Virtual power plant internal resource classification and monomer modeling method and system

Abstract

The invention discloses a virtual power plant internal resource classification and monomer modeling method and system, and relates to the technical field of virtual power plant resource modeling, and the method comprises the steps: obtaining power plant resource information of a target virtual power plant and external power characteristics of the power plant resource information participating in power grid adjustment; based on the external power characteristics, classifying the power plant resource information to obtain a plurality of resource types and resource type information corresponding to each resource type; based on the multiple pieces of resource type information, respectively constructing a resource monomer model corresponding to each resource type; constructing a constraint set of the resource monomer model; and constructing a resource monomer external characteristic mathematical model of the target virtual power plant based on the resource monomer model and the constraint set. According to the method, classified management and external resource characteristic analysis of the internal resources of the virtual power plant are facilitated, and reference can be provided for adjustment potential mining, resource aggregation analysis, operation regulation management, resource operation time sequence organization, resource configuration and the like of the internal resources of the virtual power plant.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plant resource modeling, and in particular to a method and system for classifying and modeling internal resources of a virtual power plant. Background Art

[0002] With the rise of flexible resources such as large-scale flexible adjustable loads, distributed power sources, and energy storage on the power distribution and consumption side in my country, virtual power plants (VPPs) are enabling their aggregate management, enabling them to participate in grid regulation and control, and increasingly serving as demand-side resources in the form of microgrids and regional energy interconnections. Based on communications, control, and computer technologies, VPPs aggregate independent flexible load resources, energy storage resources, and distributed generation resources, allowing them to participate in the electricity market and various transactions in the wholesale electricity market. They provide capacity and ancillary services for grid operations, improve the economic efficiency and reliability of the power system, and promote the efficient and optimized integration of renewable energy. As my country embarks on its journey towards a low-carbon energy transition, VPPs will also serve as a key means of supporting the stable operation of the new power system.

[0003] The development of virtual power plants is premised on the development of three types of controllable resources: flexible and adjustable loads, distributed power sources, and energy storage. These three fundamental resources are often aggregated in reality. Accordingly, virtual power plants can be categorized into three types, based on the underlying resources: demand-side resource-based, supply-side resource-based, and hybrid resource-based. Currently, there is a lack of unified and refined modeling and comprehensive model analysis for individual power, load, and energy storage resources within virtual power plants. In particular, there is a lack of a universal mathematical model that comprehensively considers the key characteristics and key physical factors of each type of resource within a virtual power plant. This has resulted in an inability to effectively analyze and explore the regulatory potential and resource aggregation of resources within virtual power plants. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for classifying internal resources and modeling monomers of a virtual power plant in order to solve at least one of the above technical problems.

[0005] In the first aspect, an embodiment of the present invention provides a method for classifying and modeling internal resources of a virtual power plant, including: obtaining the power plant resource information of a target virtual power plant and the external power characteristics of the power plant resource information participating in grid regulation; based on the external power characteristics, classifying the power plant resource information to obtain multiple resource types and resource type information corresponding to each resource type; the resource types include power resources, energy storage resources and load resources; the resource type information includes power resource information, energy storage resource information and load resource information; based on the multiple resource type information, constructing a resource monomer model corresponding to each resource type respectively; the resource monomer model includes: a power resource monomer model, an energy storage resource monomer model and a load resource monomer model; constructing a constraint set of the resource monomer model; based on the resource monomer model and the constraint set, constructing a resource monomer external characteristic mathematical model of the target virtual power plant; the resource monomer external characteristic mathematical model includes: a power resource monomer external characteristic mathematical model, an energy storage power resource monomer external characteristic mathematical model and a load resource monomer external characteristic mathematical model.

[0006] Optionally, the power resources include: distributed wind power generation, distributed solar power generation, distributed gas power generation, distributed hydropower generation, and trigeneration of heat and cooling; the energy storage resources include lead-acid batteries, sodium-sulfur batteries, supercapacitors, and superconducting energy storage; the load resources include curtailable loads, transferable loads, and shiftable loads, etc.

[0007] Optionally, the power source resource information includes: power source resource power generation type, upward climbing rate, downward climbing rate, single installed capacity, operating cost, minimum startup operation coefficient, start-stop constraint, single startup operation cost, single shutdown operation cost, upward rotation reserve capacity, and downward rotation reserve capacity; the energy storage resource information includes: charging and discharging energy loss factor, charging performance efficiency, discharging performance efficiency, charging power upper limit, discharging power upper limit, single installed capacity, energy storage level when starting to participate in operation scheduling, and energy storage level when ending participation in operation scheduling; the load resource information includes: actual electricity price of price-driven load resources, actual electricity demand of price-driven load resources, basic electricity demand of price-driven load resources, price-driven influencing factor, allowable time domain of price-driven acceptable price-driven load resources, load demand baseline of subsidy-incentivized load resources when not receiving subsidy incentives, actual electricity demand of subsidy-incentivized load resources, and allowable time domain of subsidy-incentivized load resources that can accept subsidy incentives.

[0008] Optionally, the power resource monomer model includes: a power resource monomer ramping model, a power resource monomer adjustment model, a power resource monomer start-stop model, a power resource monomer upward rotation spare capacity model, and a power resource monomer downward rotation spare capacity model; wherein,

[0009] The power resource single ramp-up model includes:

[0010]

[0011] Where: The downward ramp rate of the power resource unit; The upward ramp rate of a power resource unit; The power resource unit is generating power externally at time t+1; is the power supply unit's external power supply at time t; Δt is the sampling step length of the power supply unit's operation scheduling data;

[0012] The power resource monomer regulation model includes:

[0013]

[0014] Where: is the operating cost of the power resource unit at time t; is the operating state variable of the power resource unit at time t, which takes the value of 1 when it is running and 0 when it is stopped; The nth coefficient of the polynomial function of the operating cost of a single power resource; is the load rate of the power resource unit at time t; β source The minimum startup coefficient of a single power resource unit; The installed capacity of a single power resource;

[0015] The power resource monomer start-stop model includes:

[0016]

[0017] Where: T is the operation scheduling period; The operating state variable of the power resource unit at time t+1, which takes the value of 1 when it is running and 0 when it is stopped; The upper limit of the number of starts and stops allowed within the scheduling operation cycle of a power resource unit; The cost of starting and stopping the power resource unit at time t; The cost of starting and operating a single power resource unit; The cost of a single shutdown of a power resource unit;

[0018] The power resource unit upward rotation spare capacity model includes:

[0019]

[0020] Where: Ω is the upward rotation reserve capacity of the power resource unit at time t; source It is the total collection of power resource monomers; SR up The total upward spin reserve capacity limit for power resources;

[0021] The power resource unit downward rotation reserve capacity model includes:

[0022]

[0023] Where: SR is the downward rotation reserve capacity of the power resource unit at time t; down Total downward spin reserve capacity limit for power class resources.

[0024] Optionally, the energy storage resource monomer model includes: an energy storage resource monomer charge and discharge capacity level model, an energy storage resource monomer charge and discharge power model, and an energy storage resource monomer operation capacity model; wherein,

[0025] The energy storage resource monomer charge and discharge capacity level model includes:

[0026]

[0027] Where: is the energy storage level of the energy storage resource unit at time t; is the energy storage capacity level of a single energy storage resource at time t-1; δ storage is the energy loss factor of charging and discharging of energy storage resources; η storage,cha Charging performance efficiency of energy storage resources; is the charging power value of the energy storage resource unit at time t; is the discharge power value of the energy storage resource unit at time t; η storage,dis is the discharge performance efficiency of energy storage resources; Δt is the sampling step of the operation scheduling data of power resources;

[0028] The energy storage resource single charge and discharge power model includes:

[0029]

[0030] Where: The upper limit of charging power for a single energy storage resource; The upper limit of the discharge power of a single energy storage resource;

[0031] The energy storage resource single unit operation capacity model includes:

[0032]

[0033] Where: The energy storage level when the energy storage resource unit starts to participate in operation and scheduling; is the energy storage level of the energy storage resource unit when it starts to participate in operation scheduling at time t0; ε storage The energy storage level balance tolerance factor of the energy storage resource unit at the beginning and end of the operation scheduling cycle; The energy storage level of the energy storage resource unit when it stops participating in operation and scheduling; The lower limit allowable coefficient of the energy level during the operation of a single energy storage resource; The installed capacity of a single unit of energy storage resources; It is the upper limit allowable coefficient of energy level during the operation of a single energy storage resource.

[0034] Optionally, the load resource monomer module includes: a price-driven load resource monomer model and a subsidy incentive load resource monomer model; wherein,

[0035] The price-driven load resource monomer model includes:

[0036]

[0037] Where: The electricity cost of a price-driven load resource unit at time t; The actual electricity price of a price-driven load resource unit at time t; is the actual electricity demand of the price-driven load resource unit at time t; is the basic electricity demand of price-driven load resource units at time t; The change in electricity consumption of a price-driven load resource unit at time t after being affected by price driving; is the price change at time t; and are different price driving factors; Δλ The permissible time domain for price-driven load resource units to accept price-driven behavior;

[0038] The subsidy incentive load resource single model includes:

[0039]

[0040] Where: is the load demand change of the subsidy-incentive load resource unit at time t affected by the subsidy incentive; is the load demand baseline of the subsidy-incentive load resource unit at time t when it is not receiving subsidy incentives; is the actual electricity demand of the subsidy incentive load resource unit at time t; μ The permissible time domain for a single load resource unit of subsidy incentive type to receive subsidy incentive; μ is the subsidy income obtained by the subsidy incentive load resource unit at time t; I 、μ II 、μ III These are the subsidy incentive price factors for the first, second, and third tiers respectively; These are the load demand change range sets for the first echelon, second echelon, and third echelon respectively.

[0041] Optionally, the constraint set includes a power resource monomer model constraint set, an energy storage resource monomer model constraint set and a load resource monomer model constraint set; wherein the power resource monomer model constraint set includes: external power characteristic constraints, start and stop constraints of units within the operating cycle, operating cost constraints, installed capacity constraints, upward climbing rate constraints, and downward climbing rate constraints; the energy storage resource monomer model constraint set includes: discharge power constraints, charging power constraints, energy storage capacity level constraints, capacity balance level constraints within the operating cycle, installed capacity constraints, and charge and discharge power mutual exclusion constraints; the load resource monomer model constraint set includes: load call operating cost constraints, responsive change level constraints, responsive change time domain limit constraints, baseline load constraints, and responsive change limit constraints.

[0042] In the second aspect, an embodiment of the present invention further provides a virtual power plant internal resource classification and monomer modeling system, including: an acquisition module, a classification module, a first construction module, a second construction module and a third construction module; wherein the acquisition module is used to obtain the power plant resource information of the target virtual power plant and the external power characteristics of the power plant resource information participating in grid regulation; the classification module is used to classify the power plant resource information based on the external power characteristics to obtain multiple resource types and resource type information corresponding to each resource type; the resource types include power source resources, energy storage resources and load resources; the resource type information includes power source resource information, energy storage resource information and load resource information Source information; the first construction module is used to construct a resource monomer model corresponding to each resource type based on the multiple resource type information; the resource monomer model includes: a power supply resource monomer model, an energy storage resource monomer model and a load resource monomer model; the second construction module is used to construct a constraint set of the resource monomer model; the third construction module is used to construct a resource monomer external characteristic mathematical model of the target virtual power plant based on the resource monomer model and the constraint set; the resource monomer external characteristic mathematical model includes: a power supply resource monomer external characteristic mathematical model, an energy storage power supply resource monomer external characteristic mathematical model and a load resource monomer external characteristic mathematical model.

[0043] In a third aspect, an embodiment of the present invention further provides an electronic device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0044] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method provided in the embodiment of the present invention is implemented.

[0045] The present invention provides a method and system for classifying and modeling internal resources of a virtual power plant and a single entity, which fully considers the complex and diverse resources within the virtual power plant, proposes a classification method for the internal resources of the virtual power plant, and divides the internal resources of the virtual power plant into power resources, energy storage resources, and load resources, which is helpful for quickly performing asset statistics, resource profiling, and resource management of the resources; constructs a refined mathematical model of the power resources, load resources, and energy storage resources within the virtual power plant, comprehensively considers the main characteristics and elements of the resources, and is helpful for exploring the resource regulation potential and resource aggregation analysis; considers the start and stop characteristics, operating costs, and other factors of the power resources, load resources, and energy storage resources within the virtual power plant during the operation and scheduling cycle, which is helpful for comprehensive analysis of resource operation timing and resource allocation in operation scheduling and regulation management. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0047] Figure 1 A flowchart of a method for classifying internal resources and modeling individual units of a virtual power plant provided by an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of a virtual power plant internal resource classification and monomer modeling system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0050] Example 1

[0051] Figure 1 This is a flow chart of a method for classifying internal resources and modeling a single unit of a virtual power plant according to an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps:

[0052] Step S102: obtaining the power plant resource information of the target virtual power plant and the external power characteristics of the power plant resource information participating in grid regulation.

[0053] In step S104, based on the external power characteristics, the power plant resource information is classified to obtain multiple resource types and resource type information corresponding to each resource type; the resource types include power resources, energy storage resources and load resources; the resource type information includes power resource information, energy storage resource information and load resource information.

[0054] Step S106: Based on the multiple resource type information, construct a resource monomer model corresponding to each resource type; the resource monomer model includes: a power resource monomer model, an energy storage resource monomer model, and a load resource monomer model.

[0055] Step S108: constructing a constraint set of the resource monomer model.

[0056] Step S110, based on the resource unit model and the constraint set, construct a resource unit external characteristic mathematical model of the target virtual power plant; the resource unit external characteristic mathematical model includes: a power source resource unit external characteristic mathematical model, an energy storage power source resource unit external characteristic mathematical model and a load resource unit external characteristic mathematical model.

[0057] Specifically, the power plant resource information classification process in step S104 is as follows:

[0058] For power resources, the external power participating in grid regulation presents positive power, where positive power indicates an increase when it is pointing upward and a decrease when it is pointing downward;

[0059] Optionally, power resources include: distributed wind power generation, distributed solar power generation, distributed gas power generation, distributed hydropower generation, and combined heat and cool power generation;

[0060] For energy storage resources, when the external power participating in grid regulation presents positive power, the energy storage resources discharge at this time, and the positive power increases when it is upward and decreases when it is downward;

[0061] For energy storage resources, when the external power participating in grid regulation presents negative power, the energy storage resources are charged at this time, and the negative power is reduced and the positive power is increased;

[0062] Optionally, energy storage resources include lead-acid batteries, sodium-sulfur batteries, supercapacitors, and superconducting energy storage;

[0063] For load resources, the external power participating in grid regulation presents negative power. Negative power is decreasing when it is pointing upward, and increasing when it is pointing upward.

[0064] Optionally, load resources include curtailable loads, transferable loads, and shiftable loads.

[0065] Specifically, power resource information includes: power resource generation type, upward ramp rate, downward ramp rate, single installed capacity, operating cost, minimum startup coefficient, start-stop constraints, single startup operating cost, single shutdown operating cost, upward spin-up reserve capacity, and downward spin-up reserve capacity;

[0066] Energy storage resource information, including: charge and discharge energy loss factor, charging performance efficiency, discharge performance efficiency, charging power upper limit, discharge power upper limit, single unit installed capacity, energy storage level at the start of operation and scheduling, and energy storage level at the end of operation and scheduling;

[0067] Load resource information includes: actual electricity price of price-driven load resources, actual electricity demand of price-driven load resources, basic electricity demand of price-driven load resources, price-driven influencing factors, allowable time domain for price-driven individual load resources, load demand baseline when subsidy-incentivized load resources are not subsidized, actual electricity demand of subsidy-incentivized load resources, and allowable time domain for subsidy-incentivized load resources to accept subsidy incentives.

[0068] Specifically, the power resource monomer model includes: a power resource monomer ramp model, a power resource monomer adjustment model, a power resource monomer start and stop model, a power resource monomer upward rotation spare capacity model, and a power resource monomer downward rotation spare capacity model; wherein,

[0069] The power resource single ramp-up model includes:

[0070]

[0071] Where: The downward ramp rate of the power resource unit; The upward ramp rate of a power resource unit; The power resource unit is generating power externally at time t+1; is the power supply unit's external power supply at time t; Δt is the sampling step length of the power supply unit's operation scheduling data;

[0072] The power resource single-unit regulation model includes:

[0073]

[0074] Where: is the operating cost of the power resource unit at time t; is the operating state variable of the power resource unit at time t, which takes the value of 1 when it is running and 0 when it is stopped; The nth coefficient of the polynomial function of the operating cost of a single power resource; is the load rate of the power resource unit at time t; β source The minimum startup coefficient of a single power resource unit; The installed capacity of a single power resource;

[0075] The power resource single-unit start / stop model includes:

[0076]

[0077] Where: T is the operation scheduling period; The operating state variable of the power resource unit at time t+1, which takes the value of 1 when it is running and 0 when it is stopped; The upper limit of the number of starts and stops allowed within the scheduling operation cycle of a power resource unit; The cost of starting and stopping the power resource unit at time t; The cost of starting and operating a single power resource unit; The cost of a single shutdown of a power resource unit;

[0078] The upward rotation reserve capacity model for power resources includes:

[0079]

[0080] Where: Ω is the upward rotation reserve capacity of the power resource unit at time t; source It is the total collection of power resource monomers; SR up The total upward spin reserve capacity limit for power resources;

[0081] The power resource unit downward rotation reserve capacity model includes:

[0082]

[0083] Where: SR is the downward rotation reserve capacity of the power resource unit at time t; down Total downward spin reserve capacity limit for power class resources.

[0084] Specifically, the energy storage resource monomer model includes: an energy storage resource monomer charge and discharge capacity level model, an energy storage resource monomer charge and discharge power model, and an energy storage resource monomer operation capacity model; wherein,

[0085] The single-unit charge and discharge capacity level model of energy storage resources includes:

[0086]

[0087] Where: is the energy storage level of the energy storage resource unit at time t; is the energy storage capacity level of a single energy storage resource at time t-1; δ storage is the energy loss factor of charging and discharging of energy storage resources; η storage,cha Charging performance efficiency of energy storage resources; is the charging power value of the energy storage resource unit at time t; is the discharge power value of the energy storage resource unit at time t; η storage,disis the discharge performance efficiency of energy storage resources; Δt is the sampling step of the operation scheduling data of power resources;

[0088] The single-unit charging and discharging power models of energy storage resources include:

[0089]

[0090] Where: The upper limit of charging power for a single energy storage resource; The upper limit of the discharge power of a single energy storage resource;

[0091] The single-unit operating capacity model of energy storage resources includes:

[0092]

[0093] Where: The energy storage level when the energy storage resource unit starts to participate in operation and scheduling; is the energy storage level of the energy storage resource unit when it starts to participate in operation scheduling at time t0; ε storage The energy storage level balance tolerance factor of the energy storage resource unit at the beginning and end of the operation scheduling cycle; The energy storage level of the energy storage resource unit when it stops participating in operation and scheduling; The lower limit allowable coefficient of the energy level during the operation of a single energy storage resource; The installed capacity of a single unit of energy storage resources; It is the upper limit allowable coefficient of energy level during the operation of a single energy storage resource.

[0094] Specifically, the load resource monomer module includes: a price-driven load resource monomer model and a subsidy incentive load resource monomer model;

[0095] The price-driven load resource single model includes:

[0096]

[0097] Where: The electricity cost of a price-driven load resource unit at time t; The actual electricity price of a price-driven load resource unit at time t; is the actual electricity demand of the price-driven load resource unit at time t; is the basic electricity demand of price-driven load resource units at time t; The change in electricity consumption of a price-driven load resource unit at time t after being affected by price driving; is the price change at time t; and are different price driving factors; Δλ The permissible time domain for price-driven load resource units to accept price-driven behavior;

[0098] The subsidy incentive load resource single unit model includes:

[0099]

[0100] Where: is the load demand change of the subsidy-incentive load resource unit at time t affected by the subsidy incentive; is the load demand baseline of the subsidy-incentive load resource unit at time t when it is not receiving subsidy incentives; is the actual electricity demand of the subsidy incentive load resource unit at time t; μ The permissible time domain for a single load resource unit of subsidy incentive type to receive subsidy incentive; μ is the subsidy income obtained by the subsidy incentive load resource unit at time t; I 、μ II 、μ III These are the subsidy incentive price factors for the first, second, and third tiers respectively; These are the load demand change range sets for the first echelon, second echelon, and third echelon respectively.

[0101] Specifically, the constraint set includes a power resource single model constraint set, an energy storage resource single model constraint set, and a load resource single model constraint set; wherein,

[0102] The constraint set of the power resource single model includes: external power characteristics constraint, unit start and stop constraint within the operation cycle, operation cost constraint, installed capacity constraint, upward climbing rate constraint, and downward climbing rate constraint;

[0103] Constraints for individual energy storage resource models include: discharge power constraints, charging power constraints, energy storage capacity level constraints, capacity balance level constraints within the operating cycle, installed capacity constraints, and charge and discharge power mutual exclusion constraints;

[0104] The constraint set of the load resource single model includes: load call operation cost constraint, responsive change level constraint, responsive change time domain constraint, baseline load constraint, and responsive change limit constraint.

[0105] Specifically, step S110 includes the following steps:

[0106] Based on the power resource monomer model constraint set and the number and unique physical characteristics of each power resource monomer, a specific mathematical model of the external characteristics of the power resource monomer is generated according to the established power resource monomer model;

[0107] Based on the energy storage resource monomer model constraint set and the number and unique physical characteristics of each energy storage resource monomer, a specific external characteristic mathematical model of the energy storage power resource monomer is generated according to the established energy storage resource monomer model;

[0108] Based on the constraint set of the load resource monomer model and the number and unique physical characteristics of each load resource monomer, a specific mathematical model of the external characteristics of the load resource monomer is generated according to the established load resource monomer model.

[0109] The method provided by the embodiment of the present invention further includes: outputting a mathematical model of external characteristics of a resource unit of the target virtual power plant.

[0110] As can be seen from the above description, the embodiment of the present invention provides a method for classifying resources within a virtual power plant and modeling individual units. Compared with the prior art, it has the following technical effects:

[0111] (1) This invention fully considers the complex and diverse resources within a virtual power plant and proposes a classification method for the internal resources of a virtual power plant. The method divides the internal resources of a virtual power plant into power resources, energy storage resources, and load resources, which helps to quickly conduct asset statistics, resource profiling, and resource management.

[0112] (2) The present invention constructs a refined mathematical model of power resources, load resources, and energy storage resources within the virtual power plant, comprehensively considering the main characteristics and elements of the resources, which helps to explore the resource regulation potential and resource aggregation analysis;

[0113] (3) The present invention takes into account the start-stop characteristics, operating costs and other factors of the power resources, load resources and energy storage resources within the virtual power plant during the operation and scheduling cycle, which helps the operation scheduling and control management to comprehensively analyze the resource operation timing and resource allocation.

[0114] Example 2

[0115] Figure 2 Schematic diagram of a virtual power plant internal resource classification and monomer modeling system provided according to an embodiment of the present invention. Figure 2 The system includes: an acquisition module 10 , a classification module 20 , a first construction module 30 , a second construction module 40 and a third construction module 50 .

[0116] Specifically, the acquisition module 10 is used to obtain the power plant resource information of the target virtual power plant and the external power characteristics of the power plant resource information participating in grid regulation;

[0117] A classification module 20 is configured to classify power plant resource information based on external power characteristics to obtain multiple resource types and resource type information corresponding to each resource type; the resource types include power resources, energy storage resources, and load resources; and the resource type information includes power resource information, energy storage resource information, and load resource information;

[0118] The first construction module 30 is used to construct a resource monomer model corresponding to each resource type based on multiple resource type information; the resource monomer model includes: a power resource monomer model, an energy storage resource monomer model and a load resource monomer model;

[0119] The second construction module 40 is used to construct a constraint set of a resource monomer model;

[0120] The third construction module 50 is used to construct a resource unit external characteristic mathematical model of the target virtual power plant based on the resource unit model and the constraint set; the resource unit external characteristic mathematical model includes: a power source resource unit external characteristic mathematical model, an energy storage power source resource unit external characteristic mathematical model and a load resource unit external characteristic mathematical model.

[0121] The present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0122] The present invention also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, the method provided in the embodiment of the present invention is implemented.

[0123] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0124] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A method for classifying and modeling internal resources of a virtual power plant, characterized in that: include: Obtaining power plant resource information of a target virtual power plant and external power characteristics of the power plant resource information participating in grid regulation; Based on the external power characteristics, the power plant resource information is classified to obtain multiple resource types and resource type information corresponding to each resource type; the resource types include power resources, energy storage resources and load resources; the resource type information includes power resource information, energy storage resource information and load resource information; Based on the multiple resource type information, construct a resource monomer model corresponding to each resource type; The resource monomer model includes: a power resource monomer model, an energy storage resource monomer model and a load resource monomer model; Constructing a constraint set of the resource monomer model; Based on the resource monomer model and the constraint set, a mathematical model of the external characteristics of the resource monomer of the target virtual power plant is constructed; the mathematical model of the external characteristics of the resource monomer includes: a mathematical model of the external characteristics of the power supply resource monomer, a mathematical model of the external characteristics of the energy storage power supply resource monomer and a mathematical model of the external characteristics of the load resource monomer.

2. The method according to claim 1, wherein: The power resources include: distributed wind power generation, distributed solar power generation, distributed gas power generation, distributed hydropower generation, and combined heating, cooling and power generation; The energy storage resources include lead-acid batteries, sodium-sulfur batteries, supercapacitors, and superconducting energy storage; The load resources include loads that can be cut, loads that can be transferred, and loads that can be shifted.

3. The method according to claim 1, wherein: The power resource information includes: power resource generation type, upward ramp rate, downward ramp rate, single installed capacity, operating cost, minimum startup operation coefficient, start-stop constraint, single startup operation cost, single shutdown operation cost, upward rotation reserve capacity, and downward rotation reserve capacity; The energy storage resource information includes: charging and discharging energy loss factor, charging performance efficiency, discharging performance efficiency, charging power upper limit, discharging power upper limit, single unit installed capacity, energy storage level when participation in operation scheduling begins, and energy storage level when participation in operation scheduling ends; The load resource information includes: the actual electricity price of price-driven load resources, the actual electricity demand of price-driven load resources, the basic electricity demand of price-driven load resources, the price-driven influencing factor, the allowable time domain for price-driven load resource units to accept price-driven, the load demand baseline when subsidy-incentive load resources are not subsidized, the actual electricity demand of subsidy-incentive load resources, and the allowable time domain for subsidy-incentive load resources to accept subsidy incentives.

4. The method according to claim 1, wherein: The power resource monomer model includes: a power resource monomer ramp model, a power resource monomer adjustment model, a power resource monomer start and stop model, a power resource monomer upward rotation spare capacity model, and a power resource monomer downward rotation spare capacity model; wherein, The power resource single ramp-up model includes: Where: The downward ramp rate of the power resource unit; The upward ramp rate of power resource units; The power resource unit is generating power externally at time t+1; is the power supply unit's external power supply at time t; Δt is the sampling step length of the power supply unit's operation scheduling data; The power resource monomer regulation model includes: Where: is the operating cost of the power resource unit at time t; is the operating state variable of the power resource unit at time t, which takes the value of 1 when it is running and 0 when it is stopped; The nth coefficient of the polynomial function of the operating cost of a single power resource; is the load rate of the power resource unit at time t; β source The minimum startup coefficient of a single power resource unit; The installed capacity of a single power resource; The power resource monomer start-stop model includes: Where: T is the operation scheduling period; The operating state variable of the power resource unit at time t+1, which takes the value of 1 when it is running and 0 when it is stopped; The upper limit of the number of starts and stops allowed within the scheduling operation cycle of a power resource unit; The cost of starting and stopping the power resource unit at time t; The cost of starting and operating a single power resource unit; The cost of a single shutdown of a power resource unit; The power resource unit upward rotation spare capacity model includes: Where: Ω is the upward rotation reserve capacity of the power resource unit at time t; source It is the total collection of power resource monomers; SR up The total upward spin reserve capacity limit for power resources; The power resource unit downward rotation reserve capacity model includes: Where: SR is the downward rotation reserve capacity of the power resource unit at time t; down Total downward spin reserve capacity limit for power class resources.

5. The method according to claim 1, wherein: The energy storage resource monomer model includes: an energy storage resource monomer charge and discharge capacity level model, an energy storage resource monomer charge and discharge power model, and an energy storage resource monomer operation capacity model; wherein, The energy storage resource monomer charge and discharge capacity level model includes: Where: is the energy storage level of the energy storage resource unit at time t; is the energy storage capacity level of a single energy storage resource at time t-1; δ storage is the energy loss factor of charging and discharging of energy storage resources; η storage,cha Charging performance efficiency of energy storage resources; is the charging power value of the energy storage resource unit at time t; is the discharge power value of the energy storage resource unit at time t; η storage,dis is the discharge performance efficiency of energy storage resources; Δt is the sampling step of the operation scheduling data of power resources; The energy storage resource single charge and discharge power model includes: Where: The upper limit of charging power for a single energy storage resource; The upper limit of the discharge power of a single energy storage resource; The energy storage resource single unit operation capacity model includes: Where: The energy storage level when the energy storage resource unit starts to participate in operation and scheduling; is the energy storage level of the energy storage resource unit when it starts to participate in operation scheduling at time t0; ε storage The energy storage level balance tolerance factor of the energy storage resource unit at the beginning and end of the operation scheduling cycle; The energy storage level of the energy storage resource unit when it stops participating in operation and scheduling; The lower limit allowable coefficient of the energy level during the operation of a single energy storage resource; The installed capacity of a single unit of energy storage resources; It is the upper limit allowable coefficient of energy level during the operation of a single energy storage resource.

6. The method according to claim 1, wherein: The load resource monomer module includes: a price-driven load resource monomer model and a subsidy incentive load resource monomer model; wherein, The price-driven load resource monomer model includes: Where: The electricity cost of a price-driven load resource unit at time t; The actual electricity price of a price-driven load resource unit at time t; is the actual electricity demand of the price-driven load resource unit at time t; is the basic electricity demand of price-driven load resource units at time t; The change in electricity consumption of a price-driven load resource unit at time t after being affected by price driving; is the price change at time t; and are different price driving factors; Δλ The permissible time domain for price-driven load resource units to accept price-driven behavior; The subsidy incentive load resource single model includes: Where: is the load demand change of the subsidy-incentive load resource unit at time t affected by the subsidy incentive; is the load demand baseline of the subsidy-incentive load resource unit at time t when it is not receiving subsidy incentives; is the actual electricity demand of the subsidy incentive load resource unit at time t; μ The permissible time domain for a single load resource unit of subsidy incentive type to receive subsidy incentive; μ is the subsidy income obtained by the subsidy incentive load resource unit at time t; I 、μ II 、μ III These are the subsidy incentive price factors for the first, second, and third tiers respectively; These are the load demand change range sets for the first echelon, second echelon, and third echelon respectively.

7. The method according to claim 1, wherein: The constraint set includes a power resource single model constraint set, an energy storage resource single model constraint set and a load resource single model constraint set; wherein, The power resource single model constraint set includes: external power characteristics constraint, start and stop constraints of units within the operation cycle, operation cost constraint, installed capacity constraint, upward climbing rate constraint, and downward climbing rate constraint; The energy storage resource single model constraint set includes: discharge power constraint, charging power constraint, energy storage capacity level constraint, capacity balance level constraint within the operation cycle, installed capacity constraint, and charge and discharge power mutual exclusion constraint; The constraint set of the load resource monomer model includes: load call operation cost constraint, responsive change level constraint, responsive change time domain limit constraint, baseline load constraint, and responsive change limit constraint.

8. A virtual power plant internal resource classification and monomer modeling system, characterized by: include: an acquisition module, a classification module, a first construction module, a second construction module, and a third construction module; wherein, The acquisition module is used to obtain the power plant resource information of the target virtual power plant and the external power characteristics of the power plant resource information participating in grid regulation; The classification module is configured to classify the power plant resource information based on the external power characteristics to obtain a plurality of resource types and resource type information corresponding to each resource type; the resource types include power resources, energy storage resources, and load resources; and the resource type information includes power resource information, energy storage resource information, and load resource information; The first construction module is used to construct a resource monomer model corresponding to each resource type based on the multiple resource type information; the resource monomer model includes: a power resource monomer model, an energy storage resource monomer model and a load resource monomer model; The second construction module is used to construct a constraint set of the resource monomer model; The third construction module is used to construct a resource unit external characteristic mathematical model of the target virtual power plant based on the resource unit model and the constraint set; the resource unit external characteristic mathematical model includes: a power supply resource unit external characteristic mathematical model, an energy storage power supply resource unit external characteristic mathematical model and a load resource unit external characteristic mathematical model.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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