block from low to high according to the compensation coefficients corresponding to the plurality of energy blocks.
Through the scheme, the coordination control model can pre-select the energy block with a lower compensation coefficient as the target energy block, so that the convergence process of solving the minimum value of the target function is accelerated.
In some embodiments, step 2021 specifically further includes:
and selecting at least one energy block as the target energy block from low to high according to the power supply priority corresponding to the energy blocks.
In the above scheme, the power supply priority refers to a priority corresponding to the power loads in the energy block, and the preferred power supply priority in this embodiment may be a priority corresponding to the power loads in the energy block in the virtual power plant system, for example, the power supply priority may be the power loads ranked according to the user comfort level, the power supply priority of the air conditioner load in the mall is higher than the power supply priority of the water heater load in the office building, the scheduling instruction of the water heater short-time power-off response peak clipping is passed through, the scheduling instruction of the market air conditioner short-time power-off response peak clipping is passed through, and the former has a smaller influence on the user comfort level than the latter.
Through the scheme, the coordination control model can pre-select the energy block with low power supply priority as the target energy block, so that the power supply influence of the response scheduling command on the energy block is reduced, and the rationality of selecting the target energy block is improved.
In some embodiments, step 2021 specifically further includes:
and at least one energy block is selected as the target energy block from at least according to the historical response regulation and control times corresponding to the energy blocks.
In the above scheme, in order to increase the success rate of the target energy block responding to the scheduling instruction, the historical response scheduling times of the plurality of energy blocks may be counted, and the energy block with the larger historical response regulation times is selected as the target energy block.
Through the scheme, the coordination control model can pre-select the energy blocks with large historical response air-conditioning times as the target energy blocks, and the possibility of the target energy blocks responding to the scheduling instructions is increased.
It should be noted that the method of the embodiment of the present application may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment, and the multiple devices interact with each other to complete the method.
It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Based on the same inventive concept, the following embodiments can be implemented based on the corresponding embodiments of the methods of the above embodiments.
Step 1, the master station receives the scheduling instruction to reduce the load by 5MW for the next hour.
And 2, acquiring the power prediction function of the corresponding energy block by the 5 edge gateways connected with the master station.
Step 3, the integration result of the pre-stored compensation coefficients and power prediction functions of 5 energy blocks in the next hour is shown as the scheduling capacity of the energy blocks in table 1:
TABLE 1 Compensation coefficients and Power prediction function for energy blocks
| Serial number | Number 1 | Number 2 | No. 3 | Number 4 | Number 5 |
| Compensation coefficient (Yuan/MW) | 100 | 400 | 300 | 120 | 125 |
| Energy block dispatch capacity (MW) | 1 | 4 | 7 | 6 | 5 |
And 4, according to the sequencing of the power supply priority and the number of times of historical response regulation and control, the No. 1-5 energy blocks can be used as target energy blocks to be selected.
Step 5, selecting a target energy block according to the compensation coefficient sequence, selecting No. 1 No. 5 as the target energy block, or selecting No. 4 as the target energy block, or selecting No. 1 No. 5 as the target energy block, and if the regulation and control capacity 12MW is greater than or equal to the regulation and control instruction 5MW, then a scheduling strategy 1 can be constructed as follows: the compensation capacity regulated by the No. 1 energy block is 1MW, the compensation capacity regulated by the No. 5 energy block is 4MW, the compensation capacity regulated by the No. 4 energy block is 5MW for the scheduling policy 2, and the scheduling policy 3 is as follows: energy block No. 1 regulates 1MW and energy block No. 4 regulates a compensation capacity of 4MW. At this time, the backoff values of scheduling policy 1 and scheduling policy 2 are equal, but the average backoff value of energy blocks of scheduling policy 1 is 300 bins, and the average backoff value of energy blocks of scheduling policy 2 is 600 bins. In the popularization stage of the virtual power plant system, in order to attract more energy blocks to be added into the virtual power plant system, the scheduling strategy with the high average compensation value of the energy blocks is beneficial to increasing the enthusiasm of the energy blocks for receiving virtual power plant scheduling.
Step 6, maximum compensation value C of target energy block max＝ 1000 with minimum offset value of C min ＝580Maximum number of target energy blocks k max =5, minimum number k min =1, since the number of target energy blocks is greater than 1, the number of users is 0.
Step 7, scheduling the objective function value F of the strategy 1 1 =0.2 × 20/420+0.4 × 1/4=0.034, objective function value F of scheduling policy 2 2 =0.009, objective function value F of scheduling policy 3 3 =0.025, so scheduling policy 2 is selected as the energy block scheduling policy to be finally executed.
The coordination control method of the virtual power plant in the above embodiment has the beneficial effects of the coordination control method of the virtual power plant in any of the foregoing embodiments, and details are not repeated here.
Based on the same inventive concept, corresponding to the method of any embodiment, the application also provides a coordination control device of the virtual power plant.
Referring to fig. 3, the coordination control apparatus of the virtual power plant includes:
an obtaining module 301 configured to, in response to determining that a scheduling instruction is received, obtain, by the edge gateway, a power prediction function of each energy block of the plurality of energy blocks and transmit the power prediction function to the primary station, where the scheduling instruction includes: target capacity, scheduling start time and scheduling end time;
a coordination module 302 configured to input the scheduling instruction and the power prediction function into a pre-constructed coordination control model to obtain an energy block scheduling policy,
wherein, the construction process of the coordination control model comprises the following steps: selecting at least one energy block from the plurality of energy blocks as a target energy block; determining a scheduling capacity of the target energy block by integration according to the power prediction function, wherein the scheduling capacity is greater than or equal to the target capacity; determining a compensation value and compensation capacity corresponding to the target capacity through multiplication according to a pre-stored compensation coefficient and the scheduling instruction; receiving a first weight, a second weight and a third weight;
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number of the target energy blocks, h 0 The number of the users after normalization processing corresponding to the target energy block is obtained; in response to determining that the target energy block and the value of the objective function corresponding to the compensation value are minimum, combining the compensation capacity and the target energy block as the energy scheduling policy;
a scheduling module 303 configured to send the energy block scheduling policy to an edge gateway corresponding to a target energy block in the energy block scheduling policy, where the energy block scheduling policy is used for the edge gateway to control output power of the corresponding target energy block.
In some embodiments, the coordination module 302 is specifically configured to:
calculating the scheduling capacity according to:
wherein E is the scheduling capacity, P i (t) is the power prediction function of the ith target energy block, t 0 For scheduling the start time, t, in the instruction 1 And k is the scheduling ending time in the scheduling instruction, and the number of the target energy blocks is K.
In some embodiments, the coordination module 302 is further specifically configured to:
in response to determining that the number of target energy blocks is 1, calculating the scheduling capacity according to:
wherein E is the scheduling capacity, P (t)) A power prediction function for the target energy block, t 0 For the scheduling start time, t, in the scheduling instruction 1 And the scheduling end time in the scheduling instruction is used.
In some embodiments, the coordination module 302 is further specifically configured to:
calculating the compensation value according to the following formula:
wherein C is the compensation value, d i Compensation coefficient for the ith target energy block, D i Allocating compensation capacity for the ith target energy block according to the target capacity,
and is
R is the target capacity.
In some embodiments, the coordination module 302 is further specifically configured to:
and selecting at least one energy block as the target energy block from low to high according to the compensation coefficients corresponding to the plurality of energy blocks.
In some embodiments, the coordination module 302 is further specifically configured to:
and selecting at least one energy block as the target energy block according to the power supply priorities corresponding to the energy blocks from low to high.
In some embodiments, the coordination module 302 is further specifically configured to:
and at least one energy block is selected as the target energy block from at least according to the historical response regulation and control times corresponding to the energy blocks.
For convenience of description, the above devices are described as being divided into various modules by functions, which are described separately. Of course, the functionality of the various modules may be implemented in the same one or more pieces of software and/or hardware in the practice of the present application.
The device of the above embodiment is used for implementing the coordination control method of the virtual power plant in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.
Based on the same inventive concept, corresponding to the method of any embodiment, the application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the program, the coordination control method of the virtual power plant according to any embodiment is implemented.
Fig. 4 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via a bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called by the processor 1010 for execution.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (for example, USB, network cable, etc.), and can also realize communication in a wireless mode (for example, mobile network, WIFI, bluetooth, etc.).
The bus 1050 includes a path to transfer information between various components of the device, such as the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040.
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only the components necessary to implement the embodiments of the present disclosure, and need not include all of the components shown in the figures.
The electronic device of the foregoing embodiment is used for implementing the coordination control method of the virtual power plant in any one of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described again here.
Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application further provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the coordination control method of the virtual power plant according to any of the above embodiments.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the coordination control method for the virtual power plant according to any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which are not described herein again.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the context of the present application, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of brevity.
In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures for simplicity of illustration and discussion, and so as not to obscure the embodiments of the application. Further, devices may be shown in block diagram form in order to avoid obscuring embodiments of the application, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the application are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the application, it should be apparent to one skilled in the art that the embodiments of the application can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present application has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures, such as Dynamic RAM (DRAM), may use the discussed embodiments.
The present embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalents, improvements, and the like that may be made without departing from the spirit or scope of the embodiments of the present application are intended to be included within the scope of the claims.
Claims (10)
1. A coordination control method of a virtual power plant is characterized in that the method is applied to a main station of a virtual power plant system, and the virtual power plant system comprises the following steps: the system comprises a master station, a plurality of edge gateways and a plurality of energy blocks, wherein the master station is in communication connection with the edge gateways, and each edge gateway in the edge gateways is in one-to-one corresponding communication connection with each energy block in the energy blocks; the method comprises the following steps:
in response to determining that a scheduling instruction is received, obtaining, by the edge gateway, a power prediction function for each of the plurality of energy blocks and sending the power prediction function to the primary station, wherein the scheduling instruction comprises: target capacity, scheduling start time and scheduling end time;
inputting the scheduling command and the power prediction function into a pre-constructed coordination control model to obtain an energy block scheduling strategy,
wherein, the construction process of the coordination control model comprises the following steps: selecting at least one energy block from the plurality of energy blocks as a target energy block; determining a scheduling capacity of the target energy block by integration according to the power prediction function, wherein the scheduling capacity is greater than or equal to the target capacity; determining a compensation value and compensation capacity corresponding to the target capacity through multiplication according to a pre-stored compensation coefficient and the scheduling instruction; receiving a first weight, a second weight and a third weight;
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number of target energy blocks, h 0 The number of the users after normalization processing corresponding to the target energy block is obtained; in response to determining that the value of the target function corresponding to the target energy block and the compensation value is minimum, combining the compensation capacity and the target energy block as the energy scheduling policy;
and sending the energy block scheduling strategy to an edge gateway corresponding to a target energy block in the energy block scheduling strategy, wherein the energy block scheduling strategy is used for the edge gateway to control the output power of the corresponding target energy block.
2. The method of claim 1, wherein the determining the scheduling capacity of the target energy block by integrating according to the power prediction function comprises:
calculating the scheduling capacity according to:
wherein E is the scheduling capacity, P i (t) is the power prediction function of the ith target energy block, t 0 For scheduling start time, t, in scheduling instructions 1 And k is the scheduling ending time in the scheduling instruction, and the number of the target energy blocks is k.
3. The method of claim 2, wherein the determining the scheduling capacity of the target energy block by integrating according to the power prediction function further comprises:
in response to determining that the number of target energy blocks is 1, calculating the scheduling capacity according to:
where E is the scheduling capacity, P (t) is the power prediction function of the target energy block, t 0 Is a scheduling start time, t, in the scheduling instruction 1 Is the scheduling end time in the scheduling instruction.
4. The method of claim 2, wherein determining the compensation value and the compensation capacity corresponding to the target capacity by multiplying the pre-stored compensation coefficient and the scheduling command comprises:
calculating the compensation value according to:
wherein C is the compensation value, d i Compensation factor for the ith target energy block, D i A compensation capacity allocated for the ith target energy block according to the target capacity,
and is
And R is the target capacity.
5. The method of claim 4, wherein the selecting at least one energy block from the plurality of energy blocks as the target energy block comprises:
and selecting at least one energy block as the target energy block according to the compensation coefficients corresponding to the plurality of energy blocks from low to high.
6. The method of claim 1, wherein the selecting at least one energy block from the plurality of energy blocks as the target energy block further comprises:
and selecting at least one energy block as the target energy block according to the power supply priorities corresponding to the energy blocks from low to high.
7. The method of claim 1, wherein the selecting at least one energy block from the plurality of energy blocks as the target energy block further comprises:
and at least one energy block is selected as the target energy block from at least according to the historical response regulation and control times corresponding to the energy blocks.
8. A coordinated control device of a virtual power plant, characterized in that the device is installed in a main station of a virtual power plant system, the virtual power plant system comprises: the system comprises a master station, a plurality of edge gateways and a plurality of energy blocks, wherein the master station is in communication connection with the plurality of edge gateways, and each edge gateway in the plurality of edge gateways is in one-to-one corresponding communication connection with each energy block in the plurality of energy blocks; the device comprises:
an obtaining module configured to obtain, by the edge gateway, a power prediction function of each energy block of the plurality of energy blocks in response to determining that a scheduling instruction is received, and send the power prediction function to the master station, wherein the scheduling instruction includes: target capacity, scheduling start time and scheduling end time;
a coordination module configured to input the scheduling instruction and the power prediction function into a pre-constructed coordination control model to obtain an energy block scheduling policy,
wherein, the construction process of the coordination control model comprises the following steps: selecting at least one energy block from the plurality of energy blocks as a target energy block; determining a scheduling capacity of the target energy block by integration according to the power prediction function, wherein the scheduling capacity is greater than or equal to the target capacity; determining a compensation value and compensation capacity corresponding to the target capacity through multiplication according to a pre-stored compensation coefficient and the scheduling instruction; receiving a first weight, a second weight and a third weight;
calculating an objective function of the coordinated control model according to:
F＝α·C 0 +β·k 0 +γ·h 0 ，
wherein F is the objective function, α is the first weight, β is the second weight, γ is the third weight, α + β + γ =1, C 0 To normalize the processed compensation value, k 0 Is the normalized number of the target energy blocks, h 0 The number of the users after normalization processing corresponding to the target energy block is obtained; in response to determining that the target energy block and the value of the objective function corresponding to the compensation value are minimum, combining the compensation capacity and the target energy block as the energy scheduling policy;
a scheduling module configured to send the energy block scheduling policy to an edge gateway corresponding to a target energy block in the energy block scheduling policy, where the energy block scheduling policy is used for the edge gateway to control output power of the corresponding target energy block.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable by the processor, the processor implementing the method of any one of claims 1 to 7 when executing the computer program.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 7.
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