Energy limit determination method and device, storage medium, electronic device and computer program product

Abstract

The invention discloses an energy limit determination method and device, a storage medium, an electronic device and a computer program product, and the method comprises the steps: determining a carbon transaction price corresponding to each energy system in N energy systems, and obtaining N carbon transaction prices, N being an integer greater than or equal to 2; determining N target renewable energy quota prices corresponding to each energy system in the N energy systems according to the N carbon transaction prices; and determining a renewable energy quota corresponding to each energy system in the N energy systems according to the N target renewable energy quota prices. By adopting the technical scheme, the problem of low energy utilization efficiency caused by lack of an effective coordination mechanism and a market interaction strategy is solved.

Description

Technical Field

[0001] This application relates to the field of energy technology, and more specifically, to a method and apparatus for determining energy limits, a storage medium, an electronic device, and a computer program product. Background Technology

[0002] With increasing global focus on clean energy and a low-carbon economy, Integrated Energy Systems (IES) have seen rapid development and adoption as a crucial means of addressing complex energy demands and improving the utilization rate of renewable energy sources. In IES, multiple energy forms (such as electricity, heat, and natural gas) are coupled together. Through optimized operation and management, energy efficiency can be effectively improved, carbon emissions reduced, and diverse energy needs of users met.

[0003] However, in traditional energy systems, due to the lack of effective coordination mechanisms and market interaction strategies, each energy subsystem often operates independently, leading to problems such as low energy efficiency, high carbon emissions, and high system operating costs. In recent years, carbon emission trading (CET) and green certificate trading (GCT) mechanisms have been widely used as market regulation tools to guide the power industry's emission reduction actions and the development of renewable energy. However, existing research mostly focuses on the interaction analysis of single market mechanisms or fixed prices, lacking in-depth research on dynamic supply and demand relationships when considering the interaction between two markets. In multi-integrated energy systems (MIES), each IES belongs to different stakeholders. How to balance the interests of each member in the multi-integrated energy system alliance to promote their cooperation and mutual benefit has become an urgent research problem. Although some studies have conducted in-depth research on the coordinated and optimized operation of multi-energy systems from the perspective of game theory and trading revenue distribution mechanisms, research on the possibility of multi-system cooperation and the impact of the interaction between carbon trading and green certificate trading markets on the alliance game is still insufficient.

[0004] There is currently no effective solution to the problem of low energy efficiency caused by the lack of effective coordination mechanisms and market interaction strategies in related technologies.

[0005] Therefore, it is necessary to improve the existing related technologies to overcome the aforementioned defects and meet the needs of current actual production. Summary of the Invention

[0006] This application provides a method and apparatus for determining energy quotas, a storage medium, an electronic device, and a computer program product, to at least address the problem of low energy utilization efficiency caused by the lack of effective coordination mechanisms and market interaction strategies in related technologies.

[0007] According to one aspect of the embodiments of this application, a method for determining energy quotas is provided, comprising: determining the carbon trading price corresponding to each of N energy systems to obtain N carbon trading prices, wherein N is an integer greater than or equal to 2; determining N target renewable energy quota prices corresponding to each of the N energy systems based on the N carbon trading prices; and determining the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0008] In an exemplary embodiment, determining the carbon trading price corresponding to each of the N energy systems includes: determining the carbon trading price corresponding to the i-th energy system among the N energy systems through the following operations, thereby determining the carbon trading price corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: obtaining the carbon allowance trading price of the i-th energy system; determining the carbon trading price corresponding to the i-th energy system through the following formula: in, The carbon trading price corresponding to the i-th energy system. To preset a minimum carbon trading price, To preset the highest carbon trading price, The average carbon trading price over a preset time period. The carbon quota trading price is... The maximum carbon allowance trading price is preset.

[0009] In an exemplary embodiment, determining the N target renewable energy quota prices corresponding to each energy system in the N energy systems based on the N carbon trading prices includes: determining the target renewable energy quota price corresponding to the i-th energy system in the N energy systems through the following operation, to determine the target renewable energy quota price corresponding to each energy system in the N energy systems, where i is a positive integer less than or equal to N: determining the renewable energy quota price of the i-th energy system whose objective function value is minimized as the target renewable energy quota price corresponding to the i-th energy system, where the objective function is: Where y is the objective function, F ibuy Let F be the energy purchase cost of the i-th energy system. iCET Let F be the carbon trading price corresponding to the i-th energy system. iGCTLet F be the renewable energy quota price for the i-th energy system. iRES，cut Let F be the cost of waste wind and solar energy for the i-th energy system. iSS Let F be the energy storage cost of the i-th energy system. irep Let F be the equipment operation and maintenance cost of the i-th energy system. iTrans Let F be the energy transmission cost of the i-th energy system. ishare Let F be the resource sharing cost of the i-th energy system. iDR Let be the demand response cost of the i-th energy system.

[0010] In an exemplary embodiment, determining the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices includes: determining the renewable energy quota demand value corresponding to each of the N energy systems based on the N target renewable energy quota prices; determining the renewable energy quota specified value corresponding to each of the N energy systems; and determining the renewable energy quota corresponding to each energy system based on the renewable energy quota demand value and the renewable energy quota specified value corresponding to each of the N energy systems.

[0011] In an exemplary embodiment, determining the renewable energy quota demand value corresponding to each of the N energy systems based on the N target renewable energy quota prices includes: determining the renewable energy quota demand value corresponding to the i-th energy system among the N energy systems through the following operations, where i is a positive integer less than or equal to N: if the target renewable energy quota price of the i-th energy system is a preset first price, determining the renewable energy quota demand value of the i-th energy system as any value within a first preset interval; if the target renewable energy quota price of the i-th energy system is greater than the preset first price and less than a preset second price, determining the renewable energy quota demand value corresponding to the i-th energy system according to a preset function, where the preset function is a function corresponding to the renewable energy quota demand value and the target renewable energy quota price, and the preset function is a linear function; if the target renewable energy quota price of the i-th energy system is a preset second price, determining the renewable energy quota demand value of the i-th energy system as any value within a second preset interval, where the preset second price is greater than the preset first price.

[0012] In an exemplary embodiment, determining the renewable energy quota designation value corresponding to each of the N energy systems includes: determining the renewable energy quota designation value corresponding to the i-th energy system among the N energy systems through the following operation, thereby determining the renewable energy quota designation value corresponding to each of the N energy systems, where i is a positive integer less than or equal to N: determining the renewable energy quota designation value corresponding to the i-th energy system through the following formula: Among them, the Assign a value φ to the renewable energy quota corresponding to the i-th energy system. green To preset the renewable energy quota coefficient, T is the preset time period, and P is the preset renewable energy quota coefficient. i load (t) represents the load of the i-th energy system after participating in demand response within a unit time period Δt.

[0013] According to another aspect of the embodiments of this application, an energy quota determination device is also provided, comprising: a first determination module, configured to determine the carbon trading price corresponding to each of the N energy systems to obtain N carbon trading prices, wherein N is an integer greater than or equal to 2; a second determination module, configured to determine N target renewable energy quota prices corresponding to each of the N energy systems based on the N carbon trading prices; and a third determination module, configured to determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0014] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the above-described method for determining the energy limit when it is run.

[0015] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the energy limit determination method through the computer program.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program and a method for determining the above-mentioned energy limit when the computer program is executed by a processor.

[0017] This application determines the renewable energy quota price for each energy system by using the carbon trading price corresponding to each energy system across multiple energy systems, thereby obtaining the renewable energy quota for each energy system. This improves the allocation efficiency of renewable energy quotas and thus increases energy utilization. It also addresses the problem of low energy utilization efficiency caused by the lack of effective coordination mechanisms and market interaction strategies. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 This is a hardware structure block diagram of a computer terminal for a method of determining energy limits according to an embodiment of this application.

[0021] Figure 2 This is a flowchart of a method for determining an energy limit according to an embodiment of this application;

[0022] Figure 3 This is a structural block diagram of an energy limit determination device according to an embodiment of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] The methods and embodiments provided in this application can be executed on a computer terminal, mobile terminal, or similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of a computer terminal according to an embodiment of the present application of a method for determining energy limits. Figure 1 As shown, a computer terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor (CPU) or a field-programmable gate array (FPGA)) and a memory 104 for storing data are also shown. The computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0026] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the network point adjustment method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0027] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0028] This embodiment provides a method for determining energy quota. Figure 2 This is a flowchart of a method for determining an energy limit according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps S202-S206:

[0029] Step S202: Determine the carbon trading price corresponding to each of the N energy systems to obtain N carbon trading prices, where N is an integer greater than or equal to 2;

[0030] Optionally, this application is applied to a multi-energy integrated system, which includes the N energy systems, and the N energy systems are different types of energy systems, including but not limited to electric energy systems, thermal energy systems, gas energy systems, and photovoltaic energy systems.

[0031] It should be noted that the carbon trading price reflects the purchase price of carbon emission rights by the corresponding energy system.

[0032] Step S204: Determine the N target renewable energy quota prices for each of the N energy systems based on the N carbon trading prices;

[0033] It should be noted that the target renewable energy quota price is adjusted based on dynamic supply and demand, reflecting the market's demand for renewable energy certificates.

[0034] Step S206: Determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0035] It should be noted that the dynamic carbon trading price mechanism and the setting of target renewable energy quota prices have jointly guided the emission reduction behavior of the energy system, while improving the flexibility and market efficiency of green certificate (i.e., the aforementioned renewable energy quota) trading.

[0036] It should be noted that the above steps take into account a variety of cost factors, minimize the overall operating cost of the multi-energy system, improve the economic efficiency of the energy system, and promote cooperation and resource optimization among different energy systems through optimized scheduling. This further improves energy utilization efficiency and the overall reliability and stability of the system, reduces the abandonment of renewable energy, and increases the utilization rate of renewable energy in the system, thereby reducing carbon emissions and energy waste.

[0037] The above steps determine the renewable energy quota price for each energy system by using the carbon trading price corresponding to each energy system across multiple energy systems. This results in the renewable energy quota for each energy system, improving the efficiency of renewable energy quota allocation and thus increasing energy utilization. This, in turn, addresses the problem of low energy utilization efficiency caused by the lack of effective coordination mechanisms and market interaction strategies.

[0038] In an exemplary embodiment, determining the carbon trading price corresponding to each of the N energy systems can be achieved through the following steps: determining the carbon trading price corresponding to the i-th energy system among the N energy systems through steps S11-S12, thereby determining the carbon trading price corresponding to each of the N energy systems, where i is a positive integer less than or equal to N:

[0039] Step S11: Obtain the carbon quota trading price of the i-th energy system;

[0040] Optionally, it is necessary to first collect the carbon allowance trading price for each energy system. The carbon allowance trading price here refers to the price that the energy system is willing to pay in the carbon trading market to comply with carbon emission limits, or the price it can obtain by selling carbon emission allowances. Obtaining this information, based on market data and the company's own carbon emission strategies, provides a basic assessment of the market's value of carbon emission rights.

[0041] Step S12: Determine the carbon trading price corresponding to the i-th energy system using the following formula:

[0042]

[0043] in, The carbon trading price corresponding to the i-th energy system. To preset a minimum carbon trading price, To preset the highest carbon trading price, The average carbon trading price over a preset time period. The carbon quota trading price is... The maximum carbon allowance trading price is preset.

[0044] It should be noted that the preset minimum carbon trading price and the preset maximum carbon trading price define the upper and lower limits of the market price to prevent the adverse effects of extreme price fluctuations; the average carbon trading price within the preset time period reflects the average market level over a period of time; and the preset maximum carbon quota trading price is used to limit the system's expenditures or revenues in the carbon market.

[0045] Optionally, Formula 1 ensures that carbon trading prices fluctuate within a reasonable range, taking into account both the system's actual transaction costs and the market average. This means that even if the carbon quota trading price of a certain energy system is abnormally high or low, it will not cause its carbon trading price to exceed the preset price boundary, thereby avoiding an excessive impact on the overall system operating costs.

[0046] Alternatively, energy systems can optimize their carbon trading strategies based on actual conditions, such as purchasing more carbon emission credits when carbon prices are low, or choosing to reduce emissions when carbon prices are higher than average, thus achieving a balance between economic benefits and environmental responsibility.

[0047] It should be noted that the above steps in determining the carbon trading price for each energy system not only effectively integrate market and corporate strategies, but also mitigate the impact of external market fluctuations on internal operations, optimize financial planning, and ultimately promote the long-term balance of low carbon emissions, high efficiency, and economic benefits in energy systems, providing strong technical support for the sustainable development of the clean energy sector.

[0048] In an exemplary embodiment, determining the N target renewable energy quota prices for each of the N energy systems based on the N carbon trading prices can be achieved through the following steps: Determining the target renewable energy quota price for the i-th energy system among the N energy systems through the following operation, where i is a positive integer less than or equal to N: The renewable energy quota price of the i-th energy system whose objective function value is minimized is determined as the target renewable energy quota price for the i-th energy system, where the objective function is:

[0049]

[0050] F ishare +F iDR );

[0051] Where y is the objective function, F ibuy Let F be the energy purchase cost of the i-th energy system. iCET Let F be the carbon trading price corresponding to the i-th energy system. iGCT Let F be the renewable energy quota price for the i-th energy system. iRES，cut Let F be the cost of waste wind and solar energy for the i-th energy system. iSS Let F be the energy storage cost of the i-th energy system. irep Let F be the equipment operation and maintenance cost of the i-th energy system. iTrans Let F be the energy transmission cost of the i-th energy system. ishare Let F be the resource sharing cost of the i-th energy system. iDR Let be the demand response cost of the i-th energy system.

[0052] Optionally, under the objective constraints, a two-stage robust optimization algorithm is used to search the set of uncertain variables to obtain the worst-case scenario for the IES considering uncertainties. A peer-to-peer (P2P) resource-sharing cooperative game model for the Multi-Integrated Energy Systems Syndicate (MIESs) is established based on Nash negotiation theory, and solved sequentially using the Alternating Direction Method of Multipliers (ADMM) optimization algorithm. The objective constraints include: electric power balance constraints, thermal power balance constraints, gas balance constraints, P2P resource trading constraints, power flow constraints, and green certificate and carbon quota assessment constraints.

[0053] It should be noted that by minimizing the objective function, the operating costs of all (N) energy systems are optimized to the minimum. Carbon trading prices and renewable energy certificate prices serve as market signals that directly affect the value of the objective function, thereby guiding the energy systems to make optimal operational decisions under the market mechanism. This achieves seamless integration between the market mechanism and system operation. The objective function comprehensively considers various costs in the system operation process, including energy purchase, storage, operation and maintenance, and transmission, ensuring the comprehensiveness and rationality of the decision-making and avoiding a reduction in overall benefits due to the neglect of certain costs.

[0054] In an exemplary embodiment, determining the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices can be achieved through the following steps S21 to S23, wherein steps S21 and S22 are not executed in any particular order:

[0055] Step S21: Based on the N target renewable energy quota prices, determine the renewable energy quota demand value corresponding to each of the N energy systems;

[0056] Optionally, the system analyzes the renewable energy quota demand of each energy system over a future time period based on the calculated prices of N target renewable energy quotas. This is achieved by comprehensively considering factors such as system operating status forecasts, including load demand, renewable energy generation capacity, and market price trends. The demand value is determined based on the system's desired green energy use targets and the results of cost-benefit analysis, reflecting the system's actual demand for renewable energy certificates in pursuit of carbon neutrality goals.

[0057] Step S22: Determine the specified renewable energy quota value for each of the N energy systems;

[0058] Optionally, while determining the demand value, a designated renewable energy quota value should be determined for each energy system. This designated renewable energy quota value can be set by a regulatory agency, specifying how much renewable energy quota can be allocated to each energy system to ensure that the proportion of renewable energy use in the entire region or market reaches a certain level. Alternatively, it can be based on internal alliance agreements or market consensus, aiming to balance the contributions and benefits of all members and jointly promote the popularization and utilization of renewable energy. The setting of the designated value takes into account fairness, achievability, and support for the overall goals of the alliance.

[0059] Step S23: Determine the renewable energy quota corresponding to each energy system based on the renewable energy quota demand value and the renewable energy quota specified value corresponding to each of the N energy systems.

[0060] Optionally, the renewable energy quota value of the i-th system reflects the renewable energy quota required by that energy source, and the renewable energy quota specification value reflects the renewable energy quota that the implementing entity or market can provide to the i-th energy system. Through an algorithm, the renewable energy quota allocated to each energy system in the multi-integrated energy system (including the N energy systems) is optimized to maximize energy utilization efficiency. The algorithm includes, but is not limited to, weighted summation.

[0061] It should be noted that if the calculated limit conflicts with the system's physical limitations, market rules, or alliance agreements, further adjustments are needed to ensure the feasibility and consistency of the final result.

[0062] It should be noted that the above steps, which compare the demand value with the specified value, help the system determine the optimal amount of renewable energy certificates to hold, avoiding the waste of funds caused by over-purchasing or over-selling, and achieving the best balance between cost and benefit. Determining the optimal renewable energy quota for each energy system under a dynamic carbon-green certificate trading environment is of great significance for promoting the widespread application of clean energy and ensuring the economical and efficient operation of the energy system.

[0063] In an exemplary embodiment, determining the renewable energy quota demand value corresponding to each of the N energy systems based on the N target renewable energy quota prices can be achieved through the following steps: determining the renewable energy quota demand value corresponding to the i-th energy system among the N energy systems through steps S31 to S33, thereby determining the renewable energy quota demand value corresponding to each of the N energy systems, where i is a positive integer less than or equal to N:

[0064] Step S31: If the target renewable energy quota price of the i-th energy system is a preset first price, determine that the renewable energy quota demand value of the i-th energy system is any value within a first preset range;

[0065] Optionally, when the target renewable energy quota price equals a preset first price, the determined renewable energy quota demand value falls within a "first preset range." This reflects that when prices are at a low and relatively stable level, the system's demand for renewable energy quotas has a certain degree of flexibility and can be adjusted within a certain range to respond to market changes or fine-tuning of operational strategies. For example, if the target renewable energy quota price is the preset first price, which is relatively low, the energy system may choose a higher renewable energy quota demand value to obtain more green energy, and vice versa.

[0066] Step S32: If the target renewable energy quota price of the i-th energy system is greater than the preset first price and less than the preset second price, determine the renewable energy quota demand value corresponding to the i-th energy system according to the preset function, wherein the preset function is a function corresponding to the renewable energy quota demand value and the target renewable energy quota price, and the preset function is a linear function;

[0067] Optionally, when the target renewable energy quota price falls between a preset first price and a preset second price, a linear function is used to determine the renewable energy quota demand value. This means that the renewable energy quota demand value will change linearly with price fluctuations. Specifically, as prices rise, the demand value may decrease because higher prices mean increased costs for purchasing or generating more renewable energy quotas. Conversely, if prices fall, the demand value may increase, allowing the system to acquire more renewable energy quotas at a lower cost. This approach makes the relationship between demand and price clear and predictable, helping the system to plan ahead and adjust its operational strategies to cope with impending changes in market conditions.

[0068] Step S33: When the target renewable energy quota price of the i-th energy system is a preset second price, determine that the renewable energy quota demand value of the i-th energy system is any value within a second preset range, wherein the preset second price is greater than the preset first price.

[0069] Optionally, when the target renewable energy credit price equals a preset second price, the renewable energy credit demand is limited to a "second preset range". In this case, the system's demand for renewable energy credits is strictly limited because the price is too high, necessitating a reduction in the amount of credit purchased or generated to control costs or comply with financial constraints.

[0070] Optionally, the minimum value of the preset function is greater than the preset first price, and the maximum value of the preset function is less than the preset second price.

[0071] It should be noted that steps S31 to S33 are operations performed under different circumstances, and there is no specific order in their execution.

[0072] It should be noted that the above steps enable the multi-energy integrated system to respond quickly and appropriately to price fluctuations. By adjusting the renewable energy quota demand, it can effectively control costs while maintaining its green energy goals. Adjusting demand based on price signals helps to allocate resources more rationally within the alliance, avoiding resource surpluses or shortages and promoting the efficient use of green energy.

[0073] In an exemplary embodiment, determining the renewable energy quota designation value corresponding to each of the N energy systems can be achieved through the following steps: determining the renewable energy quota designation value corresponding to the i-th energy system among the N energy systems through the following operations, thereby determining the renewable energy quota designation value corresponding to each of the N energy systems, where i is a positive integer less than or equal to N:

[0074] The specified renewable energy quota value corresponding to the i-th energy system is determined by the following formula:

[0075]

[0076] Among them, the Assign a value φ to the renewable energy quota corresponding to the i-th energy system. green To preset the renewable energy quota coefficient, T is the preset time period, and P is the preset renewable energy quota coefficient. i load (t) represents the load of the i-th energy system after participating in demand response within a unit time period Δt.

[0077] Optionally, T is a preset time period, such as a week, a month, or a quarter, used to measure the time span of renewable energy credits.

[0078] It should be noted that by incorporating the demand response load into the calculation, Formula 2 can more accurately match the actual energy consumption or production potential of the energy system with the specified value of the renewable energy quota. This means that the system can set a more reasonable benchmark for renewable energy use based on its actual operation, avoiding a disconnect between the quota specification and the actual operation of the system.

[0079] Obviously, the embodiments described above are only some embodiments of this application, and not all embodiments. To better understand the method, the following description, in conjunction with embodiments, illustrates the above process, but is not intended to limit the technical solutions of the embodiments of this application. Specifically:

[0080] The multi-integrated energy system alliance involved in this application consists of multiple integrated energy systems (i.e., the aforementioned multiple energy systems) within the distribution network. Different types of IES differ in terms of equipment and load composition. The main equipment includes upstream electricity, heat, and gas networks, as well as new energy sources, combined heat and power units, power-to-gas conversion, carbon capture systems, and electricity and heat storage equipment, and residential electricity and heat loads. Among them, P2G includes electrolyzers and methane reactors.

[0081] I. Designing a dynamic carbon trading mechanism with punitive characteristics:

[0082] A dynamic carbon trading mechanism responsive to changes in carbon market demand was designed. This mechanism effectively guides emission reduction behavior and constrains and guides market participants to manage carbon emissions rationally through dynamic carbon pricing. The mechanism establishes a floor price and a penalty price. Between these two boundary values, the carbon trading price and its market supply and demand satisfy a certain relationship, described by a linear function. The dynamic carbon trading price model for the system participating in CET is based on Formula 1 above.

[0083] II. Green Certificate Trading Mechanism Based on Dynamic Supply and Demand Curves:

[0084] As the demand for green certificates (i.e., the aforementioned renewable energy quota demand) increases, the price of green certificates will gradually transition from a linearly increasing phase to a penalty phase, where the price will rise until demand reaches a pre-set threshold, at which point the price will be fixed at a punitive high. Conversely, as the volume of green certificates sold increases, the price will shift from the linear phase to a floor price phase, continuously decreasing until the sales volume reaches a certain level and is fixed at the floor price. This mechanism aims to enhance the sensitivity of the green certificate trading mechanism to current supply and demand conditions, future emission reduction expectations, technological advancements, and other factors through dynamic price signals.

[0085] It should be noted that the conversion relationship between green certificates and green electricity is that one green certificate is equivalent to 1MW of green electricity. Therefore, the number of green certificates obtained by the system is as follows:

[0086]

[0087] In the formula: P represents the number of green certificates obtained by member i. i RES (t) represents the output of member i's new energy generating unit during time period t; T represents the total time period (i.e., the preset time period mentioned above); Δt represents the unit scheduling time period.

[0088] According to the renewable energy quota mechanism, a portion of the electricity generated and consumed by enterprises or users must come from new energy sources. The calculation formula for the number of green certificates required by the system is the same as Formula 2 above.

[0089] III. Design of a MIESS alliance coordination and optimization scheduling model for a dynamic carbon-green certificate trading interaction mechanism:

[0090] 1. Objective Function: The optimization aims to minimize the overall operating cost, which includes energy purchase cost, carbon trading cost, green certificate trading cost, wind and solar curtailment cost, energy storage cost, equipment operation and maintenance cost, energy transmission cost, resource sharing cost, and demand response cost. The objective function is as follows:

[0091]

[0092] 2. Constraints: These include constraints on power balance, heat balance, gas balance, P2P resource trading, power flow, and green certificates and carbon quota assessment.

[0093] IV. Solution:

[0094] A two-stage robust optimization algorithm is used to search the set of uncertain variables, obtaining the worst-case scenario for IES considering uncertainties. A MIESS alliance P2P resource-sharing cooperative game model is established based on Nash negotiation theory, and the Alternating Direction Multiplier Method (ADMM) optimization algorithm is used to solve it sequentially.

[0095] It should be noted that the above steps designed a dynamic carbon trading mechanism that responds to changes in carbon market demand and a green certificate trading mechanism based on dynamic trading supply and demand curves. This guides emission reduction behavior and enhances the sensitivity of the green certificate trading mechanism through dynamic price signals. A MIESS alliance coordination optimization scheduling model was established, taking into account the dynamic carbon-green certificate trading interaction mechanism. The objective function is to minimize the overall operating cost, and various constraints are considered. The ADMM algorithm is used to solve the model in a distributed manner, ensuring the privacy of information of each entity while achieving efficient solution to the MIESS alliance P2P resource sharing cooperation problem.

[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0097] This embodiment also provides an energy limit determination device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0098] Figure 3 This is a structural block diagram of an energy limit determination device according to an embodiment of this application. The device includes:

[0099] The first determining module 32 is used to determine the carbon trading price corresponding to each of the N energy systems, thereby obtaining N carbon trading prices, where N is an integer greater than or equal to 2;

[0100] The second determining module 34 is used to determine the N target renewable energy quota prices corresponding to each of the N energy systems based on the N carbon trading prices;

[0101] The third determining module 36 is used to determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0102] The aforementioned device determines the renewable energy quota price for each energy system by using the carbon trading price corresponding to each energy system across multiple energy systems. This results in the renewable energy quota for each energy system, improving the allocation efficiency of renewable energy quotas and thus increasing energy utilization. This addresses the problem of low energy utilization efficiency caused by the lack of effective coordination mechanisms and market interaction strategies.

[0103] In an exemplary embodiment, the first determining module 32 is further configured to determine the carbon trading price corresponding to the i-th energy system among the N energy systems through the following operations, so as to determine the carbon trading price corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: obtaining the carbon quota trading price of the i-th energy system; determining the carbon trading price corresponding to the i-th energy system through the following formula: Formula 1; where, The carbon trading price corresponding to the i-th energy system. To preset a minimum carbon trading price, To preset the highest carbon trading price, The average carbon trading price over a preset time period. The carbon quota trading price is... The maximum carbon allowance trading price is preset.

[0104] In an exemplary embodiment, the second determining module 34 is further configured to determine the target renewable energy quota price corresponding to the i-th energy system among the N energy systems through the following operation, so as to determine the target renewable energy quota price corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: determining the renewable energy quota price of the i-th energy system whose objective function value is minimized as the target renewable energy quota price corresponding to the i-th energy system, wherein the objective function is: Where y is the objective function, F ibuyLet F be the energy purchase cost of the i-th energy system. iCET Let F be the carbon trading price corresponding to the i-th energy system. iGCT Let F be the renewable energy quota price for the i-th energy system. iRES，cut Let F be the cost of waste wind and solar energy for the i-th energy system. iSS Let F be the energy storage cost of the i-th energy system. irep Let F be the equipment operation and maintenance cost of the i-th energy system. iTrans Let F be the energy transmission cost of the i-th energy system. ishare Let F be the resource sharing cost of the i-th energy system. iDR Let be the demand response cost of the i-th energy system.

[0105] In an exemplary embodiment, the third determining module 36 is further configured to determine the renewable energy quota demand value corresponding to each of the N energy systems based on the N target renewable energy quota prices; and to determine the renewable energy quota designation value corresponding to each of the N energy systems; and to determine the renewable energy quota corresponding to each energy system based on the renewable energy quota demand value and the renewable energy quota designation value corresponding to each of the N energy systems.

[0106] In an exemplary embodiment, the third determining module 36 is further configured to determine the renewable energy quota demand value corresponding to the i-th energy system among the N energy systems through the following operations, so as to determine the renewable energy quota demand value corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: when the target renewable energy quota price of the i-th energy system is a preset first price, determine the renewable energy quota demand value of the i-th energy system as any value within a first preset interval; when the target renewable energy quota price of the i-th energy system is greater than the preset first price and less than a preset second price, determine the renewable energy quota demand value corresponding to the i-th energy system according to a preset function, where the preset function is a function corresponding to the renewable energy quota demand value and the target renewable energy quota price, and the preset function is a linear function; when the target renewable energy quota price of the i-th energy system is a preset second price, determine the renewable energy quota demand value of the i-th energy system as any value within a second preset interval, where the preset second price is greater than the preset first price.

[0107] In an exemplary embodiment, the third determining module 36 is further configured to determine the renewable energy quota designation value corresponding to the i-th energy system among the N energy systems by the following operation, so as to determine the renewable energy quota designation value corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: The renewable energy quota designation value corresponding to the i-th energy system is determined by the following formula: Among them, the Assign a value φ to the renewable energy quota corresponding to the i-th energy system. green The preset renewable energy quota coefficient is T, where T is the preset time period. Let be the load of the i-th energy system after participating in demand response within a unit time period Δt.

[0108] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

[0109] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0110] S1. Determine the carbon trading price for each of the N energy systems to obtain N carbon trading prices, where N is an integer greater than or equal to 2;

[0111] S2. Determine the N target renewable energy quota prices for each of the N energy systems based on the N carbon trading prices;

[0112] S3. Determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0113] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0114] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0115] Embodiments of this application also provide a computer program product, including a computer program, wherein the computer program, when executed by a processor, performs the steps in any of the above method embodiments.

[0116] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0117] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0118] Optionally, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0119] S1. Determine the carbon trading price for each of the N energy systems to obtain N carbon trading prices, where N is an integer greater than or equal to 2;

[0120] S2. Determine the N target renewable energy quota prices for each of the N energy systems based on the N carbon trading prices;

[0121] S3. Determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

[0122] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0123] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0124] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of N computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or N modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0125] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining energy quotas, characterized in that, include: Determine the carbon trading price for each of the N energy systems to obtain N carbon trading prices, where N is an integer greater than or equal to 2; Based on the N carbon trading prices, determine the N target renewable energy quota prices for each of the N energy systems; The renewable energy quota for each of the N energy systems is determined based on the N target renewable energy quota prices.

2. The method for determining energy quota according to claim 1, characterized in that, Determine the carbon trading price for each of the N energy systems, including: The carbon trading price corresponding to the i-th energy system among the N energy systems is determined through the following operations, thereby determining the carbon trading price corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: Obtain the carbon quota trading price of the i-th energy system; The carbon trading price corresponding to the i-th energy system is determined using the following formula: in, The carbon trading price corresponding to the i-th energy system. To preset a minimum carbon trading price, To preset the highest carbon trading price, The average carbon trading price over a preset time period. The carbon quota trading price is... The maximum carbon allowance trading price is preset.

3. The method for determining energy quota according to claim 1, characterized in that, Based on the N carbon trading prices, determine the N target renewable energy quota prices for each of the N energy systems, including: The target renewable energy quota price corresponding to the i-th energy system among the N energy systems is determined by the following operations, thereby determining the target renewable energy quota price corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: The renewable energy quota price for the i-th energy system when the objective function value is minimized is determined as the target renewable energy quota price for the i-th energy system, wherein the objective function is: Where y is the objective function, F ibuy Let i be the energy purchase cost of the i-th energy system. F iCET Let F be the carbon trading price corresponding to the i-th energy system. iGCT Let F be the renewable energy quota price for the i-th energy system. iRES，cut Let F be the cost of waste wind and solar energy for the i-th energy system. iSS Let F be the energy storage cost of the i-th energy system. irep Let F be the equipment operation and maintenance cost of the i-th energy system. iTrans Let F be the energy transmission cost of the i-th energy system. ishare Let F be the resource sharing cost of the i-th energy system. iDR Let be the demand response cost of the i-th energy system.

4. The method for determining energy quota according to claim 1, characterized in that, Determining the renewable energy quota for each of the N energy systems based on the N target renewable energy quota prices includes: Based on the N target renewable energy quota prices, determine the renewable energy quota demand value for each of the N energy systems; and Determine the renewable energy quota specified value for each of the N energy systems; determine the renewable energy quota for each energy system based on the renewable energy quota demand value and the renewable energy quota specified value for each of the N energy systems.

5. The method for determining energy quota according to claim 4, characterized in that, Based on the N target renewable energy quota prices, determine the renewable energy quota demand value for each of the N energy systems, including: The renewable energy quota requirement value corresponding to the i-th energy system among the N energy systems is determined by the following operations, thereby determining the renewable energy quota requirement value corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: If the target renewable energy quota price for the i-th energy system is a preset first price, the renewable energy quota demand value for the i-th energy system is determined to be any value within a first preset range. When the target renewable energy quota price of the i-th energy system is greater than the preset first price and less than the preset second price, the renewable energy quota demand value corresponding to the i-th energy system is determined according to the preset function, wherein the preset function is a function corresponding to the renewable energy quota demand value and the target renewable energy quota price, and the preset function is a linear function; When the target renewable energy quota price for the i-th energy system is a preset second price, the renewable energy quota demand value for the i-th energy system is determined to be any value within a second preset range, wherein the preset second price is greater than the preset first price.

6. The method for determining energy quota according to claim 4, characterized in that, Determining the renewable energy quota allocation for each of the N energy systems includes: The renewable energy quota allocation value corresponding to the i-th energy system among the N energy systems is determined by the following operations, thereby determining the renewable energy quota allocation value corresponding to each energy system among the N energy systems, where i is a positive integer less than or equal to N: The specified renewable energy quota value corresponding to the i-th energy system is determined by the following formula: Among them, the Assign a value φ to the renewable energy quota corresponding to the i-th energy system. green The preset renewable energy quota coefficient is T, where T is the preset time period. Let be the load of the i-th energy system after participating in demand response within a unit time period Δt.

7. A device for determining energy quota, characterized in that, include: The first determining module is used to determine the carbon trading price corresponding to each of the N energy systems, thereby obtaining N carbon trading prices, where N is an integer greater than or equal to 2; The second determining module is used to determine the N target renewable energy quota prices corresponding to each of the N energy systems based on the N carbon trading prices; The third determining module is used to determine the renewable energy quota corresponding to each of the N energy systems based on the N target renewable energy quota prices.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 6.

9. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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