A method and apparatus for coordinated regulation of power network and communication network

Abstract

The application discloses a kind of power network and communication network collaborative regulation method and device, method includes: obtaining flexible resource data information;According to the flexible resource data information, the regulation data value of flexible resource is calculated;According to equivalent power network composition structure, the output of power and communication coupling network equivalent model is calculated;Power network operation constraint set is constructed;According to the regulation data value of the flexible resource, the output of power and communication coupling network equivalent model and the power network operation constraint set, collaborative regulation target function is constructed, and the target of the collaborative regulation target function is power regulation net income and data communication net income maximum;According to the collaborative regulation target function, coupling network collaborative regulation is carried out.The application realizes network collaborative regulation, and improves collaborative regulation benefit.The application can be widely applied to power flexible resource scheduling technical field.

Description

Technical Field

[0001] This invention relates to the field of flexible power resource dispatching technology, and in particular to a method and apparatus for coordinated control of power networks and communication networks. Background Technology

[0002] With the rapid development of renewable energy, the pressure on real-time power grid supply and demand balance is increasing, and the safe and stable operation of the power grid urgently requires the dispatch of large-scale flexible resources. The purpose of flexible resource dispatch is to rationally allocate resources between the power network and the communication network to improve the benefits of power regulation and data communication. The dispatch of large-scale flexible resources will generate massive amounts of concurrent data and increase the demand for high-frequency data transmission, placing higher demands on the coordinated regulation of the power network and the communication network. In existing technologies, the regulation of flexible power resources often relies on static and stable communication networks. However, in actual power communication systems, the transmission capacity of the communication network has spatial dynamic variation characteristics, and the communication capabilities between different nodes have differentiated distribution characteristics, resulting in low benefits of coordinated regulation.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] This invention provides a method and apparatus for coordinated control of power networks and communication networks, which effectively improves the benefits of coordinated control.

[0005] On one hand, embodiments of the present invention provide a method for coordinated control of power networks and communication networks, comprising the following steps:

[0006] Acquire flexible resource data information, including data quality, data timeliness, and the value of electricity resources;

[0007] Based on the aforementioned flexible resource data information, calculate the value of the flexible resource regulation data;

[0008] Based on the equivalent power network composition structure, the output of the equivalent model of the power and communication coupled network is calculated. The equivalent power network composition structure includes the communication node structure, communication branch structure, or communication topology structure. The output of the equivalent model of the power and communication coupled network includes the data injection amount of the communication node, the communication cost of communication power flow transmission, or the node communication power flow balance constraint.

[0009] Construct a set of power network operation constraints;

[0010] Based on the value of the flexible resource regulation data, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set, a collaborative regulation objective function is constructed. The objective of the collaborative regulation objective function is to maximize the net benefits of power regulation and the net benefits of data communication.

[0011] Based on the aforementioned collaborative regulation objective function, coupled network collaborative regulation is performed.

[0012] In some embodiments, calculating the regulatory data value of flexible resources based on the flexible resource data information includes:

[0013] Calculate the intrinsic attribute evaluation value of the data based on the data quality, the data timeliness, the data quality weight, and the data timeliness weight.

[0014] Based on the power resource value, power dispatch cycle, data acquisition interval, and unit conversion factor, calculate the evaluation value of the external attributes of the data;

[0015] The value of the flexible resource control data is calculated based on the intrinsic attribute evaluation value of the data, the extrinsic attribute evaluation value of the data, and the set of auxiliary service scenarios.

[0016] In some embodiments, when the equivalent power network structure is the communication node structure, the step of calculating the equivalent model output of the power-communication coupling network based on the equivalent power network structure includes:

[0017] The amount of power control data injected by the communication node is calculated based on the correlation coefficient between the amount of power control resources, the amount of flexible resource adjustment and the amount of control data generated.

[0018] The amount of power control data flowing out of the communication node is calculated based on the correlation coefficient between the amount of power control resources and the amount of flexible resource adjustment and the amount of control data generated.

[0019] The data injection amount of the communication node is calculated based on the element node association matrix of the data injection communication node and the full communication node, the element node association matrix of the data outflow communication node and the full communication node, the amount of power control data injected by the communication node, and the amount of power control data outflowed by the communication node.

[0020] In some embodiments, when the equivalent power network structure is the communication branch structure, the step of calculating the equivalent model output of the power-communication coupled network based on the equivalent power network structure includes:

[0021] Calculate the communication flow in a single auxiliary service scenario based on the data flow allocated to the communication tributaries;

[0022] Based on the communication flow matrix of multiple communication branches and the communication flow under the single auxiliary service scenario, calculate the branch communication flow under the multiple auxiliary service scenario;

[0023] Based on the branch communication flow in the multi-auxiliary service scenario, construct the communication branch transmission constraints;

[0024] The communication cost of the communication flow transmission is calculated based on the branch communication flow in the multi-auxiliary service scenario, the transmission constraints of the communication branch, and the communication charging price parameters.

[0025] In some embodiments, when the equivalent power network structure is the communication topology, calculating the output of the equivalent model of the power-communication coupled network based on the equivalent power network structure includes:

[0026] Calculate the node-branch association value based on the association relationship between the communication node and the communication branch;

[0027] Calculate the node-branch association matrix based on the node-branch association values;

[0028] Based on the data injection volume of the communication node, the node-branch association matrix, and the branch communication flow in the multi-auxiliary service scenario, the node communication flow balance constraint is constructed.

[0029] In some embodiments, the power network operation constraint set includes a generator operation constraint set and a regulation resource balance constraint set, wherein constructing the power network operation constraint set includes:

[0030] Based on the generator's power output before participating in ancillary services, the generator's power output after participating in ancillary services, and the regulation power provided by the generator participating in ancillary services, the first generator's operating constraints are constructed.

[0031] Based on the upper limit of the generator's power generation after participating in ancillary services and the lower limit of the generator's power generation after participating in ancillary services, a second generator operation constraint is constructed;

[0032] Based on the reactive power of the generator after participating in ancillary services, the upper limit of the reactive power of the generator after participating in ancillary services, and the lower limit of the reactive power of the generator after participating in ancillary services, the third generator operation constraints are constructed.

[0033] Based on the active power regulation capacity limitation of the generator, the operating constraints of the fourth generator are constructed;

[0034] Based on the generator's reactive power regulation capacity limit and the generator's reactive power before participating in ancillary services, the fifth generator's operating constraints are constructed.

[0035] The first generator operation constraint, the second generator operation constraint, the third generator operation constraint, the fourth generator operation constraint, and the fifth generator operation constraint are combined to obtain the generator operation constraint set;

[0036] Based on the generator set-node association matrix, the flexible resource aggregator-node association matrix, the regulation power provided by the flexible resource aggregator in ancillary services, and the regulation demand vector of each ancillary service scenario, the regulation resource balance constraint is constructed.

[0037] In some embodiments, the power network operation constraint set includes a flexible resource aggregator regulation operation constraint set and a node power balance constraint set, wherein constructing the power network operation constraint set includes:

[0038] Based on the load power before the flexible resource aggregator participates in ancillary services, the load power after the flexible resource aggregator participates in ancillary services, and the regulation power provided by the flexible resource aggregator participating in ancillary services, the first flexible resource aggregator's control and operation constraints are constructed.

[0039] Based on the upper limit of load power after the flexible resource aggregator participates in ancillary services and the lower limit of load power after the flexible resource aggregator participates in ancillary services, a second flexible resource aggregator regulation and operation constraint is constructed.

[0040] Based on the adjustment capacity limitations of flexible resource aggregators, construct the control and operation constraints for third flexible resource aggregators;

[0041] The first flexible resource aggregator control operation constraint, the second flexible resource aggregator control operation constraint, and the third flexible resource aggregator control operation constraint are combined to obtain the flexible resource aggregator control operation constraint set.

[0042] Based on the injected active power flow of power nodes, the association matrix between generator sets and nodes, the power generation of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the load power after flexible resource aggregators participate in ancillary services, the power balance constraints of the first node are constructed.

[0043] Based on the injected reactive power flow of power nodes, the association matrix between generator sets and nodes, the reactive power of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the reactive power of flexible resource aggregators after participating in ancillary services, a second node power balance constraint is constructed.

[0044] Based on the node-branch association matrix of the power network and the active power flow of the power branches, a third node power balance constraint is constructed.

[0045] Based on the node-branch association matrix of the power network and the reactive power flow of the power branches, a fourth node power balance constraint is constructed.

[0046] The first node power balance constraint, the second node power balance constraint, the third node power balance constraint, and the fourth node power balance constraint are combined to obtain the node power balance constraint set.

[0047] In some embodiments, the power network operation constraint set includes a power grid flow constraint set, and constructing the power network operation constraint set includes:

[0048] The first power flow constraint is constructed based on the active power flow of the power branch, the real part of the branch admittance, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage magnitude of the power node, and the phase angle of the power node.

[0049] The second power flow constraint is constructed based on the reactive power flow of the power branch, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage amplitude of the power node, and the phase angle of the power node.

[0050] A third power flow constraint is constructed based on the upper and lower limits of the voltage amplitude of the power nodes.

[0051] The fourth power flow constraint is constructed based on the upper and lower limits of the phase angle of the power nodes.

[0052] Based on the upper limit and lower limit of the active power flow of the power branch, the power flow constraints of the fifth power grid are constructed.

[0053] Based on the upper and lower limits of reactive power flow of the power branch, a sixth power flow constraint is constructed.

[0054] The first power flow constraint, the second power flow constraint, the third power flow constraint, the fourth power flow constraint, the fifth power flow constraint, and the sixth power flow constraint are combined to obtain the power flow constraint set.

[0055] In some embodiments, constructing a coordinated control objective function based on the control data value of the flexible resources, the output of the equivalent model of the power-communication coupled network, and the power network operation constraint set includes:

[0056] Calculate the revenue of generators participating in multiple ancillary services based on the regulation resource prices of grid nodes and the regulation power provided by generators participating in ancillary services.

[0057] Calculate the revenue of flexible resource aggregators participating in multiple ancillary service scenarios based on the regulation resource prices of grid nodes and the regulation power provided by flexible resource aggregators participating in ancillary services.

[0058] The value of coordinated control data between the power and communication networks is calculated based on the value of the control data of the flexible resources and the amount of power control data injected by the communication nodes.

[0059] Calculate the cost of generator participation in multiple ancillary services scenarios based on the generator's regulation power cost coefficient and the regulation power provided by the generator in participating in ancillary services.

[0060] Calculate the cost of flexible resource aggregators participating in multiple ancillary service scenarios based on the adjustment power cost coefficient of flexible resource aggregators and the adjustment power provided by flexible resource aggregators in participating in ancillary services.

[0061] Based on the output of the equivalent model of the power and communication coupled network, the power network operation constraint set, the benefits of the generator participating in multiple ancillary service scenarios, the benefits of the flexible resource aggregator participating in multiple ancillary service scenarios, the data value of the power and communication network collaborative regulation, the cost of the generator participating in multiple ancillary service scenarios, the cost of the flexible resource aggregator participating in multiple ancillary service scenarios, and the data communication cost of the power and communication network collaborative regulation, the collaborative regulation objective function is constructed.

[0062] On the other hand, embodiments of the present invention provide a power network and communication network coordinated control device, comprising:

[0063] The first module is used to acquire flexible resource data information, which includes data quality, data timeliness, and the value of electricity resources.

[0064] The second module is used to calculate the value of the control data of the flexible resources based on the flexible resource data information.

[0065] The third module is used to calculate the output of the equivalent model of the power and communication coupling network based on the equivalent power network composition structure. The equivalent power network composition structure includes the communication node structure, communication branch structure or communication topology structure. The output of the equivalent model of the power and communication coupling network includes the data injection amount of the communication node, the communication cost of communication power flow transmission or the node communication power flow balance constraint.

[0066] The fourth module is used to construct the power network operation constraint set;

[0067] The fifth module is used to construct a collaborative regulation objective function based on the regulation data value of the flexible resources, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set. The objective function of the collaborative regulation objective function is to maximize the net benefits of power regulation and the net benefits of data communication.

[0068] The sixth module is used to perform coupled network coordinated regulation based on the aforementioned coordinated regulation objective function.

[0069] The beneficial effects of this invention are as follows:

[0070] This invention first acquires flexible resource data information, calculates the control data value of flexible resources based on the flexible resource data information, then calculates the output of the equivalent model of the power and communication coupled network based on the equivalent power network composition structure, and constructs a power network operation constraint set. Next, based on the control data value of flexible resources, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set, a collaborative control objective function is constructed. Finally, based on the collaborative control objective function, collaborative control of the coupled network is performed, thereby enabling network collaborative control through the calculation of the revenue of the power and communication coupled network, and thus improving the revenue of collaborative control.

[0071] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description and the drawings. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a flowchart illustrating a method for coordinated control of power networks and communication networks according to an embodiment of the present invention;

[0074] Figure 2 This is a schematic diagram of a power-communication network based on an IEEE standard 5-node system, according to an embodiment of the present invention.

[0075] Figure 3 This is a comparison diagram of the total regulation capacity of a traditional generator participating in multiple ancillary services according to an embodiment of the present invention;

[0076] Figure 4 This is a comparison chart of the total adjustment capacity of a flexible resource aggregator participating in multiple ancillary services scenarios according to an embodiment of the present invention;

[0077] Figure 5 This is a comparison diagram of the adjustment capacity of a traditional generator participating in various ancillary service scenarios according to an embodiment of the present invention;

[0078] Figure 6 This is a comparison chart of the adjustment capacity of flexible resource aggregators participating in various ancillary service scenarios according to an embodiment of the present invention;

[0079] Figure 7 This is a schematic diagram of the structure of a power network and communication network coordinated control device according to an embodiment of the present invention. Detailed Implementation

[0080] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0081] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0082] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0083] Unless otherwise defined, 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. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0084] According to data from the Renewable Energy Organization, the proportion of renewable energy generation in the power system is expected to continue to increase. With the rapid development of renewable energy and its continuous integration, the pressure on real-time grid supply and demand balance is increasing. Against this backdrop, the safe and stable operation of the power grid urgently requires the regulation of large-scale flexible resources. Compared to traditional generating units, the individual regulation capacity of flexible resources is relatively low. Therefore, it is necessary to aggregate large-scale flexible resources to achieve a regulation effect equivalent to that of traditional generating units. The regulation of large-scale flexible resources will generate massive concurrent data and high-frequency data transmission demands, placing higher requirements on the coordinated operation of power and communication networks. Therefore, researching optimized regulation methods for flexible resources under power-communication coupled networks is of great significance for improving the level of power resource dispatch. Existing technical solutions for coordinated optimization regulation of power and communication mainly focus on: the regulation characteristics of energy storage facilities equipped with communication base stations as flexible power resources; the impact of communication network security issues on power network operation; and the regulation of flexible power resources based on reliable and fast communication networks. In existing technologies, the regulation of flexible power resources often relies on reliable, fast, and statically stable communication networks. However, in actual power communication systems, the transmission capacity of communication networks has spatial dynamic variation characteristics, and the communication capabilities between different nodes exhibit differentiated distribution characteristics, resulting in low benefits from coordinated regulation.

[0085] In view of this, this embodiment first assesses the value of control data in a scenario where flexible resources participate in multiple ancillary services, then calculates the output of an equivalent model of the power and communication coupled network for flexible resource control, and then constructs and solves the objective function for the coordinated control of power and communication networks in a scenario with multiple ancillary services. This yields a coordinated control strategy for power and communication networks in a scenario where flexible resources participate in multiple ancillary services under the influence of data value. This embodiment can describe the spatial dynamic characteristics of the communication network, promote the priority transmission of high-value data, and improve the level of flexible resource control and the benefits of coordinated control by considering the data value benefits and data communication costs.

[0086] This application provides a method for coordinated control of power networks and communication networks, relating to the field of flexible power resource scheduling technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing a method for coordinated control of power networks and communication networks, but is not limited to the above forms.

[0087] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0088] The embodiments of this application will be explained in detail below with reference to the accompanying drawings:

[0089] Figure 1 This is an optional flowchart of a method for coordinated control of power networks and communication networks provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S106.

[0090] Step S101: Obtain flexible resource data information, which includes data quality, data timeliness, and the value of electricity resources;

[0091] Step S102: Calculate the value of the flexible resource regulation data based on the flexible resource data information;

[0092] Step S103: Based on the equivalent power network composition structure, calculate the output of the equivalent model of the power and communication coupling network. The equivalent power network composition structure includes the communication node structure, communication branch structure or communication topology structure. The output of the equivalent model of the power and communication coupling network includes the data injection amount of the communication node, the communication cost of communication power flow transmission or the node communication power flow balance constraint.

[0093] Step S104: Construct a set of power network operation constraints;

[0094] Step S105: Based on the data value of flexible resource regulation, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set, construct a collaborative regulation objective function. The objective of the collaborative regulation objective function is to maximize the net benefits of power regulation and the net benefits of data communication.

[0095] Step S106: Perform coupled network coordinated regulation according to the coordinated regulation objective function.

[0096] Steps S101 to S106 as shown in the embodiments of this application realize network collaborative regulation and improve the benefits of collaborative regulation.

[0097] In step S101 of some embodiments, flexible resource data information can be obtained through a resource database. Flexible resource data information can also be obtained through other means, and is not limited to these. The flexible resource data information may include data quality, data timeliness, and the value of electricity resources.

[0098] In some embodiments, in step S102, calculating the control data value of flexible resources based on flexible resource data information may include, but is not limited to, the following steps:

[0099] Calculate the intrinsic attribute evaluation value of data based on data quality, data timeliness, data quality weight, and data timeliness weight.

[0100] The value of the external attributes of the data is calculated based on the value of power resources, power dispatch cycle, data acquisition interval and unit conversion factor.

[0101] The value of data for the regulation of flexible resources is calculated based on the evaluation of the intrinsic attributes of the data, the evaluation of the extrinsic attributes of the data, and the set of auxiliary service scenarios.

[0102] In some embodiments, a data value assessment model for flexible resources participating in multiple auxiliary services can be established to calculate the data value of flexible resources. The intrinsic attribute assessment value of the data can be calculated first based on data quality, data timeliness, data quality weight, and data timeliness weight. For example, the intrinsic attribute assessment value of the data is affected by both data quality and data timeliness. The formula for calculating the intrinsic attribute assessment value is as follows: In the formula, VoI w To assess the value of the data's intrinsic attributes, For data quality weights, To improve data quality in auxiliary service scenario w, Weighting based on data timeliness. To improve data timeliness in auxiliary service scenario w, This is a set of auxiliary service scenarios. Then, based on the value of power resources, power dispatch cycle, data collection interval, and unit conversion factor, the external attribute assessment value of the data is calculated. For example, the external attribute assessment value of the control data depends on the power value of the data application scenario. The formula for calculating the external attribute assessment value of the data is: In the formula, VoE w To assess the value of external attributes of data, χ is the unit conversion factor, converting the value of electricity resources ($ / MW) into the value of data ($ / GB), τ w For the power dispatch cycle under the auxiliary service scenario w, f w For the data collection interval in auxiliary service scenario w, p w To enhance the value of electricity resources in auxiliary service scenario w, τ w / f w This indicates the data collection frequency. Then, based on the data's intrinsic attribute evaluation value, extrinsic attribute evaluation value, and the set of auxiliary service scenarios, the data value for the regulation of flexible resources is calculated. The formula for calculating the data value for the regulation of flexible resources is: In the formula, VoD w To enhance the value of data for flexible resource management in auxiliary service scenarios w, ⊙ represents the Hadamard product, used for multiplying two matrices of the same dimension, where the corresponding elements of the two matrices are multiplied to obtain the elements of the new matrix.

[0103] In some embodiments, in step S103, when the equivalent power network structure is a communication node structure, the equivalent model output of the power and communication coupling network is calculated based on the equivalent power network structure, which may include, but is not limited to, the following steps:

[0104] The amount of power control data injected by the communication node is calculated based on the correlation coefficient between the amount of power control resources, the amount of flexible resource adjustment and the amount of control data generated.

[0105] The amount of power control data flowing out of the communication node is calculated based on the correlation coefficient between the amount of power control resources and the amount of flexible resource adjustment and the amount of control data generated.

[0106] The data injection amount of a communication node is calculated based on the element node association matrix of the data injection communication node and the full communication node, the element node association matrix of the data outflow communication node and the full communication node, the amount of power control data injected into the communication node, and the amount of power control data outflowed from the communication node.

[0107] In some embodiments, when the equivalent power network structure is a communication node structure, the power regulation process involving flexible resources in multiple ancillary service scenarios generates a large amount of regulation data. This regulation data is transmitted through the communication network into the data center, which further supports the dispatch center operators in performing centralized optimization and regulation of power resources. Therefore, the data nodes corresponding to flexible resources are data injection communication nodes, and the data nodes corresponding to the dispatch center are data outflow communication nodes. The amount of power regulation data injected by the communication nodes can be calculated first based on the correlation coefficient between the amount of power regulation resources, the amount of flexible resource regulation, and the amount of generated regulation data. For example, for data injection communication nodes, the amount of power regulation data and the amount of power regulation resources satisfy the following relationship: In the formula, The amount of power regulation data injected into the communication node, h w The correlation coefficient between the amount of flexible resource adjustment and the amount of control data generated. This refers to the amount of power regulation resources. Then, based on the correlation coefficient between the power regulation resources, flexible resource adjustment volume, and the amount of regulation data generated, the amount of power regulation data flowing out of the communication node is calculated. For example, the communication network has only one data center, i.e., only one data-outflow communication node, and this node satisfies the requirement for the outflow of power regulation data. The total amount of power control data injected into the communication network is equal to the sum of all power control data injected into the network. The formula for calculating the amount of power control data flowing out of the communication node is: In the formula, This represents the amount of power regulation data flowing out of the communication node. Then, based on the element-node association matrix of the data-injected communication node and the entire communication node, the element-node association matrix of the data-outflowing communication node and the entire communication node, the amount of power regulation data injected into the communication node, and the amount of power regulation data flowing out of the communication node, the data injection amount of the communication node is calculated. The formula for calculating the data injection amount of the communication node is: In the formula, E represents the amount of data injected into all communication nodes in the communication network. S For the element node association matrix of the A×I order data injection communication node and the full communication node in the auxiliary service scenario w, E L This is the element-node association matrix between data-outflow communication nodes and all-communication nodes. This is the power regulation data volume vector for data outflow communication nodes. This represents the value of the j-th element in the power regulation data vector, i.e., the amount of power regulation data flowing out from the j-th node.

[0108] In some embodiments, in step S103, when the equivalent power network structure is a communication branch structure, the equivalent model output of the power and communication coupling network is calculated based on the equivalent power network structure, which may include, but is not limited to, the following steps:

[0109] Calculate the communication flow in a single auxiliary service scenario based on the data flow allocated to the communication tributaries;

[0110] Based on the communication flow matrix of multiple communication branches and the communication flow in a single auxiliary service scenario, calculate the branch communication flow in a multi-auxiliary service scenario;

[0111] Based on the branch communication flow in a multi-auxiliary service scenario, construct the communication branch transmission constraints;

[0112] The communication cost of communication flow transmission is calculated based on the branch communication flow, communication branch transmission constraints, and communication pricing parameters in a multi-auxiliary service scenario.

[0113] In some embodiments, when the equivalent power network structure is a communication branch structure, the communication flow in a single ancillary service scenario can be calculated first based on the data flow allocated to the communication branch. For example, similar to the power flow in a power network, the amount of data transmitted in the communication branch is defined as the communication flow. The formula for calculating the communication flow in a single ancillary service scenario is as follows: In the formula, The communication flow of the communication network in a single auxiliary service scenario w. Assign the data traffic from the i-th communication node to the k-th communication branch, 1 I Let K be a 1×I order vector of order 1, where all elements in the vector are 1. Then, based on the communication flow matrix of multiple communication branches and the communication flow in a single auxiliary service scenario, the branch communication flow in the multi-auxiliary service scenario is calculated. For example, the branch communication flow in the multi-auxiliary service scenario is represented as a K×1 order vector. D F =D FinW 1 W , In the formula, D F This refers to the communication flow of a communication network. For the communication flow of the k-th communication branch, D FinW This is the communication flow matrix for K communication branches in a scenario with W auxiliary services, where K is the total number of communication branches, 1 WLet D be a 1×W order vector of type 1, where a vector of type 1 represents all elements of the vector being 1. Then, based on the branch communication flow in a multi-auxiliary service scenario, communication branch transmission constraints are constructed. For example, the communication branch flow should satisfy the transmission restrictions of the communication branch. The expression for the communication branch transmission constraint is: D F,- ≤D F ≤D F,+ , In the formula, D F,- D represents the lower limit of the transmission capacity of a communication tributary. F,+ This represents the upper limit of the transmission capacity of the communication tributary. Finally, based on the tributary communication flow, communication tributary transmission constraints, and communication pricing parameters in the multi-auxiliary service scenario, the communication cost of communication flow transmission is calculated. For example, considering the needs of communication network operation, the transmission of communication flow will generate communication costs. The formula for calculating the communication cost of communication flow transmission is: C F =diag(σ)(D F ⊙D F )+diag(ζ)(D F ), In the formula, C F The communication cost for power flow transmission is used to construct the target for coordinated control of power and communication networks in multi-ancillary service scenarios. σ and ζ are both communication charge price parameters, and diag(*) represents the constructor of the diagonal matrix.

[0114] In some embodiments, in step S103, when the equivalent power network structure is a communication topology, the equivalent model output of the power and communication coupled network is calculated based on the equivalent power network structure, which may include, but is not limited to, the following steps:

[0115] Calculate the node-branch association value based on the association relationship between the communication node and the communication branch;

[0116] Calculate the node-branch association matrix based on the node-branch association values;

[0117] Based on the data injection volume of communication nodes, the node-branch association matrix, and the branch communication flow in multi-auxiliary service scenarios, a node communication flow balance constraint is constructed.

[0118] In some embodiments, when the equivalent power network structure is a communication topology, the node-branch association value can be calculated first based on the association relationship between communication nodes and communication branches. The formula for calculating the node-branch association value is as follows: In the formula, B i,k Let be the node-branch association values. Then, based on these values, calculate the node-branch association matrix, where the expression for the node-branch association matrix is: In the formula, B FThis is the node-branch association matrix. Let I be the node-to-branch association value of the k-th branch of the i-th node, and K be the total number of communication nodes and the total number of communication branches. Then, based on the data injection volume of the communication nodes, the node-to-branch association matrix, and the branch communication flow in a multi-auxiliary service scenario, a node communication flow balance constraint is constructed. The expression for the node communication flow balance constraint is: D NetS 1 W -B F (D F ) T =0 I , In the formula, D NetS 1 W The amount of data injected into the communication node, 0 I It is a 1×I order zero vector, where a zero vector means that all elements in the vector are 0.

[0119] In some embodiments, in step S104, the power network operation constraint set includes a generator operation constraint set and a regulation resource balance constraint set. Constructing the power network operation constraint set may include, but is not limited to, the following steps:

[0120] Based on the generator's power output before participating in ancillary services, the generator's power output after participating in ancillary services, and the regulation power provided by the generator participating in ancillary services, the first generator's operating constraints are constructed.

[0121] Based on the upper limit of the generator's power generation after participating in ancillary services and the lower limit of the generator's power generation after participating in ancillary services, a second generator operation constraint is constructed;

[0122] Based on the reactive power of the generator after participating in ancillary services, the upper limit of the reactive power of the generator after participating in ancillary services, and the lower limit of the reactive power of the generator after participating in ancillary services, the third generator operation constraints are constructed.

[0123] Based on the active power regulation capacity limitation of the generator, the operating constraints of the fourth generator are constructed;

[0124] Based on the generator's reactive power regulation capacity limit and the generator's reactive power before participating in ancillary services, the fifth generator's operating constraints are constructed.

[0125] The first generator operation constraint, the second generator operation constraint, the third generator operation constraint, the fourth generator operation constraint, and the fifth generator operation constraint are combined to obtain the generator operation constraint set;

[0126] Based on the generator set-node association matrix, the flexible resource aggregator-node association matrix, the regulation power provided by the flexible resource aggregator in ancillary services, and the regulation demand vector of each ancillary service scenario, a regulation resource balance constraint is constructed.

[0127] In some embodiments, a first generator operating constraint can be constructed based on the generator's power output before participating in ancillary services, the generator's power output after participating in ancillary services, and the regulating power provided by the generator participating in ancillary services. The expression for the first generator operating constraint is: P D,G =P S,G +R G 1 W , In the formula, P D,G P represents the power output of the generator after it participates in ancillary services. S,G R is the power output of the generator before it participates in ancillary services. G The regulating power provided by the generator for ancillary services. Based on the upper and lower limits of the generator's power generation after participating in ancillary services, a second generator operating constraint is constructed, where the expression for the second generator operating constraint is: P D,G,- ≤P D,G ≤P D,G,+ In the formula, P D,G,- P represents the lower limit of the generator's output capacity after it participates in ancillary services. D,G,+ This represents the upper limit of the generator's power output after it participates in ancillary services. Based on the reactive power output after generator participation in ancillary services, the upper limit of the reactive power output after generator participation in ancillary services, and the lower limit of the reactive power output after generator participation in ancillary services, a third generator operating constraint is constructed. The expression for the third generator operating constraint is: Q D,G,- ≤Q D,G ≤Q D,G,+ In the formula, Q D,G Q represents the reactive power generated after the generator participates in ancillary services. D,G,- Q represents the lower limit of reactive power after the generator participates in ancillary services. D,G,+ This represents the upper limit of reactive power after the generator participates in ancillary services. Based on the generator's active power regulation capability limitations, a fourth generator operating constraint is constructed, where the expression for the fourth generator operating constraint is: -PR D,G ≤P D,G -P S,G ≤PR D,G In the formula, PR D,G The active power regulation capability of the generator is limited. Based on the reactive power regulation capability limit of the generator and the reactive power of the generator before participating in ancillary services, a fifth generator operating constraint is constructed, where the expression of the fifth generator operating constraint is: -QR D,G ≤Q D ,G -Q S,G ≤QR D,G In the formula, QR D,GDue to the limitation of the generator's reactive power regulation capability, Q S,G The reactive power of the generator before it participates in ancillary services. Then, the operating constraints of the first, second, third, fourth, and fifth generators are combined to obtain the generator operating constraint set. Next, based on the generator set-node association matrix, the flexible resource aggregator-node association matrix, the regulating power provided by the flexible resource aggregator participating in ancillary services, and the regulating demand vector for each ancillary service scenario, a regulation resource balance constraint is constructed. The expression for the regulation resource balance constraint is: 1 M (J G ) T R G +1 M (J A ) T R A =R, where 1 M J is a 1×M order vector of type 1, where a vector of type 1 represents a vector whose elements are all 1. G Let J be the G×M order generator set and node association matrix. A Let R be the A×M order flexible resource aggregator and node association matrix, and let R be the adjustment demand vector for each auxiliary service scenario.

[0128] In some embodiments, in step S104, the power network operation constraint set includes a flexible resource aggregator regulation operation constraint set and a node power balance constraint set. Constructing the power network operation constraint set may include, but is not limited to, the following steps:

[0129] Based on the load power before the flexible resource aggregator participates in ancillary services, the load power after the flexible resource aggregator participates in ancillary services, and the regulation power provided by the flexible resource aggregator participating in ancillary services, the first flexible resource aggregator's control and operation constraints are constructed.

[0130] Based on the upper limit of load power after the flexible resource aggregator participates in ancillary services and the lower limit of load power after the flexible resource aggregator participates in ancillary services, a second flexible resource aggregator regulation and operation constraint is constructed.

[0131] Based on the adjustment capacity limitations of flexible resource aggregators, construct the control and operation constraints for third flexible resource aggregators;

[0132] The first flexible resource aggregator regulation and operation constraints, the second flexible resource aggregator regulation and operation constraints, and the third flexible resource aggregator regulation and operation constraints are combined to obtain the flexible resource aggregator regulation and operation constraint set;

[0133] Based on the injected active power flow of power nodes, the association matrix between generator sets and nodes, the power generation of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the load power after flexible resource aggregators participate in ancillary services, the power balance constraints of the first node are constructed.

[0134] Based on the injected reactive power flow of power nodes, the association matrix between generator sets and nodes, the reactive power of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the reactive power of flexible resource aggregators after participating in ancillary services, a second node power balance constraint is constructed.

[0135] Based on the node-branch association matrix of the power network and the active power flow of the power branches, a third node power balance constraint is constructed.

[0136] Based on the node-branch association matrix of the power network and the reactive power flow of the power branches, a fourth node power balance constraint is constructed.

[0137] The power balance constraints of the first node, the second node, the third node, and the fourth node are combined to obtain the set of node power balance constraints.

[0138] In some embodiments, a first flexible resource aggregator control operation constraint can be constructed based on the load power before the flexible resource aggregator participates in ancillary services, the load power after the flexible resource aggregator participates in ancillary services, and the regulation power provided by the flexible resource aggregator participating in ancillary services. The expression for the first flexible resource aggregator control operation constraint is: P D,A =P S,A -R A 1 W , In the formula, P D,A For the load power after flexible resource aggregators participate in ancillary services, P S,A For the load power before flexible resource aggregators participate in ancillary services, R A The regulating power provided for flexible resource aggregators participating in ancillary services. Based on the upper and lower limits of load power after flexible resource aggregators participate in ancillary services, a second flexible resource aggregator regulation and operation constraint is constructed, where the expression for the second flexible resource aggregator regulation and operation constraint is: P D,A,- ≤P D,A ≤P D,A,+ In the formula, P D,A,- P is the lower limit of load power after flexible resource aggregators participate in ancillary services. D,A,+This defines the upper limit of load power after the flexible resource aggregator participates in ancillary services. Based on the adjustment capacity limitations of the flexible resource aggregator, a third flexible resource aggregator control operation constraint is constructed, where the expression for the third flexible resource aggregator control operation constraint is: -R D,A ≤P S,A -P D,A ≤R D,A In the formula, R D,A To limit the adjustment capabilities of flexible resource aggregators, the operational constraints of the first, second, and third flexible resource aggregators are combined to obtain a set of operational constraints for flexible resource aggregators.

[0139] Then, based on the injected active power flow of the power nodes, the association matrix between generator units and nodes, the power generation of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the load power after flexible resource aggregators participate in ancillary services, the power balance constraint of the first node is constructed. The expression for the power balance constraint of the first node is: P NetD =(J G ) T P D,G -(J A ) T P D,A In the formula, P NetD For injecting active power flow into power nodes, J G Let J be the G×M order generator set and node association matrix. A Let Q be an A×M order flexible resource aggregator and node association matrix. Based on the injected reactive power flow of power nodes, the generator-node association matrix, the reactive power of generators participating in ancillary services, the flexible resource aggregator-node association matrix, and the reactive power of flexible resource aggregators participating in ancillary services, a second node power balance constraint is constructed. The expression for the second node power balance constraint is: Q NetD =(J G ) T Q D,G -(J A ) T Q D,A In the formula, Q NetD To inject reactive power flow into power nodes, Q D,A This refers to the reactive power after flexible resource aggregators participate in ancillary services. Based on the node-branch association matrix of the power network and the active power flow of the power branches, a third-node power balance constraint is constructed, where the expression for the third-node power balance constraint is: B P P F -P NetD =0 M In the formula, B PLet P be the node-branch association matrix of the power network. F For the active power flow of the power branch, 0 M Let B be a 1×M order zero vector, where a zero vector represents a vector where all elements are 0. Based on the node-branch association matrix of the power network and the reactive power flow of the power branches, a fourth node power balance constraint is constructed, where the expression for the fourth node power balance constraint is: B P Q F -Q NetD =0 M In the formula, Q NetD This represents the reactive power flow of the power branch. The power balance constraints of the first node, second node, third node, and fourth node are combined to obtain the node power balance constraint set.

[0140] In some embodiments, in step S104, the power network operation constraint set includes the power grid power flow constraint set. Constructing the power network operation constraint set may include, but is not limited to, the following steps:

[0141] The first power flow constraint is constructed based on the active power flow of the power branch, the real part of the branch admittance, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage magnitude of the power node, and the phase angle of the power node.

[0142] The second power flow constraint is constructed based on the reactive power flow of the power branch, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage amplitude of the power node, and the phase angle of the power node.

[0143] A third power flow constraint is constructed based on the upper and lower limits of the voltage amplitude of the power nodes.

[0144] The fourth power flow constraint is constructed based on the upper and lower limits of the phase angle of the power nodes.

[0145] Based on the upper limit and lower limit of the active power flow of the power branch, the power flow constraints of the fifth power grid are constructed.

[0146] Based on the upper and lower limits of reactive power flow of the power branch, a sixth power flow constraint is constructed.

[0147] The power flow constraints of the first, second, third, fourth, fifth, and sixth power grids are combined to obtain the power flow constraint set.

[0148] In some embodiments, a first power flow constraint can be constructed first based on the active power flow of the power branch, the real part of the branch admittance, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage magnitude of the power node, and the phase angle of the power node. The expression for the first power flow constraint is: P F =diag(Y1)*B P *U+diag(Y2)*B P *δ, where P F For the active power flow of the power branch, B P Let be the node-branch correlation matrix of the power network, U be the voltage magnitude of the power node, δ be the phase angle of the power node, Y1 be the real part of the branch admittance, and Y2 be the imaginary part of the branch admittance. Based on the reactive power flow of the power branches, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage magnitude of the power nodes, and the phase angle of the power nodes, a second power flow constraint is constructed. The expression for the second power flow constraint is: Q F =diag(Y2)*B P *U-diag(Y1)*B P *δ, where Q F This represents the reactive power flow of the power branch. Based on the upper and lower limits of the voltage amplitude at the power nodes, a third power flow constraint is constructed, where the expression for the third power flow constraint is: U - ≤U≤U + In the formula, U - U is the lower limit of the voltage amplitude at the power node. + Let δ be the upper limit of the voltage amplitude of the power node. Based on the upper and lower limits of the phase angle of the power node, a fourth power flow constraint is constructed, where the expression for the fourth power flow constraint is: δ - ≤δ≤δ + In the formula, δ - δ represents the lower limit of the phase angle of the power node. + Let P be the upper limit of the phase angle of the power node. Based on the upper and lower limits of the active power flow of the power branch, the fifth power flow constraint is constructed, where the expression for the fifth power flow constraint is: P F,- ≤P F ≤P F,+ In the formula, P F,- P is the lower limit of the active power flow of the power branch. F,+ Let Q be the upper limit of the active power flow of the power branch. Based on the upper and lower limits of the reactive power flow of the power branch, a sixth power flow constraint is constructed, where the expression for the sixth power flow constraint is: Q F,- ≤Q F ≤Q F,+In the formula, Q F,- Q is the lower limit of reactive power flow for the power branch. F,+ The upper limit of reactive power flow for the power branch is defined. Then, the first, second, third, fourth, fifth, and sixth power flow constraints of the power grid are combined to obtain the power grid power flow constraint set.

[0149] In some embodiments, in step S105, the collaborative control objective function is constructed based on the value of the flexible resource regulation data, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set. This may include, but is not limited to, the following steps:

[0150] Calculate the revenue of generators participating in multiple ancillary services based on the regulation resource prices of grid nodes and the regulation power provided by generators participating in ancillary services.

[0151] Calculate the revenue of flexible resource aggregators participating in multiple ancillary service scenarios based on the regulation resource prices of grid nodes and the regulation power provided by flexible resource aggregators participating in ancillary services.

[0152] The value of coordinated control data between power and communication networks is calculated based on the value of flexible resource control data and the amount of power control data injected by communication nodes.

[0153] Calculate the cost of generator participation in multiple ancillary services scenarios based on the generator's regulation power cost coefficient and the regulation power provided by the generator in participating in ancillary services.

[0154] Calculate the cost of flexible resource aggregators participating in multiple ancillary service scenarios based on the adjustment power cost coefficient of flexible resource aggregators and the adjustment power provided by flexible resource aggregators in participating in ancillary services.

[0155] Based on the output of the equivalent model of the power and communication coupled network, the power network operation constraint set, the benefits of generators participating in multiple ancillary service scenarios, the benefits of flexible resource aggregators participating in multiple ancillary service scenarios, the data value of power and communication network collaborative regulation, the cost of generators participating in multiple ancillary service scenarios, the cost of flexible resource aggregators participating in multiple ancillary service scenarios, and the data communication cost of power and communication network collaborative regulation, a collaborative regulation objective function is constructed.

[0156] In some embodiments, when flexible resources participate in multiple ancillary service scenarios, a coordinated control objective function is constructed based on the control data value of flexible resources, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set. The objective function aims to maximize the net revenue from power regulation and the net revenue from data communication. The revenue of generators participating in multiple ancillary services can be calculated first based on the control resource prices of grid nodes and the control power provided by generators participating in ancillary services. The formula for calculating the revenue of generators participating in multiple ancillary services is as follows: In the formula, For the benefits of generators participating in multiple ancillary service scenarios, τ w To assist in adjusting resource prices for power grid nodes in scenario w. The regulating power provided by generators for ancillary services. Based on the regulating resource prices at grid nodes and the regulating power provided by flexible resource aggregators in ancillary service scenarios, the revenue of flexible resource aggregators participating in multiple ancillary service scenarios is calculated. The formula for calculating the revenue of flexible resource aggregators participating in multiple ancillary service scenarios is as follows: In the formula, To enable flexible resource aggregators to participate in multiple ancillary service scenarios and generate revenue, The regulating power provided for flexible resource aggregators to participate in ancillary services. Based on the regulating data value of flexible resources and the amount of power regulating data injected by communication nodes, the value of power and communication network coordinated regulation data is calculated. The formula for calculating the value of power and communication network coordinated regulation data is as follows: In the formula, VoD (Voice of Data) is used to coordinate the regulation of power and communication networks and enhance their data value. w To leverage the value of data for flexible resource management The amount of power regulation data injected into the communication node. Based on the generator's regulation power cost coefficient and the regulation power provided by the generator participating in ancillary services, the cost of generator participation in multiple ancillary service scenarios is calculated. The formula for calculating the cost of generator participation in multiple ancillary service scenarios is as follows: In the formula, For the cost of generators participating in multiple ancillary service scenarios, a G and b G All figures represent the generator's regulation power cost coefficient. Based on the flexible resource aggregator's regulation power cost coefficient and the regulation power provided by the flexible resource aggregator in participating in ancillary services, the cost of the flexible resource aggregator participating in multiple ancillary service scenarios is calculated. The formula for calculating the cost of the flexible resource aggregator participating in multiple ancillary service scenarios is as follows: In the formula, To reduce the cost for flexible resource aggregators participating in multiple ancillary service scenarios, a A and b AAll are the adjustable power cost coefficients for flexible resource aggregators.

[0157] Then, based on the output of the equivalent model of the power-communication coupled network, the power network operation constraint set, the benefits of generators participating in multiple ancillary service scenarios, the benefits of flexible resource aggregators participating in multiple ancillary service scenarios, the data value of power-communication network collaborative regulation, the costs of generators participating in multiple ancillary service scenarios, the costs of flexible resource aggregators participating in multiple ancillary service scenarios, and the data communication costs of power-communication network collaborative regulation, a collaborative regulation objective function is constructed. The expression of the collaborative regulation objective function is as follows: In the formula, To coordinate and regulate the value of the objective function, To assist in the coordinated regulation of data communication costs between power and communication networks in service scenario w, To coordinate and regulate the overall data communication costs.

[0158] In some embodiments, in step S106, coupled network coordinated regulation can be performed based on the coordinated regulation objective function. For example, the coordinated regulation objective function can be solved to obtain its value, and then coupled network coordinated regulation can be performed based on this value. It is understood that when solving the coordinated regulation objective function, the goal is to maximize the net benefits of power regulation and data communication, and the output of the equivalent model of the coupled power and communication network and the power network operation constraint set are used as the solution constraints to calculate the value of the coordinated regulation objective function. Further, the power and communication network coordinated optimization regulation problem in the multi-ancillary service scenario of this embodiment is a typical convex optimization problem, which can be directly solved using the commercial solver Gurobi. By considering the data communication demand generated by power resource regulation and the corresponding differential distribution of data value, a coordinated regulation method for power and communication networks in the multi-ancillary service scenario is proposed. The coordinated regulation objective function is used to obtain aggregator power resource regulation strategies for multiple ancillary service scenarios, as well as a communication resource optimization regulation strategy with spatiotemporal dynamic distribution within the communication network.

[0159] In some embodiments, the method of this embodiment can be experimentally tested, such as in a power-communication network based on the IEEE standard 5-bus system. Figure 2As shown, the power nodes where traditional generators are located are G-1, G-2, G-3, G-4, and G-5 in the diagram; the power nodes where flexible resource aggregators are located are LA-1, LA-2, and LA-3 in the diagram; the data injection type communication nodes are located at BS-2, BS-3, and BS-4 in the communication network; and the data outflow type communication node is located at BS-1 in the communication network. This embodiment considers three ancillary service scenarios: Scenario w1: frequency regulation; Scenario w2: primary standby; and Scenario w3: secondary standby. This embodiment compares the following two schemes: Scheme 1 is the traditional scheme, where the dispatch center does not consider the data communication cost and data value gain in the communication network; Scheme 2 is the method of this embodiment, where the dispatch center considers the data communication cost and data value gain, and performs resource regulation and control for flexible resources participating in multiple ancillary service scenarios. A comparison of the total regulation capacity of traditional generators participating in multiple ancillary service scenarios is provided. Figure 3 As shown, the total adjustment capacity of flexible resource aggregators participating in multiple ancillary service scenarios is compared to... Figure 4 As shown, compared with traditional solutions, this embodiment, considering data communication costs and data value gains, shows an overall decreasing trend in the total regulation capacity of flexible resource aggregators participating in multiple ancillary service scenarios, while the total regulation capacity of traditional generators participating in multiple ancillary service scenarios increases. A comparison of the regulation capacity of traditional generators participating in various ancillary service scenarios is provided. Figure 5 As shown, the comparison of the capacity adjustment of flexible resource aggregators in various ancillary service scenarios is as follows: Figure 6 As shown, by considering data communication costs and data value gains, each flexible resource aggregator readjusts its adjustment capacity for various ancillary service scenarios. For example, because the frequency modulation ancillary service scenario requires a high data collection frequency, resulting in high data communication costs and low data value, the adjustment capacity of the flexible resource aggregator is reduced to 0. In contrast, in the primary and secondary backup ancillary service scenarios, the data collection frequency is lower, the communication cost is lower, and the data value is higher; therefore, the adjustment capacity of the flexible resource aggregator decreases relatively less, by 2.01% and 0.81%, respectively.

[0160] In some embodiments, this embodiment first explores the value of regulation data in scenarios where flexible resources participate in multiple ancillary services, providing a value reference for the priority of power regulation data transmission in the communication network. Then, it establishes an equivalent model of the power-communication coupled network for flexible resource regulation and calculates the model output to describe the spatial dynamic characteristics of the communication network. Next, by considering the impact of data communication costs and data value on power regulation resources, it establishes a collaborative regulation model of the power-communication network in multiple ancillary service scenarios under the influence of data value, which is used to construct and solve the collaborative regulation objective function. Finally, it realizes the effective regulation of the power system's flexible resources in multiple ancillary service scenarios, improving the benefits of collaborative optimization regulation of the power-communication network.

[0161] The beneficial effects of implementing the embodiments of the present invention include: First, the embodiments of the present invention acquire flexible resource data information, calculate the control data value of flexible resources based on the flexible resource data information, then calculate the output of the equivalent model of the power and communication coupled network based on the equivalent power network composition structure, and construct a power network operation constraint set. Then, based on the control data value of flexible resources, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set, construct a collaborative control objective function. Finally, based on the collaborative control objective function, perform collaborative control of the coupled network, thereby enabling network collaborative control through the calculation of the revenue of the power and communication coupled network, and thus improving the revenue of collaborative control.

[0162] like Figure 7 As shown, this embodiment of the invention also provides a power network and communication network coordinated control device, comprising:

[0163] The first module 801 is used to acquire flexible resource data information, which includes data quality, data timeliness, and the value of power resources.

[0164] The second module 802 is used to calculate the value of the control data of flexible resources based on the flexible resource data information;

[0165] The third module 803 is used to calculate the output of the equivalent model of the power and communication coupled network based on the equivalent power network composition structure. The equivalent power network composition structure includes the communication node structure, communication branch structure or communication topology structure. The output of the equivalent model of the power and communication coupled network includes the data injection amount of the communication node, the communication cost of communication power flow transmission or the node communication power flow balance constraint.

[0166] Module 4, 804, is used to construct the power network operation constraint set;

[0167] Module 5, 805, is used to construct a collaborative control objective function based on the value of flexible resource regulation data, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set. The objective of the collaborative control objective function is to maximize the net benefits of power regulation and the net benefits of data communication.

[0168] The sixth module, 806, is used for coupled network coordinated regulation based on the coordinated regulation objective function.

[0169] The content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0170] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for coordinated control of power grids and communication networks, characterized in that, Includes the following steps: Acquire flexible resource data information, including data quality, data timeliness, and the value of electricity resources; Based on the aforementioned flexible resource data information, calculate the value of the flexible resource regulation data; Based on the equivalent power network composition structure, the output of the equivalent model of the power and communication coupled network is calculated. The equivalent power network composition structure includes the communication node structure, communication branch structure, or communication topology structure. The output of the equivalent model of the power and communication coupled network includes the data injection amount of the communication node, the communication cost of communication power flow transmission, or the node communication power flow balance constraint. Construct a set of power network operation constraints; Based on the value of the flexible resource regulation data, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set, a collaborative regulation objective function is constructed. The objective of the collaborative regulation objective function is to maximize the net benefits of power regulation and the net benefits of data communication. Based on the aforementioned collaborative regulation objective function, coupled network collaborative regulation is performed; Wherein, when the equivalent power network composition structure is the communication node structure, the step of calculating the output of the equivalent model of the power and communication coupling network based on the equivalent power network composition structure includes: The amount of power control data injected by the communication node is calculated based on the correlation coefficient between the amount of power control resources, the amount of flexible resource adjustment and the amount of control data generated. The amount of power control data flowing out of the communication node is calculated based on the correlation coefficient between the amount of power control resources and the amount of flexible resource adjustment and the amount of control data generated. The data injection amount of the communication node is calculated based on the element node association matrix of the data injection communication node and the full communication node, the element node association matrix of the data outflow communication node and the full communication node, the amount of power control data injected by the communication node, and the amount of power control data outflowed by the communication node.

2. The method according to claim 1, characterized in that, The step of calculating the regulatory data value of flexible resources based on the flexible resource data information includes: Calculate the intrinsic attribute evaluation value of the data based on the data quality, the data timeliness, the data quality weight, and the data timeliness weight. Based on the power resource value, power dispatch cycle, data acquisition interval, and unit conversion factor, calculate the evaluation value of the external attributes of the data; The value of the flexible resource control data is calculated based on the intrinsic attribute evaluation value of the data, the extrinsic attribute evaluation value of the data, and the set of auxiliary service scenarios.

3. The method according to claim 1, characterized in that, When the equivalent power network structure is the communication branch structure, the step of calculating the equivalent model output of the power-communication coupled network based on the equivalent power network structure includes: Calculate the communication flow in a single auxiliary service scenario based on the data flow allocated to the communication tributaries; Based on the communication flow matrix of multiple communication branches and the communication flow under the single auxiliary service scenario, calculate the branch communication flow under the multiple auxiliary service scenario; Based on the branch communication flow in the multi-auxiliary service scenario, construct the communication branch transmission constraints; The communication cost of the communication flow transmission is calculated based on the branch communication flow in the multi-auxiliary service scenario, the transmission constraints of the communication branch, and the communication charging price parameters.

4. The method according to claim 1, characterized in that, When the equivalent power network structure is the communication topology, the step of calculating the equivalent model output of the power-communication coupled network based on the equivalent power network structure includes: Calculate the node-branch association value based on the association relationship between the communication node and the communication branch; Calculate the node-branch association matrix based on the node-branch association values; Based on the data injection volume of the communication node, the node-branch association matrix, and the branch communication flow in the multi-auxiliary service scenario, the node communication flow balance constraint is constructed.

5. The method according to claim 1, characterized in that, The power network operation constraint set includes a generator operation constraint set and a regulation resource balance constraint set. Constructing the power network operation constraint set includes: Based on the generator's power output before participating in ancillary services, the generator's power output after participating in ancillary services, and the regulation power provided by the generator participating in ancillary services, the first generator's operating constraints are constructed. Based on the upper limit of the generator's power generation after participating in ancillary services and the lower limit of the generator's power generation after participating in ancillary services, a second generator operation constraint is constructed; Based on the reactive power of the generator after participating in ancillary services, the upper limit of the reactive power of the generator after participating in ancillary services, and the lower limit of the reactive power of the generator after participating in ancillary services, a third generator operation constraint is constructed. Based on the active power regulation capacity limitation of the generator, the operating constraints of the fourth generator are constructed; Based on the generator's reactive power regulation capacity limit and the generator's reactive power before participating in ancillary services, the fifth generator's operating constraints are constructed. The first generator operation constraint, the second generator operation constraint, the third generator operation constraint, the fourth generator operation constraint, and the fifth generator operation constraint are combined to obtain the generator operation constraint set; Based on the generator set-node association matrix, the flexible resource aggregator-node association matrix, the regulation power provided by the flexible resource aggregator in ancillary services, and the regulation demand vector of each ancillary service scenario, the regulation resource balance constraint is constructed.

6. The method according to claim 1, characterized in that, The power network operation constraint set includes a flexible resource aggregator regulation operation constraint set and a node power balance constraint set. The construction of the power network operation constraint set includes: Based on the load power before the flexible resource aggregator participates in ancillary services, the load power after the flexible resource aggregator participates in ancillary services, and the regulation power provided by the flexible resource aggregator participating in ancillary services, the first flexible resource aggregator's control and operation constraints are constructed. Based on the upper limit of load power after the flexible resource aggregator participates in ancillary services and the lower limit of load power after the flexible resource aggregator participates in ancillary services, a second flexible resource aggregator regulation and operation constraint is constructed. Based on the adjustment capacity limitations of flexible resource aggregators, construct the control and operation constraints for third flexible resource aggregators; The first flexible resource aggregator control operation constraint, the second flexible resource aggregator control operation constraint, and the third flexible resource aggregator control operation constraint are combined to obtain the flexible resource aggregator control operation constraint set. Based on the injected active power flow of power nodes, the association matrix between generator sets and nodes, the power generation of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the load power after flexible resource aggregators participate in ancillary services, the power balance constraints of the first node are constructed. Based on the injected reactive power flow of power nodes, the association matrix between generator sets and nodes, the reactive power of generators after participating in ancillary services, the association matrix between flexible resource aggregators and nodes, and the reactive power of flexible resource aggregators after participating in ancillary services, a second node power balance constraint is constructed. Based on the node-branch association matrix of the power network and the active power flow of the power branches, a third node power balance constraint is constructed. Based on the node-branch association matrix of the power network and the reactive power flow of the power branches, a fourth node power balance constraint is constructed. The first node power balance constraint, the second node power balance constraint, the third node power balance constraint, and the fourth node power balance constraint are combined to obtain the node power balance constraint set.

7. The method according to claim 1, characterized in that, The power network operation constraint set includes a power grid flow constraint set, and the construction of the power network operation constraint set includes: The first power flow constraint is constructed based on the active power flow of the power branch, the real part of the branch admittance, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage magnitude of the power node, and the phase angle of the power node. The second power flow constraint is constructed based on the reactive power flow of the power branch, the imaginary part of the branch admittance, the node-branch correlation matrix of the power network, the voltage amplitude of the power node, and the phase angle of the power node. A third power flow constraint is constructed based on the upper and lower limits of the voltage amplitude of the power nodes. The fourth power flow constraint is constructed based on the upper and lower limits of the phase angle of the power nodes. Based on the upper limit and lower limit of the active power flow of the power branch, the power flow constraints of the fifth power grid are constructed. Based on the upper limit and lower limit of reactive power flow of the power branch, the sixth power flow constraint of the power grid is constructed. The first power flow constraint, the second power flow constraint, the third power flow constraint, the fourth power flow constraint, the fifth power flow constraint, and the sixth power flow constraint are combined to obtain the power flow constraint set.

8. The method according to claim 1, characterized in that, The step of constructing a collaborative control objective function based on the control data value of the flexible resources, the output of the equivalent model of the power-communication coupled network, and the power network operation constraint set includes: Calculate the revenue of generators participating in multiple ancillary services based on the regulation resource prices of grid nodes and the regulation power provided by generators participating in ancillary services. Calculate the revenue of flexible resource aggregators participating in multiple ancillary service scenarios based on the regulation resource prices of grid nodes and the regulation power provided by flexible resource aggregators participating in ancillary services. The value of coordinated control data between the power and communication networks is calculated based on the value of the control data of the flexible resources and the amount of power control data injected by the communication nodes. Calculate the cost of generator participation in multiple ancillary services scenarios based on the generator's regulation power cost coefficient and the regulation power provided by the generator in participating in ancillary services. Calculate the cost of flexible resource aggregators participating in multiple ancillary service scenarios based on the adjustment power cost coefficient of flexible resource aggregators and the adjustment power provided by flexible resource aggregators in participating in ancillary services. Based on the output of the equivalent model of the power and communication coupled network, the power network operation constraint set, the benefits of the generator participating in multiple ancillary service scenarios, the benefits of the flexible resource aggregator participating in multiple ancillary service scenarios, the data value of the power and communication network collaborative regulation, the cost of the generator participating in multiple ancillary service scenarios, the cost of the flexible resource aggregator participating in multiple ancillary service scenarios, and the data communication cost of the power and communication network collaborative regulation, the collaborative regulation objective function is constructed.

9. A power network and communication network coordinated control device, characterized in that, include: The first module is used to acquire flexible resource data information, which includes data quality, data timeliness, and the value of electricity resources. The second module is used to calculate the value of the control data of the flexible resources based on the flexible resource data information. The third module is used to calculate the output of the equivalent model of the power and communication coupling network based on the equivalent power network composition structure. The equivalent power network composition structure includes the communication node structure, communication branch structure or communication topology structure. The output of the equivalent model of the power and communication coupling network includes the data injection amount of the communication node, the communication cost of communication power flow transmission or the node communication power flow balance constraint. The fourth module is used to construct the power network operation constraint set; The fifth module is used to construct a collaborative regulation objective function based on the regulation data value of the flexible resources, the output of the equivalent model of the power and communication coupled network, and the power network operation constraint set. The objective function of the collaborative regulation objective function is to maximize the net benefits of power regulation and the net benefits of data communication. The sixth module is used to perform coupled network coordinated regulation based on the aforementioned coordinated regulation objective function; Wherein, when the equivalent power network composition structure is the communication node structure, the step of calculating the output of the equivalent model of the power and communication coupling network based on the equivalent power network composition structure includes: The amount of power control data injected by the communication node is calculated based on the correlation coefficient between the amount of power control resources, the amount of flexible resource adjustment and the amount of control data generated. The amount of power control data flowing out of the communication node is calculated based on the correlation coefficient between the amount of power control resources and the amount of flexible resource adjustment and the amount of control data generated. The data injection amount of the communication node is calculated based on the element node association matrix of the data injection communication node and the full communication node, the element node association matrix of the data outflow communication node and the full communication node, the amount of power control data injected by the communication node, and the amount of power control data outflowed by the communication node.

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