CN115207917A - Layered-distributed multi-target tracking method and system for virtual power plant - Google Patents
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Abstract
The invention discloses a layered-distributed multi-target tracking method and a layered-distributed multi-target tracking system for a virtual power plant, and relates to the technical field of operation and control of power systems. Based on a multi-objective optimization model of a virtual power plant, a layered-distributed implementation method of the model is designed. The virtual power plant control center is responsible for making coordination information, and each distributed energy local controller is responsible for making a distributed energy control signal for local control, namely each distributed energy controller makes independent and parallel decisions. Meanwhile, a control signal of distributed energy single control is obtained based on a decoupling calculation mode of a coordination variable and a control solution, and the purpose is to accelerate the control speed and reduce the single response time. The method finally realizes the quick and accurate tracking of the virtual power plant on the optimal running state under various optimization targets.
Description
Technical Field
The invention relates to the technical field of operation and control of power systems, in particular to a layered-dispersed multi-target tracking method and system for a virtual power plant.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
The permeability of renewable distributed energy resources is improved year by year, and in order to promote the consumption and safe and reliable grid connection, the organization of the multi-element distributed energy resources into a virtual power plant is one of the ways for realizing the effective regulation and control of the virtual power plant. Specifically, the virtual power plant can control the internal distributed energy to run in a coordinated manner, no specific requirements are placed on the geographic position of the distributed energy, and the like, the virtual power plant is a distributed energy regulation and control mode with strong flexibility, high adaptability and good economical efficiency, and the non-patent document 1 utilizes the virtual power plant to perform peak-shaving frequency modulation service.
The virtual power plant is merged into an upper power grid to receive a dispatching instruction of the upper power grid, and the accurate tracking of the dispatching instruction of the upper power grid is one of the optimization targets of the virtual power plant. Currently, the virtual power plant regulates the output of distributed energy sources therein to track the optimization target in a centralized, distributed and decentralized manner. Non-patent document 2 discloses a centralized target tracking method, but the centralized target tracking method faces the threat of single-point failure, and the reliability is weak. Distributed and decentralized are currently the more prevalent implementations. However, the traditional distributed and scattered target tracking methods have the defects of low speed, incapability of fully considering a plurality of optimization targets and unsatisfactory tracking and response effects on the operation of a plurality of operation targets. Therefore, how to efficiently and highly accurately realize multi-objective optimization and track the multi-objective optimization result in the virtual power plant becomes a problem to be solved urgently in the existing virtual power plant objective optimization process.
Li Jia Mei, ai Qian, yingshui Rui the market mechanism of the virtual power plant participating in the peak-regulating and frequency-modulating service and the foreign experience are used for reference [ J ]. China Motor engineering newspapers, 2022,42 (1): 19.
Non-patent document 2, a distributed saddle point dynamic solution [ J ] containing the optimal power flow of a high-photovoltaic infiltration power distribution network, a report of electrical engineering in china, 2019, 39 (02): 459-468+643.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a layered-distributed multi-target tracking method and a layered-distributed multi-target tracking system for a virtual power plant. The multi-target tracking model comprises an accurate response target and an economic operation target of the multi-target tracking model. In the layered-distributed architecture, the upper layer is a virtual power plant control center, and the lower layer is each controllable distributed energy local controller. And the virtual power plant control center formulates coordination information and broadcasts the coordination information to each distributed energy local controller, and then each distributed energy local controller independently and parallelly formulates a local control decision and controls the local control decision. The algorithm is realized based on a Lagrange gradient descent method, and finally, the realization steps of the layered-dispersed multi-target tracking method of the virtual power plant are given.
In order to achieve the purpose, the invention is realized by the following technical scheme:
the first aspect of the disclosure provides a layered-distributed multi-target tracking method for a virtual power plant, which includes the following steps:
collecting target parameters of distributed energy;
establishing a target function of multi-target tracking by using the target parameters;
implementing multi-target tracking according to a target function of the multi-target tracking, and judging a response state to a superior power grid dispatching instruction and measuring a self running state;
and updating the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state.
Further, the target parameters of the distributed energy resource include: the active power demand value of the upper-level power grid, the active power actually injected into the upper-level power grid by the virtual power plant, and the active power and the reactive power output by each distributed energy source participating in scheduling.
Further, the objective function of the multi-target tracking is as follows:
in the formula: the superscript t of the variable represents the time t; p is i t 、
Outputting active power and reactive power set values for the distributed energy connected to the node i; subscript i of the variable is a node label; the first item in the formula is an economic target, and the second item and the third item are targets for responding to superior power grid dispatching instructions;
is the actual power vector of the virtual power plant and the connection point of the superior power grid,
scheduling instruction vectors of the virtual power plant for the superior power grid; c. C 1 And c 2 Are weight coefficients.
Further, the constraint conditions of the objective function of the multi-target tracking are as follows: the distributed energy output power adjustable range constraint, the safety constraint and the network constraint.
Further, the coordination signal is immediately executed upon update.
The second aspect of the present disclosure provides a virtual power plant layered-distributed multi-target tracking system, including:
a parameter acquisition module configured to acquire a target parameter of the distributed energy resource;
the establishing target function module is configured to establish a target function of the multi-target tracking by using the target parameters;
the multi-target tracking module is configured to implement multi-target tracking according to a target function of the multi-target tracking, judge a response state to a superior power grid dispatching instruction and measure a self running state;
and the coordination signal updating module is configured to update the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state.
The system further comprises a virtual power plant control center and controllable distributed energy local controllers, wherein the virtual power plant control center is used for receiving the scheduling instruction and transmitting the scheduling instruction to each controllable distributed energy local controller.
Furthermore, the virtual power plant control center is also used for receiving dispatching instruction response feedback and self running state feedback.
A third aspect of the present disclosure provides a medium having a program stored thereon, the program, when executed by a processor, implementing the steps in the virtual power plant layered-decentralized multi-target tracking method according to the first aspect of the present disclosure.
A fourth aspect of the present disclosure provides an apparatus comprising a memory, a processor, and a program stored on the memory and executable on the processor, the processor implementing the steps of the virtual power plant layered-decentralized multi-target tracking method as described in the first aspect of the present disclosure when executing the program.
The beneficial effects of the above-mentioned embodiment of the present invention are as follows:
the layered-distributed multi-target tracking method for the virtual power plant has the advantages that the current situation of a non-single optimization target in the operation of the virtual power plant is fully considered, and the tracking and response of multiple operation targets can be simultaneously met. By adopting a layered-decentralized tracking architecture and mode, the problem size needing to be processed by each part can be reduced. And the decoupling calculation mode of the coordination variables and the control decisions accelerates the single control speed. The above two points both accelerate the target tracking speed. Meanwhile, real-time measurement data of the operation state of the virtual power plant are introduced into the framework, so that the error of a theoretical value can be corrected, and the accuracy is improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a schematic diagram of a framework of a layered-distributed multi-target tracking method for a virtual power plant according to an embodiment of the present invention.
The specific implementation mode is as follows:
it should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof;
the first embodiment is as follows:
the embodiment of the disclosure provides a layered-distributed multi-target tracking method for a virtual power plant, as shown in fig. 1, including the following steps:
the method comprises the following steps:
and collecting target parameters of the distributed energy.
Preferably, the target parameters of the distributed energy sources include the active power demand value of the upper-level power grid, the active power actually injected into the upper-level power grid by the virtual power plant, and the output active power and the reactive power of each distributed energy source participating in scheduling. The normal operation state of the virtual power plant communication equipment is measured and obtained through the existing distributed energy output power measuring device.
Establishing a target function of multi-target tracking by using the target parameters:
in the formula: the superscript t of the variable represents the time t; p i t 、
Outputting active power and reactive power set values for the distributed energy connected to the node i; subscript i of the variable is a node label; the first term in the formula is the economic objective, f i t Representing an economic objective function. The second item and the third item are objects for responding to the superior power grid dispatching instruction;
is the actual power vector of the virtual power plant and the superior power grid connection point,
scheduling instruction vectors of the virtual power plant for the superior power grid; c. C 1 And c 2 Are weight coefficients.
Preferably, the constraint condition satisfied by equation (1) is:
1) And (3) restricting the adjustable range of the output power of the distributed energy:
2) Safety restraint:
3) Network constraint:
v＝h(P,Q) (4)
in the formula: g respectively represents a set of nodes connected with distributed energy resources; m is a set of nodes with metrology devices;
and
the node voltage amplitude and the upper limit and the lower limit of the node voltage amplitude of the node i;
the output power of the distributed energy source connected to the node i can be adjusted within a range; v is a virtual power plant node voltage vector; p and Q are respectively active power and reactive power vectors injected into the virtual power plant node; equation (4) is a power flow equation.
Implementing multi-target tracking according to a target function of the multi-target tracking, judging a response state to a superior power grid dispatching instruction and measuring an operation state of the superior power grid dispatching instruction; and updating the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state. In the present embodiment, the self-running state is the economy running condition.
Preferably, the following steps are performed to accomplish multi-target tracking:
step 1: at the moment t, the virtual power plant control center receives a dispatching instruction of a superior power grid
Constructing an objective function comprising a plurality of targets according to the economic requirement of self operation;
step 2: and transmitting collectable measurement information in the virtual power plant to a virtual power plant control center in real time.
And step 3: and the virtual power plant control center judges the accuracy of response to the higher-level power grid dispatching instruction according to the last two items in the target function and measures the self-running state at the moment according to the first item in the target function according to the real-time measurement information. And if the response deviation of the dispatching command to the superior power grid is larger than an allowable value, or the running economy is poor, or both the allowable value and the running economy are poor, starting an updating coordination signal. The coordination signal is updated by the following formula:
in the formula: proj Ω { x } represents finding the point in the domain Ω that is closest to x; wherein, the first and the second end of the pipe are connected with each other,
x＝u t′ +αΔu t and | u | represents the dimension of the coordination signal u; t' represents the last time; u. of t And u t′ Respectively representing coordination signals at the t moment and the t' moment, wherein alpha is a step length; Δ u t The method is used for measuring the running state of the virtual power plant according to the measurement information received at the moment t and combining the correction quantity of the coordination signal formulated by the dispatching instruction of the superior power grid.
And 4, step 4: and broadcasting the updated coordination signal to each distributed energy local controller.
And 5: each distributed energy local controller receives the local real-time measurement information and the coordination signal, and updates the output power of the controlled distributed energy according to the following formula. Once updated, the output power is used as a control instruction to control the distributed energy resource to execute, and the node injection power of the connected node is changed.
Wherein the content of the first and second substances,
the output power adjustable range of the distributed energy connected to the node i requires that the set value of the output power of the distributed energy meets the time-varying adjustable range constraint of the distributed energy all the time;
according to the local measurement information and the coordination signal u received by the local controller at the time t t And formulating the distributed energy output power correction according to the economic target in the formula and the related network operation safety constraint. After the calculation of the formula (3) is completed, the local controller does not need to communicate with the adjacent controller to iterate until convergence, and immediately executes the obtained output power set value.
And 6: and completing one-time multi-target tracking. And then returning to the step 1, and continuously circulating the steps 1-6, so that efficient and high-precision tracking can be realized on the premise of ensuring that whether the target in the multiple targets is changed or not is accurately identified.
Example two:
the second embodiment of the disclosure provides a virtual power plant layered-distributed multi-target tracking system, which comprises a virtual power plant control center and controllable distributed energy local controllers, wherein the virtual power plant control center is used for receiving a scheduling instruction, transmitting the scheduling instruction to each controllable distributed energy local controller, and receiving scheduling instruction response feedback and self-running state feedback. Specifically, the virtual power plant control center judges the accuracy of response to the higher-level power grid dispatching instruction and measures the self running state at the moment according to the real-time measuring information.
Further comprising: the device comprises a parameter acquisition module, a target function establishing module, a multi-target tracking module and a coordination signal updating module.
A parameter acquisition module configured to acquire target parameters of the distributed energy resources;
the establishing target function module is configured to establish a target function of multi-target tracking by using the target parameters;
the multi-target tracking module is configured to implement multi-target tracking according to a target function of the multi-target tracking, judge a response state to a superior power grid dispatching instruction and measure a self running state;
and the coordination signal updating module is configured to update the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state.
Example three:
the third embodiment of the present disclosure provides a medium, on which a program is stored, and when the program is executed by a processor, the method implements the steps in the virtual power plant layered-distributed multi-target tracking method according to the first embodiment of the present disclosure, where the steps are:
collecting target parameters of distributed energy;
establishing a target function of multi-target tracking by using the target parameters;
implementing multi-target tracking according to a target function of the multi-target tracking, and judging a response state to a superior power grid dispatching instruction and measuring a self running state;
and updating the coordination signal based on the response state of the superior power grid dispatching command and the self running state.
The detailed steps are the same as those of the virtual power plant layered-distributed multi-target tracking method provided in the first embodiment, and are not repeated herein.
Example four:
the fourth embodiment of the present disclosure provides an apparatus, including a memory, a processor, and a program stored on the memory and executable on the processor, where the processor executes the program to implement the steps in the virtual power plant layered-distributed multi-target tracking method according to the first embodiment of the present disclosure, where the steps are:
collecting target parameters of distributed energy;
establishing a target function of multi-target tracking by using the target parameters;
implementing multi-target tracking according to a target function of the multi-target tracking, judging a response state to a superior power grid dispatching instruction and measuring an operation state of the superior power grid dispatching instruction;
and updating the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state.
The detailed steps are the same as those of the virtual power plant layered-distributed multi-target tracking method provided by the first embodiment, and are not described herein again.
The steps involved in the apparatuses of the above second, third and fourth embodiments correspond to the first embodiment of the method, and the detailed description thereof can be found in the relevant description section of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media that include one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present invention.
Those skilled in the art will appreciate that the modules or steps of the invention described above can be implemented using general purpose computing apparatus, or alternatively, they can be implemented using program code executable by computing apparatus, such that the program code is stored in a memory device and executed by computing apparatus, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps thereof are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A layered-distributed multi-target tracking method for a virtual power plant is characterized by comprising the following steps:
collecting target parameters of distributed energy;
establishing a target function of multi-target tracking by using the target parameters;
implementing multi-target tracking according to a target function of the multi-target tracking, and judging a response state to a superior power grid dispatching instruction and measuring a self running state;
and updating the coordination signal based on the response state of the superior power grid dispatching instruction and the self running state.
2. The virtual power plant layered-decentralized multi-objective tracking method of claim 1,
the target parameters of the distributed energy source include: the active power demand value of the upper-level power grid, the active power actually injected into the upper-level power grid by the virtual power plant, and the output active power and reactive power of each distributed energy source participating in scheduling.
3. The virtual power plant layered-decentralized multi-target tracking method according to claim 1, wherein an objective function of the multi-target tracking is as follows:
in the formula: the superscript t of the variable represents the time t; p i t 、
Outputting set values of active power and reactive power for the distributed energy sources connected to the node i; subscript i of the variable is a node label; the first item in the formula is an economic target, and the second item and the third item are targets for responding to a superior power grid dispatching instruction;
is the actual power vector of the virtual power plant and the upper-level grid connection point,
scheduling instruction vectors of the virtual power plant for the superior power grid; c. C 1 And c 2 Is a weight systemAnd (4) counting.
4. The virtual power plant layered-decentralized multi-target tracking method according to claim 1, wherein the constraint condition of the objective function of the multi-target tracking is: the distributed energy output power adjustable range constraint, the safety constraint and the network constraint.
5. The virtual power plant layered-decentralized multi-objective tracking method of claim 1, characterized in that the coordination signal is executed immediately upon update.
6. A layered-distributed multi-target tracking system for a virtual power plant, comprising:
a parameter acquisition module configured to acquire a target parameter of the distributed energy resource;
the establishing target function module is configured to establish a target function of the multi-target tracking by using the target parameters;
the multi-target tracking module is configured to implement multi-target tracking according to a target function of the multi-target tracking, judge a response state to a superior power grid dispatching instruction and measure a self running state;
and the coordination signal updating module is configured to update the coordination signal based on the superior power grid dispatching command response state and the self running state.
7. The virtual power plant layered-decentralized multi-target tracking system of claim 6, further comprising a virtual power plant control center and controllable distributed energy local controllers, wherein the virtual power plant control center is configured to receive the scheduling command and transmit the scheduling command to each controllable distributed energy local controller.
8. The virtual power plant layered-decentralized multi-objective tracking system of claim 7, wherein the virtual power plant control center is further configured to receive scheduling command response feedback and self-operating state feedback.
9. A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute the virtual power plant generation layered-decentralized multi-target tracking method of any one of claims 1-5.
10. A terminal device comprising a processor and a computer readable storage medium, the processor configured to implement instructions; the computer readable storage medium is for storing a plurality of instructions adapted to be loaded by a processor and to perform the virtual power plant layered-decentralized multi-target tracking method of any one of claims 1-5.
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|---|---|---|---|---|
| CN106056256A (en) * | 2016-06-28 | 2016-10-26 | 华北电力大学 | Interdynamic microgrid scheduling method for balancing power supply and demand relation |
| CN110135613A (en) * | 2018-10-23 | 2019-08-16 | 上海交通大学 | It is a kind of based on receive assorted negotiation more virtual plants collaboration optimization operating scheme |
| CN113919717A (en) * | 2021-10-18 | 2022-01-11 | 内蒙古电力（集团）有限责任公司内蒙古电力经济技术研究院分公司 | Multi-objective synchronous optimization oriented virtual power plant resource scheduling method and device |
| CN114513017A (en) * | 2022-02-15 | 2022-05-17 | 山东大学 | Distributed tracking method and system for power distribution network instructions of alternating current-direct current micro-grid |
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2022
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106056256A (en) * | 2016-06-28 | 2016-10-26 | 华北电力大学 | Interdynamic microgrid scheduling method for balancing power supply and demand relation |
| CN110135613A (en) * | 2018-10-23 | 2019-08-16 | 上海交通大学 | It is a kind of based on receive assorted negotiation more virtual plants collaboration optimization operating scheme |
| CN113919717A (en) * | 2021-10-18 | 2022-01-11 | 内蒙古电力（集团）有限责任公司内蒙古电力经济技术研究院分公司 | Multi-objective synchronous optimization oriented virtual power plant resource scheduling method and device |
| CN114513017A (en) * | 2022-02-15 | 2022-05-17 | 山东大学 | Distributed tracking method and system for power distribution network instructions of alternating current-direct current micro-grid |
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