Method, system, medium, terminal and electronic device for dispatching and controlling energy storage and distributed resources to participate in ramping auxiliary service in cooperation

Abstract

The application relates to the technical field of climbing auxiliary service, and is a dispatching control method, system, medium, terminal and electronic equipment for energy storage and distributed resources participating in climbing auxiliary service in cooperation, which comprises a framework construction unit, a parameter input unit and a P2P transaction unit.The framework construction unit constructs a double-layer FRP and P2P energy transaction framework; the parameter input unit inputs energy transaction parameters in the double-layer FRP and P2P energy transaction framework; and the P2P transaction unit constructs an optimization model of P2P electric energy transaction in the lower layer.The application is characterized in that a flexible climbing quantity mechanism of distributed resources participation is coupled with a P2P-FRP market depth coupling architecture, demand side resources (such as electric vehicles and intelligent buildings) are standardized into tradable FRP commodities according to dynamic adjustment capacity, supply and demand are dynamically matched through a parameterized model, the climbing capacity supply of the system is significantly improved, and the renewable energy abandonment rate is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of hill-climbing assistance service technology, and in particular to a scheduling and control method, system, medium, terminal and electronic device for energy storage and distributed resources to collaboratively participate in hill-climbing assistance services. Background Technology

[0002] Flexible ramping products (FRPs) and peer-to-peer (P2P) electricity trading are two major technological paths for improving the flexibility of current power systems, but their existing mechanisms are significantly fragmented. The FRP market uses a centralized optimization model to jointly clear energy and ramping capacity on a 5-15 minute timescale. Its core reliance is on the physical regulation capabilities of traditional thermal power units (e.g., coal-fired units with a ramp rate of 2-5% / minute), compensating for energy losses due to reserved ramping capacity through opportunity cost pricing. However, this mechanism treats the demand side as a fixed load and fails to quantify the minute-level regulation potential of user-side resources (such as electric vehicles and smart buildings), leading to insufficient generation flexibility and rising system ramping costs in scenarios with high renewable energy penetration. P2P trading technology supports decentralized direct trading of electricity from resources such as distributed photovoltaics, but its commodity scope is limited to energy itself, lacking standardized definitions and trading rules for ramping capacity.

[0003] While existing technologies such as Virtual Power Plants (VPPs) attempt to aggregate demand-side resources to participate in the main energy market, their static bidding models cannot dynamically track user-level ramp-up capabilities. Furthermore, the decentralized decision-making characteristics of P2P networks conflict with the scheduling requirements of centralized Free Grid Ramp-Up (FRP) systems—for example, simultaneous load increases from multiple microgrids may cause line congestion, and existing mechanisms lack cross-node ramp-up capability coordination algorithms. More fundamentally, the opportunity cost pricing model of FRPs does not cover the utility loss from demand-side adjustments, resulting in a dual silo between "centralized ramp-up scheduling" and "distributed energy trading," leading to low overall system flexibility and resource utilization.

[0004] Furthermore, the current Flexible Ramp-up Product (FRP) market technology system is centered on generation-side resources, relying on the traditional unit regulation capabilities to construct deterministic or stochastic optimization models (such as real-time unit combination and economic dispatch of CAISO / MISO), and reserving generation-side ramp-up capacity to cope with net load fluctuations. Although demand-side resources achieve load shifting through price signals in demand response, they have not yet been deeply integrated into the FRP market mechanism, and their ramp-up contribution has not been quantitatively modeled. In the peer-to-peer (P2P) electricity trading field, existing technologies focus on the direct electrical energy of distributed energy sources, while ramp-up capacity is not defined as an independent traded commodity. The ancillary service market and P2P trading exhibit a mechanism-based separation: Virtual power plants (VPPs) use static aggregation models to bid in the energy market, but it is difficult to dynamically track user-level ramp-up capacity; the decentralized decision-making characteristics of P2P nodes are difficult to coordinate with centralized FRP dispatch, resulting in an imbalance between regional ramp-up resource supply and demand. More notably, existing technologies lack a joint market architecture that integrates "source-load coordination," resulting in a double constraint of limited flexibility on the power generation side and untapped potential on the demand side. Furthermore, P2P scenarios face new challenges such as distorted dynamic response capability assessments, cross-market incentive conflicts, and contradictions between privacy protection and real-time dispatch, ultimately leading to high system ramp-up costs, redundant reserve capacity, and low market clearing efficiency. Summary of the Invention

[0005] This invention provides a scheduling and control method, system, medium, terminal, and electronic device for energy storage and distributed resources to collaboratively participate in ramp-up assistance services. It overcomes the shortcomings of the prior art and can effectively solve the problems of low ramp-up capability and high renewable energy abandonment rate in existing ramp-up services, which cannot integrate energy storage and distributed resources.

[0006] To address the above problems, one of the technical solutions of this invention is achieved through the following method: a scheduling and control method for energy storage and distributed resources to collaboratively participate in ramp-up assistance services, comprising the following steps:

[0007] Construct a two-tier FRP and P2P energy trading framework; the energy trading framework includes independent energy storage, energy producers, energy consumers and distribution system operators;

[0008] In the two-tier FRP and P2P energy trading framework, energy trading parameters are input. These parameters include upper-tier and lower-tier energy trading parameters. The lower-tier parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-tier parameters include power distribution system operator parameters.

[0009] The lower layer constructs an optimized model for P2P electricity trading, and calculates the clearing results of the lower layer P2P electricity trading based on the lower layer energy trading parameters;

[0010] The upper layer constructs an FRP trading mechanism, updates the FRP trading power based on the P2P electricity trading clearing results, and combines the updated FRP trading power with the upper layer energy trading parameters to obtain the FRP trading clearing results.

[0011] In the aforementioned two-tier FRP and P2P energy trading framework, both two-tier FRP and P2P energy trading need to satisfy the constraints of the distribution network model, which is as follows:

[0012] (1a)

[0013] (1b)

[0014] (1c)

[0015] in, and It is a bus and The voltage; and These are the bus and The resistance and reactance of the transmission line between them; , It is a busbar and The active and reactive power flow between them; and It is a busbar and The active power flow and reactive power flow between them, of which ; and This represents the active and reactive power injection into bus n; and These are the sets of upstream and downstream buses of the bus. , Indicates the empty set; This represents the set of buses that act as a node agent.

[0016] The aforementioned lower-level optimization model for P2P electricity trading includes:

[0017] The distributed alternating direction multiplier algorithm is used to coordinate the electricity trading of all independent energy storage, energy producers and energy consumers in a decentralized manner, and bid for the electricity to participate in the trading to the distribution system operator through node agents;

[0018] Establish an optimization model for the P2P trading market under the distribution network, for the first For individual market participants, including independent energy storage providers, energy producers, and energy consumers, the objective function is:

[0019] (2)

[0020] (3)

[0021] In the formula, For the first The objective function of each market participant; The power generation cost of combined heat and power units and gas turbine units; , and These are the quadratic coefficient, linear coefficient, and constant parameter of the unit's power generation cost curve, respectively. Electricity prices will be adjusted upwards to allow participation in FRP services by distribution network operators; Lowering electricity prices for FRP services provided by distribution network operators; For the first Individual market participants Constantly adjust power from the grid and electricity retailers; For the first Individual market participants Constantly adjusting power from the grid's electricity retailers; For the first Individual market participants From the moment The electricity purchase price for each market participant; For the first Individual market participants At all times towards the first The electricity sales price of each market participant; For the first Individual market participants From the moment Electricity purchase capacity of each market participant; For the first Individual market participants At all times towards the first Electricity sales power of each market participant;

[0022] The node injection power constraints are as follows:

[0023] (4)

[0024] In the formula, , users respectively At the node The active and reactive power injected at the point; For users From other users The sum of power purchased and sold at the point; , , and users respectively The active or reactive power generated by combined heat and power and gas turbines; , , and users respectively The active or reactive power of adjustable loads and fixed loads.

[0025] The above layers construct the FRP transaction mechanism; including:

[0026] Based on the master-slave game mechanism, that is, as the leader of the FRP-P2P transaction, the distribution system operator will first determine the FRP transaction price between the distribution system operator and independent energy storage, energy producers, and energy consumers. The transaction and energy management costs of the distribution system operator are expressed as follows:

[0027] (5)

[0028] in, This represents the transaction and energy management costs for power distribution system operators; This refers to the operating and maintenance costs of diesel generators;

[0029] For energy trading, the settlement price and electricity volume of FRP commodities from distribution system operators are within the maximum and minimum ranges shown below:

[0030] (6)

[0031] (7)

[0032] in, and This represents the lower and upper limits of the price adjustment for FRP at time t; and This represents the lower and upper limits of the price adjustment under FRP at time t; and This represents the lower and upper limits of the power adjusted on the FRP at time t; and This represents the lower and upper limits of the power regulation under FRP at time t.

[0033] The optimization problem of minimizing the local P2P transaction costs for each market participant i can be expressed as:

[0034] (8)

[0035] st(3)-(4),(7)

[0036] In the formula, For the first A vector set of decision variables for each market participant. ; Let z be the reference value from the previous iteration; The iteration step size constant for the ADMM algorithm is taken as 1e-3; for initialization, the objective function at this time... And the electricity trading price in the first iteration The values ​​are all equal to 0, and the initial solution is obtained through local optimization. .

[0037] The above-mentioned clearing results for FRP transactions include:

[0038] The clearing results of FRP transactions are as follows:

[0039] (9)

[0040] st(1),(6)

[0041] Therefore, FRP and P2P are iteratively solved until the FRP market and P2P market solutions converge, generating transaction results for distributed resources participating in hill-climbing auxiliary services.

[0042] The second technical solution of this invention is achieved through the following means: a scheduling and control system for energy storage and distributed resources to collaboratively participate in ramp-up assistance services, comprising:

[0043] The framework building unit constructs a two-tier FRP and P2P energy trading framework; the energy trading framework includes independent energy storage, energy producers, energy consumers, and distribution system operators.

[0044] The parameter input unit inputs energy trading parameters in the two-layer FRP and P2P energy trading framework. The energy trading parameters include upper-layer energy trading parameters and lower-layer energy trading parameters. The lower-layer energy trading parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-layer energy trading parameters include power distribution system operator parameters.

[0045] The P2P trading unit constructs an optimized model for P2P electricity trading at the lower level, and calculates the clearing result of the lower-level P2P electricity trading based on the lower-level energy trading parameters.

[0046] The FRP trading unit is constructed at the upper layer. The FRP trading mechanism is updated according to the clearing results of P2P electricity trading. The clearing results of FRP trading are obtained by combining the updated FRP trading power and the upper-layer energy trading parameters.

[0047] The third technical solution of the present invention is achieved by the following means: a storage medium storing a computer program that can be read by a computer, the computer program being configured to execute the scheduling and control method for energy storage and distributed resources to participate in ramp-up auxiliary services during runtime.

[0048] The fourth technical solution of the present invention is implemented in the following way: a terminal, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for performing the steps in the scheduling and control method for collaborative participation of energy storage and distributed resources in hill-climbing assistance services.

[0049] The fifth technical solution of the present invention is achieved in the following way: an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the computer program is loaded and executed by the processor to realize the scheduling and control method for energy storage and distributed resources to participate in ramp-up auxiliary services.

[0050] Compared with the prior art, the present invention has the following advantages:

[0051] (1) This invention standardizes the dynamic adjustment capability of demand-side resources (such as electric vehicles and smart buildings) into tradable FRP commodities through a flexible ramping quantification mechanism involving distributed resources and a deep coupling architecture of P2P-FRP market. By dynamically matching supply and demand through parameterized models, it significantly improves the supply of system ramping capability and effectively reduces the renewable energy abandonment rate.

[0052] (2) This invention supports users to participate in P2P transactions in the form of "energy + ramp" combined commodities, integrates distributed resources, improves user income, significantly reduces FRP procurement costs and total system operating costs, and builds a market-oriented solution that combines economy and flexibility for high-proportion renewable energy systems. Attached Figure Description

[0053] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0054] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention.

[0055] Figure 2 This is a flowchart of the power trading process according to Embodiment 1 of the present invention.

[0056] Figure 3 This is a system block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0057] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0058] The present invention will be further described below with reference to embodiments and accompanying drawings:

[0059] Example 1: As Figure 1 and 2 As shown in the figure, this invention discloses a scheduling and control method for energy storage and distributed resources to collaboratively participate in ramp-up assistance services, including the following steps:

[0060] Step S101: Construct a two-layer FRP (Flexible Ramping Product) and P2P (Peer-to-Peer) energy trading framework. This framework includes independent energy storage, energy producers, energy consumers, and distribution system operators. Energy producers and consumers connect to the distribution network of the distribution system operator through node agents, and different node agents connect to all energy producers and consumers. Each node agent is located in a different branch of the distribution network. Energy producers and consumers coordinate with the distribution system operator in a decentralized manner to participate in ramping ancillary services through flexible energy exchange.

[0061] Step S102: Input energy trading parameters in the two-layer FRP and P2P energy trading framework. The energy trading parameters include upper-layer energy trading parameters and lower-layer energy trading parameters. The lower-layer energy trading parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-layer energy trading parameters include power distribution system operator parameters.

[0062] Step S103: The lower layer constructs an optimization model for P2P electricity trading and calculates the clearing result of the lower layer P2P electricity trading based on the lower layer energy trading parameters;

[0063] Step S104: The upper layer constructs an FRP trading mechanism, updates the FRP trading power based on the P2P electricity trading clearing results, and combines the updated FRP trading power with the upper layer energy trading parameters to obtain the FRP trading clearing results.

[0064] In step S101, within the two-layer FRP and P2P energy trading framework, the two-layer FRP and P2P energy trading need to satisfy the constraints of the distribution network model, whereby the distribution network model is:

[0065] (1a)

[0066] (1b)

[0067] (1c)

[0068] in, and It is a bus and The voltage; and These are the bus and The resistance and reactance of the transmission line between them; , It is a busbar and The active and reactive power flow between them; and It is a busbar and The active power flow and reactive power flow between them, of which ; and This represents the active and reactive power injection into bus n; and These are the sets of upstream and downstream buses of the bus. , Indicates the empty set; This represents the set of buses that act as a node agent.

[0069] In step S103, the lower-level optimization model for P2P electricity trading is constructed, including:

[0070] The distributed alternating direction multiplier algorithm is used to coordinate the electricity trading of all independent energy storage, energy producers and energy consumers in a decentralized manner, and bid for the electricity to participate in the trading to the distribution system operator through node agents;

[0071] Establish an optimization model for the P2P trading market under the distribution network, for the first For individual market participants, including independent energy storage providers, energy producers, and energy consumers, the objective function is:

[0072] (2)

[0073] (3)

[0074] In the formula, For the first The objective function of each market participant; The power generation cost of combined heat and power units and gas turbine units; , and These are the quadratic coefficient, linear coefficient, and constant parameter of the unit's power generation cost curve, respectively. Electricity prices will be adjusted upwards to allow participation in FRP services by distribution network operators; Lowering electricity prices for FRP services provided by distribution network operators; For the first Individual market participants Constantly adjust power from the grid and electricity retailers; For the first Individual market participants Constantly adjusting power from the grid's electricity retailers; For the first Individual market participants From the moment The electricity purchase price for each market participant; For the first Individual market participants At all times towards the first The electricity sales price of each market participant; For the first Individual market participants From the moment Electricity purchase capacity of each market participant; For the first Individual market participants At all times towards the first Electricity sales power of each market participant;

[0075] The node injection power constraints are as follows:

[0076] (4)

[0077] In the formula, , users respectively At the node The active and reactive power injected at the point; For users From other users The sum of power purchased and sold at the point; , , and users respectively The active or reactive power generated by combined heat and power and gas turbines; , , and users respectively The active or reactive power of adjustable loads and fixed loads.

[0078] In step S104, the upper layer constructs the FRP transaction mechanism, including:

[0079] Based on the master-slave game mechanism, that is, as the leader of the FRP-P2P transaction, the distribution system operator will first determine the FRP transaction price between the distribution system operator and independent energy storage, energy producers, and energy consumers. The transaction and energy management costs of the distribution system operator are expressed as follows:

[0080] (5)

[0081] in, This represents the transaction and energy management costs for power distribution system operators; This refers to the operating and maintenance costs of diesel generators;

[0082] For energy trading, the settlement price and electricity volume of FRP commodities from distribution system operators are within the maximum and minimum ranges shown below:

[0083] (6)

[0084] (7)

[0085] in, and This represents the lower and upper limits of the price adjustment for FRP at time t; and This represents the lower and upper limits of the price adjustment under FRP at time t; and This represents the lower and upper limits of the power adjusted on the FRP at time t; and This represents the lower and upper limits of the power regulation under FRP at time t.

[0086] For each market participant i, the optimization problem of minimizing its local P2P transaction costs can be expressed as:

[0087] (8)

[0088] st(3)-(4),(7)

[0089] In the formula, For the first A vector set of decision variables for each market participant. ; Let z be the reference value from the previous iteration; The iteration step size constant for the ADMM algorithm is taken as 1e-3; for initialization, the objective function at this time... And the electricity trading price in the first iteration The values ​​are all equal to 0, and the initial solution is obtained through local optimization. .

[0090] In step S104, the clearing result of the FRP transaction is obtained, including:

[0091] The clearing results of FRP transactions are as follows:

[0092] (9)

[0093] st(1),(6)

[0094] Therefore, FRP and P2P are iteratively solved until the FRP market and P2P market solutions converge, generating transaction results for distributed resources participating in hill-climbing auxiliary services.

[0095] In summary, the present invention has the following advantages compared with the prior art:

[0096] 1) This invention standardizes the dynamic adjustment capability of demand-side resources (such as electric vehicles and smart buildings) into tradable FRP commodities through a flexible ramping quantification mechanism involving distributed resources and a deeply coupled P2P-FRP market architecture. By dynamically matching supply and demand through a parameterized model, it significantly improves the supply of system ramping capability and effectively reduces the renewable energy curtailment rate.

[0097] 2) This invention supports users to participate in P2P transactions in the form of "energy + ramp" combined commodities, integrates distributed resources, improves user income, significantly reduces FRP procurement costs and total system operating costs, and builds a market-oriented solution that combines economy and flexibility for high-proportion renewable energy systems.

[0098] Example 2: As Figure 2 As shown in the figure, an embodiment of the present invention discloses a scheduling and control system for energy storage and distributed resources to collaboratively participate in ramp-up assistance services, comprising:

[0099] The framework building unit constructs a two-tier FRP and P2P energy trading framework; the energy trading framework includes independent energy storage, energy producers, energy consumers, and distribution system operators.

[0100] The parameter input unit inputs energy trading parameters in the two-layer FRP and P2P energy trading framework. The energy trading parameters include upper-layer energy trading parameters and lower-layer energy trading parameters. The lower-layer energy trading parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-layer energy trading parameters include power distribution system operator parameters.

[0101] The P2P trading unit constructs an optimized model for P2P electricity trading at the lower level, and calculates the clearing result of the lower-level P2P electricity trading based on the lower-level energy trading parameters.

[0102] The FRP trading unit is constructed at the upper layer. The FRP trading mechanism is updated according to the clearing results of P2P electricity trading. The clearing results of FRP trading are obtained by combining the updated FRP trading power and the upper-layer energy trading parameters.

[0103] Example 3: A storage medium: The storage medium stores a computer program that can be read by a computer, and the computer program is configured to execute a scheduling and control method for energy storage and distributed resources to participate in hill-climbing auxiliary services during runtime.

[0104] The aforementioned storage media may include, but are not limited to, USB flash drives, read-only memory, portable hard drives, magnetic disks, optical disks, and other media capable of storing computer programs.

[0105] Example 4: A terminal includes a processor, a memory, a communication interface, and one or more programs, the one or more programs being stored in the memory and configured to be executed by the processor, the programs including instructions for performing steps in a scheduling control method for collaborative participation of energy storage and distributed resources in hill-climbing assistance services.

[0106] Example 5: An electronic device, including a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement a scheduling and control method for energy storage and distributed resources to collaboratively participate in hill-climbing auxiliary services.

[0107] The aforementioned electronic device also includes transmission devices and input / output devices, wherein both the transmission devices and the input / output devices are connected to the processor.

[0108] The processor described above can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. It can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The memory can include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory, portable hard drives, magnetic disks, or optical disks.

[0109] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0110] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0111] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

Claims

1. A scheduling and control method for collaborative participation of energy storage and distributed resources in hill-climbing auxiliary services, characterized in that, Includes the following steps: Construct a two-tier FRP and P2P energy trading framework; the energy trading framework includes independent energy storage, energy producers, energy consumers and distribution system operators; In the two-tier FRP and P2P energy trading framework, energy trading parameters are input. These parameters include upper-tier and lower-tier energy trading parameters. The lower-tier parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-tier parameters include power distribution system operator parameters. The lower layer constructs an optimized model for P2P electricity trading, and calculates the clearing results of the lower layer P2P electricity trading based on the lower layer energy trading parameters; The upper layer constructs an FRP trading mechanism, updates the FRP trading power based on the P2P electricity trading clearing results, and combines the updated FRP trading power with the upper layer energy trading parameters to obtain the FRP trading clearing results.

2. The scheduling and control method for coordinated participation of energy storage and distributed resources in ramp-up assistance services according to claim 1, characterized in that, In the aforementioned two-tier FRP and P2P energy trading framework, the two-tier FRP and P2P energy trading need to satisfy the constraints of the distribution network model, wherein the distribution network model is: (1a) (1b) (1c) in, and It is a bus and The voltage; and These are the bus and The resistance and reactance of the transmission line between them; , It is a busbar and The active and reactive power flow between them; and It is a busbar and The active power flow and reactive power flow between them, of which ; and This represents the active and reactive power injection into bus n; and These are the sets of upstream and downstream buses of the bus. , Indicates the empty set; This represents the set of buses that act as a node agent.

3. The scheduling and control method for coordinated participation of energy storage and distributed resources in ramp-up assistance services according to claim 1, characterized in that, The underlying optimized model for P2P electricity trading includes: The distributed alternating direction multiplier algorithm is used to coordinate the electricity trading of all independent energy storage, energy producers and energy consumers in a decentralized manner, and bid for the electricity to participate in the trading to the distribution system operator through node agents; Establish an optimization model for the P2P trading market under the distribution network, for the first For individual market participants, including independent energy storage providers, energy producers, and energy consumers, the objective function is: (2) (3) In the formula, For the first The objective function of each market participant; The power generation cost of combined heat and power units and gas turbine units; , and These are the quadratic coefficient, linear coefficient, and constant parameter of the unit's power generation cost curve, respectively. Electricity prices will be adjusted upwards to allow participation in FRP services by distribution network operators; Lowering electricity prices for FRP services provided by distribution network operators; For the first Individual market participants Constantly adjust power from the grid and electricity retailers; For the first Individual market participants Constantly adjusting power from the grid's electricity retailers; For the first Individual market participants Time from the first The electricity purchase price for each market participant; For the first Individual market participants At all times towards the first The electricity sales price of each market participant; For the first Individual market participants Time from the first Electricity purchase capacity of each market participant; For the first Individual market participants At all times towards the first Electricity sales power of each market participant; The node injection power constraints are as follows: (4) In the formula, , users respectively At the node The active and reactive power injected at the point; For users From other users The sum of power purchased and sold at the point; , , and users respectively The active or reactive power generated by cogeneration and gas turbines; , , and users respectively The active or reactive power of adjustable loads and fixed loads.

4. The scheduling and control method for coordinated participation of energy storage and distributed resources in ramp-up assistance services according to claim 1, characterized in that, The upper-layer FRP transaction mechanism includes: Based on the master-slave game mechanism, that is, as the leader of the FRP-P2P transaction, the distribution system operator will first determine the FRP transaction price between the distribution system operator and independent energy storage, energy producers, and energy consumers. The transaction and energy management costs of the distribution system operator are expressed as follows: (5) in, This represents the transaction and energy management costs for power distribution system operators; This refers to the operating and maintenance costs of diesel generators; For energy trading, the settlement price and electricity volume of FRP commodities from distribution system operators are within the maximum and minimum ranges shown below: (6) (7) in, and This represents the lower and upper limits of the price adjustment for FRP at time t; and This represents the lower and upper limits of the price adjustment under FRP at time t; and This represents the lower and upper limits of the power adjusted on the FRP at time t; and This represents the lower and upper limits of the power regulation under FRP at time t.

5. The scheduling and control method for coordinated participation of energy storage and distributed resources in ramp-up assistance services according to claim 3, characterized in that, For each market participant i, the optimization problem of minimizing its local P2P transaction costs can be expressed as: (8) st(3)-(4),(7) In the formula, For the first A vector set of decision variables for each market participant. ; Let z be the reference value from the previous iteration; The iteration step size constant for the ADMM algorithm is taken as 1e-3; for initialization, the objective function at this time... And the electricity trading price in the first iteration The values ​​are all equal to 0, and the initial solution is obtained through local optimization. .

6. The scheduling and control method for coordinated participation of energy storage and distributed resources in ramp-up assistance services according to claim 5, characterized in that, The process of obtaining the clearing results of FRP transactions includes: The clearing results of FRP transactions are as follows: (9) st(1),(6) Therefore, FRP and P2P are iteratively solved until the FRP market and P2P market solutions converge, generating transaction results for distributed resources participating in hill-climbing auxiliary services.

7. A scheduling and control system for coordinated participation of energy storage and distributed resources in hill-climbing assistance services, characterized in that, include: The framework building unit constructs a two-tier FRP and P2P energy trading framework; the energy trading framework includes independent energy storage, energy producers, energy consumers, and distribution system operators. The parameter input unit inputs energy trading parameters in the two-layer FRP and P2P energy trading framework. The energy trading parameters include upper-layer energy trading parameters and lower-layer energy trading parameters. The lower-layer energy trading parameters include independent energy storage parameters, energy producer parameters, and energy consumer parameters. The upper-layer energy trading parameters include power distribution system operator parameters. The P2P trading unit constructs an optimized model for P2P electricity trading at the lower level, and calculates the clearing result of the lower-level P2P electricity trading based on the lower-level energy trading parameters. The FRP trading unit is constructed at the upper layer. The FRP trading mechanism is updated according to the clearing results of P2P electricity trading. The clearing results of FRP trading are obtained by combining the updated FRP trading power and the upper layer energy trading parameters.

8. A storage medium, characterized in that, The storage medium stores a computer program that can be read by a computer, and the computer program is configured to execute the scheduling and control method for collaborative participation of energy storage and distributed resources in hill-climbing auxiliary services as described in any one of claims 1 to 6 when it runs.

9. A terminal, characterized in that, The system includes a processor, a memory, a communication interface, and one or more programs, said programs being stored in the memory and configured to be executed by the processor, said programs including instructions for performing steps in the scheduling control method for collaborative participation of energy storage and distributed resources in hill-climbing assistance services as described in any one of claims 1 to 6.

10. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the scheduling and control method for energy storage and distributed resources to collaboratively participate in hill-climbing auxiliary services as described in claims 1 to 6.

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