Bidding decision-making method, system and device for participation of integrated energy park in spot-carbon market with consideration of internal production characteristics, and storage medium
By constructing an output model, an operation model, and a comprehensive clearing model, and combining the gurobi solver to optimize the bidding decision-making of the park, the problem of bidding accuracy and economic benefits of the integrated energy park under the dual constraints of the electricity and carbon markets was solved, and the optimized dispatch of the electricity market and carbon emission compliance were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-07
AI Technical Summary
Existing integrated energy parks have not fully considered the internal production characteristics, multi-energy coupling, and equipment operation constraints when participating in bidding decisions for the electricity spot market and carbon market. This has resulted in low accuracy of bidding decisions, separate consideration of carbon emission management and electricity market transactions, and a lack of optimization strategies under the dual constraints of the electricity and carbon markets, making it difficult to achieve both economic benefits and carbon emission compliance goals.
A comprehensive energy park bidding decision-making method considering internal production characteristics is constructed. By inputting industrial user information and market information, an output model, an operation model, and a comprehensive clearing model are formed. A joint two-layer model is used to solve the problem in Matlab by calling the gurobi commercial solver, thereby optimizing the park bidding decision.
It has achieved optimized scheduling of power production and market clearing in the park, ensuring maximum economic benefits and meeting carbon emission compliance requirements, improving the accuracy and flexibility of bidding strategies, reducing market risks, and optimizing the bidding volume.
Smart Images
Figure CN121810075A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of energy management optimization technology, specifically to a bidding decision-making method, system, equipment, and storage medium for integrated energy parks participating in the spot-carbon market, taking into account their internal production characteristics. Background Technology
[0002] With the advancement of power market reform, integrated energy parks are increasingly facing the need to participate in the spot market. The fluctuation of electricity prices in the spot market has brought complexity to the bidding decisions of the parks. Bidding decisions are usually based on simple predictions of the park's load demand, but they ignore the volatility of electricity market prices and the potential for demand-side response. Various energy production equipment in the park, such as combined heat and power units, energy storage equipment, and interruptible loads, are often not effectively coordinated and optimized, resulting in the waste of energy resources. In this context, most existing bidding strategies have failed to deeply explore the potential of multi-energy coupling within the park, and also lack comprehensive consideration of the dual constraints of market prices and carbon emission quotas. The core issue facing the parks is how to formulate a reasonable bidding strategy under the dual constraints of electricity market price fluctuations and carbon emission targets to maximize profits and meet environmental compliance requirements.
[0003] Furthermore, with increasingly stringent carbon emission regulations, industrial parks not only need to consider economic benefits but also the allocation and use of carbon emission allowances. Existing carbon emission management is usually considered separately from electricity market transactions, which makes it impossible to balance emission reduction targets and economic benefits when participating in market transactions. Many traditional methods only focus on the management of carbon allowances or electricity market transactions, lacking an overall strategy that considers both simultaneously. The park's power production and carbon emission targets are often not optimized in sync, resulting in certain limitations on the economic benefits of market participation. How to optimize the park's bidding decisions under the dual constraints of the electricity market and the carbon market, so as to achieve both the economic benefits of the electricity market and meet the carbon emission compliance requirements, has become a key challenge. Summary of the Invention
[0004] In view of the above-mentioned problems, the present invention is proposed.
[0005] Therefore, the technical problem solved by this invention is that existing technologies, when used in integrated energy parks to participate in bidding decisions for the electricity spot market and carbon market, have limitations such as insufficient consideration of the park's internal production characteristics, multi-energy coupling, and equipment operation constraints, resulting in low accuracy of bidding decisions and separate consideration of carbon emission management and electricity market transactions. The invention also addresses how to optimize the park's bidding strategy under the dual constraints of the electricity and carbon markets to achieve both economic benefits and carbon emission compliance goals.
[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a bidding decision-making method for integrated energy parks participating in the spot-carbon market, considering their internal production characteristics. This method includes inputting industrial user information and constructing an output model for the industrial users based on their production characteristics, thus forming a description of the park's internal production constraints. Based on the output model, integrated energy park information and market information are simultaneously input to construct an operational model for the integrated energy park and a comprehensive clearing model for the spot-carbon market, respectively, forming parallel descriptions of the park's operational constraints and market clearing constraints. The output model, operational model, and comprehensive clearing model are constructed into a joint two-layer model, which is then solved using the gurobi commercial solver in Matlab, outputting the bidding decision.
[0007] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics in the spot-carbon market as described in this invention, the output model includes: binding the production plan variables of industrial users with energy consumption variables, and limiting the range of output changes of industrial users within the decision-making period through production load continuity constraints; the output model is expressed as: , in, Indicates industrial users At any moment The lower limit of power, the minimum power requirement of the user in the current time period. Indicates industrial users At any moment The power limit, the user's maximum power demand during the current time period. Indicates industrial users At any moment The electricity demand, the actual electricity consumption of the user in the current time period. Indicates industrial users At any moment Power requirements, Indicates industrial users At any moment The time it has been running continuously, Indicates the user's shortest continuous power consumption duration. Indicates landslide restrictions, industrial users At any moment Upper limit constraint on power consumption Indicates landslide restrictions, industrial users At any moment Lower limit constraint on power supply.
[0008] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics in the spot-carbon market as described in this invention, the operating model includes: constructing energy balance constraints for electricity-heat-energy storage within the park based on the output model of industrial users; constructing endogenous constraint variables for the operating model using industrial production loads; and obtaining the objective function for the current operating constraints of the integrated energy park, expressed as: , , , , , in, The objective function for the integrated energy park includes the objective of minimizing the operating costs. Indicates in the scene and the The electricity production cost of a load unit in a comprehensive energy park during a given time period. Indicates in the scene and the The cost of purchasing electricity from the electricity market for integrated energy parks during specific time periods. Indicates in the scene and the The cost of purchasing electricity from the carbon market for integrated energy parks during specific time periods. This indicates the unit electricity price of a load unit in an integrated energy park, referring to the revenue generated from the load unit's electricity production capacity. Indicates the first Heaven, the First Time period and scene The load power consumption refers specifically to the electricity consumed by the load units of the integrated energy park during the current time period. Indicates the first Heaven, the First Time period and scene The clearing price of electricity in the off-market. Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park from the energy market Indicates the first Heaven, the First Time period and scene Electricity sold in the energy market by the integrated energy park Indicates the first Heaven, the First Time period and scene Clearing electricity prices in the off-carbon market Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park in the carbon market Indicates the first Heaven, the First Time period and scene Electricity sold in the carbon market by the integrated energy park The objective function representing the total cost of electricity market transactions is... This indicates the probability of electricity demand and supply conditions occurring under different market environments. Integrated energy park in the scenario The total operating cost.
[0009] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market as described in this invention, the integrated clearing model includes: determining market rule conditions and network security operation conditions; introducing electricity trading constraints and carbon emission quota constraints under the same decision-making framework; using the energy exchange volume of the park operation model as the constraint input for market clearing; and obtaining the current objective function.
[0010] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market as described in this invention, the parallel description includes forming a set of park operation constraints and a set of market clearing constraints within a unified time scale, and adjusting the two types of constraints to a unified variable.
[0011] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market as described in this invention, the joint two-layer model includes: imposing constraints on the decision variables of the lower integrated energy park operation model on the upper spot-carbon market integrated clearing model, and feeding back feasible output boundaries from the lower model to the upper model.
[0012] As a preferred embodiment of the bidding decision-making method for integrated energy parks considering internal production characteristics in the spot-carbon market as described in this invention, the step of calling the gurobi commercial solver includes: generating an optimization algorithm in Matlab, defining the objective function and constraints of the two-level optimization problem, setting the parameters of the gurobi solver, selecting the current solution strategy, the maximum number of iterations and the convergence threshold, calling the gurobi solver to solve the optimization problem, calculating the optimal park production plan and electricity bidding decision, verifying the solution results, and if they are not satisfied, adjusting the input parameters and iterating to solve again.
[0013] Another objective of this invention is to provide a bidding decision system for integrated energy parks participating in the spot-carbon market that takes into account their internal production characteristics. This system can simultaneously optimize the operational constraints of multi-energy coupling equipment within the park with the dual constraints of the electricity market and carbon emissions, thus solving the technical problem that current bidding decision systems fail to fully integrate internal production characteristics and carbon emission management, thereby improving the accuracy of decision-making and the economic benefits of the park in the market.
[0014] As a preferred embodiment of the bidding decision-making system for integrated energy parks considering internal production characteristics in the spot-carbon market as described in this invention, the system includes: an information input module, a model building module, and an optimization solution module. The information input module is responsible for inputting basic market information and basic information about the integrated energy park, including electricity market, carbon market, network information, and internal equipment information. Based on the production characteristics of industrial users within the park, it constructs an industrial user output model. The model building module, based on the input industrial user output model, park operation information, and market rule information, constructs the park's operation model and a comprehensive clearing model for the spot-carbon market, respectively, describing the park's internal production constraints and market clearing constraints in parallel. Through optimization calculations, it obtains the park's bidding electricity volume and market trading electricity volume. The optimization solution module generates optimization algorithms using Matlab, calls the gurobi commercial solver to solve the bi-level optimization problem, defines the objective function and constraints, sets the solver parameters, and executes the solution, outputting the optimal park production plan, bidding electricity volume, and carbon quota trading plan. During the solution process, parameter adjustments and iterative optimizations are performed.
[0015] Another object of the present invention is to provide a bidding decision-making device for integrated energy parks considering internal production characteristics to participate in the spot-carbon market, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market.
[0016] Another object of the present invention is to provide a storage medium for bidding decisions of integrated energy parks participating in the spot-carbon market, taking into account their internal production characteristics, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of a bidding decision method for integrated energy parks participating in the spot-carbon market, taking into account their internal production characteristics, are implemented.
[0017] The beneficial effects of this invention are as follows: The integrated energy park bidding decision-making method for participating in the spot-carbon market, which considers the internal production characteristics, introduced by this invention introduces the output model of multi-energy coupling equipment within the park, fully considering the production characteristics and equipment operation constraints of industrial users. This achieves optimized scheduling of park power production and market clearing, resulting in better performance in park production scheduling, market bidding strategies, and carbon emission compliance. It ensures the maximization of economic benefits under the dual constraints of the electricity market and carbon market, while simultaneously achieving compliance with carbon emission targets. By solving a two-level optimization problem, it can efficiently handle the complex constraints of internal production and market transactions within the park, ensuring the accuracy and flexibility of the park's bidding strategy, significantly reducing market risks, and optimizing the bidding volume. This provides a practical and feasible solution for parks to make decisions in a complex electricity-carbon market environment. Attached Figure Description
[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 The overall flowchart of the bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market, as provided in Embodiment 1 of the present invention. Detailed Implementation
[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.
[0021] Example 1, referring to Figure 1 As one embodiment of the present invention, a bidding decision-making method for integrated energy parks participating in the spot-carbon market, taking into account their internal production characteristics, is provided, including: S1: Input industrial user information and construct the industrial user's output model 100 based on the industrial user's production characteristics to form a description of production constraints within the park.
[0022] It should be noted that the input market basic information and integrated energy park basic information include network information, spot market, carbon market and other participants' basic information, and information on various equipment within the integrated energy park.
[0023] First, input the basic market information and the basic information of the integrated energy park, bind the industrial user's production plan variables and energy consumption variables, and limit the range of output changes of industrial users within the decision-making cycle through production load continuity constraints.
[0024] Basic market information includes online information and market information.
[0025] Network information includes the upper and lower limits of transmission capacity of transmission lines, the upper and lower limits of output of other units, the ramp rate and landslide rate of other units in adjacent time periods, network topology, node admittance matrix, and the upper and lower limits of carbon quota requirements.
[0026] Market information includes the energy cost factor for other generating units and the carbon quota cost factor for other generating units.
[0027] Basic information about the integrated energy park includes: the multi-energy equipment within the park mainly consists of combined heat and power (CHP) units, thermal energy storage units, electric energy storage units, interruptible loads; the ramp rate and slip rate of CHP units (CHP), the upper and lower limits of thermal output, and the upper and lower limits of electrical output; the upper and lower limits of the capacity of thermal energy storage units (S), the maximum heat storage rate and maximum heat release rate of thermal energy storage units, and the initial and final heat storage capacity of thermal energy storage units; the upper and lower limits of the charging power and the discharging power of electric energy storage (ESS); the upper and lower limits of the state of energy (SOC), the initial value of the state of energy, and the energy storage charging and discharging efficiency; and the maximum power reduction of interruptible loads (DR).
[0028] Output model 100 is represented as: , in, Indicates industrial users At any moment The lower limit of power, the minimum power requirement of the user in the current time period. Indicates industrial users At any moment The power limit, the user's maximum power demand during the current time period. Indicates industrial users At any moment The electricity demand, the actual electricity consumption of the user in the current time period. Indicates industrial users At any moment Power requirements, Indicates industrial users At any moment The time it has been running continuously, Indicates the user's shortest continuous power consumption duration. Indicates landslide restrictions, industrial users At any moment Upper limit constraint on power consumption Indicates landslide restrictions, industrial users At any moment Lower limit constraint on power supply.
[0029] S2: Based on the output model 100, the integrated energy park information and market information are input simultaneously to construct the integrated energy park operation model 200 and the spot-carbon market integrated clearing model 201, forming a parallel description of park operation constraints and market clearing constraints.
[0030] Based on the basic information of the integrated energy park, the parameter information of each industrial user in the park, the energy relationship and safe operation conditions within the park, the constraints for park operation and bidding, as well as the objective function, are determined.
[0031] Based on the energy relationships and safe operating conditions within the integrated energy park, safe operation and the establishment of energy coupling constraints are established.
[0032] The safe operation of internal equipment, time: Combined heat and power (CH) units are represented as: , in, Indicates the first Taiwan's combined heat and power units in the first Time period and scene The power output of the power supply is as follows: Indicates the first The elasticity coefficient between electrical and thermal power during condensing operation of a Taiwan thermal power unit. Indicates the first Taiwan's combined heat and power units in the first Time period and scene The heat power below, Represents a constant used to adjust for changes in electrical and thermal power. Indicates the first The minimum electrical power of a combined heat and power unit in Taiwan Indicates the first The reduction in power generation per unit of heat supplied by a Taiwanese thermal power unit. Indicates the first The maximum electrical power of the combined heat and power unit in Taiwan Indicates the first The ramp rate of the Taiwanese generator set. Indicates the first Landslide rate of the Taiwanese unit.
[0033] Thermal energy storage unit (S) is represented as: , , in, Indicates the maximum capacity of the thermal storage tank. This indicates the maximum heat storage rate of the thermal storage tank. This indicates the maximum heat release rate of the thermal storage tank. This indicates the initial heat storage capacity of the thermal storage tank. This indicates the final heat storage capacity of the thermal storage tank. Indicates the first Time period and scene The energy storage status of the energy storage system.
[0034] Energy Storage Unit (ESS) is represented as: , , , , in, Indicates energy storage unit In the Time period and scene The discharge power at that time, Indicates energy storage unit In the Time period and scene The charging power at the following levels Indicates energy storage unit In the Time period and scene The state of charge under these conditions, This indicates the energy conversion efficiency of the energy storage system during charging. This indicates the energy conversion efficiency of the energy storage system during discharge. Indicates energy storage system The amount of electricity in the initial period, Indicates energy storage system The amount of electricity consumed in the final period, Indicates energy storage unit In the Time period and scene The upper limit of charging power, Indicates energy storage unit In the Time period and scene The upper limit of discharge power.
[0035] Interruptible load (DR) is represented as: , in, This indicates that interruptible loads can reduce power output. This indicates that interruptible loads can reduce maximum power.
[0036] It should also be noted that the energy coupling relationship in the integrated energy park includes electrical load balance, expressed as: , Heat load balance is represented as: , in, This indicates the electricity sales volume of the integrated energy park. This indicates the electricity purchased by the integrated energy park. Indicates the first Time period and scene The amount of electricity adjustment related to demand response, Indicates the first Time period and scene The actual electrical load value under the following conditions Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park from the energy market Indicates the first Heaven, the First Time period and scene Electricity sold in the energy market by the integrated energy park This indicates the actual heat load value of the integrated energy park. Indicates the number of combined heat and power (CHP) units. This indicates the number of energy storage units.
[0037] The comprehensive clearing model 201 includes determining market rule conditions and network security operation conditions, introducing electricity trading constraints and carbon emission quota constraints under the same decision-making framework, using the energy exchange volume of the park operation model 200 as the constraint input for market clearing, and obtaining the current objective function.
[0038] The parallel description includes forming a set of park operation constraints and a set of market clearing constraints within a unified time scale, and adjusting the two types of constraints to a unified variable.
[0039] It should also be noted that the operation model 200 includes constructing energy balance constraints for electricity-heat-energy storage within the park based on the output model 100 of industrial users, constructing endogenous constraint variables for the operation model 200 using industrial production load, and obtaining the objective function for the current integrated energy park operation constraints, expressed as: , , , , , in, The objective function for the integrated energy park includes the objective of minimizing the operating costs. Indicates in the scene and the The electricity production cost of a load unit in a comprehensive energy park during a given time period. Indicates in the scene and the The cost of purchasing electricity from the electricity market for integrated energy parks during specific time periods. Indicates in the scene and the The cost of purchasing electricity from the carbon market for integrated energy parks during specific time periods. This indicates the unit electricity price of a load unit in an integrated energy park, referring to the revenue generated from the load unit's electricity production capacity. Indicates the first Heaven, the First Time period and scene The load power consumption refers specifically to the electricity consumed by the load units of the integrated energy park during the current time period. Indicates the first Heaven, the First Time period and scene The clearing price of electricity in the off-market. Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park from the energy market Indicates the first Heaven, the First Time period and scene Electricity sold in the energy market by the integrated energy park Indicates the first Heaven, the First Time period and scene Clearing electricity prices in the off-carbon market Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park in the carbon market Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park in the carbon market The objective function representing the total cost of electricity market transactions is... This indicates the probability of electricity demand and supply conditions occurring under different market environments. Integrated energy park in the scenario The total operating cost.
[0040] Based on market and network information, a comprehensive clearing model 201 for the spot and carbon markets is established to determine market rules and network security operation conditions, as well as the objective function.
[0041] The spot market establishes market and network constraints based on network information and safe operating conditions, including constraints on ordinary generating units, line power constraints, and node power constraints.
[0042] The objective function of the spot market, with the goal of maximizing social welfare, is expressed as: , The carbon market establishes carbon quota balance and upper and lower limits for carbon quota sales based on carbon quota information.
[0043] The objective function of the carbon market, aiming to maximize social welfare, is expressed as: , in, This represents the objective function of the spot market. This represents the objective function of the carbon market. Representing a scene The probability reflects the likelihood of occurrence under different market conditions. Indicates the time period and the The carbon market electricity price at a load point refers to the carbon market price at that load point during a specific time period. Indicates the time period and the The carbon market electricity price at a load point refers to the carbon market purchase price at that load point during a specific time period. The carbon emission allowances traded in the carbon market refer to the amount of allowances sold by participants in the carbon market. The carbon emission allowances traded in the carbon market refer to the amount of allowances purchased to participate in the carbon market. This indicates the total volume of the carbon market.
[0044] S3: Construct the output model 100, the operation model 200, and the comprehensive clearing model 201 into a joint two-layer model 300, and use the gurobi commercial solver in Matlab to solve it and output the bidding decision.
[0045] It should be noted that the joint two-layer model 300 includes imposing constraints on the decision variables of the lower-layer integrated energy park operation model 200 on the spot-carbon market integrated clearing model 201 at the upper layer, and feeding back the feasible output boundary from the lower-layer model to the upper-layer model.
[0046] The process of using the commercial gurobi solver involves generating the optimization algorithm in Matlab, defining the objective function and constraints of the bi-level optimization problem, setting the parameters of the gurobi solver, selecting the current solution strategy, the maximum number of iterations, and the convergence threshold, calling the gurobi solver to solve the optimization problem, calculating the optimal park production plan and electricity bidding decision, verifying the solution results, and if the requirements are not met, adjusting the input parameters and iterating again to solve the problem.
[0047] It should also be noted that, based on the bi-level optimization problem, the current optimization problem is described using Matlab and solved using the commercial Gurobi solver. This yields an optimization method for integrated energy parks participating in spot-carbon bidding, considering their internal production characteristics. The specific model and constraints for integrated energy parks participating in the spot-carbon joint clearing market are obtained. The optimization problem is programmed using Matlab and solved using Gurobi, generating a bidding method for integrated energy parks considering their internal production characteristics.
[0048] Example 2, an embodiment of the present invention, provides a bidding decision system for integrated energy parks participating in the spot-carbon market that takes into account internal production characteristics, including an information input module, a model building module, and an optimization solution module.
[0049] The information input module is responsible for inputting basic market information and basic information of the integrated energy park, including electricity market, carbon market, network information and internal equipment information of the park. Based on the production characteristics of industrial users in the park, it constructs an industrial user output model 100.
[0050] The model building module is used to construct the park's operation model 200 and the spot-carbon market integrated clearing model 201 based on the input industrial user output model 100, park operation information and market rule information, respectively. It describes the internal production constraints and market clearing constraints of the park in parallel, and obtains the park's bidding electricity and market trading electricity through optimization calculation.
[0051] The optimization and solution module is used to generate optimization algorithms through Matlab, call the gurobi commercial solver to solve bi-level optimization problems, define objective functions and constraints, set solver parameters and execute the solution, and output the optimal park production plan, bidding electricity volume and carbon quota trading plan. During the solution process, parameter adjustment and iterative optimization are performed.
[0052] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the bidding decision system for participating in the spot-carbon market of an integrated energy park that takes into account the internal production characteristics, as proposed in the above embodiment.
[0053] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the bidding decision system for integrated energy parks participating in the spot-carbon market, which takes into account internal production characteristics, as proposed in the above embodiment.
[0054] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0055] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.
[0056] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.
[0057] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0058] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A bidding decision-making method for integrated energy parks considering internal production characteristics to participate in the spot-carbon market, characterized in that: include: Input industrial user information and construct an output model for industrial users based on their production characteristics to form a description of production constraints within the park. Based on the output model, integrated energy park information and market information are input simultaneously to construct an operation model for the integrated energy park and a comprehensive clearing model for the spot-carbon market, forming a parallel description of park operation constraints and market clearing constraints. The output model, operation model, and integrated clearing model are constructed into a joint two-layer model, which is then solved using the gurobi commercial solver in Matlab, and the bidding decision is output.
2. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in claim 1, characterized in that: The output model includes, The production plan variables of industrial users are linked with energy consumption variables, and the range of output changes of industrial users within the decision-making cycle is limited by the production load continuity constraint. The output model is expressed as follows: ， in, Indicates industrial users At any moment The lower limit of power, the minimum power requirement of the user in the current time period. Indicates industrial users At any moment The power limit, the user's maximum power demand during the current time period. Indicates industrial users At any moment The electricity demand, the actual electricity consumption of the user in the current time period. Indicates industrial users At any moment Power requirements, Indicates industrial users At any moment The time it has been running continuously, Indicates the user's shortest continuous power consumption duration. Indicates landslide restrictions, industrial users At any moment Upper limit constraint on power consumption Indicates landslide restrictions, industrial users At any moment Lower limit constraint on power supply.
3. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in claim 1 or 2, characterized in that: The operating model includes, Based on the output model of industrial users, an energy balance constraint for electricity, heat, and energy storage within the park is constructed. Endogenous constraint variables for the operation model are constructed using industrial production load. The objective function for the current integrated energy park operation constraint is obtained, expressed as: ， ， ， ， ， in, The objective function for the integrated energy park includes the objective of minimizing the operating costs. Indicates in the scene and the The electricity production cost of a load unit in a comprehensive energy park during a given time period. Indicates in the scene and the The cost of purchasing electricity from the electricity market for integrated energy parks during specific time periods. Indicates in the scene and the The cost of purchasing electricity from the carbon market for integrated energy parks during specific time periods. This indicates the unit electricity price of a load unit in an integrated energy park, referring to the revenue generated from the load unit's electricity production capacity. Indicates the first Heaven, the First Time period and scene The load power consumption refers specifically to the electricity consumed by the load units of the integrated energy park during the current time period. Indicates the first Heaven, the First Time period and scene The clearing price of electricity in the off-market. Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park from the energy market Indicates the first Heaven, the First Time period and scene Electricity sold in the energy market by the integrated energy park Indicates the first Heaven, the First Time period and scene Clearing electricity prices in the off-carbon market Indicates the first Heaven, the First Time period and scene Electricity purchased by the integrated energy park in the carbon market Indicates the first Heaven, the First Time period and scene Electricity sold in the carbon market by the integrated energy park The objective function representing the total cost of electricity market transactions is... This indicates the probability of electricity demand and supply conditions occurring under different market environments. Integrated energy park in the scenario The total operating cost.
4. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in claim 3, characterized in that: The comprehensive clearing model includes, By defining market rules and network security operation conditions, introducing electricity trading constraints and carbon emission quota constraints under the same decision-making framework, and using the energy exchange volume of the park operation model as the constraint input for market clearing, the current objective function is obtained.
5. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in any one of claims 1, 2, and 4, characterized in that: The parallel description includes, Within a unified time scale, separate sets of constraints for park operation and market clearing are formed, and the two types of constraints are adjusted to a unified variable.
6. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in claim 5, characterized in that: The joint two-layer model includes, The upper-level spot-carbon market integrated clearing model imposes constraints on the decision variables of the lower-level integrated energy park operation model, and the lower-level model feeds back the feasible output boundary to the upper-level model.
7. The bidding decision-making method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in any one of claims 1, 2, 4, and 6, characterized in that: The process of calling the gurobi commercial solver to solve the problem includes... In Matlab, an optimization algorithm is generated, defining the objective function and constraints of the two-level optimization problem. The parameters of the gurobi solver are set, and the current solution strategy, maximum number of iterations, and convergence threshold are selected. The gurobi solver is then called to solve the optimization problem, calculating the optimal park production plan and electricity bidding decision. The solution results are verified, and if they are not satisfied, the input parameters are adjusted and the solution is iterated again.
8. A bidding decision system for integrated energy parks considering internal production characteristics participating in the spot-carbon market, employing the bidding decision method for integrated energy parks considering internal production characteristics participating in the spot-carbon market as described in any one of claims 1 to 7, characterized in that: It includes an information input module, a model building module, and an optimization solution module; The information input module is responsible for inputting basic market information and basic information of the integrated energy park, including electricity market, carbon market, network information and internal equipment information of the park, and constructing an industrial user output model based on the production characteristics of industrial users in the park. The model building module is used to construct the park's operation model and the comprehensive clearing model of the spot-carbon market based on the input industrial user output model, park operation information and market rule information. It describes the internal production constraints and market clearing constraints of the park in parallel, and obtains the park's bidding electricity and market trading electricity through optimization calculation. The optimization solution module is used to generate optimization algorithms through Matlab, call the gurobi commercial solver to solve the bi-level optimization problem, define the objective function and constraints, set the solver parameters and execute the solution, and output the optimal park production plan, bidding electricity volume and carbon quota trading plan. During the solution process, parameter adjustment and iterative optimization are performed.
9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the bidding decision-making method for integrated energy parks participating in the spot-carbon market, as described in any one of claims 1 to 7, which takes into account internal production characteristics.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the bidding decision-making method for integrated energy parks participating in the spot-carbon market, taking into account the internal production characteristics, as described in any one of claims 1 to 7.