A collaborative transaction method for electric-thermal-carbon coupling in a regional integrated energy system

Abstract

The application discloses a kind of electric-thermal-carbon coupling collaborative transaction methods in regional integrated energy system, first, the modeling of operation cost in single energy hub in regional integrated energy system, including: the climbing constraint and output power constraint of gas turbine and gas boiler, electric energy storage and thermal energy storage constraint, physical network constraint and carbon emission constraint etc., next, with the minimum of the operation cost of entire regional integrated energy system as objective function, considering the constraint of multiple actual existence in park, establish the model of electric, carbon, heat flow coupling of entire park integrated energy system, through ADMM algorithm design electric-carbon-heat coupling multi-energy transaction method, to obtain the transaction result in advance of day.For further more accurate regional integrated energy system transaction volume and transaction price, the loss coefficient in transaction process is obtained by using distributed algorithm, and finally the final transaction result is obtained by executing the transaction method of dynamically updating the loss coefficient.

Description

Technical Field

[0001] This invention relates to the field of trading and operation of integrated electric and thermal energy systems, and in particular to a collaborative trading method for coupling electricity, heat, and carbon in a regional integrated energy system. Background Technology

[0002] Integrated energy systems provide multiple energy conversion pathways, such as electricity, cooling, heating, and gas, through the synergy of various energy sources. This promotes the large-scale integration and consumption of intermittent renewable energy sources, thereby improving energy efficiency, reducing pollutant emissions, and achieving sustainable development.

[0003] Distribution networks and district heating systems are important components of regional integrated energy systems. Users participating in these systems can both consume their own electricity and engage in transactions with neighboring users. Furthermore, the introduction of carbon markets has accelerated the green and low-carbon transformation of energy systems. Li et al. proposed a peer-to-peer trading approach considering the electricity-carbon integrated market. However, this framework does not consider the thermal energy market and requires the introduction of a third-party market participant to formulate market clearing rules. This approach fails to protect the privacy of market participants. (Li J, Ge S, Xu Z, Liu H, Li J, Wang C, et al. A network-secure peer-to-peer trading framework for electricity-carbon integrated market among local prosumers. Applied Energy 2023;335:120420.) Summary of the Invention

[0004] This invention proposes a collaborative trading and clearing method for electricity-carbon-heat coupling in a regional integrated energy system. First, it models the operating costs of individual market participants (energy hubs, EHs) within the regional integrated energy system, including EH production costs, electricity trading costs, heat trading costs, and carbon quota trading costs. It also considers constraints during the park's operation, such as ramp-up and output power constraints for gas turbines and boilers, constraints on electrical and thermal energy storage, physical network constraints, and carbon quota constraints. Next, with the goal of minimizing the overall operating cost of the regional integrated energy system, it establishes an electricity, carbon, and heat flow model for the entire park's integrated energy system, considering various existing constraints. An ADMM algorithm is used to design an electricity-carbon-heat coupling collaborative trading method to obtain the current trading results. To further refine the accuracy of trading volume and prices in the regional integrated energy system, a distributed algorithm is used to obtain the current power flow information of the power grid and heating network, thereby obtaining the current loss coefficients. Finally, the electricity-heat-carbon coupling collaborative trading method with dynamically updated loss coefficients is executed to obtain the final trading information. This distributed transaction method performs calculations with only local privacy information required, which greatly protects the privacy of market participants.

[0005] The present invention is achieved by at least one of the following technical solutions.

[0006] A coordinated trading method for electricity-heat-carbon coupling in a regional integrated energy system includes the following steps:

[0007] 1) Establish an EH operating cost model in the regional integrated energy system, including: the current production cost, electricity trading cost, heat trading cost, and carbon emission cost of the EH;

[0008] 2) Establish an operating status model for the EH gas-fired boiler and gas turbine in the regional integrated energy system;

[0009] 3) Establish EH carbon emission constraints, carbon quota constraints, carbon balance constraints, and electric energy storage and thermal energy storage constraints models in regional integrated energy systems;

[0010] 4) Establish an EH supply and demand balance constraint model and energy transmission constraints in the regional integrated energy system;

[0011] 5) Construct a model of the overall operating cost of the entire district heating system, and design a collaborative distributed trading method for electricity, carbon, and heat using the ADMM algorithm.

[0012] Furthermore, the EH operating cost model in step 1) includes:

[0013]

[0014] in Represents the operating cost of an energy hub (EH) within the park. It is EH i At any moment t Electricity trading prices It is EH j At any moment t Electricity trading prices Representing EH i At any moment t The price of heat energy trading Representing EH j The price of heat energy trading, Representing EH i At any moment t The price of carbon allowance sales transactions Representing EH j At any moment t The price at which carbon allowances are sold, Representing EH i Neighbors connected to nearby power lines, Representing EH i Neighbors connected to nearby heating pipes, Representing EH i The neighbors nearby who trade carbon allowances. It is the production cost of the gas turbine GT. For the production cost of gas-fired boilers GB, For the cost of BES for energy storage, and Costs of carbon emissions and thermal energy storage TES; The cost of purchasing electricity from the main grid Revenue from selling electricity to the main grid, of which Represents time scale, Represents the moment t Purchase electricity from the mainnet Represents the moment t Electricity sold from the mainnet Represents the moment t The retail price of electricity purchased from the main grid. Represents the moment t The retail price of electricity sold from the main grid. The costs incurred in trading carbon allowances, of which Representing EH i Neighbors nearby who trade carbon credits Represents the moment t EH j The price at which carbon allowances are sold, Represents the moment t The trading volume of carbon allowances. The revenue from selling carbon emission rights, of which It is EH i At any moment t Electricity trading prices It is EH i At any moment t Carbon allowance sales volume The cost of purchasing electricity from surrounding producers and consumers, of which It is EH j At any moment t Electricity trading prices EH i At any moment t To EH j Purchased electrical energy, (This indicates the energy loss during the transaction process). Revenue from the sale of electricity, of which It is EH i Electricity trading prices EH i (total electricity sold). For the expenditure on purchasing heat energy, The revenue from selling heat energy, of which Represents the moment t EH i The price of heat energy trading, Represents the moment t EH i Total sales volume Represents the moment t Loss coefficient of heat energy trading Indicates at time t EH i To EH j Total heat output purchased; and These are the network access fees paid to distribution network operators and heating network operators, respectively. The decision variables for each EH include the electric and thermal output of the gas turbine, the thermal output of the gas boiler, the output of electric and thermal energy storage, carbon emission credits, the amount of electric heat purchased, the amount of carbon credits purchased, the amount of electric heat sold, and the amount of carbon credits sold. The specific expressions for the decision variables are as follows:

[0015]

[0016] in, Indicates the electric thermal output of the gas turbine, Indicates the heat output of the gas-fired boiler, and These represent the output power of electrical energy storage and thermal energy storage, respectively. , and These represent the purchase volume of electric heating and carbon quotas, respectively. , and These represent the sales volume of electric heating carbon.

[0017] Furthermore, in step 2), the operating constraints for the gas turbine GT in the regional integrated energy system are as follows:

[0018]

[0019]

[0020]

[0021] in and It is a gas turbine in t The heat and electricity produced at all times It is the coupling ratio of electrical energy and thermal energy produced by a gas turbine during operation; It is the lowest operating point during the operation of a gas turbine. It is the highest operating point in the operation of a gas turbine. This indicates the maximum power reduction per hour of the gas turbine. This indicates the maximum power increase per hour of the gas turbine.

[0022] Furthermore, in step 2), the operational constraints for the gas filter GB in the regional integrated energy system are as follows:

[0023]

[0024] In the formula, It is the lowest operating point during the operation of a gas turbine. It is the highest operating point in the operation of a gas turbine. Indicates the time of the gas boiler t Thermal energy output.

[0025] Furthermore, in step 2), the electrical / thermal energy balance constraints of the regional integrated energy system are modeled:

[0026]

[0027]

[0028] In the formula, and It is a gas turbine in t The heat and electricity produced at all times Is t Time EH i Electricity purchased from the mainnet, It is EH i exist t The electrical energy purchased from the adjacent EH at all times, of which Representing EH i Neighbors connected to nearby power lines, EH i At any moment t To EH j Purchased electricity; It is EH i exist t The output of the battery pack at all times. It is EH i exist t The amount of electricity sold to the main network at any time It is EH i exist t The electrical energy sold to the adjacent EH at all times For EH i exist t The power demand at any time It is the heat generated by the gas turbine. It is the heat output of the gas-fired boiler. It is EH i exist t Constantly purchasing heat energy from the surrounding area Representing EH i The neighbors whose power lines are connected nearby, Indicates at time t EH i To EH j Purchased heat energy; It is EH i exist t The output of thermal energy storage at all times, It is EH i exist t The heat energy sold to the adjacent EH at all times. For EH i exist t The constant demand for thermal energy.

[0029] Furthermore, in step 3), carbon quota constraints in the regional integrated energy system are modeled:

[0030]

[0031]

[0032]

[0033] In the formula, This represents the amount of new energy used. Carbon allowances obtained through the use of new energy sources. The carbon emissions caused by using each unit of energy in the power distribution network. To reduce carbon emissions from the use of gas-fired boilers, Carbon quotas generated during natural gas combustion To reduce carbon emissions from the use of gas turbines, and The gas turbine and gas boiler are respectively EH i exist t The electrical energy output at any given moment.

[0034] Furthermore, in step 3), carbon balance constraints in the regional integrated energy system are modeled.

[0035]

[0036] In the formula, Energy Hub EH i exist t Carbon emission allowances at any time For EH i exist t The total amount of carbon allowances purchased from neighboring EHs at any given time. Representing EH i Neighbors connected to nearby heating pipes, The representative is EH i exist t Always towards EH j The amount of carbon credits purchased. For EH i exist t Carbon allowances sold to neighboring EHs at any given time Carbon emissions generated from the use of new energy sources (negative values ​​indicate carbon allowances obtained). Carbon emissions from using gas-fired boilers Carbon emissions generated from the use of gas turbines.

[0037] Furthermore, in step 3), the energy storage constraints of the regional integrated energy system are modeled:

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] In the formula, It is EH i exist t The power output of the battery pack at all times. It is EH i exist t The discharge energy of the battery pack at all times. It is EH i exist t The charging energy of the battery pack at all times; This is the maximum charging and discharging power of the battery pack; This is the minimum limit for the state of charge of the battery pack. This is the maximum limitation on the charging state of the battery pack; Is it the battery? t The charging state at time =0. This refers to the battery's initial state of charge. Represents battery pack i At any moment t Charging status, Indicates battery pack i Battery life Indicates the charging efficiency of the battery pack, Indicates the battery pack at time t The charging power, Indicates the discharge efficiency of the battery pack, Indicates time scale, Indicates the charging status at the end of the day. This indicates the charging status at the start of the day.

[0044] Furthermore, in step 3), the thermal energy storage constraint model is performed on the regional integrated energy system:

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] It is EH i exist t The thermal output of the battery pack at all times It is EH i exist t The thermal energy storage unit releases heat energy at all times. It is EH i exist tThe heat energy absorbed by the thermal power unit at all times; This is the maximum charging and discharging power of the battery pack; This is the minimum limit for the state of charge of the battery pack. This is the maximum limitation on the charging state of the battery pack; Is it the battery? t The charging state at time =0. This refers to the battery's initial state of charge. Indicates the status of the thermal energy storage unit, This indicates the working status of the thermal energy storage unit at the end of the day.

[0051] Furthermore, in step 4), energy transmission constraints in the regional integrated energy system are modeled:

[0052]

[0053]

[0054]

[0055] In the formula, Representing EH i exist t The electricity purchased from the main network at all times It is EH i exist t The electrical energy constantly sold to the main network It is EH i exist t Always towards EH j Purchased electrical energy It is the maximum power transmitted in the transmission line. Yes, it's EH. i exist t Always towards EH j Purchased thermal energy It is the maximum heat transfer power in the transmission line. Indicates the maximum power transfer volume in transactions with the mainnet. Indicates EH i Neighbors connected by power lines Indicates EH i Neighbors connected by heating pipes.

[0056] Furthermore, in step 4), the supply and demand balance constraints of the regional integrated energy system are modeled:

[0057]

[0058]

[0059]

[0060] In the formula, Representing EH i exist t The total amount of electricity sold at any given time Representing EH j exist t Always towards EH i Purchased electricity Indicates EH i Neighbors connected by power lines This represents the point loss incurred between transactions. Representing EH i exist t The total amount of heat energy sold at any given time The heat loss coefficient between transactions, Representing EH j exist t Always towards EH i Purchased heat energy, Indicates EH i Neighbors connected by heating pipes It is EH i exist t The total amount of carbon allowances available for sale at any given time. It is EH i exist t EH always j The total amount of carbon allowances sold, EH i exist t Time EH j Electricity sold

[0061] Further, in step 5), a model of the overall operating cost of the entire district heating system is constructed. The transaction decision-making stage of the electricity-carbon-heat coupled collaborative trading method is designed using the ADMM algorithm, including the following steps:

[0062] First, the operating cost of the entire regional integrated energy system is modeled, and the objective function for the modeling is as follows:

[0063]

[0064] in Represents the total operating cost within the park. It is EH i At any moment t Electricity trading prices It is EH j At any moment t Electricity trading prices Representing EH i At any momentt The price of heat energy trading Representing EH j The price of heat energy trading, Representing EH i At any moment t The price of carbon allowance sales transactions Representing EH j At any moment t The price at which carbon allowances are sold, Representing EH i Neighbors connected to nearby power lines, Representing EH i Neighbors connected to nearby heating pipes, Representing EH i Neighbors nearby who trade carbon allowances; It is a decision variable. It is the production cost of the gas turbine GT. For the production cost of gas-fired boilers GB, For the cost of BES for energy storage, For carbon emissions and The cost of thermal energy storage TES; The cost of purchasing electricity from the main grid Revenue from selling electricity to the main grid; This represents the collection of energy hubs (EH) within the park. Indicates the total timescale of operation within the park, Indicates time scale, Represents the moment t Purchase electricity from the mainnet Represents the moment t Electricity sold from the mainnet Represents the moment t The retail price of electricity purchased from the main grid. Represents the moment t The retail price of electricity sold from the main grid.

[0065] The ADMM algorithm is used to design a distributed transaction method, as detailed below.

[0066] In the k In each cycle, each EH calculates in parallel its required energy production, required energy trading, required carbon allowances, and required carbon allowances trading, following the update formula:

[0067]

[0068] In the formula, The set representing decision variables. Representative decision EHi Local constraints, Represents the cost function of an EH. Representative at k EH during the -1st cycle i Electricity prices Representative at k EH during the -1st cycle i Heat energy price Representative and EH i Neighbors connected by power lines Representative at k EH during the -1st cycle j The price of heat energy.

[0069] in The penalty term will equal 0 after convergence, and its specific expression is:

[0070]

[0071] In the formula, Representing electricity trading in the k The price of the next iteration. This is the step size during the update. It's worth noting that... The selection, This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times t To EH i The total heat energy purchased, Representing EH i At any moment t Total carbon allowances sold, Representing EH i The neighbors at all times t To EH i The total carbon allowances purchased.

[0072] Further, in step 5), a model of the overall operating cost of the entire district heating system is constructed. The price update stage of the electricity-carbon-heat coupled collaborative trading method is designed using the ADMM algorithm, including:

[0073] In the k In each subsequent cycle, each EH will receive transaction requests from its neighbors and simultaneously update the current electricity price according to the following update formula. Heat price And carbon emission rights price :

[0074]

[0075]

[0076]

[0077] In the formula, Representing electricity trading in the k The price of the next iteration. This is the step size during the update. It's worth noting that... The choice of does not affect the convergence result. This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times t To EH i The total heat energy purchased, This represents the heat loss coefficient during the transaction process. Representing EH i At any moment t Total carbon quotas sold It is worth noting that the price update formula described above mimics price changes caused by market supply and demand. Taking electricity as an example, when EH... i Current desired sales volume Greater than the total demand of the surrounding EH If the price increases, the price will decrease. Conversely, the price will decrease.

[0078] The terms in parentheses can be used to measure the convergence of the algorithm. The convergence of the algorithm is determined by defining the following metrics:

[0079]

[0080] In the formula, This represents the terms inside the curly braces in the electricity price update formula. This represents the terms within the curly braces in the heat price update formula. This represents the terms within the curly braces in the carbon quota price update formula.

[0081] After obtaining the current transaction status, the current heat network flow is obtained using the fourth-generation district heating system distributed heat flow acquisition method (CN202210833841.5.), and the loss coefficient in the transaction process is updated according to the following method. and .

[0082]

[0083]

[0084] In the formula, and This represents the loss caused during transmission. For EH i and EH j The volume of heat energy traded between them. Indicates the rated node voltage in an active distribution network. Indicates the line resistance. EH i and EH j At any moment t Transaction volume.

[0085] Step 5 is executed repeatedly using the updated loss coefficient, i.e., the electro-thermal-carbon coupled collaborative trading method that dynamically updates the loss parameters is executed until convergence and the trading result is obtained.

[0086] Compared with existing technologies, the beneficial effects of the present invention are as follows:

[0087] (1) Taking into account the impact of carbon emissions in the process of trading electricity and heat in the regional integrated energy system is helpful for the low-carbon transformation of the integrated energy system.

[0088] (2) It has good scalability. The method of the present invention can adapt to the continuous addition of energy hubs to the district heating system.

[0089] (3) In the process of regional integrated energy trading, the losses generated in the electricity-heat-carbon trading should be considered to obtain a more accurate trading price. Attached Figure Description

[0090] Figure 1 To implement a regional integrated energy system model;

[0091] Figure 2 This is a topology diagram of the EH connection in a specific implementation example;

[0092] Figure 3 Flowchart for the invention of an electricity-heat-carbon collaborative trading and clearing method. Detailed Implementation

[0093] To make the objectives, technical solutions, and advantages of the present invention clearer and more explicit, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0094] Example 1

[0095] A coordinated trading method for electricity-heat-carbon coupling in a regional integrated energy system includes the following steps:

[0096] 1) Establish an EH operating cost model in the regional integrated energy system, including: the current production cost, electricity trading cost, heat trading cost, and carbon emission cost of the EH;

[0097] 2) Establish an operating status model for the EH gas-fired boiler and gas turbine in the regional integrated energy system;

[0098] 3) Establish EH carbon emission constraints, carbon quota constraints, carbon balance constraints, and electric energy storage and thermal energy storage constraints models in regional integrated energy systems;

[0099] 4) Establish an EH supply and demand balance constraint model and energy transmission constraints in the regional integrated energy system;

[0100] 5) Construct a model of the overall operating cost of the entire district heating system, and design a coordinated distributed method for electricity, heat and carbon through the ADMM algorithm.

[0101] like Figure 1 As shown, this example uses a 4-node multi-EH scenario as the simulation object to specifically illustrate the electro-thermal-carbon coupled collaborative trading method provided by this invention. Its network topology is as follows: Figure 2 As shown, the specific steps are as follows:

[0102] Step S110: Obtain network data and transaction information of the heating network system, including: the total number of nodes in the heating network and the length of each pipeline. Producers and consumers i heat source or load Pipe roughness coefficient The region has a total of 4 energy hubs; the pipeline length is... , and Pipe roughness coefficient The energy hubs obtained in this embodiment are shown in Table 1.

[0103] Table 1 Load data information of the 4-node system at 24 hours

[0104]

[0105] Step S120, in the k In each cycle, each EH calculates in parallel its required energy production, required energy trading, required carbon allowances, and required carbon allowances trading, following the update formula:

[0106]

[0107] In the formula, The set representing decision variables. Representative decision EH i Local constraints, Represents the cost function of an EH. Representative at k EH during the -1st cycle i Electricity prices Representative at k EH during the -1st cycle i Heat energy price Representative and EH i Neighbors connected by power lines Representative at k EH during the -1st cycle j The price of heat energy.

[0108] in The penalty term will equal 0 after convergence, and its specific expression is:

[0109] In the formula, Representing electricity trading in the k The price of the next iteration. This is the step size during the update. It's worth noting that... The selection, This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times t To EH i The total heat energy purchased, Representing EH i At any moment t Total carbon allowances sold, Representing EH i The neighbors at all times t To EH i The total carbon allowances purchased.

[0110] Step S130: Interact with supply and demand information to simulate market behavior and update prices.

[0111] In the k In each subsequent cycle, each EH will receive transaction requests from its neighbors and simultaneously update the current electricity price according to the following update formula. Heat price and carbon quota prices :

[0112]

[0113]

[0114]

[0115] In the formula, Representing electricity trading in the k The price of the next iteration. This is the step size during the update. It's worth noting that... The choice of does not affect the convergence result. This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times tTo EH i The total heat energy purchased, This represents the heat loss coefficient during the transaction process. Representing EH i At any moment t Total carbon quotas sold It is worth noting that the price update formula described above mimics price changes caused by market supply and demand. Taking electricity as an example, when EH... i Current desired sales volume Greater than the total demand of the surrounding EH If the price increases, the price will decrease. Conversely, the price will decrease.

[0116] Step S140: Obtain the updated loss coefficients, and iteratively execute steps S120 and S130 until convergence.

[0117] The terms in parentheses can be used to measure the convergence of the algorithm. The convergence of the algorithm is determined by defining the following metrics:

[0118]

[0119] In the formula, This represents the terms inside the curly braces in the electricity price update formula. This represents the terms within the curly braces in the heat price update formula. This represents the terms within the curly braces in the carbon price update formula.

[0120] After obtaining the current transaction status, the current heat network flow is obtained using the distributed heat flow acquisition method for fourth-generation district heating systems (Sun Chao, Liu Yun, Zhu Jizhong. "A distributed heat network flow acquisition method for fourth-generation district heating systems", invention patent, published, application number: 202210833841.5.), and the loss coefficient in the heat transaction process is updated according to the following method. and :

[0121]

[0122]

[0123] In the formula, and This represents the loss caused during transmission. For EH i and EH j The volume of heat energy traded between them. Indicates the rated node voltage in an active distribution network. Indicates the line resistance. EH i and EH j At any momentt Transaction volume.

[0124] Steps S130 and 140 are repeatedly executed using the updated loss coefficients, i.e., the collaborative trading method of dynamically updating loss parameters in an electricity-heat-carbon coupling is implemented until convergence and the trading results are obtained. The converged solution includes the gas turbine's electric thermal output, the gas boiler's thermal output, the output of electric and thermal energy storage, carbon emission allowances, the amount of electric thermal purchased, the amount of carbon emission rights purchased, the amount of electric thermal sold, the amount of allowances sold, the electricity price, the thermal price, and the carbon allowance trading price. Some of the trading volume information and trading prices are shown in the table below.

[0125] Table 2 24-hour energy trading prices for the 4-node system

[0126]

[0127] Table 3. 24-hour transaction volume information for the 4-node system

[0128]

[0129] Example 2

[0130] Table 4. Load data of the node system at 24 hours.

[0131]

[0132] Table 5. 24-hour transaction price information for the 4-node system.

[0133]

[0134] Table 6. 24-hour transaction volume information for the 4-node system

[0135]

[0136] Example 3

[0137] In Example 3, the pipe and other parameters are still the same as in Example 1. The load data used in the four nodes of the heating network is different from that in Example 1 and Example 2. The load data of Example 3 is shown in Table 7.

[0138] Table 7 Node System Load Data Information at 24 Hours

[0139]

[0140] Table 8. 24-hour energy trading prices for the 4-node system

[0141]

[0142] Table 9. 24-hour transaction volume information for the 4-node system

[0143]

[0144] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system, characterized in that, Includes the following steps: 1) Establish an EH operating cost model in the regional integrated energy system, including: the current production cost, electricity trading cost, heat trading cost, and carbon emission cost of the EH; 2) Establish an operating status model for the EH gas-fired boiler and gas turbine in the regional integrated energy system; 3) Establish EH carbon emission constraints, carbon quota constraints, carbon balance constraints, and electric energy storage and thermal energy storage constraints models in regional integrated energy systems; 4) Establish an EH supply and demand balance constraint model and energy transmission constraints in the regional integrated energy system; 5) Construct a model of the overall operating cost of the entire district heating system, and design a coordinated distributed trading method for electricity, carbon, and heat using the ADMM algorithm; In step 5), a model of the overall operating cost of the entire district heating system is constructed. The transaction decision-making stage of the electricity-carbon-heat coupled collaborative trading method is designed using the ADMM algorithm, including the following steps: First, the operating cost of the entire regional integrated energy system is modeled, and the objective function for the modeling is as follows: in Represents the total operating cost within the park. It is EH i At any moment t Electricity trading prices It is EH j At any moment t Electricity trading prices Representing EH i At any moment t The price of heat energy trading Representing EH j The price of heat energy trading, Representing EH i At any moment t The price of carbon allowance sales transactions Representing EH j At any moment t The price of carbon allowances sold Representing EH i Neighbors connected to nearby power lines, Representing EH i Neighbors connected to nearby heating pipes, Representing EH i Neighbors nearby who trade carbon allowances; It is a decision variable. It is the production cost of the gas turbine GT. For the production cost of gas-fired boilers GB, For the cost of BES for energy storage, For carbon emissions and The cost of thermal energy storage TES; The cost of purchasing electricity from the main grid Revenue from selling electricity to the main grid; This represents the collection of energy hubs (EH) within the park. Indicates the total timescale of operation within the park, Indicates time scale, Represents the moment t Purchase electricity from the mainnet Represents the moment t Electricity sold from the mainnet Represents the moment t The retail price of electricity purchased from the main grid. Represents the moment t The retail price of electricity sold from the main grid; The ADMM algorithm is used to design a distributed transaction method, as detailed below. In the k In each cycle, each EH calculates in parallel its required energy production, required energy trading, required carbon allowances, and required carbon allowances trading, following the update formula: In the formula, The set representing decision variables. Representative decision EH i Local constraints, Represents the cost function of an EH. Representative at k EH during the -1st cycle i Electricity prices Representative at k EH during the -1st cycle i Heat energy price Representative and EH i Neighbors connected by power lines Representative at k EH during the -1st cycle j The price of heat energy, in The penalty term will equal 0 after convergence, and its specific expression is: In the formula, Representing electricity trading in the k The price of the next iteration. It is the step size during the update. The selection, This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times t To EH i The total heat energy purchased, Representing EH i At any moment t Total carbon allowances sold, Representing EH i The neighbors at all times t To EH i The total carbon allowances purchased; Further, in step 5), a model of the overall operating cost of the entire district heating system is constructed. The price update stage of the electricity-carbon-heat coupled collaborative trading method is designed using the ADMM algorithm, including: In the k In each subsequent cycle, each EH will receive transaction requests from its neighbors and simultaneously update the current electricity price according to the following update formula. Heat price And carbon emission rights price : In the formula, Representing electricity trading in the k The price of the next iteration. This is the step size during the update. It's worth noting that... The choice of does not affect the convergence result. This represents the price of heat energy trading. The trading price representing carbon allowances. Representing EH i At any moment t Total electricity sold Representing EH i The neighbors at all times t To EH i The total amount of electricity purchased, This represents the losses incurred during the transaction process. Representing EH i At any moment t Total heat energy sold, Representing EH i The neighbors at all times t To EH i The total heat energy purchased, This represents the heat loss coefficient during the transaction process. Representing EH i At any moment t Total carbon quotas sold The above price update formula mimics price changes caused by market supply and demand. When EH i Current desired sales volume Greater than the total demand of the surrounding EH The price will then decrease; We can determine whether the algorithm has converged by defining the following metric: In the formula, This represents the terms inside the curly braces in the electricity price update formula. This represents the terms within the curly braces in the heat price update formula. This represents the term within curly braces in the carbon quota price update formula; After obtaining the current transaction status, the current heat network flow is obtained using the fourth-generation district heating system distributed heat network flow acquisition method, and the loss coefficient in the transaction process is updated according to the following method. and : In the formula, and This represents the loss caused during transmission. For EH i and EH j The volume of heat energy traded between them Indicates the rated node voltage in an active distribution network. Indicates the line resistance. EH i and EH j At any moment t Transaction volume; Step 5 is executed repeatedly using the updated loss coefficient, i.e., the electro-thermal-carbon coupled collaborative trading method that dynamically updates the loss parameters is executed until convergence and the trading result is obtained.

2. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, Step 1) The EH operating cost model includes: in Represents the operating cost of an energy hub (EH) within the park. It is EH i At any moment t Electricity trading prices It is EH j At any moment t Electricity trading prices Representing EH i At any moment t The price of heat energy trading Representing EH j The price of heat energy trading, Representing EH i At any moment t The price of carbon allowance sales transactions Representing EH j At any moment t The price of carbon allowances sold Representing EH i Neighbors connected to nearby power lines, Representing EH i Neighbors connected to nearby heating pipes, Representing EH i Neighbors nearby who trade carbon allowances It is the production cost of the gas turbine GT. For the production cost of gas-fired boilers GB, For the cost of BES for energy storage, and Costs of carbon emissions and thermal energy storage TES; The cost of purchasing electricity from the main grid Revenue from selling electricity to the main grid, of which Represents time scale, Represents the moment t Purchase electricity from the mainnet Represents the moment t Electricity sold from the mainnet Represents the moment t The retail price of electricity purchased from the main grid. Represents the moment t The retail price of electricity sold from the main grid. The costs incurred in trading carbon allowances, of which Representing EH i Neighbors nearby who trade carbon credits Represents the moment t EH j The price of carbon allowances sold Represents the moment t The trading volume of carbon allowances. The revenue from selling carbon emission rights, of which It is EH i At any moment t Electricity trading prices It is EH i At any moment t Carbon allowance sales volume The cost of purchasing electricity from surrounding producers and consumers, of which It is EH j At any moment t Electricity trading prices EH i At any moment t To EH j Purchased electrical energy, (This indicates the energy loss during the transaction process). Revenue from the sale of electricity, of which It is EH i Electricity trading prices EH i (total electricity sold). For the expenditure on purchasing heat energy, The revenue from selling heat energy, of which Represents the moment t EH i The price of heat energy trading, Represents the moment t EH i Total sales volume Represents the moment t Loss coefficient of heat energy trading Indicates at time t EH i To EH j Total heat output purchased; and These are the network access fees paid to distribution network operators and heating network operators, respectively. The decision variables for each EH include the electric and thermal output of the gas turbine, the thermal output of the gas boiler, the output of electric and thermal energy storage, carbon emission credits, the amount of electric heat purchased, the amount of carbon credits purchased, the amount of electric heat sold, and the amount of carbon credits sold. The specific expressions for the decision variables are as follows: in, Indicates the electric thermal output of the gas turbine, Indicates the heat output of the gas-fired boiler, and These represent the output power of electrical energy storage and thermal energy storage, respectively. , and These represent the purchase volume of electric heating and carbon quotas, respectively. , and These represent the sales volume of electric heating carbon.

3. The coordinated trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 2), the operational constraints on the gas turbine GT in the regional integrated energy system are as follows: in and It is a gas turbine in t The heat and electricity produced at all times It is the coupling ratio of electrical energy and thermal energy produced by a gas turbine during operation; It is the lowest operating point during the operation of a gas turbine. It is the highest operating point in the operation of a gas turbine. This indicates the maximum power reduction per hour of the gas turbine. This indicates the maximum power increase per hour of the gas turbine.

4. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 2), the operational constraints for the gas filter GB in the regional integrated energy system are as follows: In the formula, It is the lowest operating point during the operation of a gas turbine. It is the highest operating point in the operation of a gas turbine. Indicates the time of the gas boiler t Thermal energy output.

5. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 2), the electrical / thermal energy balance constraints of the regional integrated energy system are modeled: In the formula, and It is a gas turbine in t The heat and electricity produced at all times Is t Time EH i Electricity purchased from the mainnet, It is EH i exist t The electrical energy purchased from the adjacent EH at all times, of which Representing EH i Neighbors connected to nearby power lines, EH i At any moment t To EH j Purchased electricity; It is EH i exist t The output of the battery pack at all times. It is EH i exist t The amount of electricity sold to the main network at any time It is EH i exist t The electrical energy sold to the adjacent EH at all times For EH i exist t The power demand at any time It is the heat generated by the gas turbine. It is the heat output of the gas-fired boiler. It is EH i exist t Constantly purchasing heat energy from the surrounding area Representing EH i The neighbors whose power lines are connected nearby, Indicates at time t EH i To EH j Purchased heat energy; It is EH i exist t The output of thermal energy storage at all times, It is EH i exist t The heat energy sold to the adjacent EH at all times. For EH i exist t The constant demand for thermal energy.

6. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 3), carbon quota constraints in the regional integrated energy system are modeled: In the formula, This represents the amount of new energy used. Carbon allowances obtained through the use of new energy sources. The carbon emissions caused by using each unit of energy in the power distribution network. To reduce carbon emissions from the use of gas-fired boilers, Carbon allowances generated during natural gas combustion To reduce carbon emissions from the use of gas turbines, and The gas turbine and gas boiler are respectively EH i exist t The electrical energy output at any given moment.

7. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 3), carbon balance constraints are modeled in the regional integrated energy system. In the formula, Energy Hub EH i exist t Carbon emission allowances at any time For EH i exist t The total amount of carbon allowances purchased from neighboring EHs at any given time. Representing EH i Neighbors connected to nearby heating pipes, The representative is EH i exist t Always towards EH j The amount of carbon credits purchased. For EH i exist t Carbon allowances sold to neighboring EHs at any given time Carbon emissions generated from the use of new energy sources (negative values ​​indicate carbon allowances obtained). Carbon emissions from using gas-fired boilers Carbon emissions generated from the use of gas turbines.

8. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 3), the energy storage constraints of the regional integrated energy system are modeled: In the formula, It is EH i exist t The power output of the battery pack at all times. It is EH i exist t The discharge energy of the battery pack at all times. It is EH i exist t The charging energy of the battery pack at all times; This is the maximum charging and discharging power of the battery pack; This is the minimum limit for the state of charge of the battery pack. This is the maximum limitation on the charging state of the battery pack; Is it the battery? t The charging state at time =0. This refers to the battery's initial state of charge. Represents battery pack i At any moment t Charging status, Indicates battery pack i Battery life Indicates the charging efficiency of the battery pack, Indicates the battery pack at time t The charging power, Indicates the discharge efficiency of the battery pack, Indicates time scale, Indicates the charging status at the end of the day. Indicates the charging status at the start of the day; Modeling the thermal energy storage constraints in a regional integrated energy system: It is EH i exist t The thermal output of the battery pack at all times It is EH i exist t The thermal energy storage unit releases heat energy at all times. It is EH i exist t The heat energy absorbed by the thermal power unit at all times; This is the maximum charging and discharging power of the battery pack; This is the minimum limit for the state of charge of the battery pack. This is the maximum limitation on the charging state of the battery pack; Is it the battery? t The charging state at time =0. This refers to the battery's initial state of charge. Indicates the status of the thermal energy storage unit, This indicates the working status of the thermal energy storage unit at the end of the day; Modeling energy transmission constraints in a regional integrated energy system: In the formula, Representing EH i exist t The electricity purchased from the main network at all times It is EH i exist t The electrical energy constantly sold to the main network It is EH i exist t Always towards EH j Purchased electrical energy It is the maximum power transmitted in the transmission line. Yes, it's EH. i exist t Always towards EH j Purchased thermal energy It is the maximum heat transfer power in the transmission line. Indicates the maximum power transfer volume in transactions with the mainnet. Indicates EH i Neighbors connected by power lines Indicates EH i Neighbors connected by heating pipes.

9. The collaborative trading method for electricity-heat-carbon coupling in a regional integrated energy system according to claim 1, characterized in that, In step 4), the supply and demand balance constraints of the regional integrated energy system are modeled: In the formula, Representing EH i exist t The total amount of electricity sold at any given time Representing EH j exist t Always towards EH i Purchased electricity Indicates EH i Neighbors connected by power lines This represents the point loss incurred between transactions. Representing EH i exist t The total amount of heat energy sold at any given time The heat loss coefficient between transactions, Representing EH j exist t Always towards EH i Purchased heat energy, Indicates EH i Neighbors connected by heating pipes It is EH i exist t The total amount of carbon allowances available for sale at any given time. It is EH i exist t EH always j The total amount of carbon allowances sold, EH i exist t Time EH j Electricity sold.

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