Virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism

Abstract

In order to solve the problems of cross-market bidding and flexible value of a virtual power plant, the invention provides a VPP electricity-carbon joint bidding strategy considering a national voluntary verification emission reduction mechanism, and the strategy comprises the steps: building a bidding model, considering a CCER transaction mechanism, of VPP participating in an electricity-carbon joint market, and taking the maximum net income as an objective function; determining a VPP bidding decision model considering a CCER transaction mechanism, wherein the VPP bidding decision model comprises a VPP power generation cost function, a constraint condition of the VPP power generation cost function and a VPP market operation decision optimization model; establishing a lower-layer market joint clearing model, and taking the minimum market operation cost as a target function; comprising active balance constraint and power generation unit operation constraint; an optimal solution is iterated by adopting a master-slave game loop, and a market clearing result and VPP internal scheduling can be obtained; vPP cross-market bidding and flexibility value problems can be effectively improved, the operation capability in a low-carbon environment can be effectively improved, and social development with low carbon and emission reduction is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of joint dispatching operation and centralized control of energy, and in particular to a virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism. Background Art

[0002] With the steady development of new power system construction, the proportion of new energy continues to increase, and carbon emission reduction policies are constantly changing. Different energy interest entities with different characteristics, such as traditional power generators, new energy power generators, and load aggregators, participate in the competition in the power market. The realization of efficient and low-carbon operation of energy has become the focus of continuous attention in the energy and power industry. Among them, VPP (Virtual PowerPlant) technology is an important means to achieve low-carbon and efficient operation of various energy production and consumption enterprises and promote the consumption of new energy. VPP technology aggregates distributed energy, energy storage, flexible loads and other resources, and uses intelligent control and communication technologies to respond to the economic dispatch of the power grid and the country's low-carbon emission reduction requirements, improve the comprehensive benefits of VPP market-oriented operations, and help the low-carbon emission reduction of the power system.

[0003] In recent years, the restart of the CCER (Chinese certified emission reduction) mechanism has provided a new path for the efficient and low-carbon operation of energy production and consumption enterprises. According to the National Climate Strategy Center's Guide to the Design and Implementation of Voluntary Greenhouse Gas Emission Reduction Projects, various energy production and consumption entities can independently and voluntarily develop greenhouse gas emission reduction projects in accordance with the guidelines. After the emission reduction effects of the projects are quantified and verified by scientific methods and applied for registration, they can be sold in the market to obtain corresponding emission reduction contribution income. Accordingly, VPP agents can apply for free CEA (Carbonemission allowance) for traditional power sources and CCER certification for new energy power generation, implement the CCER offset mechanism, and hedge the actual carbon emissions generated by traditional power generation through free CEA. The remaining carbon emissions are further offset by CCER, and the CCER surplus and shortage enter the carbon market trading balance. Through the CCER offset mechanism, the carbon emission reduction income channel of VPP is increased, which can effectively motivate VPP to participate in the efficient and low-carbon operation of the electricity carbon market and promote the consumption of new energy.

[0004] At present, there have been extensive studies on the market-oriented operation of VPPs guided by the carbon emission quota CEA. In the article "Low-carbon economic dispatch of wind power-carbon capture virtual power plants under dual carbon quantity constraints" in Volume 38, Issue 6 of the Proceedings of the CSEE, a two-stage low-carbon economic dispatch model of day-ahead and real-time was established to maximize the net income of the VPP electricity-carbon joint market. In the article "Master-slave game optimization dispatch of virtual power plants under the electricity-carbon joint market" in Volume 43, Issue 5 of Electric Power Automation Equipment, a master-slave game optimization dispatch model of virtual power plants under the electricity-carbon joint market was established. In the article "Research on bidding strategies for virtual power plants participating in the electricity-carbon joint market operation" in Volume 51, Issue 11 of Power System Protection and Control, an operation mechanism of VPP participating in the electricity-carbon joint market was proposed, including a two-stage double-layer bidding strategy of multi-agent interactive game. In the article "Multi-virtual power plant electricity-carbon-reserve P2P trading model based on conditional risk value" in Volume 46, Issue 18 of Electric Power Automation Equipment, a multi-VPP electricity-carbon-reserve point-to-point trading model was proposed.

[0005] However, the single CEA trading guidance cannot give full play to the initiative of VPP in reducing carbon emissions. This deficiency can be solved by introducing the CCER mechanism related to green electricity. The CCER mechanism refers to the fact that power generation enterprises take the initiative to carry out low-carbon emission reduction and confirm their emission reduction through certification and other means. The participation of CCER brings new impetus to the consumption of new energy. The article "Water-thermal power synergistic bidding model of carbon-electricity coupling market considering CCER mechanism" in Volume 47, Issue 21 of "Electric Power Automation Equipment" is based on the current carbon market policy and proposes a carbon-electricity joint market bidding model considering CCER mechanism based on the current carbon market policy. The article "Low-carbon dispatch of power system considering CCER revenue sharing to encourage deep peak regulation of thermal power units" published on May 24, 2024 in "Electric Power Automation Equipment" proposes the use of dynamic revenue sharing factors to compensate for deep peak regulation costs by sharing CCER revenue with thermal power units to encourage deep peak regulation of thermal power units and incorporate them into the power system dispatch model. Another article published on May 24, 2024 in the journal "Electric Power Automation Equipment" entitled "Electricity-Carbon Two-Layer Collaborative Decision-making Mechanism for Building-based Virtual Power Plants Based on Mutual Recognition of Green Electricity Emission Reductions" proposes a green electricity-CCER mutual recognition method based on emission reduction equivalence, and verifies this method with the building entity as the research object. The above studies show that the introduction of the CCER mechanism by power generators can not only increase their profits, but also stimulate the enthusiasm of the power system to reduce carbon emissions. However, research on introducing the CCER mechanism into virtual power plants and conducting joint bidding for electricity and carbon has not yet been involved. To this end, the present invention proposes that VPPs that consider the CCER mechanism participate in the operation of the electricity-carbon joint market, which is an effective way to promote low-carbon dispatch of the power system and improve the efficient operation benefits of VPPs. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a virtual power plant electricity-carbon joint bidding strategy taking into account the CCER mechanism, so as to solve the cross-market bidding and flexibility value problems of virtual power plants (VPP).

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is a virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism, including: Step 1: Establish a virtual power plant that takes the CCER mechanism into consideration, which includes distributed gas turbines, distributed wind and solar power, distributed photovoltaic power, and distributed energy storage. The virtual power plant acts as an independent entity to conduct cross-market bidding and flexible scheduling; Step 2: Virtual power plant bidding strategy based on CCER mechanism, with maximum net profit as the objective function; Step 3: Determine the VPP bidding decision model considering the CCER trading mechanism; Step 4: Establish a joint clearing model for the lower-level market, with the minimum market operating cost as the objective function; Step 5: After establishing the lower-level objective function, the virtual power plant bidding model based on the CCER mechanism determines the lower-level constraints, including active power balance constraints and power generation unit operation constraints; Step 6: Use the master-slave game cycle to iterate and find the optimal solution, which can obtain the market clearing result and VPP internal scheduling.

[0008] In the preferred solution, the calculation formula of the objective function in Step 2 is as follows: (1) in, Clearing electricity prices for the electricity energy market; The number of successful bids of VPP in the electricity market; , The purchase price of CEA shortage and the selling price of CCER surplus in the carbon market; , It is the net CEA shortfall and CCER net surplus after VPP integrates carbon quota; , is the carbon state of VPP; and is the operating cost of the energy storage unit f and gas turbine h inside the VPP; , For wind and solar operating costs.

[0009] In the preferred solution, the VPP bidding decision model in Step 3 includes VPP power generation cost function, VPP carbon quota certification, CCER certification, CCER write-off of VPP's CEA shortfall and quotation constraints of VPP electric energy market. The constraints of VPP power generation cost function include power generation constraint and ramp constraint as well as energy storage unit operation constraint; VPP carbon quota certification includes VPP's day-ahead initial CEA certification calculation, VPP's day-ahead time-based initial CEA decomposition, VPP time-based CEA hedging shortfall calculation. Calculation and VPP time-based CEA hedging shortfall ; CCER certification includes VPP’s CCER certification rules and VPP’s internal wind and solar power generation CCER certification; VPP’s CEA shortfall CCER write-off includes net CCER income and shortfall carbon quota costs.

[0010] In the preferred solution, the VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism includes: (2) (3) in, t is the trading period, T is the total number of trading periods the day before, F, H, B, K are the number of energy storage units, gas generator units, wind power units and photovoltaic units respectively, and this group of superscript and subscript variables shall be the same in the following text; and It is the energy storage unit inside the VPP f and gas turbines h The running cost, , For energy storage f Unit cost coefficient of charge and discharge, , Indicates energy storage f Charge and discharge power; For gas turbines h The bidding power, , , For gas turbines h Cost coefficient of , The operating cost of wind and solar power is and for t Wind turbines b and photovoltaic units k The bidding effort, , is the operating cost coefficient of wind and solar units.

[0011] In a preferred solution, the constraints of the VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism, wherein the power generation constraint and ramp constraint include: (4) in, and For gas turbines h The upper and lower limits of output, and Gas turbine h The upward and downward climbing rates, , for t Wind turbines b Upper and lower limits of output; for t Photovoltaic unit k Output limit; The energy storage unit operation constraints include: (5) in, , , , for t Time storage f Upper and lower limits of charge and discharge power; for t Time storage f state of charge.

[0012] In the preferred solution, the VPP carbon quota certification of the VPP bidding decision model considering the CCER trading mechanism includes VPP day-ahead initial CEA certification calculation, VPP day-ahead time-based initial CEA decomposition, VPP time-based CEA hedging shortfall calculation, and VPP time-based CEA hedging shortfall calculation. Calculate and hedge shortfalls with VPP time-based CEA , where the VPP’s initial CEA certification is calculated as follows: (6) in, For VPP internal gas turbine units h Total power generation without considering low-carbon dispatch on the previous day, For VPP internal gas turbine units h No. d The total power generation simulation value for the day, H is the number of gas turbines, D The total number of days for Monte Carlo simulation is set to 365 days in this paper; The initial CEA certification volume of VPP on the previous day, For internal gas turbine units hCarbon emission baseline value; The VPP day-ahead time-segment initial CEA decomposition includes: (7) Among them, the carbon emission allocation factor The total amount of carbon emissions certified for one day Decompose it into each trading period to obtain the VPP carbon emission certification value for each period of the day , participate in the market's time-sharing transactions; for t VPP internal gas turbine units h of power generation; The VPP time-based CEA hedge shortfall calculate (8) in, is the actual total carbon emissions of VPP; For gas turbine units in VPP h carbon emission intensity; for t Gas turbines in VPP h The actual power generation; for t Gas Turbine h Actual carbon emissions; The VPP time-based CEA hedge shortfall

[0013] (9) in, It will be further offset by CCER certified by VPP and then enter the carbon market for trading.

[0014] In a preferred solution, the CCER certification of the VPP bidding decision model considering the CCER trading mechanism includes CCER certification rules and CCER certification of wind and solar power generation within the VPP, wherein the CCER certification rules include: (10) in, for t The amount of electricity that is online for VPP internal renewable energy units during the period; for t CCER certified quantity of VPP in the period; is the carbon dioxide emission reduction factor of each new energy unit; is the marginal emission factor of electricity; is the capacity marginal emission factor.

[0015] The CCER certification of wind and solar power generation within the VPP includes: (11) in, , The CCER certified for wind power and photovoltaic power in VPP for one day is expressed as , .

[0016] In the preferred solution, the CCER write-off of the CEA shortfall of the VPP considering the CCER trading mechanism includes net CCER income and shortfall carbon quota costs, wherein the net CCER income includes: (12) The cost of the missing carbon quota includes (13) In the preferred solution, the quotation constraints of the VPP electric energy market considering the CCER trading mechanism include: (14) in, , They are t The amount of electricity reported and bid-winning by VPP in the electricity market during the period.

[0017] In a preferred solution, the method for calculating the minimum market operating cost of the lower objective function includes: (15) in,( , )and( , ) is a conventional unit i and VPP electricity market quotations and quantities.

[0018] In a preferred solution, the lower-level constraints include active power balance constraints and power generation unit operation constraints, wherein the active power balance constraints include: (16) in, is the energy market load demand during period t; The power generation unit operation constraints include the above power generation operation related constraints.

[0019] The present invention provides a virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism, which has the following beneficial effects: 1. This invention solves the problem of cross-market bidding and flexibility value of virtual power plants (VPPs); 2. The VPP participating in the electricity-carbon joint market operation taking into account the CCER mechanism adopted in the present invention is an effective way to promote low-carbon dispatch of the power system and improve the efficient operation benefits of VPP; 3. The VPP of the virtual power plant of the present invention aggregates renewable energy, non-renewable energy and energy storage resources, takes VPP only participating in the operation of the electric energy market as the baseline scenario, and applies for initial CEA and CCER certification; takes VPP participating in the electric-carbon joint market as the carbon emission reduction project scenario, gives play to the flexible aggregation effect of multiple energy sources, responds to the market's electric energy dispatch and low-carbon emission reduction dispatch needs, and while achieving energy optimization dispatch to promote the consumption of new energy, reduces carbon emissions, improves the comprehensive benefits of VPP market-oriented operations, and helps the power system to reduce carbon emissions; 4. The present invention considers the two branches of the carbon trading market in detail, fully considers the interactive collaboration of distributed energy within the virtual power plant, including the distributed energy on the power generation side of gas turbines, wind power, photovoltaics and energy storage, complies with the virtual power plant dispatching rules, and is conducive to practical reference; 5. This invention considers in detail the electricity-carbon interaction of the virtual power plant as an independent individual, and considers the interactive offset of the CCER mechanism, providing a new idea for the rational use of the restarted CCER mechanism; 6. The present invention has made detailed considerations on the carbon trading mechanism and the interactive offset between the carbon quota and CCER mechanism, but the patent does not consider uncertainty analysis; 7. After considering the CCER offset mechanism, the total power generation of VPP has increased, and the amount of electricity won by external thermal power units has decreased, which has led to a decrease in the total carbon emissions in the market. This shows that the introduction of the CCER offset mechanism can give full play to the incentive of VPP to reduce carbon emissions and promote the low-carbon transformation of the power system. 8. The present invention takes CCER and CEA into consideration. VPP optimizes its own power generation strategy by quoting quantity and price, increases additional carbon income, reduces overall operating costs, and improves the overall benefits of VPP. This shows that VPP introduces CCER offset mechanism, increases VPP's carbon emission reduction income channels, and improves the profitability of VPP's internal members. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below in conjunction with the accompanying drawings and implementation examples: Figure 1 This is a schematic diagram of the VPP electricity-carbon joint market framework considering the CCER mechanism in Example 2 of the present invention; Figure 2 This is an electric energy clearing diagram of VPP electricity-carbon joint market scenario 1 considering CCER mechanism in Example 2 of the present invention; Figure 3 This is an electric energy clearing diagram of VPP electricity-carbon joint market scenario 2 considering CCER mechanism in Example 2 of the present invention; Figure 4 This is an electric energy clearing diagram of VPP electricity-carbon joint market scenario 3 considering CCER mechanism in Example 2 of the present invention; Figure 5 This is a diagram of clearing electricity prices in different scenarios of the VPP electricity-carbon joint market considering the CCER mechanism according to Example 2 of the present invention; Figure 6 This is a market carbon emissions diagram under different scenarios of Example 2 of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described below in conjunction with the embodiments and drawings: Example 1 A virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism, including: Step 1: Establish a virtual power plant that takes the CCER mechanism into consideration, which includes distributed gas turbines, distributed wind and solar power, distributed photovoltaic power, and distributed energy storage. The virtual power plant acts as an independent entity to conduct cross-market bidding and flexible scheduling; Step 2: Virtual power plant bidding strategy based on CCER mechanism, with maximum net profit as the objective function; Step 3: Determine the VPP bidding decision model considering the CCER trading mechanism; Step 4: Establish a joint clearing model for the lower-level market, with the minimum market operating cost as the objective function; Step 5: After establishing the lower-level objective function, the virtual power plant bidding model based on the CCER mechanism determines the lower-level constraints, including active power balance constraints and power generation unit operation constraints; Step 6: Use the master-slave game cycle to iterate and find the optimal solution, which can obtain the market clearing result and VPP internal scheduling.

[0022] In this embodiment, the calculation formula of the objective function in Step 2 is as follows: (1) in, Clearing electricity prices for the electricity energy market; The number of successful bids of VPP in the electricity market; , The purchase price of CEA shortage and the selling price of CCER surplus in the carbon market; , It is the net shortfall of CEA and net surplus of CCER after VPP integrates carbon quota; , is the carbon state of VPP; and is the operating cost of the energy storage unit f and gas turbine h inside the VPP; , For wind and solar operating costs.

[0023] Furthermore, the VPP bidding decision model in Step 3 includes VPP power generation cost function, VPP carbon quota certification, CCER certification, CCER write-off of VPP's CEA shortfall and quotation constraints of VPP electric energy market. The constraints of VPP power generation cost function include power generation constraint, ramp constraint and energy storage unit operation constraint; VPP carbon quota certification includes VPP's day-ahead initial CEA certification calculation, VPP's day-ahead time-based initial CEA decomposition, VPP time-based CEA hedging shortfall calculation. Calculation and VPP time-based CEA hedging shortfall ; CCER certification includes VPP’s CCER certification rules and VPP’s internal wind and solar power generation CCER certification; VPP’s CEA shortfall CCER write-off includes net CCER income and shortfall carbon quota costs.

[0024] Furthermore, the VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism includes: (2) (3) in, t is the trading period, T is the total number of trading periods the day before, F, H, B, K are the number of energy storage units, gas generator units, wind power units and photovoltaic units respectively, and this group of superscript and subscript variables shall be the same in the following text; and It is the energy storage unit inside the VPP f and gas turbines h The running cost, , For energy storage f Unit cost coefficient of charge and discharge, , Indicates energy storage f Charge and discharge power; For gas turbines h The bidding power, , , For gas turbines h Cost coefficient of , The operating cost of wind and solar power is and for t Wind turbinesb and photovoltaic units k The bidding effort, , is the operating cost coefficient of wind and solar units.

[0025] Furthermore, the constraints of the VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism, wherein the power generation constraint and ramp constraint include: (4) in, and For gas turbines h The upper and lower limits of output, and Gas turbine h The upward and downward climbing rates, , for t Wind turbines b Upper and lower limits of output; for t Photovoltaic unit k Output limit; The energy storage unit operation constraints include: (5) in, , , , for t Time storage f Upper and lower limits of charge and discharge power; for t Time storage f state of charge.

[0026] Furthermore, the VPP carbon quota certification of the VPP bidding decision model considering the CCER trading mechanism includes the VPP day-ahead initial CEA certification calculation, the VPP day-ahead time-based initial CEA decomposition, and the VPP time-based CEA hedging shortfall. Calculate and hedge shortfalls with VPP time-based CEA , where the VPP’s initial CEA certification is calculated as follows: (6) in, For VPP internal gas turbine units h Total power generation without considering low-carbon dispatch on the previous day, For VPP internal gas turbine units h No. d The total power generation simulation value for the day, H is the number of gas turbines,D The total number of days for Monte Carlo simulation is set to 365 days in this paper; The initial CEA certification volume of VPP on the previous day, For internal gas turbine units h Carbon emission baseline value; The VPP day-ahead time-segment initial CEA decomposition includes: (7) Among them, the carbon emission allocation factor The total amount of carbon emissions certified for one day Decompose it into each trading period to obtain the VPP carbon emission certification value for each period of the day , participate in the market's time-sharing transactions; for t VPP internal gas turbine units h of power generation; The VPP time-based CEA hedge shortfall calculate (8) in, is the actual total carbon emissions of VPP; For gas turbine units in VPP h carbon emission intensity; for t Gas turbines in VPP h The actual power generation; for t Gas Turbine h Actual carbon emissions; The VPP time-based CEA hedging shortfall

[0027] (9) in, It will be further offset by CCER certified by VPP and then enter the carbon market for trading.

[0028] Furthermore, the CCER certification of the VPP bidding decision model considering the CCER trading mechanism includes CCER certification rules and CCER certification of wind and solar power generation within the VPP, wherein the CCER certification rules include: (10) in, for t The amount of electricity that is online for VPP internal renewable energy units during the period; for t CCER certified quantity of VPP in the period; is the carbon dioxide emission reduction factor of each new energy unit; is the marginal emission factor of electricity; is the capacity marginal emission factor.

[0029] The CCER certification of wind and solar power generation within the VPP includes: (11) in, , The CCER certified for wind power and photovoltaic power in VPP for one day is expressed as , .

[0030] Furthermore, the CCER write-off of the CEA shortfall of the VPP considering the CCER trading mechanism includes net CCER income and shortfall carbon quota costs, wherein the net CCER income includes: (12) The cost of the missing carbon quota includes (13) Furthermore, the bidding constraints of the VPP electric energy market considering the CCER trading mechanism include: (14) in, , They are t The amount of electricity reported and bid-winning by VPP in the electricity market during the period.

[0031] Furthermore, the method for calculating the minimum market operation cost of the lower objective function includes: (15) in,( , )and( , ) is a conventional unit i and VPP electricity market quotations and quantities.

[0032] Furthermore, the lower-level constraints include active power balance constraints and power generation unit operation constraints, wherein the active power balance constraints include: (16) in, is the energy market load demand in period t; the power generation unit operation constraints include the above-mentioned power generation operation related constraints.

[0033] Example 2 In another preferred embodiment, based on the above embodiment 1, Figures 1 to 4 As shown, in order to better reflect the multi-market bidding advantages of the CCER mechanism constructed by the present invention and realize the practical effectiveness of the proposed model, the present invention has built Figure 1 The VPP electricity-carbon joint market framework considering the CCER mechanism is shown, and three scenarios are set up for comparative analysis.

[0034] Scenario 1: VPP only participates in the electricity energy market, without considering the CCER mechanism and CEA transactions.

[0035] Scenario 2: VPP participates in the electricity energy market and considers CEA transactions.

[0036] Scenario 3: VPP participates in the electricity energy market, taking into account both the CCER mechanism and CEA transactions.

[0037] In the above three scenarios, VPP aims to maximize its own benefits and optimize its output and bidding strategy in the electricity-carbon joint market.

[0038] Figures 2~5 The market bidding results and clearing electricity prices under each scenario are shown respectively.

[0039] like Figure 2 As shown in the figure, conventional units provide the vast majority of energy in the energy market. Since VPP is composed of distributed energy entities, it is small in size and does not have an advantage in market competition. Therefore, if VPP wants to gain more benefits, it must adjust its own bidding strategy and introduce more constraints in the external market mechanism for clearing adjustments.

[0040] Combination Figures 2~4 and Figure 5 It can be seen that in scenario 1, only considering the constraints of the electricity market, VPP and other conventional units only consider the operating costs of the power generation process, so their clearing electricity prices are relatively minimal. In scenario 2, VPP and other conventional units need to consider carbon trading costs, which increases the costs of bidding entities, so the clearing electricity price is slightly higher than the clearing price in scenario 1.

[0041] In scenario 3, based on the scenario setting of this article, after considering the CCER offset mechanism, conventional units still bid and report based on their own operating costs and carbon trading costs because they cannot offset CCER, so the market clearing price does not change significantly. However, since VPP is also a bidding entity, after considering the CCER mechanism, the power generation of other market entities has decreased, giving up some power generation space to VPP. VPP adjusts its own power generation strategy and increases the power generation of new energy units and a small amount of gas turbines to obtain more available CCER and offset more carbon emissions to increase revenue during market bidding. According to the carbon emission laws of coal-fired units and gas-fired units across the country, the carbon emissions of a 1MW thermal power unit are higher than those of a 1MW gas turbine unit, which just fits the scenario setting of this article. This also means that under the same load, a 1MW gas turbine unit can replace a thermal power unit of the same magnitude to reduce carbon emissions and reduce power generation costs, which also makes the market clearing price scenario 3 slightly lower than scenario 2.

[0042] like Figure 6 As shown in the figure, carbon emissions change with the load trend. When the load is low, the carbon emissions are low, and when the load is high, the carbon emissions are high. The total carbon emissions in the three scenarios decrease in sequence. Compared with scenario 1, scenario 2 reduces the total carbon emissions by 107.82t; and scenario 3 reduces it by another 180.6t on the basis of scenario 2, indicating that the introduction of the CCER mechanism can further reduce market carbon emissions. According to general rules, the carbon emission coefficient of gas turbines is smaller than that of thermal power units. Therefore, the electricity-carbon combination considering the CCER mechanism can better achieve the goal of low-carbon emission reduction.

[0043] In summary, this paper aims at the VPP market bidding and distributed energy benefit allocation problems with a large number of distributed energy resources, and establishes a VPP electricity-carbon joint bidding strategy considering the CCER mechanism. The following conclusions are drawn through simulation analysis: (1) After considering the CCER offset mechanism, the total power generation of VPP increased, and the winning bid amount of external thermal power units decreased, which led to a decrease in the total carbon emissions in the market. This shows that the introduction of the CCER offset mechanism can give full play to the incentive of VPP to reduce carbon emissions and promote the low-carbon transformation of the power system.

[0044] (2) Taking CCER and CEA into consideration at the same time, VPP optimizes its own power generation strategy by quoting volume, increasing additional carbon revenue, reducing overall operating costs, and improving the overall benefits of VPP. This shows that the introduction of CCER offset mechanism by VPP increases the carbon emission reduction income path of VPP and improves the profitability of VPP internal members.

[0045] In summary, the present invention provides a virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism, which solves the virtual power plant (VPP) Plant) cross-market bidding and flexibility value issues; the present invention introduces the national voluntary certified emission reduction (CCER) mechanism into the electricity-carbon joint bidding strategy of the virtual power plant (VPP) for the first time. Traditionally, the bidding strategy of VPP is mainly based on the electricity energy market and carbon emission quota (CEA) trading, and this scheme provides VPP with a new carbon emission reduction benefit channel by adding the CCER mechanism; this scheme proposes a joint bidding strategy for VPP in the electricity energy market and the carbon market, and optimizes the power generation and carbon quota management of VPP by comprehensively considering the electricity price in the electricity energy market and the carbon price in the carbon market to maximize the net profit; this scheme has made a refined design for the carbon quota management of VPP, including the initial CEA certification calculation of the day before, the initial CEA decomposition of the time period, the calculation of the hedging shortfall of the time period CEA, and the certification and cancellation of CCER, etc., to ensure the accurate operation and efficient utilization of VPP in the carbon market; the present invention adopts the master-slave game cyclic iteration method to solve the optimal solution , not only takes into account the power generation costs and constraints within the VPP, but also takes into account the overall operating costs and constraints of the market, making the VPP's bidding strategy more in line with the actual market situation; by introducing the CCER mechanism, the scheme significantly improves the VPP's carbon emission reduction revenue channel, allowing the VPP to obtain higher net benefits when participating in the electricity-carbon joint market. This innovative bidding strategy not only promotes the consumption of new energy, but also promotes the low-carbon transformation of the power system; the scheme proposes a new market-oriented operation mechanism, that is, VPP participates in the bidding and scheduling of the electricity-carbon joint market by applying for initial CEA and CCER certification. This mechanism innovation provides new ideas and methods for the efficient and low-carbon operation of VPP in the power market; the scheme effectively integrates and innovatively applies technologies in multiple fields such as VPP technology, intelligent control and communication technology, CCER mechanism, and power market operation mechanism, forming a VPP electricity-carbon joint bidding strategy with independent intellectual property rights. This technological integration and application innovation provides strong support for the low-carbon and intelligent development of the power system; the solution has carried out fine-grained design and optimization of VPP's power generation costs, carbon quota management, market quotation and scheduling, ensuring VPP's dominant position and efficient operation in market competition; this fine-grained management and optimization innovation has enhanced VPP's market competitiveness and economic benefits; it is an effective way to promote the consumption of new energy, improve the efficient operation of VPP and the low-carbon scheduling of power systems; in addition, the strategy has also designed a dynamic adjustment mechanism to flexibly adjust VPP's power generation strategy and carbon trading strategy according to market carbon price fluctuations and changes in electricity supply and demand, to ensure the optimal balance between long-term economic and environmental benefits.

Claims

1. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism, characterized by: The strategies include: Step 1: Establish a virtual power plant that takes the CCER mechanism into consideration, which includes distributed gas turbines, distributed wind and solar power, distributed photovoltaic power, and distributed energy storage. The virtual power plant acts as an independent entity to conduct cross-market bidding and flexible scheduling; Step 2: Virtual power plant bidding strategy based on CCER mechanism, with maximum net profit as the objective function; Step 3: Determine the VPP bidding decision model considering the CCER trading mechanism; Step 4: Establish a joint clearing model for the lower-level market, with the minimum market operating cost as the objective function; Step 5: After establishing the lower-level objective function, the virtual power plant bidding model based on the CCER mechanism determines the lower-level constraints, including active power balance constraints and power generation unit operation constraints; Step 6: Use the master-slave game cycle to iterate and find the optimal solution, which can obtain the market clearing result and VPP internal scheduling.

2. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 1, characterized in that: The calculation formula of the objective function in Step 2 is as follows: （1） in, Clearing electricity prices for the electricity energy market; The number of successful bids of VPP in the electricity market; , The purchase price of CEA shortage and the selling price of CCER surplus in the carbon market; , It is the net CEA shortfall and CCER net surplus after VPP integrates carbon quota; , is the carbon state of VPP; and is the operating cost of the energy storage unit f and gas turbine h inside the VPP; , For wind and solar operating costs.

3. According to claim 1, a virtual power plant electricity-carbon joint bidding strategy considering the CCER mechanism is characterized by: The VPP bidding decision model in Step 3 includes VPP power generation cost function, VPP carbon quota certification, CCER certification, CCER write-off of VPP's CEA shortfall and quotation constraints of VPP electric energy market. The constraints of VPP power generation cost function include power generation constraint, ramp constraint and energy storage unit operation constraint. VPP carbon quota certification includes VPP's day-ahead initial CEA certification calculation, VPP's day-ahead time-based initial CEA decomposition, VPP time-based CEA hedging shortfall calculation. Calculation and VPP time-based CEA hedging shortfall ; CCER certification includes VPP’s CCER certification rules and VPP’s internal wind and solar power generation CCER certification; VPP’s CEA shortfall CCER write-off includes net CCER income and shortfall carbon quota costs.

4. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism includes: （2） （3） in, t is the trading period, T is the total number of trading periods a day ago, F, H, B, K are the number of energy storage units, gas turbine units, wind power units and photovoltaic units respectively, and this group of superscript and subscript variables shall be the same in the following text; and It is the energy storage unit inside the VPP f and gas turbines h The running cost, , For energy storage f Unit cost coefficient of charge and discharge, , Indicates energy storage f Charge and discharge power; For gas turbines h The bidding power, , , For gas turbines h Cost coefficient of , The operating cost of wind and solar power is and for t Wind turbines b and photovoltaic units k The bidding effort, , is the operating cost coefficient of wind and solar units.

5. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The constraints of the VPP power generation cost function of the VPP bidding decision model considering the CCER trading mechanism, wherein the power generation constraint and ramp constraint include: （4） in, and For gas turbines h The upper and lower limits of output, and Gas turbine h The upward and downward climbing rates, , for t Wind turbines b Upper and lower limits of output; for t Photovoltaic units k Output limit; The energy storage unit operation constraints include: （5） in, , , , for t Time storage f Upper and lower limits of charge and discharge power; for t Time storage f state of charge.

6. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The VPP carbon quota certification of the VPP bidding decision model considering the CCER trading mechanism includes the VPP day-ahead initial CEA certification calculation, VPP day-ahead time-based initial CEA decomposition, VPP time-based CEA hedging shortfall Calculate and hedge shortfalls with VPP time-based CEA , where the VPP’s initial CEA certification is calculated as follows: （6） in, For VPP internal gas turbine units h Total power generation without considering low-carbon dispatch on the previous day, For VPP internal gas turbine units h No. d The total power generation simulation value for the day, H is the number of gas turbines, D The total number of days for Monte Carlo simulation is set to 365 days in this paper; The initial CEA certification volume of VPP on the previous day, For internal gas turbine units h Carbon emission baseline value; The VPP day-ahead time-segment initial CEA decomposition includes: （7） Among them, the carbon emission allocation factor The total amount of carbon emissions certified for one day Decompose it into each trading period to obtain the VPP carbon emission certification value for each period of the day , participate in the market's time-sharing transactions; for t VPP internal gas turbine units h of power generation; The VPP time-based CEA hedging shortfall calculate （8） in, is the actual total carbon emissions of VPP; For gas turbine units in VPP h carbon emission intensity; for t Gas turbines in VPP h The actual power generation; for t Gas Turbine h Actual carbon emissions; The VPP time-based CEA hedging shortfall （9） in, It will be further offset by CCER certified by VPP and then enter the carbon market for trading.

7. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The CCER certification of the VPP bidding decision model considering the CCER trading mechanism includes CCER certification rules and CCER certification of wind and solar power generation within the VPP, wherein the CCER certification rules include: （10） in, for t The amount of electricity that is online for VPP internal renewable energy units during the period; for t CCER certified quantity of VPP in the period; is the carbon dioxide emission reduction factor of each new energy unit; is the marginal emission factor of electricity; is the capacity marginal emission factor; The CCER certification of wind and solar power generation within the VPP includes: （11） in, , The CCER certified for wind power and photovoltaic power in VPP for one day is expressed as , .

8. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The CCER write-off of the CEA shortfall of the VPP considering the CCER trading mechanism includes net CCER income and shortfall carbon quota costs, wherein the net CCER income includes: （12） The cost of the missing carbon quota includes （13）。 9. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 3, characterized in that: The bidding constraints of the VPP electric energy market considering the CCER trading mechanism include: （14） in, , They are t The amount of electricity reported and bid-winning by VPP in the electricity market during the period.

10. A virtual power plant electricity-carbon joint bidding strategy considering CCER mechanism according to claim 1, characterized in that: The calculation method of the minimum market operation cost of the lower objective function in Step 5 includes: （15） in,( , )and( , ) is a conventional unit i and VPP electricity market quotation and quantity; The lower-level constraints of Step 5 include active power balance constraints and power generation unit operation constraints, wherein the active power balance constraints include: （16） in, is the energy market load demand during period t; The power generation unit operation constraints include the above power generation operation related constraints.

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