Operation control methods, devices and media for generator sets in the carbon trading market

Abstract

This application relates to a method, apparatus, computer equipment, storage medium, and computer program product for the operation control of generator sets in an electricity carbon trading market. The method includes: obtaining the operating costs of generator sets in the electricity carbon trading market; the operating costs of generator sets are obtained based on the unit price and unit carbon emission cost; combining market clearing boundary conditions and constraints on the safety-constrained unit combination, optimizing the safety-constrained unit combination model and the safety-constrained economic dispatch model with the optimization objective of minimizing the generator set start-up cost and operating cost, to obtain the market clearing result; based on the market clearing result and various cost-benefit factors on the generation side, obtaining the total benefit on the generation side; and adjusting the operation mode of the generator sets on the generation side according to the total benefit on the generation side. This method can improve the accuracy of the assessment of the total benefit on the generation side.

Description

Technical Field

[0001] This application relates to the field of power grid technology, and in particular to an operation control method, apparatus, computer equipment, computer-readable storage medium, and computer program product for generator sets in an electricity carbon trading market. Background Technology

[0002] Generally, cost-benefit studies on the generation side help to understand the profitability and trading intentions of various market participants, thereby guiding the market to formulate more reasonable trading mechanisms. Currently, cost-benefit assessment methods for the generation side can include those based on spot electricity market transactions and those based on carbon emission trading (CET) markets.

[0003] However, the accuracy of the cost-benefit assessment method described above is low in obtaining the total benefits on the power generation side. Summary of the Invention

[0004] Therefore, it is necessary to provide an operation control method, device, computer equipment, computer-readable storage medium, and computer program product for generator sets in an electricity carbon trading market that can improve the accuracy of the assessment of the overall benefits on the power generation side, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides an operation control method for generating units under an electricity carbon trading market. The method includes:

[0006] The operating costs of generator sets under the carbon trading market are obtained; the operating costs of generator sets are obtained based on the unit price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply of the unit.

[0007] Combining market clearing boundary conditions and safety-constrained unit combination constraints, with the optimization objective of minimizing the start-up cost and operating cost of the generator units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result.

[0008] Based on the market clearing results and the various cost-benefit factors on the power generation side, the total benefit on the power generation side is obtained; the various cost-benefit factors on the power generation side include: day-ahead market settlement revenue on the power generation side, real-time market settlement revenue on the power generation side, revenue from medium- and long-term contract trading on the power generation side, benefits from the power generation side's participation in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs on the power generation side.

[0009] The operating mode of the generator set on the power generation side is adjusted according to the overall benefits of the power generation side.

[0010] In one embodiment, the operating cost of the generator set is the sum of the first multipliers for each stage; the first multiplier for each stage is the product of the unit's bid for the mth segment in time period t and the winning bid for the electricity in the mth output range of the unit in time period t; the unit's bid for the mth segment in time period t is the sum of the energy price corresponding to the mth output range declared by the unit and the unit's unit carbon emission cost in time period t; the energy price corresponding to the mth output range declared by the unit is the unit's bid.

[0011] In one embodiment, the unit carbon emission cost of the unit in time period t is: the ratio of the second multiplier to the first sum; the first sum is the sum of the maximum output of the unit in each stage; the second multiplier is the product of the second sum minus the first value and the carbon emission pricing of the unit in time period t; the second sum is the sum of the third multipliers of each stage; the third multiplier of each stage is the product of the carbon emission intensity coefficient corresponding to the unit and the maximum output of unit i; the first value is the product of the proportion of free allowances and the total carbon emission allowance of the unit; the total carbon emission allowance of the unit is the sum of the carbon allowance for power supply and the carbon allowance for heating.

[0012] In one embodiment, the total benefit on the power generation side is the difference between the sum of the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract transactions, and the benefit from the power generation side's participation in demand response, and a third sum; the third sum is the sum of the power generation cost and carbon emission trading cost and the market deviation assessment cost on the power generation side.

[0013] In one embodiment, the market clearing result includes the day-ahead marginal electricity price and the real-time marginal electricity price. The day-ahead market settlement revenue of the generation side is the sum of the fourth multipliers of each stage. The fourth multiplier of each stage is the product of the generation side's demand for electricity in the day-ahead market at time t and the generation side's contracted electricity in the medium- and long-term market at time t, multiplied by the day-ahead marginal electricity price of the node where the generation side is located at time t. The real-time market settlement revenue of the generation side is the sum of the tenth multipliers of each stage. The tenth multiplier of each stage is the product of the generation side's real-time market grid connection electricity and the generation side's demand for electricity in the day-ahead market at time t, multiplied by the real-time marginal electricity price of the node where the generation side is located at time t. The benefit of the generation side participating in demand response is the difference between the reduced unit investment cost and the reduced generation revenue of the generation side participating in demand response. The reduced unit investment cost is the sum of the fifth multipliers of each stage, where the fifth multiplier is the product of the unit investment cost per unit of generation and the unit investment capacity avoided by participating in demand response in time period t. The reduced generation revenue is the sum of the sixth multipliers of each stage, where the sixth multiplier is the product of the difference between the real-time node marginal price at the node where the generation side is located in time period t and the generation cost of the unit in time period t, and the change before and after participating in demand response in time period t.

[0014] In one embodiment, the power generation cost and carbon emission trading cost are: the sum of the seventh multipliers of each stage, where the seventh multiplier of each stage is the product of the power generation cost of the unit in time period t and the output of the unit in time period t; the market clearing result includes the day-ahead marginal electricity price; the power generation side market deviation assessment cost is the sum of the eighth multipliers of each stage; the eighth multiplier of each stage is the product of the second value and the third value of each stage; the second value of each stage is the maximum value between 0 and the first difference of each stage, where the first difference is the difference between the declared response capacity and the response ratio threshold of the power generation side in time period t and the actual response capacity of the power generation side in time period t; the third value of each stage is the maximum value between the ninth multiplier of each stage and the lower limit of the assessment price, where the ninth multiplier of each stage is the product of the day-ahead marginal electricity price of the node where the power generation side is located in time period t and the penalty factor.

[0015] In one embodiment, the constraints of the safety-constrained unit combination include system constraints, unit constraints, and network constraints; the system constraints include system load balance constraints, system positive and negative reserve capacity constraints, and system spinning reserve constraints; the unit constraints include unit output upper and lower limit constraints, unit ramping constraints, unit minimum continuous start-stop time constraints, and unit maximum start-stop frequency constraints; and the network constraints include line power flow constraints.

[0016] Secondly, this application also provides an operation control device for generator sets in an electricity carbon trading market. The device includes:

[0017] The acquisition module is used to acquire the operating costs of generator sets under the electricity carbon trading market; the operating costs of the generator sets are obtained based on the unit price and the unit carbon emission cost, and the unit carbon emission cost is related to the carbon quota for heating and the carbon quota for power supply of the unit.

[0018] The result determination module is used to combine the market clearing boundary conditions and the constraints of the safety-constrained unit combination, with the optimization objective of minimizing the start-up cost and operating cost of the generator sets, to optimize the safety-constrained unit combination model and the safety-constrained economic dispatch model, and obtain the market clearing result.

[0019] The benefit determination module is used to obtain the total benefit of the power generation side based on the market clearing results and various cost-benefit factors of the power generation side. The various cost-benefit factors of the power generation side include: day-ahead market settlement revenue of the power generation side, real-time market settlement revenue of the power generation side, revenue from medium- and long-term contract trading of the power generation side, benefits of the power generation side participating in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs of the power generation side.

[0020] The control module is used to adjust the operating mode of the generator set on the power generation side according to the total benefits on the power generation side.

[0021] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0022] The operating costs of generator sets under the carbon trading market are obtained; the operating costs of generator sets are obtained based on the unit price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply of the unit.

[0023] Combining market clearing boundary conditions and safety-constrained unit combination constraints, with the optimization objective of minimizing the start-up cost and operating cost of the generator units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result.

[0024] Based on the market clearing results and the various cost-benefit factors on the power generation side, the total benefit on the power generation side is obtained; the various cost-benefit factors on the power generation side include: day-ahead market settlement revenue on the power generation side, real-time market settlement revenue on the power generation side, revenue from medium- and long-term contract trading on the power generation side, benefits from the power generation side's participation in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs on the power generation side.

[0025] The operating mode of the generator set on the power generation side is adjusted according to the overall benefits of the power generation side.

[0026] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0027] The operating costs of generator sets under the carbon trading market are obtained; the operating costs of generator sets are obtained based on the unit price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply of the unit.

[0028] Combining market clearing boundary conditions and safety-constrained unit combination constraints, with the optimization objective of minimizing the start-up cost and operating cost of the generator units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result.

[0029] Based on the market clearing results and the various cost-benefit factors on the power generation side, the total benefit on the power generation side is obtained; the various cost-benefit factors on the power generation side include: day-ahead market settlement revenue on the power generation side, real-time market settlement revenue on the power generation side, revenue from medium- and long-term contract trading on the power generation side, benefits from the power generation side's participation in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs on the power generation side.

[0030] The operating mode of the generator set on the power generation side is adjusted according to the overall benefits of the power generation side.

[0031] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0032] The operating costs of generator sets under the carbon trading market are obtained; the operating costs of generator sets are obtained based on the unit price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply of the unit.

[0033] Combining market clearing boundary conditions and safety-constrained unit combination constraints, with the optimization objective of minimizing the start-up cost and operating cost of the generator units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result.

[0034] Based on the market clearing results and the various cost-benefit factors on the power generation side, the total benefit on the power generation side is obtained; the various cost-benefit factors on the power generation side include: day-ahead market settlement revenue on the power generation side, real-time market settlement revenue on the power generation side, revenue from medium- and long-term contract trading on the power generation side, benefits from the power generation side's participation in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs on the power generation side.

[0035] The operating mode of the generator set on the power generation side is adjusted according to the overall benefits of the power generation side.

[0036] The aforementioned operation and control methods, devices, computer equipment, storage media, and computer program products for generator units in the electricity carbon trading market obtain the unit carbon emission cost through the carbon quotas for heating and power generation. Then, based on the unit carbon emission cost, the operating costs of the generator units in the electricity carbon trading market are obtained. Thus, combining market clearing boundary conditions and constraints on the safety-constrained unit combination, with the optimization objective of minimizing the generator unit start-up and operating costs, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result. Based on the market clearing result... By considering the various costs and benefits on the generation side, the total benefit on the generation side is obtained. Since the total benefit on the generation side includes the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract trading, the benefits of the generation side participating in demand response, the generation cost and carbon emission trading cost, and the market deviation assessment cost on the generation side, the process of obtaining the total benefit on the generation side takes into account the impact of carbon emission trading and the implementation of demand response on the generation side's benefits. This is consistent with the current actual operation and trading situation of the electricity-carbon market integration that takes into account demand response products. Therefore, it can improve the accuracy of the assessment of the total benefit on the generation side. Attached Figure Description

[0037] Figure 1 This is an application environment diagram of an operation control method for generator sets under an electricity carbon trading market in one embodiment.

[0038] Figure 2 This is a flowchart illustrating an operation control method for generator sets under an electricity carbon trading market in one embodiment.

[0039] Figure 3 This is a schematic diagram of a market clearing model in one embodiment;

[0040] Figure 4This is a structural block diagram of a cost-benefit quantification analysis model in one embodiment;

[0041] Figure 5 This is a schematic diagram of load and demand response power consumption in an application example.

[0042] Figure 6 This is a diagram showing a comparison of the day-ahead electricity market clearing price considering the impact of the carbon trading market, the day-ahead electricity market clearing price considering the impact of the carbon trading market and improved carbon pricing, and the clearing price not considering the impact of the carbon trading market in an application example.

[0043] Figure 7 This is a diagram showing a comparison between the day-ahead electricity market clearing price and the real-time electricity market clearing price after implementing demand response, taking into account the impact of the carbon trading market and improved carbon pricing in an application example.

[0044] Figure 8 This is a schematic diagram illustrating the settlement results of day-ahead market settlement revenue at various time periods in an application example.

[0045] Figure 9 This is a schematic diagram illustrating the settlement results of real-time market settlement revenue at various time periods in an application example.

[0046] Figure 10 This is a schematic diagram illustrating the settlement results of medium- and long-term market settlement returns at various time periods in an application example.

[0047] Figure 11 This is a schematic diagram illustrating the settlement results of demand response benefits at different time periods in an application example.

[0048] Figure 12 This is a schematic diagram illustrating the settlement results of power generation costs and carbon emission quota trading costs at various time periods in an application example.

[0049] Figure 13 This is a schematic diagram illustrating the settlement results of market deviation assessment costs at different time periods in an application example.

[0050] Figure 14 This is a schematic diagram illustrating the total revenue of the power generation side on a specific operating day in an application example.

[0051] Figure 15 This is a structural block diagram of the operation control device for a generator set in an electricity carbon trading market, as shown in one embodiment.

[0052] Figure 16 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] Generally, cost-benefit studies on the generation side help to understand the benefits and trading intentions of various market participants, thereby guiding the market to formulate more reasonable trading mechanisms. Currently, cost-benefit assessment methods for the generation side can include cost-benefit assessment methods based on spot electricity market transactions and cost-benefit assessment methods based on the CET market.

[0055] However, with the development of the carbon trading market and the electricity market, the existing cost-benefit assessment models for the generation side do not simultaneously consider the costs and benefits of generating units under both carbon trading prices and electricity market trading prices. This is not conducive to accurately assessing the total benefits of the generation side participating in the electricity carbon market. Moreover, demand response projects in the spot market and carbon emission rights trading in the CET market will affect the cost-benefit models of generating units. Existing technologies do not comprehensively consider the impact of carbon emission rights trading and the implementation of demand response on the benefits of the generation side. This does not conform to the actual operation and trading situation of the current electricity carbon market integration that takes demand response products into account. As a result, the accuracy of the assessment of the total benefits of the generation side is low, which in turn makes it impossible to effectively guide the trading strategies and operating models of generating units.

[0056] In view of this, this application provides an operation control method for generator sets under an electricity carbon trading market. The method of this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets. The data storage system can store the data that server 104 needs to process. The data storage system can be integrated on server 104 or placed on the cloud or other network servers.

[0057] Specifically, after obtaining the unit carbon emission cost based on the carbon quota for heating and the carbon quota for power generation, terminal 102 can send the unit carbon emission cost to server 104. This allows server 104 to obtain the operating costs of generator units in the electricity carbon trading market based on the unit price and the unit carbon emission cost. Thus, server 104, based on the operating costs of generator units in the electricity carbon trading market, combined with market clearing boundary conditions and constraints on the safety-constrained unit combination, optimizes the safety-constrained unit combination model and the safety-constrained economic dispatch model with the goal of minimizing the generator unit start-up and operating costs. This yields the market clearing result. Based on the market clearing result and the various cost-benefit factors on the generation side, the total benefit on the generation side can be obtained. Furthermore, the operating mode of the generator units on the generation side can be adjusted based on the total benefit on the generation side.

[0058] Understandably, terminal 102 can also obtain the unit carbon emission cost based on the carbon quota for heating and the carbon quota for power generation, and after obtaining the operating cost of the generator set under the electricity carbon trading market based on the unit price and the unit carbon emission cost, it can send the operating cost of the generator set under the electricity carbon trading market to server 104, so that server 104 can carry out the subsequent execution process.

[0059] It should be noted that, in order to analyze the impact of CET market operations on the day-ahead electricity market clearing, this application considers the coupled interaction between the CET market and the day-ahead electricity market, incorporating carbon trading costs into the unit bids in the market clearing model to combine the trading mechanisms of the two markets and reflect the coupled impact of the CET market. The trading mechanism between the CET market and the day-ahead electricity market can be summarized as follows: In the day-ahead electricity market, each generating unit provides bidding information to the electricity trading center daily. Coal-fired and gas-fired units trade carbon emission allowances on the primary carbon emission market quarterly. In the CET market, coal-fired and gas-fired units can profit by trading their remaining carbon emission allowances. Conversely, when a unit's carbon emissions exceed its allocated free allowances, the unit needs to pay additional carbon emission costs, thus increasing its power generation costs. Therefore, before bidding in the day-ahead electricity market, coal-fired and gas-fired units assess the carbon emission costs they need to pay based on the carbon emission allowances allocated by the government. It can be seen that the CET market has a unilateral impact on the day-ahead electricity market.

[0060] Currently, in existing technologies, the time scale for allocating carbon emission allowances to various industries can be set to an annual scale. In this application, in order to study the impact of the CET market on the spot market, the time scale for carbon emission allowance allocation is modified to a day, month, minute, or second, etc. For example, if 15 minutes is used as a scale to calculate one day, then t is 1 to 96; if 1 hour is used as a scale to calculate three days, then t is 1 to 72. For ease of description, the formulas described below will use t as an example of 1 to 24.

[0061] In one embodiment, such as Figure 2 As shown, an operation control method for generator sets under an electricity carbon trading market is provided, which can be applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0062] S202, Obtain the operating costs of generator sets under the electricity carbon trading market.

[0063] In this embodiment, the operating cost of the generator set is obtained based on the unit's bid price and the unit carbon emission cost. The unit carbon emission cost is related to the carbon quota for heating and the carbon quota for power generation. Specifically, the operating cost of the generator set is the sum of the first multipliers of each stage. The first multiplier of each stage is the product of the unit's bid price in the mth segment of time period t and the winning bid for the unit's power in the mth output interval of time period t.

[0064] In this embodiment, the unit i's price for the m-th segment in time period t is obtained by "the generation side submits a price quote and the load side submits a price quote but does not quote". When the operation of the CET market is not considered, the price quote of unit i is an incremental tiered electricity price. However, due to the addition of the CET market, the total generation cost of unit i will change due to the operation of the CET market. Therefore, each unit will adjust its price quote in the spot market based on the unit carbon emission cost paid. Therefore, after considering the impact of the CET market operation, the unit's price quote for the m-th segment in time period t is: the sum of the energy price corresponding to the m-th output range declared by the unit and the unit's unit carbon emission cost in time period t; the energy price corresponding to the m-th output range declared by the unit is the unit's price quote.

[0065] For example, C i，t，m P represents the quote from unit i in the m-th segment of time period t. i，t，m This represents the winning bid power of unit i in the m-th output interval during time period t, where C represents the power awarded to unit i in different values ​​of m. i，t，m This corresponds to the price quoted by unit i in the m-th segment of time period t for each stage, P. i，t，mThis corresponds to the winning bid power of unit i in the m-th output interval of time period t in each stage. Based on the bid price of unit i in the m-th segment of time period t in each stage and the winning bid power of unit i in the m-th output interval of time period t in each stage, the first multiplier value of each stage can be obtained. The first multiplier value of each stage satisfies the following formula: First multiplier value = C i，t，m ×P i，t，m .

[0066] Furthermore, summing the first multipliers of each stage yields the operating cost of generator set i. For example, if C i，t (P i，t Let C represent the operating cost of generator set i, and NM be the total number of segments in the generator set quotation. i，t (P i，t It satisfies the following formula:

[0067] Wherein, the price quoted by unit i in the m-th segment of time period t is the sum of the energy price corresponding to the m-th output interval declared by unit i and the unit carbon emission cost of unit i in time period t. For example, if C i，t，m C represents the price quoted by unit i in the m-th segment of time period t at each stage. i，m This represents the energy price corresponding to the m-th output range declared by unit i, Carbon i，t Let C represent the unit carbon emission cost of unit i during time period t. i，t，m Satisfy the following formula: C i，t，m =C i，m +Carbon i，t .

[0068] Wherein, the unit carbon emission cost of unit i in time period t is the ratio of the second multiplier to the first sum, the first sum is the sum of the maximum output of the unit in each stage, the second multiplier is the product of the second sum and the first value, and the carbon emission pricing of the unit in time period t, the second sum is the sum of the third multipliers of each stage, the third multiplier of each stage is the product of the carbon emission intensity coefficient corresponding to the unit and the maximum output of unit i, the first value is the product of the proportion of free allowances and the total carbon emission allowance of the unit, and the total carbon emission allowance of the unit is the sum of the carbon allowance for power supply and the carbon allowance for heating.

[0069] For example, if E q，i E represents the total carbon emission allowance for unit i. e，i E represents the carbon quota for the power supplied by unit i. h，i The carbon quota for heating supplied by unit i can be obtained using the baseline method, E. q，i E q，i Satisfy the following formula: E q，i =E e，i +Eh，i If η represents the proportion of quotas distributed free of charge, then the first value satisfies the following formula: First value = η × E q，i If β i P represents the carbon emission intensity coefficient corresponding to unit i. i，max If the maximum output of unit i is represented by β, then the third multiplier satisfies the following formula: Third multiplier = β i ×P i，max Then the second sum satisfies the following formula: If P re，i，t Let represent the carbon emission pricing of unit i during time period t. Then the second multiplier satisfies the following formula: If Carbon i，t P represents the unit carbon emission cost of unit i during time period t. i，max If the maximum output of unit i is represented by Carbon, then Carbon i，t Satisfy the following formula:

[0070]

[0071] Currently, under the CET market mechanism, if the carbon emissions generated by unit i exceed its allocated free allowances, the unit needs to pay the corresponding carbon emission costs. Typically, in the CET market mechanism, the unit's unit carbon emission cost is based on a fixed carbon emission price. However, in the current carbon trading market, carbon emission prices are dynamic, primarily depending on market supply and demand and government macro-control. For day-ahead electricity market operating days, the carbon emission price for the following day is unavailable, hindering the clearing of day-ahead units considering the carbon trading market. A fixed carbon emission price... Furthermore, the market cannot differentiate between different trading prices for different generating units. Moreover, in the trading market, companies with surplus carbon emission allowances will inevitably put them on the carbon emission market for trading. As demand response develops, some peak loads are reduced, and market competition intensifies. This makes the profits for power generation companies trading carbon emission allowances increasingly smaller. Companies tend to focus on meeting the carbon emission targets set by the government, leading to companies ceasing to invest in low-carbon technologies and reducing their enthusiasm for carbon emission trading. Ultimately, this reduces the supply in the carbon trading market, causing carbon emission prices to rise again, which contradicts the concept of low-carbon emission reduction.

[0072] Therefore, to address the issue of reduced corporate enthusiasm for low-carbon investment under this demand-response environment and to provide more accurate data support for subsequent cost-benefit analysis on the power generation side, this application proposes a carbon emission pricing mechanism based on dynamic changes in trading volume. Specifically, the carbon emission pricing of unit i in time period t is the ratio of the carbon emission cost of unit i in time period t to the amount of carbon emission allowances the company needs to purchase in time period t. For example, if P... re，i，t C represents the carbon emission pricing of unit i during time period t. i，t (ΔPi，t ) represents the carbon emission cost of unit i during time period t, ΔP i，t Let P represent the amount of carbon emission allowances that the company needs to purchase during period t. re，i，t Satisfy the following formula: C i，t (ΔP i，t ) = a i ×(ΔP i，t ) 2 +b i ×ΔP i，t +c i Then P re，i，t This can be further expressed as:

[0073]

[0074] Among them, a i b i and c i This represents the fuel cost coefficient for unit i.

[0075] Among the possible methods, the carbon allowance E for unit i's power supply e，i For example, E is the product of the power supply of unit i, the power supply base value of the category to which unit i belongs, the correction factor for the cooling method of unit i, the correction factor for the heat supply of unit i, and the correction factor for the output of unit i. e，i P represents the carbon quota for the power supply of unit i. e，i B represents the power supply of unit i. e，i F represents the power supply reference value for the category to which unit i belongs. l，i F represents the correction factor for the cooling method of unit i. r，i F represents the heat supply correction factor for unit i. f，i Let E represent the output correction factor for unit i. e，i Satisfy the following formula: E e，i =P e，i ×B e，i ×F l，i ×F r，i ×F f，i .

[0076] Among them, the power supply of unit i P e，i The unit is megawatt-hour (MWh). The larger the power supply of the unit, the more quota it will receive. In order to obtain more quota, the unit needs to reduce the power loss of the plant or improve the efficiency of the generator to increase the power supply under the same power generation.

[0077] Table 1 provides carbon emission baseline values ​​for each type of generating unit. Based on Table 1, the power supply baseline value B corresponding to different generating unit categories can be determined. e，i(t / MWh), which is then used to obtain the carbon allowance for the unit's power supply.

[0078] Table 1

[0079]

[0080] The unit cooling method can refer to the condenser cooling method, such as water cooling and air cooling. Specifically, when the condenser cooling method is water cooling, the unit cooling method correction factor is 1; when the condenser cooling method is air cooling, the unit cooling method correction factor is 1.05. According to the carbon quota formula for the unit's power supply, air-cooled units will increase the unit's power supply carbon quota by 5% compared to water-cooled units. However, the specific back pressure difference between air-cooled and water-cooled units is not explained in detail. Therefore, air-cooled units can take into account factors such as plant power consumption rate and investment to minimize the unit back pressure and plant power consumption rate in order to achieve lower actual carbon emissions.

[0081] Among them, the heat supply correction factor F of unit i r，i Satisfy the following formula: F r，i =1-0.22×K r，i K r，i Let K be the heat supply ratio of unit i, when K r，i When the value is 0, it is a pure condensing unit. For heating units, the greater the heat output, the smaller the power output, and the corresponding carbon quota for the power supply part also decreases, but the carbon quota for the heating part will increase accordingly.

[0082] Among them, the output correction factor F of unit i f，i (%) The unit category is distinguished solely by whether it is pure condensing or non-pure condensing. Typically, for non-pure condensing units, F f，i =1. The correction factor for coal-fired condensing generator units is shown in Table 2. Based on Table 2, the corresponding correction factor F can be determined by combining the unit load factor F during the statistical period. f，i This information is then used to obtain the carbon quota for the unit's power supply.

[0083] Table 2

[0084]

[0085] In one possible approach, the carbon allowance for unit heating is the product of the unit's heating capacity and the base heating value for the unit's category. For example, if E h，i Q represents the carbon quota for heating provided by unit i. h，i Indicates the heat supplied by unit i, B h，i E represents the heating baseline value for the category to which unit i belongs. h，i Satisfy the following formula: E h，i =Q h，i ×B h，i .

[0086] The heating capacity of the unit is directly proportional to the total heating quota of the unit. The type of unit can include coal-fired units and gas-fired units. Specifically, the heating benchmark value of coal-fired units can be 0.135 t / GJ, and the heating benchmark value of coal-fired units can be 0.059 t / GJ.

[0087] S204 combines the market clearing boundary conditions and the constraints of the safety-constrained unit combination, and optimizes the safety-constrained unit combination model and the safety-constrained economic dispatch model with the goal of minimizing the start-up cost and operating cost of the generator units, to obtain the market clearing result.

[0088] In this embodiment, by comprehensively considering factors such as load forecasting of the central dispatch, bus load forecasting, generator maintenance plan, transmission and transformation equipment maintenance plan, generator operation constraints, and power grid safety operation constraints, and optimizing the market clearing model with the goal of minimizing the total electricity purchase cost, i.e., minimizing the generator start-up cost and generator operation cost, the spot market clearing result can be obtained. The market clearing model includes the Security-Constrained Unit Commitment (SCUC) model and the Security-Constrained Economic Dispatch (SCED) model.

[0089] The factors considered above can be collectively referred to as the constraints of the safety-constrained unit combination. These constraints can be summarized as system constraints, unit constraints, and network constraints. Specifically, system constraints may include system load balance constraints, system positive and negative reserve capacity constraints, and system spinning reserve constraints. Unit constraints may include upper and lower limits of unit output constraints, unit ramping constraints, minimum continuous start-stop time constraints, and maximum number of start-stop cycles constraints. Network constraints may include line power flow constraints. Market clearing boundary conditions may include load forecast curves, tie-line power plans, grid topology, unit operating characteristic parameters, node branch parameters, and unit bids considering the CET market.

[0090] It is understood that the specific content of the constraints on the combination of safety-constrained units and the market clearing boundary conditions can be set according to the actual application scenario, and this embodiment does not limit them.

[0091] Specifically, by combining the market clearing boundary conditions, the start-up cost and operating cost of the generator set can be input into the SCUC model, so that the SCUC model obtains the generator set start-up combination under the constraints of the safety-constrained generator set combination. Inputting the generator set start-up combination into the SCED model can yield the market clearing result.

[0092] like Figure 3 The diagram illustrates a market clearing model. It incorporates load forecast curves, tie-line power plans, grid topology, generator operating characteristic parameters, node branch parameters, and generator bids from the CET market. The starting and operating costs of generator units are input into the market clearing model. Specifically, these costs are input into the SCUC model. Under the constraint of safe-constrained generator unit combinations, optimization of the SCUC model yields the generator unit start-up combinations. These combinations are then input into the SCED model. Optimization of the SCED model yields the Lagrange multipliers for system load balance constraints. Based on these Lagrange multipliers, nodal marginal electricity prices can be calculated, resulting in spot electricity prices, generator bidding outcomes, and carbon emissions. The market clearing results include spot electricity prices, generator bidding outcomes, and carbon emissions. Specifically, the spot electricity price includes day-ahead nodal marginal electricity prices and real-time nodal marginal electricity prices.

[0093] S206, based on the market clearing results and various cost-benefit analysis on the generation side, yields the total benefit on the generation side; the various cost-benefit analysis on the generation side includes: day-ahead market settlement revenue on the generation side, real-time market settlement revenue on the generation side, revenue from medium- and long-term contract trading on the generation side, benefits from the generation side's participation in demand response, generation costs and carbon emission trading costs, and market deviation assessment costs on the generation side.

[0094] In this embodiment, a cost-benefit quantitative analysis model can be constructed based on various cost-benefit factors on the power generation side, such as... Figure 4 As shown, a structural block diagram of a cost-benefit quantitative analysis model is provided. After inputting the market clearing results into the cost-benefit quantitative analysis model, the total benefit on the power generation side can be obtained. Based on the total benefit on the power generation side, the benefit situation and trading intentions of each market participant can be understood, thereby guiding the market to formulate a more reasonable trading mechanism.

[0095] Specifically, the total benefit on the generation side is the difference between the sum of the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract trading, and the benefit from the generation side's participation in demand response, and a third sum; the third sum is the sum of generation costs and carbon emission rights trading costs and the aforementioned market deviation assessment costs on the generation side; for example, if G represents the total benefit on the generation side, B... c B represents the day-ahead market settlement revenue on the generation side. r B represents the real-time market settlement revenue on the generation side. LCfD B represents the revenue from medium- to long-term contract transactions on the power generation side. DR C represents the benefits of the generation side participating in demand response. g C represents the cost of electricity generation and the cost of carbon emission trading.ch If the third sum represents the market deviation assessment cost on the generation side, then the third sum satisfies the following formula: Third sum = C g +C ch Then G satisfies the following formula:

[0096] G = B c +B r +B LCfD +B DR -C g -C ch ;

[0097] The market clearing result includes the day-ahead marginal electricity price. Specifically, the day-ahead market settlement revenue for the generation side is the sum of the fourth multipliers for each stage. The fourth multiplier for each stage is the product of the generation side's demand for electricity in the day-ahead market at time t and the generation side's contracted electricity in the medium-to-long-term market at time t, multiplied by the day-ahead marginal electricity price at the generation side's node at time t. For example, if P Gc，t Q represents the day-ahead marginal electricity price at node t on the generation side. Gc，t Q represents the day-ahead market demand for electricity during time period t on the generation side. GL，t Let Q represent the contracted electricity volume of the power generation side in the medium-to-long-term market during period t. Then, the fourth multiplier satisfies the following formula: Fourth multiplier = (Q Gc，t -Q GL，t )×P Gc，t When t is different, if B c B represents the day-ahead market settlement revenue on the generation side. c Satisfy the following formula: B c =∑((Q) Gc，t -Q GL，t )×P Gc，t ).

[0098] The market clearing result also includes the real-time node marginal electricity price. Specifically, the benefit of generation-side participation in demand response is the difference between the reduced unit investment cost and the reduced generation revenue of generation-side participants. The reduced unit investment cost is the sum of the fifth multipliers of each stage, where the fifth multiplier is the product of the unit investment cost per unit of generation and the unit investment capacity avoided by participating in demand response in time period t. The reduced generation revenue is the sum of the sixth multipliers of each stage, where the sixth multiplier is the product of the real-time node marginal electricity price at the generation-side node in time period t and the unit's generation cost in time period t, plus the change before and after participating in demand response in time period t. For example, if P... Gr，t C represents the real-time nodal marginal electricity price at node t on the generation side during time period t. t ' represents the power generation cost of the unit in time period t, ΔQ DR，tLet t represent the change in demand response before and after participation in the demand response. Then, the sixth multiplier satisfies the following formula: Sixth multiplier = (P Gr，t -C t ′)×ΔQ DR，t Furthermore, when t is different, if C drg C represents the reduced generation revenue from participating in demand response on the generation side. drg Satisfy the following formula: C drg =∑((P) Gr，t -C t ′)×ΔQ DR，t If C o P represents the unit investment cost per unit of electricity generated. DR，t Let t represent the unit investment capacity participating in demand response avoidance during time period t. Then, the fifth multiplier satisfies the following formula: Fifth multiplier = C o ×P DR，t Furthermore, when t is different, if B i B represents the reduction in generator investment costs associated with participating in demand response on the generation side. i Satisfy the following formula: B i =∑C o ×P DR，t Furthermore, if B DR If B represents the benefit of the generation side participating in demand response, then... DR Satisfy the following formula: B DR =B i -C drg .

[0099] The real-time market settlement revenue on the generation side is derived from the real-time market supply of electricity on the generation side, the real-time marginal electricity price of the node where the generation side is located, and the demand electricity of the generation side in the day-ahead market at time t. Specifically, the real-time market settlement revenue on the generation side is the sum of the tenth multipliers of each stage. The tenth multiplier of each stage is the product of the difference between the real-time market supply of electricity on the generation side and the demand electricity of the generation side in the day-ahead market at time t, and the real-time marginal electricity price of the node where the generation side is located at time t. For example, if B... r Q represents the real-time market settlement revenue on the generation side. u，t P represents the real-time electricity generated and fed into the market from the power generation side. Gr，t Q represents the real-time nodal marginal electricity price at node t on the generation side during time period t. Gc，t If the demand for electricity in the day-ahead market at time t represents the generation side, then the tenth multiplier satisfies the following formula: Tenth multiplier = (Q u，t -Q Gc，t )×P Gr，t When t is different, then B r Satisfy the following formula: B r =∑((Q) u，t -Q Gc，t)×P Gr，t ).

[0100] The revenue from medium- and long-term contracts on the power generation side is derived from the net medium- and long-term contract electricity volume in time period t and the net contract price on the power generation side in time period t. For example, if B... LCfD Q represents the return on medium- to long-term contracts traded on the power generation side. GL，t P represents the contracted electricity volume of the power generation side in the medium- to long-term market during period t. GL，t This represents the net contract price on the power generation side during time period t. At different times t, B... LCfD Satisfy the following formula: B LCfD =∑(Q GL，t ×P GL，t ).

[0101] Among them, the power generation cost and carbon emission trading cost are: the sum of the seventh multipliers of each stage, where the seventh multiplier of each stage is the product of the unit's power generation cost in time period t and the unit's output in time period t; for example, if C g C represents the cost of electricity generation and the cost of carbon emission trading. t P represents the power generation cost of the unit during time period t. t C represents the unit's output during time period t. At different times t, C... g Satisfy the following formula: C g =∑(C t ×P t ).

[0102] The market clearing results include the day-ahead marginal electricity price, and the market deviation assessment cost for the generation side is the sum of the eighth multipliers for each stage. The eighth multiplier for each stage is the product of the second and third values ​​for each stage. The second value for each stage is the maximum value between 0 and the first difference for each stage. The first difference for each stage is the difference between the declared response capacity and the response ratio threshold for time period t on the generation side and the actual response capacity for time period t on the generation side. The third value for each stage is the maximum value between the ninth multiplier for each stage and the lower limit of the assessment price. The ninth multiplier for each stage is the product of the day-ahead marginal electricity price for time period t on the generation side and the penalty factor. For example, if P Gc，t Let represent the day-ahead marginal electricity price at node t on the generation side, and M represent the penalty factor. Then, the ninth multiplier satisfies the following formula: Ninth multiplier = P Gc，t ×M; if P min If the lower limit of the assessment price is represented, then the third value satisfies the following formula: Third value = max(P) Gc，t ×M, P min If P dec，DR，t R represents the reported response capacity on the power generation side during time period t, and P represents the response ratio threshold. real，DR，tLet represent the actual response capacity of the power generation side during time period t. Then, the first difference satisfies the following formula: First difference = (P dec，DR，t ×RP real，DR，t If the second value satisfies the following formula: Second value = max(P) dec，DR，t ×RP real，DR，t , 0), further, when t is different, if C ch C represents the market deviation assessment cost on the generation side. ch Satisfy the following formula:

[0103] C ch =∑max(P dec，DR，t ×RP real，DR，t ,0)×max(P Gc，t ×M, P min );

[0104] S208, adjust the operation mode of the generator sets on the power generation side according to the overall benefits on the power generation side.

[0105] In this embodiment, the generator set can be upgraded according to the total benefits on the power generation side, or low-carbon investment can be made in the generator set, or the trading strategy of the generator set can be optimized to improve efficiency. In addition, the total benefits on the power generation side can guide how to further reduce the operating costs of the generator set. For example, the operating costs of the generator set can be reduced by lowering the unit price or reducing the unit carbon emission cost, so that the generator set can implement the corresponding operation mode based on the reduced operating costs.

[0106] In summary, this embodiment obtains the unit carbon emission cost by calculating the carbon allowances for heating and power generation. Then, based on the unit carbon emission cost, the operating costs of the generating units in the electricity carbon trading market are obtained. Thus, by combining market clearing boundary conditions and the constraints of the safety-constrained unit combination, and with the optimization objective of minimizing the start-up and operating costs of the generating units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result. Based on the market clearing result and the various cost-benefit factors on the generation side, the total benefit on the generation side is obtained. These cost-benefit factors include: day-ahead market settlement revenue, real-time market settlement revenue, revenue from medium- and long-term contract trading, benefits from demand response participation, generation costs and carbon emission rights trading costs, and market deviation assessment costs. In obtaining the total benefit on the generation side, the impact of carbon emission rights trading and demand response implementation on the generation side's benefits is considered, which aligns with the current actual operation and trading situation of electricity carbon market integration that considers demand response products. Therefore, the accuracy of the assessment of the total benefit on the generation side can be improved.

[0107] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0108] Understandably, this application proposes a cost-benefit assessment method for the generation side under the coupling of the electricity carbon trading market and demand response. First, the baseline method is used to obtain the total carbon emission allowance of the generating units, and the carbon emission cost in the trading is included in the bidding function of each generating unit. Here, the generation cost of thermal power units is used to represent the carbon emission cost of unit i in time period t, which reflects the coupling of the carbon trading market and the spot market operation. This solves the problems that day-ahead carbon emission prices are not available, fixed carbon emission prices cannot accurately represent the carbon trading costs of each generating unit, and the assessment of unit benefits is inaccurate. Second, the trading mechanism of generating units under the demand response scenario in the electricity spot market is considered, and the various indicators in the cost-benefit quantitative analysis model are quantitatively calculated. This solves the problem that the current cost-benefit analysis model does not consider the impact of demand response, thereby improving the accuracy of the estimation of the total benefit of the generation side.

[0109] In summary, the cost-benefit assessment method for the generation side under the coupling of the demand-response carbon trading market proposed in this application has the following advantages: First, the conventional unit bidding method considering the carbon trading market proposed in this application uses the baseline method to derive the unit's free carbon emission allowances and incorporates the carbon emission costs in the trading into the bidding function of each unit, reflecting the coupling between the carbon trading market and the spot market. The day-ahead unit carbon emission cost is expressed using the generation cost of thermal power units, reflecting the market's supply and demand relationship. This not only characterizes the day-ahead carbon emission price, promoting energy conservation and emission reduction for power generation enterprises and improving power generation efficiency, but also makes subsequent cost-benefit analysis of generating units considering carbon trading more accurate. Second, the method considering demand-response... A cost-benefit quantitative analysis model for generating units under the coupling of the demand response and the electricity carbon trading market was proposed. Quantitative calculations were performed using numerical examples. This model incorporates the demand response scenario into the daily power generation plan, considering not only day-ahead, real-time, and medium-to-long-term market transactions and settlements, but also avoiding unit investment, power generation costs, and daily carbon trading costs under the demand response scenario. This makes the model more comprehensive and more consistent with the actual operation and trading situation of the current spot electricity market. Thirdly, the cost-benefit quantitative analysis model for generating units under the coupling of the demand response and the electricity carbon trading market proposed in this application is a general model for generating units. When the type of generating unit changes, only the model parameters need to be adjusted for quantitative calculations, demonstrating good adaptability.

[0110] Based on the method provided in this application, after calculating the market clearing results considering the coupling of the CET market and the day-ahead market, the resulting electricity price is used to quantitatively analyze the cost and benefit indicators of each generation side proposed below. The following example uses July 15, 2021 as the operating day (when there were 5 peak loads). The day-ahead load forecast and actual load data of that day are used to clear the day-ahead market and the real-time market respectively, serving as the data source for unit quotations and market transaction volume. The medium- and long-term contract electricity is decomposed into daily electricity volumes, with the daily electricity volume ratio set at 0.85. In the example, demand response reduces peak load by 3%, of which 2% of peak load is reduced by users participating in interruptible load projects, and 1% of peak load is transferred by energy storage during peak load periods. This portion of electricity is supplemented during off-peak periods (0:00-8:00). Specifically, as follows... Figure 5 As shown, a schematic diagram of load and demand response power is provided.

[0111] Table 3 shows the carbon emission allowance trading prices derived from the carbon emission pricing method proposed in this application. The table indicates that the more carbon emission allowances a generating unit needs to purchase and the higher its fuel cost coefficient, the higher the unit price it will have to pay. Carbon emission pricing based on this calculation method is conducive to promoting low-carbon investment in various generating units. Under the incentive compatibility of the market, generating units that originally needed to purchase emission allowances will try to increase low-carbon investment, improve unit efficiency, reduce fuel cost coefficients, and reduce unit carbon emissions in order to reduce acquisition costs, thus minimizing the amount of carbon emission allowances that need to be purchased and keeping prices as low as possible. Meanwhile, generating units with surplus carbon emission allowances tend to sell more carbon emission allowances after fulfilling their power generation targets to obtain more additional income, which will also incentivize them to increase low-carbon investment and increase trading revenue. In this environment, it is conducive to mobilizing the entire society's initiative in energy conservation and emission reduction, rather than passively reducing emissions under the requirement of meeting carbon reduction targets.

[0112] Table 3

[0113] Unit 1 0.1538-0.9231 37.9 20 31.66-89.97 Unit 2 0.1632-0.9231 35 17.5 28.92-82.12 Unit 3 0.0696-0.7692 55 10 17.66-94.61 Unit 4 0.0707-1.0385 16.7 32.5 34.86-67.24 Unit 5 0.2116-0.8462 45 30 49.04-97.16 Unit 6 0.0385-0.7692 60.3 28 32.64-120.77

[0114] Furthermore, the aforementioned market clearing model was used to simulate the clearing of the IEEE 30-node system. Ignoring line congestion, the day-ahead electricity market clearing price (pre = 79.92 yuan / ton) considering the impact of the carbon trading market, the day-ahead electricity market clearing price considering the impact of the carbon trading market and improved carbon pricing, and the clearing price without considering the impact of the carbon trading market were obtained. Additionally, the day-ahead electricity market clearing price considering the impact of the carbon trading market and improved carbon pricing, as well as the real-time electricity market clearing price after implementing demand response were obtained.

[0115] Specifically, such as Figure 6 As shown, a comparative diagram is provided, illustrating the day-ahead electricity market clearing price considering the impact of the carbon trading market (pre = 79.92 yuan / ton), the day-ahead electricity market clearing price considering the impact of the carbon trading market and improved carbon pricing, and the clearing price without considering the impact of the carbon trading market. The diagram shows that after considering the operation of the carbon market, the electricity market clearing price changes. The market clearing price increases significantly throughout the day compared to when the carbon trading market is not considered, with the highest increases being 25.95% and 22.86% (improved carbon pricing), but the overall price trend remains largely the same.

[0116] Specifically, such as Figure 7As shown, a comparison chart is provided of the day-ahead electricity market clearing price and the real-time electricity market clearing price after implementing demand response, taking into account the impact of the carbon trading market and improved carbon pricing. The clearing results are the nodal marginal electricity price curves of the day-ahead electricity market and the real-time electricity market on July 15, 2021. This result is used to quantify various cost-benefit indicators on the generation side in the following text.

[0117] Using the clearing prices of the day-ahead and real-time electricity markets obtained above, the cost-benefit indicators of the generation side under the proposed demand-response-based electricity carbon trading market coupling are quantitatively calculated. Specifically, Figure 8 This provides a schematic diagram illustrating the settlement results of market settlement revenue for various time periods prior to the current day. Figure 9 This provides a schematic diagram illustrating the settlement results of real-time market settlement revenue at various time periods. Figure 10 This provides a schematic diagram illustrating the settlement results of medium- and long-term market settlement returns for various periods. Figure 11 A schematic diagram illustrating the settlement results of demand response benefits at various time periods is provided. Figure 12 This provides a schematic diagram illustrating the settlement results of power generation costs and carbon emission allowance trading costs at various time periods. Figure 13 A schematic diagram illustrating the settlement results of market deviation assessment costs at various time periods is provided. Figure 14 A schematic diagram illustrating the total revenue of the power generation side on a given operating day is provided, wherein, from Figure 14 It is evident that the power generation side reduces a significant amount of unit investment costs by participating in demand response projects, far exceeding its power generation revenue in the electricity market. Therefore, the benefits of participating in demand response on the operating day are quite substantial.

[0118] It should be noted that, in Figures 5 to 14 In this context, the day-ahead electricity market clearing price refers to the day-ahead marginal electricity price, while the real-time electricity market clearing price refers to the real-time marginal electricity price. The methods for obtaining the day-ahead and real-time marginal electricity prices can be found in the aforementioned description and will not be repeated here.

[0119] Based on the same inventive concept, this application also provides an operation control device for generator sets operating under a carbon trading market, used to implement the above-mentioned operation control method for generator sets operating under a carbon trading market. The solution provided by this device is similar to the solution described in the above-described method. Therefore, the specific limitations in one or more embodiments of the operation control device for generator sets operating under a carbon trading market provided below can be found in the limitations of the operation control method for generator sets operating under a carbon trading market described above, and will not be repeated here.

[0120] In one embodiment, such as Figure 15As shown, an operation control device for generator sets under an electricity carbon trading market is provided, comprising: an acquisition module 1502, a result determination module 1504, a benefit determination module 1506, and a control module 1508, wherein:

[0121] The acquisition module 1502 is used to acquire the operating costs of generator units under the electricity carbon trading market. The operating costs of generator units are obtained based on the unit's bid price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply. The result determination module 1504 is used to optimize the safety-constrained unit combination model and the safety-constrained economic dispatch model by combining the market clearing boundary conditions and the constraints of the safety-constrained unit combination, with the optimization objective of minimizing the generator unit's start-up cost and operating cost, to obtain the market clearing result. The benefit determination module 1506 is used to obtain the total benefit of the generation side based on the market clearing result and the various cost-benefit factors on the generation side. The various cost-benefit factors on the generation side include: the day-ahead market settlement revenue of the generation side, the real-time market settlement revenue of the generation side, the revenue from medium- and long-term contract trading of the generation side, the benefit of the generation side participating in demand response, the generation cost and carbon emission rights trading cost, and the market deviation assessment cost of the generation side. The control module 1508 is used to adjust the operation mode of the generator units on the generation side according to the total benefit of the generation side.

[0122] In one embodiment, the operating cost of the generator set is the sum of the first multipliers of each stage; the first multiplier of each stage is the product of the unit's bid for the mth segment in time period t and the winning bid for the electricity in the mth output range of the unit in time period t; the unit's bid for the mth segment in time period t is the sum of the energy price corresponding to the mth output range declared by the unit and the unit's unit carbon emission cost in time period t; the energy price corresponding to the mth output range declared by the unit is the unit's bid.

[0123] In one embodiment, the unit carbon emission cost of the unit in time period t is: the ratio of the second multiplier to the first sum; the first sum is the sum of the maximum output of the unit in each stage; the second multiplier is the product of the second sum minus the first value and the carbon emission pricing of the unit in time period t; the second sum is the sum of the third multipliers of each stage; the third multiplier of each stage is the product of the carbon emission intensity coefficient corresponding to the unit and the maximum output of unit i; the first value is the product of the proportion of free allowances and the total carbon emission allowance of the unit; the total carbon emission allowance of the unit is the sum of the carbon allowance for power supply and the carbon allowance for heating.

[0124] In one embodiment, the total benefit on the power generation side is the difference between the sum of the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract transactions on the power generation side, and the benefit of the power generation side participating in demand response, and the third sum; the third sum is the sum of the power generation cost and carbon emission trading cost and the market deviation assessment cost on the power generation side.

[0125] In one embodiment, the market clearing result includes the day-ahead marginal electricity price and the real-time marginal electricity price. The day-ahead market settlement revenue for the generation side is the sum of the fourth multipliers of each stage. The fourth multiplier of each stage is the product of the generation side's demand for electricity in the day-ahead market at time t and the generation side's contracted electricity in the medium-to-long-term market at time t, multiplied by the day-ahead marginal electricity price of the generation side at time t. The real-time market settlement revenue for the generation side is the sum of the tenth multipliers of each stage. The tenth multiplier of each stage is the product of the generation side's real-time market grid connection electricity and the generation side's demand for electricity in the day-ahead market at time t, multiplied by the real-time marginal electricity price of the generation side at time t. The value of the generation side participating in demand response is: the difference between the reduced unit investment cost and the reduced generation revenue of the generation side participating in demand response; the reduced unit investment cost is the sum of the fifth multipliers of each stage, where the fifth multiplier is the product of the unit investment cost per unit of generation and the unit investment capacity avoided by participating in demand response in time period t; the reduced generation revenue is the sum of the sixth multipliers of each stage, where the sixth multiplier is the product of the real-time node marginal price at the node where the generation side is located in time period t and the unit's generation cost in time period t, and the change before and after participating in demand response in time period t.

[0126] In one embodiment, the generation cost and carbon emission trading cost are: the sum of the seventh multipliers of each stage, where the seventh multiplier is the product of the generation cost of the unit in time period t and the output of the unit in time period t; the market clearing result includes the day-ahead node marginal electricity price, and the generation-side market deviation assessment cost is the sum of the eighth multipliers of each stage; the eighth multiplier of each stage is the product of the second value and the third value of each stage; the second value of each stage is the maximum value between 0 and the first difference of each stage, where the first difference is the difference between the generation-side declared response capacity in time period t and the response ratio threshold, and the actual response capacity of the generation-side in time period t; the third value of each stage is the maximum value between the ninth multiplier of each stage and the assessment price lower limit, where the ninth multiplier is the product of the day-ahead node marginal electricity price in time period t of the node where the generation-side is located and the penalty factor.

[0127] In one embodiment, the constraints on the safety-constrained unit combination include system constraints, unit constraints, and network constraints; system constraints include system load balance constraints, system positive and negative reserve capacity constraints, and system spinning reserve constraints; unit constraints include unit output upper and lower limit constraints, unit ramping constraints, unit minimum continuous start-stop time constraints, and unit maximum start-stop frequency constraints; and network constraints include line power flow constraints.

[0128] The various modules in the operation control device of the generator set under the aforementioned carbon trading market can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0129] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 16 As shown. The computer device includes a processor, memory, and network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores market clearing boundary conditions and constraints on the combination of safety-constrained generator sets. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements an operation control method for generator sets in an electric carbon trading market; those skilled in the art will understand that... Figure 16 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0130] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method in the above embodiments; in another embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the method in the above embodiments; in yet another embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of the method in the above embodiments.

[0131] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0132] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application. It should be noted that for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for operating and controlling generator units under an electricity carbon trading market, characterized in that, include: The operating costs of generator sets under the carbon trading market are obtained; the operating costs of generator sets are obtained based on the unit price and the unit carbon emission cost, which is related to the carbon quota for heating and the carbon quota for power supply of the unit. Combining market clearing boundary conditions and safety-constrained unit combination constraints, with the optimization objective of minimizing the start-up cost and operating cost of the generator units, the safety-constrained unit combination model and the safety-constrained economic dispatch model are optimized to obtain the market clearing result. Based on the market clearing results and the various cost-benefit factors on the power generation side, the total benefit on the power generation side is obtained; the various cost-benefit factors on the power generation side include: day-ahead market settlement revenue on the power generation side, real-time market settlement revenue on the power generation side, revenue from medium- and long-term contract trading on the power generation side, benefits from the power generation side's participation in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs on the power generation side. Based on the overall benefits of the power generation side, adjust the operation mode of the generator set on the power generation side; The total benefit on the power generation side is the difference between the sum of the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract trading, and the benefit from the power generation side's participation in demand response, and a third sum. The third sum is the sum of the power generation cost, the carbon emission rights trading cost, and the market deviation assessment cost on the power generation side. The revenue from medium- and long-term contract trading on the power generation side is obtained based on the net medium- and long-term contract electricity volume in time period t and the net contract price on the power generation side in time period t. The market clearing result includes the day-ahead marginal electricity price and the real-time marginal electricity price; the day-ahead market settlement revenue of the generation side is the sum of the fourth multipliers of each stage; the fourth multiplier of each stage is the product of the demand electricity of the generation side in the day-ahead market at time t and the contracted electricity of the generation side in the medium- and long-term market at time t, and the day-ahead marginal electricity price of the node where the generation side is located at time t. The real-time market settlement revenue on the generation side is the sum of the tenth multipliers of each stage; the tenth multiplier of each stage is the sum of the electricity fed into the real-time market on the generation side and the electricity demanded in the daytime market t period on the generation side, multiplied by the marginal electricity price of the real-time node at the node where the generation side is located in t period. The benefit of the generation side participating in demand response is the difference between the reduced unit investment cost and the reduced generation revenue of the generation side participating in demand response. The reduced unit investment cost is the sum of the fifth multipliers of each stage. The fifth multiplier of each stage is the product of the unit investment cost per unit of generation and the unit investment capacity avoided by participating in demand response in time period t. The reduced generation revenue is the sum of the sixth multipliers of each stage. The sixth multiplier of each stage is the product of the real-time node marginal electricity price at the node where the generation side is located in time period t, the difference between the unit's generation cost in time period t and the change before and after participating in demand response in time period t.

2. The method according to claim 1, characterized in that, The operating cost of the generator set is the sum of the first multipliers of each stage; the first multiplier of each stage is the product of the unit's bid in the mth segment of time period t and the winning bid for the unit's power in the mth output interval of time period t. The unit's bid for the mth segment in time period t is the sum of the energy price corresponding to the mth output range declared by the unit and the unit's unit carbon emission cost in time period t; the energy price corresponding to the mth output range declared by the unit is the unit's bid.

3. The method according to claim 2, characterized in that, The unit carbon emission cost of the unit in time period t is: the ratio of the second multiplier to the first sum; the first sum is the sum of the maximum output of the unit in each stage; The second multiplier is the product of the second sum minus the first value and the unit's carbon emission pricing in time period t; the second sum is the sum of the third multipliers for each stage; the third multiplier for each stage is the product of the unit's corresponding carbon emission intensity coefficient and the unit i's maximum output; the first value is the product of the proportion of free allowances and the unit's total carbon emission allowances; the unit's total carbon emission allowances are the sum of the unit's carbon allowances for power generation and the unit's carbon allowances for heating.

4. The method according to claim 3, characterized in that, The carbon emission pricing of the unit in time period t is: the ratio of the carbon emission cost of the unit in time period t to the amount of carbon emission allowances that the enterprise needs to purchase in time period t.

5. The method according to claim 1, characterized in that, The carbon quota for power supply by the unit is the product of the unit's power supply, the power supply benchmark value of the unit's category, the unit's cooling method correction factor, the unit's heat supply correction factor, and the unit's output correction factor.

6. The method according to claim 1, characterized in that, The power generation cost and carbon emission trading cost are: the sum of the seventh multipliers of each stage; the seventh multiplier of each stage is the product of the power generation cost of the unit in time period t and the output of the unit in time period t. The market deviation assessment cost for the power generation side is the sum of the eighth multipliers for each stage; the eighth multiplier for each stage is the product of the second value and the third value for each stage. The second value for each stage is the maximum value between 0 and the first difference for each stage; The first difference in each stage is the difference between the multiplication of the declared response capacity and the response ratio threshold on the power generation side in time period t and the actual response capacity on the power generation side in time period t. The third value for each stage is the maximum value between the ninth multiplier for each stage and the lower limit of the assessment price; the ninth multiplier for each stage is the product of the day-ahead marginal electricity price and the penalty factor at the node t where the power generation side is located.

7. The method according to claim 1, characterized in that, The constraints on the safety-constrained unit combination include system constraints, unit constraints, and network constraints; the system constraints include system load balance constraints, system positive and negative reserve capacity constraints, and system spinning reserve constraints; the unit constraints include unit output upper and lower limit constraints, unit ramping constraints, unit minimum continuous start-stop time constraints, and unit maximum start-stop frequency constraints; the network constraints include line power flow constraints.

8. An operation control device for generator sets under an electricity carbon trading market, characterized in that, The device includes: The acquisition module is used to acquire the operating costs of generator sets under the electricity carbon trading market; the operating costs of the generator sets are obtained based on the unit price and the unit carbon emission cost, and the unit carbon emission cost is related to the carbon quota for heating and the carbon quota for power supply of the unit. The result determination module is used to combine the market clearing boundary conditions and the constraints of the safety-constrained unit combination, with the optimization objective of minimizing the start-up cost and operating cost of the generator sets, to optimize the safety-constrained unit combination model and the safety-constrained economic dispatch model, and obtain the market clearing result. The benefit determination module is used to obtain the total benefit of the power generation side based on the market clearing results and various cost-benefit factors of the power generation side. The various cost-benefit factors of the power generation side include: day-ahead market settlement revenue of the power generation side, real-time market settlement revenue of the power generation side, revenue from medium- and long-term contract transactions of the power generation side, benefits of the power generation side participating in demand response, power generation costs and carbon emission rights trading costs, and market deviation assessment costs of the power generation side. A control module is used to adjust the operating mode of the generator set on the power generation side according to the total benefits on the power generation side; The total benefit on the power generation side is the difference between the sum of the day-ahead market settlement revenue, the real-time market settlement revenue, the revenue from medium- and long-term contract trading, and the benefit from the power generation side's participation in demand response, and a third sum. The third sum is the sum of the power generation cost, the carbon emission rights trading cost, and the market deviation assessment cost on the power generation side. The revenue from medium- and long-term contract trading on the power generation side is obtained based on the net medium- and long-term contract electricity volume in time period t and the net contract price on the power generation side in time period t. The market clearing result includes the day-ahead marginal electricity price and the real-time marginal electricity price; the day-ahead market settlement revenue of the generation side is the sum of the fourth multipliers of each stage; the fourth multiplier of each stage is the product of the demand electricity of the generation side in the day-ahead market at time t and the contracted electricity of the generation side in the medium- and long-term market at time t, and the day-ahead marginal electricity price of the node where the generation side is located at time t. The real-time market settlement revenue on the generation side is the sum of the tenth multipliers of each stage; the tenth multiplier of each stage is the sum of the electricity fed into the real-time market on the generation side and the electricity demanded in the daytime market t period on the generation side, multiplied by the marginal electricity price of the real-time node at the node where the generation side is located in t period. The benefit of the generation side participating in demand response is the difference between the reduced unit investment cost and the reduced generation revenue of the generation side participating in demand response. The reduced unit investment cost is the sum of the fifth multipliers of each stage. The fifth multiplier of each stage is the product of the unit investment cost per unit of generation and the unit investment capacity avoided by participating in demand response in time period t. The reduced generation revenue is the sum of the sixth multipliers of each stage. The sixth multiplier of each stage is the product of the real-time node marginal electricity price at the node where the generation side is located in time period t, the difference between the unit's generation cost in time period t and the change before and after participating in demand response in time period t.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

Images