Zero-carbon scheduling method of virtual power plant with multiple resources game considering photovoltaic-thermal power station

Abstract

The application discloses a kind of zero carbon scheduling method of virtual power plant with photothermal power station considering and multi-element resource game, first, according to the different division of resource, the park controlled by the virtual power plant with photothermal power station is divided into park 1, park 2, park 3;Establish the game architecture of virtual power plant with photothermal power station and its internal multi-element resource;Establish the output model of photothermal power station containing organic rankine cycle ORC, heat collection mirror field HF, heat storage tank TES;Establish the output model of combined heat and power unit CHP, combined cooling heating and power unit CCHP, and establish actual carbon emission model based on it;Carbon responsibility on power supply side is apportioned to park 1, park 2 by position fair apportionment rule;Establish carbon capture-electricity to gas coupling model;Establish carbon trading model and green certificate income model after responsibility apportionment;According to photothermal power station output model, carbon capture-electricity to gas coupling model, carbon trading model and green certificate income model after responsibility apportionment, construct the master-slave game model of one master and multiple slaves with power balance as constraint condition, leader with realizing zero carbon operation and total income maximum as target, follower with income maximum as target;And solve the maximum income of leader and follower in master-slave game, obtain scheduling scheme.

Description

Technical Field

[0001] The present invention relates to a zero-carbon scheduling method for a virtual power plant including a solar thermal power station taking into account game with multiple resources, and belongs to the field of low-carbon economic scheduling. Background Art

[0002] As China's carbon market matures, free carbon allowances will gradually decrease, while society's demand for energy will increase, leading to an increase in greenhouse gas emissions from traditional power generation. The contradiction between the need for carbon reduction and carbon emissions is becoming increasingly prominent. Industrial parks are important economic engines in my country, but their combined energy carbon emissions account for nearly one-third of the nation's total. Therefore, the development of zero-carbon industrial parks is a key focus for the power industry in implementing its "dual carbon" strategy. However, the volatility of wind and photovoltaic power makes it impossible for industrial parks to achieve zero carbon through traditional clean energy sources alone. Concentrated solar power generation, due to the mismatch between conventional capacity and industrial park loads, cannot be scaled up within industrial parks. Therefore, virtual power plants (VPPs) have emerged, using advanced communication technologies to aggregate various energy sources to achieve zero-carbon dispatch within industrial parks. Using VPPs to aggregate distributed wind, solar, and thermal power capacity that matches industrial park loads has become a prerequisite for building zero-carbon industrial parks.

[0003] The carbon reduction operation strategy is an important core part of achieving zero carbonization for park-level VPPs. The carbon reduction strategy is to optimize low carbon performance from the "soft power" of the system. However, there are still non-electric loads such as thermal load, so traditional power sources are still indispensable. The lack of the "hard power" of hardware facilities makes the VPP low-carbon optimization degree not high, which restricts the system's advancement from low carbon to zero carbon.

[0004] In terms of carbon control technology, carbon capture and storage (CCS) and power to gas (P2G) and other carbon reduction technologies are relatively mature. Using carbon reduction technologies to achieve carbon control is a control from the emission process. If carbon emissions cannot be reduced from the source, VPP cannot achieve true zero net carbon dioxide emissions.

[0005] The volatility of traditional renewable energy requires the system to mobilize a large amount of flexible resources to balance supply and demand. Solar thermal power is a clean energy source that retains the flexibility of traditional thermal power units. CSP power generation offers advantages such as flexibility and certainty that traditional wind and solar power generation lack. However, high costs have always restricted the large-scale deployment of concentrating solar power (CSP) stations. Therefore, how to reduce the cost of CSP power generation and, against the backdrop of a gradual reduction in free carbon quotas, increase load-side participation in carbon trading and increase the use of CSP power have become key to achieving zero-carbon operation in VPPs.

[0006] In view of this, the present invention is proposed. Summary of the Invention

[0007] The present invention provides a zero-carbon scheduling method for a virtual power plant containing a solar thermal power station, which takes into account the game with multiple resources. It adopts a one-master-multiple-slave game framework with the virtual power plant as the game leader, and the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper power grid as followers. The method solves the problem and obtains the optimal operation plan to maximize the benefits of the leader and followers.

[0008] To achieve the purpose of the present invention, the technical solution provided by the present invention is:

[0009] The present invention provides a zero-carbon scheduling method for a virtual power plant including a solar thermal power station taking into account the game with multiple resources, comprising the following steps:

[0010] Step S1: The parks included in the virtual power plant control of the CSP plant are divided into Park 1, Park 2, and Park 3 based on different resources; a game architecture is established between the virtual power plant containing the CSP plant and its internal multiple resources; the virtual power plant is the game leader, and the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper-level power grid are followers; the virtual power plant containing the CSP plant includes a power supply side, a load side, an energy storage side, and carbon utilization equipment; Park 1 is a cooling, heating, and electricity load co-generation park, Park 2 is a heat and electricity load co-generation park, and Park 3 is an electricity load park;

[0011] Step S2: establishing a CSP power plant output model including an organic Rankine cycle (ORC), a solar collector field (HF), and a thermal storage tank (TES);

[0012] Step S3: Establish output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; establish an actual carbon emission model based on the output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; and allocate the carbon responsibility on the power supply side to Park 1 and Park 2 using the location-equitable allocation principle.

[0013] Step S4, establishing a carbon capture-power-to-gas coupling model;

[0014] Step S5: Establishing a carbon trading model and a green certificate income model after responsibility sharing;

[0015] Step S6: Based on the output model of the solar thermal power station, the carbon capture-power-to-gas coupling model, the carbon trading model after responsibility sharing, and the green certificate income model, a master-slave game model with one master and multiple followers is constructed, with power balance as the constraint condition, the leader's goal of achieving zero-carbon operation and maximizing total income, and the follower's goal of maximizing income; and the maximum income of the leader and follower in the master-slave game is solved.

[0016] Furthermore, the carbon trading model after responsibility sharing is as follows:

[0017]

[0018] Where: are the carbon costs borne by gas-fired units on the power supply side and the carbon costs borne by the load side; is the total cost of carbon emissions; k is the apportionment coefficient; λ is the carbon trading base price; α is the increase in reward and punishment prices; l is the interval length; D a The actual total carbon emissions are obtained based on the actual carbon emission model.

[0019] Furthermore, the green certificate income model after responsibility sharing is specifically as follows:

[0020]

[0021] Where: G CSP is the total income of CSP; α CSP P is the selling price of green certificates; CSP (t) is the CSP output during period t; Δt is the step length of the scheduling period; B L,i The green certificate income allocated to the i-th park; k is the proportional coefficient of allocation; B CSP It is the remaining green certificate income of the solar thermal power station after the apportionment.

[0022] Furthermore, the master-slave game model with one master and multiple followers, which is constructed with power balance as a constraint condition, the leader's goal of achieving zero-carbon operation and maximizing total benefits, and the follower's goal of maximizing benefits, includes the leader's benefit model, the follower's benefit model, and constraints.

[0023] The leader's profit model is specifically as follows:

[0024]

[0025] Where C Leader is the total benefit of the leader; C IES 、C NEW are the total revenues of gas-fired units and new energy units in the virtual power plant respectively; P i,PV (t), P i,CHP (t) are the ith PV and CHP outputs in period t, λ P2P ,λ CHP These are the unit prices for electricity sold by photovoltaic and gas-fired units respectively; is the thermal power of the nth GB device in period t; is the thermal power of the nth GT unit in period t; h P is the unit price of heat; air (t) is the cooling power during period t; λ e is the unit price of cooling power; C IDRThe comprehensive demand response benefit; The cost of capturing greenhouse gases; g The gas purchase cost; The carbon cost borne by the power side heat and power cogeneration unit CHP and the combined heat and power cogeneration unit CCHP; buy The electricity purchase cost; e,DR , C h,DR The electricity and heat benefits of the park user respectively; i,WIND (t) is the power delivered by wind power to the i-th park at time t; λ WT , λ ORC The unit selling price of wind power and ORC; CSP (t) is the CSP output at time t; P windess (t) is the selling power of wind power to the energy storage station; P WT,P2G (t) is the power supplied by wind power to P2G at time t; P WT,CCS (t) is the power supplied by wind power to CCS at time t; P ORC,CCS (t) is the power supplied by ORC to CCS; P ORC,P2G (t) is the power supplied by ORC to P2G; λ CSP , λ csp The unit selling price and unit power generation cost of CSP respectively; B CSP The green certificate benefit left over by the allocated photo-thermal power station.

[0026] Further, the follower's benefit model is:

[0027] max C D =C ESS +C Grid +C L,DR ;

[0028]

[0029] In the formula, C D The total benefit of the follower; C ESS The energy storage station benefit; C Grid The upper grid benefit; C L,DR The total benefit of the park user; P i,ch (t), P i,dis (t) are the charging and discharging power of the energy storage station to the i-th park at time t; λ CESS The unit selling price of the energy storage station; P wind (t) is the charging power of the wind farm to the energy storage station at time t; P i,buy (t) is the power purchased by the i-th park from the upper grid at time t; λ dis The unit selling price of the upper grid; P windgrid (t) is the power purchased by the upper grid from the wind farm at time t; Ce,DR The benefits of electricity users after participating in the response; C h,DR B is the benefit of heat users after participating in the response; L,i The green certificate income allocated to the i-th park; The carbon transaction cost borne by the load side after carbon responsibility sharing; WT The unit price of wind power sales.

[0030] The beneficial effects of the present invention are:

[0031] (1) The present invention establishes a CSP output mathematical model including a mirror field, a heat storage tank, and an organic Rankine cycle (ORC). When the CSP electricity is sold at the grid electricity price, the ORC electricity is bundled and sold with the CSP electricity at a price lower than the park electricity price to supply power to carbon reduction equipment. The surplus ORC electricity is directly supplied to the park power load, which is equivalent to reducing the power generation cost of CSP. CSP participates in zero-carbon construction by improving its own energy efficiency: that is, when the load accepts more CSP electricity, more ORC electricity is generated to supply carbon equipment, thereby reducing carbon emissions and carbon costs.

[0032] (2) Based on the principle of location fairness, the carbon responsibility of the park's combined heat and power (CHP) and combined cooling heating and power (CCHP) units and the green certificate income of CSP are allocated to the park, thereby increasing the enthusiasm of loads to accept CSP electricity and better participating in carbon emission trading (CET).

[0033] (3) When both the virtual power plant and the park users have the demand for carbon reduction, a master-slave game linkage framework is established. The main side formulates the incentive strategy for followers to participate in the game with the optimization goal of achieving zero-carbon operation and maximizing total benefits, that is: the virtual power plant formulates the ORC real-time electricity price, the electricity and heat sales prices of gas-fired units, and the electricity and heat incentive compensation prices that are lower than all power supply prices; and each follower participates in the leader's strategy with the purpose of maximizing benefits. The two parties in the game optimize with the guidance of step-by-step carbon trading to achieve the scheduling strategy of zero-carbon operation of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flowchart of the present invention;

[0035] Figure 2 This is an energy cycle diagram under the framework of the present invention;

[0036] Figure 3 It is the electricity, heating and cooling load curve of each park;

[0037] Figure 4 It is the renewable energy output and the solar field collection power diagram in the VPP;

[0038] Figure 5 To optimize the price chart of electricity and heat sales;

[0039] Figure 6 This is the result diagram of the excitation compensation after optimization;

[0040] Figure 7 This is the electric power balance diagram of Park 3 under Case 6 provided according to an embodiment of the present invention;

[0041] Figure 8 This is the electric power balance diagram of Park 2 under Case 6 provided according to an embodiment of the present invention;

[0042] Figure 9 This is a thermal power balance diagram of Park 2 under Case 6 provided according to an embodiment of the present invention;

[0043] Figure 10 This is the electric power balance diagram of Park 1 under Case 6 provided according to an embodiment of the present invention;

[0044] Figure 11 This is a thermal power balance diagram of Park 1 under Case 6 provided according to an embodiment of the present invention;

[0045] Figure 12 This is a cooling power balance diagram for Park 1 under Case 6 provided according to an embodiment of the present invention;

[0046] Figure 13 This is a coupling diagram of a solar thermal power station and carbon capture capacity in Case 6 provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other in any way.

[0048] Example 1: Figure 1-13 As shown, according to a first aspect of an embodiment of the present invention, a zero-carbon scheduling method for a virtual power plant including a solar thermal power station taking into account game with multiple resources is provided, comprising the following steps:

[0049] Step S1: The parks included in the virtual power plant control of the CSP plant are divided into Park 1, Park 2, and Park 3 based on different resources; a game architecture is established between the virtual power plant containing the CSP plant and its internal multiple resources; the virtual power plant is the game leader, and the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper-level power grid are followers; the virtual power plant containing the CSP plant includes a power supply side, a load side, an energy storage side, and carbon utilization equipment; Park 1 is a cooling, heating, and electricity load co-generation park, Park 2 is a heat and electricity load co-generation park, and Park 3 is an electricity load park;

[0050] Specifically, the power supply side includes a solar thermal power station CSP containing an organic Rankine cycle device, photovoltaic PV, wind power WT, a combined heat and power unit CHP, and a combined cooling, heating and power unit CCHP. The load side includes electrical load, thermal load, and cooling load. The energy storage side includes electrical energy storage ESS. The carbon utilization equipment includes a carbon capture device CCS and a power-to-gas device P2G. The solar thermal power station CSP containing an organic Rankine cycle device includes an organic Rankine cycle device ORC, a solar thermal collector field HF, and a heat storage tank TES. The combined heat and power unit CHP involves a gas turbine GT, a gas boiler GB, and a waste heat boiler WHB (a device that collects heat to supply thermal loads). The combined cooling, heating and power unit CCHP involves a gas turbine GT, a gas boiler GB, a waste heat boiler WHB, a refrigerator RC, and an air conditioner AC.

[0051] Step S2: establishing a CSP power plant output model including an organic Rankine cycle (ORC), a solar collector field (HF), and a thermal storage tank (TES);

[0052] Step S3: Establish output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; establish an actual carbon emission model based on the output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; and allocate the carbon responsibility on the power supply side to Park 1 and Park 2 using the location-equitable allocation principle.

[0053] Step S4, establishing a carbon capture-power-to-gas coupling model;

[0054] Step S5: Establishing a carbon trading model and a green certificate income model after responsibility sharing;

[0055] Step S6: Based on the output model of the solar thermal power station, the carbon capture-power-to-gas coupling model, the carbon trading model after responsibility sharing, and the green certificate income model, a master-slave game model with one master and multiple followers is constructed, with power balance as the constraint condition, the leader's goal of achieving zero-carbon operation and maximizing total income, and the follower's goal of maximizing income; and the maximum income of the leader and follower in the master-slave game is solved.

[0056] Further, the step 2 is specifically: considering the thermal energy utilization efficiency, an organic Rankine cycle output model using solar waste heat power generation is established as formula (3); after establishing the organic Rankine cycle output model, the solar collector field HF of formula (2), the heat storage tank model of formula (4) are combined to establish a power station output model containing an organic Rankine cycle ORC, a collector field HF and a heat storage tank, which is specifically as follows:

[0057]

[0058]

[0059] In the formula, P CSP (t) is the CSP output at t period; respectively, the heat provided by the collector field and the heat storage tank to the generator; η r-d is the thermoelectric conversion efficiency; respectively, the maximum and minimum output of the CSP; R max , R min respectively, the upper and lower limits of the CSP climbing; Q HF (t) is the heat collection amount of the collector field at t period; Q toss (t) is the self-heat dissipation amount at t period; η g-r is the photo-thermal conversion efficiency of the collector field; S HF is the total area of the collector field; D t is the light intensity at t period; H ORC (t) is the heat recovery amount of the ORC device; η RE is the heat recovery efficiency; η loss is the system self-heat dissipation efficiency; η ORC is the thermoelectric conversion efficiency of the ORC, P ORC,1 (t), P ORC,2 (t), P ORC,3 (t) are respectively the electric power supplied by the ORC to the parks 1, 2 and 3 at t period; P CSP,1 (t), P CSP,2 (t), P CSP,3 (t) are respectively the electric power supplied by the CSP power station to the parks 1, 2 and 3 at t period; P ORC,CCS (t), P ORC,P2G (t) are respectively the electric power supplied by the ORC to the CCS and P2G; E(t) is the heat storage amount of the heat storage tank at t period; ρ is the heat dissipation efficiency of the heat storage tank; η in , η out respectively, the heat storage and heat release efficiency of the heat storage tank; E in (t), E out (t) are respectively the heat storage and heat release amount of the heat storage tank at t period; is the residual heat power of the collector field; P ORC(t) is the total electric power generated by the organic Rankine cycle using waste heat.

[0060] Further, the heat supply and power supply unit CHP, the combined cooling, heat and power unit CCHP output model is:

[0061]

[0062] Q AC (t) = η AC P ac (t) (9) ;

[0063] The actual carbon emission model is:

[0064]

[0065] D a = D IE,a - D cap,a (11) ;

[0066] The power supply side carbon responsibility is allocated to the park 1 and the park 2 by the position fair allocation rule, and the expression is:

[0067]

[0068] In the formula, is the electric power of the GT unit of the nth park of the virtual power plant at the t period; is the gas power required by the GT of the nth park at the t period; is the electric conversion efficiency of the GT unit of the nth park; is the heat power of the GT unit of the nth park at the t period; is the heat conversion efficiency of the GT unit of the nth park; are respectively the upper and lower limits of the gas power of the GT unit of the nth park; is the heat power of the nth WHB at the t period; is the heat dissipation efficiency of the nth WHB of the park; is the heat power of the GB device of the nth park at the t period; is the gas power required by the GB of the nth park at the t period; is the heat conversion efficiency of the GB of the nth park; are respectively the upper and lower limits of the gas power of the GB of the nth park; is the WHB heat output of the park 1; P rc (t) is the heat power absorbed by the refrigerator; P h,load (t) is the heat power supplied by the GB to the load; P c,ac (t) is the refrigeration power; η acis the electric cooling conversion coefficient; Q AC (t) is the cooling power of the air conditioner, P ac (t) is the power consumption of the air conditioner;

[0069] D IE,a is the actual carbon emission of CHP; is the equivalent output of the gas-fired units in the nth park of the virtual power plant during period t; x2, y2, and z2 are the carbon emission coefficients of the gas-fired units; is the mass of greenhouse gases captured by CCS during period t; D cap,a Carbon emissions reduced by carbon capture devices; D a is the actual total carbon emissions;

[0070] is the carbon responsibility that the power supply side should bear during period t; k is the proportional coefficient; T is the scheduling period, which is 24; is the carbon responsibility borne by the nth park load in period t.

[0071] Furthermore, the carbon capture-power-to-gas (CCS-P2G) coupled model is expressed as:

[0072]

[0073] Where, P CCS (t) is the electric power consumed by CCS in period t; P ORC,CCS (t), P WT,CCS (t) is the electric power supplied by ORC and wind farm WT to CCS during period t; η CO2 is the carbon capture efficiency; P ORC,P2G (t), P WT,P2G (t) are the electric power supplied by ORC and wind farm WT to P2G respectively; P P2G (t) is the power consumed by P2G during period t; P2G is the P2G conversion coefficient; g is the natural gas synthesis coefficient; P P2G,g (t) is the resultant gas power; is the mass of greenhouse gases captured by CCS during period t.

[0074] Furthermore, the carbon trading model after responsibility sharing is as follows:

[0075]

[0076] Furthermore, the green certificate income model is specifically as follows:

[0077]

[0078] Where: are the carbon costs borne by gas-fired units on the power supply side and the carbon costs borne by the load side; is the total cost of carbon emissions; k is the apportionment coefficient, which is 0.5 in this invention; λ is the carbon trading base price; α is the price increase for rewards and penalties; l is the interval length; G CSP is the total income of CSP; α CSP The unit price of green certificate is RMB 80 / MWh; CSP (t) is the CSP output during period t; Δt is the scheduling period step, which is 1h; B L,i Green certificate income shared by the i-th park; B CSP It is the remaining green certificate income of the solar thermal power station after the apportionment.

[0079] Furthermore, the master-slave game model with one master and multiple followers, which is constructed with power balance as a constraint condition, the leader's goal of achieving zero-carbon operation and maximizing total benefits, and the follower's goal of maximizing benefits, includes the leader's benefit model, the follower's benefit model, and constraints.

[0080] Furthermore, the leader's profit model is specifically as follows:

[0081]

[0082] Where C Leader is the total benefit of the leader (subject side); C IES 、C NEW are the total revenue of gas-fired units and new energy units in the virtual power plant (C NEW That is, the total income of new energy sources such as solar thermal power stations, wind power, and photovoltaic power); P i,PV (t), P i,CHP (t) are the ith PV and CHP outputs in period t, λ P2P ,λ CHP are the electricity selling prices of photovoltaic and gas-fired units respectively; h P is the unit price of heat; air (t) is the cooling power during period t; λ e is the unit price of cooling power; Cost of capturing greenhouse gases; g is the gas purchase cost; WT ,λ ORC are the unit prices of wind power and ORC electricity respectively; P windess (t) is the power sold by wind power to the energy storage station; CSP ,λ csp are the unit electricity selling price and unit power generation cost of CSP respectively; C IDR is the comprehensive demand response benefit; C e,DR 、C h,DR are the electricity and heat benefits of the park users respectively; P P2G(t) is the power consumption of the power-to-gas (P2G) device; P CCS (t) is the power consumption of the carbon capture (CCS) device; λ ORC is the electricity price of the Organic Rankine Cycle (ORC) device; P ORC,CCS (t) the electrical power supplied by the organic Rankine cycle (ORC) plant to the carbon capture (CCS) plant; P ORC,P2G (t) is the electrical power supplied by the organic Rankine cycle (ORC) device to the power-to-gas (P2G) device; g is the unit price of gas purchase; is the gas power required by the GT of the nth park in period t; is the gas power required by the nth GB in period t; The carbon cost borne by the combined heat and power (CHP) unit and the combined cooling, heating and power (CCHP) unit on the power supply side; f buy is the electricity purchase cost; P i,WIND (t) is the wind power transmission power to the i-th park during period t; P WT,CCS (t) is the power of wind power supplied to carbon capture CCS during period t; P WT,P2G (t) is the power of wind power supplied to P2G during period t.

[0083] Furthermore, taking the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper-level power grid as followers, and maximizing the total profit as the objective function, the follower's profit model is:

[0084] maxC D =C ESS +C Grid +C L,DR (twenty one);

[0085]

[0086] Where C D is the total revenue of the followers; C ESS is the income of the energy storage station; C Grid Upper grid income; C L,DR is the total revenue of park users; P i,ch (t), P i,dis (t) are the charging and discharging power of the energy storage station to the i-park during period t; P wind (t) is the charging power from the wind farm to the energy storage station during period t; P i,buy (t) is the power purchased by the i-th park from the upper power grid during period t; dis P is the electricity selling price of the upper power grid; windgrid (t) is the power purchased by the upper power grid from the wind farm during period t; δ P , δ cUnit price of compensation for transferable and reducible electric load; μ p 、μ c are the compensation unit prices for transferable and reducible heat loads respectively; CESS C is the unit price of energy storage electricity; e,DR The benefits of electricity users after participating in the response; C h,DR B is the benefit of heat users after participating in the response; L,i is the green certificate income shared by the i-th park; f L,CO2 The carbon trading costs borne by the load side after carbon responsibility sharing; is the amount of electrical load that can be transferred; is the amount of electrical load that can be reduced; is the amount of heat load that can be transferred; is the amount of heat load that can be reduced; WT The unit price of wind power sales.

[0087] Furthermore, the constraints include power balances of Park 1, Park 2, and Park 3, and their expressions are:

[0088]

[0089]

[0090] Where, P 1,buy (t) is the power purchased by Park 1 from the upper power grid during period t; P 12 (t), P 13 (t) is the power transmitted from Park 1 to Park 2 and Park 3 during period t; P 21 (t) is the transmission power from park 2 to park 1 during period t; are the discharging and charging powers of energy storage to Park 1 during period t respectively; is the electric load of Park 1 after response in period t; is the CHP output of Park 1 during period t; The power supplied by the wind farm to Park 1 during period t; P is the photovoltaic power supply to Park 1 during period t; CSP,1 (t) is the power supplied by the CSP power station to Park 1 during period t; P ORC,1 (t) is the electric power provided by ORC to Park 1 during period t;

[0091] P 2,buy (t) is the purchased power of Park 2 during period t; are the discharging and charging power of energy storage to Park 2 during period t; P 23 (t) is the transmission power from park 2 to park 3 during period t; is the CHP output of Park 2 during period t; are the power supplied by wind farm and photovoltaic power station to Park 2 during period t; P CSP,2 (t) is the electric power provided by the CSP power station to Park 2 during period t; P ORC,2 (t) is the electric power provided by ORC to Park 2 during period t; is the electric load of Park 2 after the response in period t;

[0092] P 3,buy (t) is the purchased power of Park 3 during period t; P is the power supplied by the wind farm to Park 3 during period t; CSP,3 (t) is the electric power provided by the CSP power station to Park 3 during period t; P ORC,3 (t) is the electric power provided by ORC to Park 3 during period t; is the electric load of Park 3 after the response in period t;

[0093] is the load after thermal response of the nth park in period t; P c,load (t) is the cooling load during period t; P ac (t) is the power consumption of the air conditioner; is the thermal power of the nth GT unit in period t; is the thermal power of the nth GB device in period t; P c,ac (t) is the cooling power after heat-cold conversion; Q AC (t) is the cooling power of the air conditioner.

[0094] Furthermore, the process of solving the one-master-multiple-slave game model in step S6 is as follows:

[0095] S6.1. Input the original load, HF collector parameters, wind power WT, photovoltaic PV output data, gas-fired unit (CHP, CCHP) operating parameters, energy storage operating parameters, and upper-level grid transmission limits.

[0096] S6.2. Set the maximum number of iterations of the improved particle swarm algorithm: k max =200, initialize the number of iterations k0 = 0, initialize the electricity price λ of the organic Rankine cycle ORC ORC 、Gas-fired unit electricity sales priceλ CHP (The unit price of electricity sold by CHP and CCHP is the same), heat selling price λ h and the transferable electricity compensation unit price δ P , can reduce the electricity compensation unit price δ c , Transferable heat compensation unit price μ P , can reduce the unit price of heat compensation μ c Initial parameters;

[0097] S6.3, according to S6.2, the step is solved with total revenue maximization as the goal, when the number of iterations K=200, the ORC electricity price of the organic Rankine cycle λ ORC , the gas unit electricity selling price λ CHP (CHP, CCHP electricity selling price is the same), heat selling price λ h , and the transferable electricity compensation unit price δ P , the reducible electricity compensation unit price δ c , the transferable heat compensation unit price μ P , the reducible heat compensation unit price μ c ;

[0098] S6.4, after the park users receive the electricity selling price, heat selling price and transferable, reducible incentive compensation information, and the ORC price information is received by the carbon reduction equipment, the electricity and heat load response amount when the park users maximize the income is solved by the GUROBI solver, and the ORC power utilization amount and carbon dioxide utilization amount of the carbon reduction equipment under the optimal ORC electricity price;

[0099] S6.5, after the energy storage station and the superior power grid receive the optimal electricity selling price information, the electricity amount absorbed by the superior power grid and the energy storage station at the maximum discount is solved by the GUROBI solver;

[0100] S6.6, proof of the unique solution of the master-slave game:

[0101] There are three conditions for the unique solution of the master-slave game: the first is that the leader and follower strategies are non-empty sets; the second is that the follower has only one solution when participating in the leader's decision; the third is that the leader has a maximum (minimum) value after the follower participates in the decision.

[0102] According to the application, the leader sets the electricity and heat price and incentive compensation as a non-empty set; the load participates in the game as a CSP electricity acceptor, and the energy storage participates in the game as a surplus electricity accepter of other power sources, the superior power grid aims to reduce the energy purchase cost and sell more electricity as much as possible, and the three are not in conflict, the total income of the follower is composed of the maximum income of the three, that is, each follower also has a unique maximum value; after the follower participates in the decision, the simulation results show that the leader's income also has a unique maximum value. Therefore, it can be proved that the solution of the game strategy of the application is the optimal solution.

[0103] Further, in order to analyze the influence of the model on the carbon emission and economic benefit of the virtual power plant, the application sets six cases for comparative analysis, which are:

[0104] Case 1: the virtual power plant VPP has a 10MW capacity of CSP, when the VPP has 40% of the free quota, the time-sharing electricity selling price, heat selling price and demand response compensation price are optimized;

[0105] Case 2: A virtual power plant (VPP) with a 10MW CSP capacity optimizes time-of-use electricity and heat sales prices and demand response compensation prices when the VPP has 18% uncompensated quota.

[0106] Case 3: A virtual power plant (VPP) with a 10MW CSP capacity optimizes its electricity and heat sales prices and demand response compensation prices when the VPP has no free quotas.

[0107] Case 4: A virtual power plant (VPP) with a 10MW CSP capacity uses a master-slave game strategy to optimize when the VPP has 40% of its unpaid quota.

[0108] Case 5: A virtual power plant (VPP) with a 10MW CSP capacity uses a master-slave game strategy to optimize when the VPP has 18% unpaid quota.

[0109] Case 6: A virtual power plant (VPP) has a 10MW CSP capacity. When the VPP has no free quota, it is optimized through a master-slave game strategy.

[0110] For the above 6 cases, the scheduling results are analyzed.

[0111] To verify the effectiveness and applicability of the proposed model, a VPP was constructed to integrate a 10MW CSP capacity and a 2MW wind farm. Park 1 was equipped with small-scale photovoltaic and combined cooling, heating, and power (CCHP) units, while Park 2 was equipped with small-scale photovoltaic and CHP units, both of which were owned by the VPP. Park 3 was a non-powered park. To clarify the carbon responsibility of each park, the VPP only allowed the purchase and sale of renewable energy between parks. Due to the low photovoltaic output of the VPP, its green certificate income was ignored. The energy storage station had a capacity of 3MWh. The gas-fired units within the VPP provided CHP and CHP. This paper used MATLAB 2018b for simulation verification. The incentive compensation, electricity sales, and heat sales prices were optimized using an improved particle swarm optimization algorithm, and the objective functions were solved using the GUROBI solver. Figure 3 is the initial load of the park, Figure 4 = PV output, wind power output, and solar field collector power for the VPP; the gas purchase price is 0.35 yuan, the CSP on-grid tariff and power generation cost are 1.15 yuan / kWh and 0.85 yuan / kWh, respectively; Table 1 shows parameters for the CHP, CCHP, and thermal storage tanks, and Table 2 shows time-of-use pricing. The operating conditions under different cases are shown in Table 3.

[0112] Table 1

[0113] equipment Power limit / kW(kWh) Conversion factor / % P2G 600 75 GT 600 35 ORC / 80 WHB 1600 72 GB 700 90 air conditioner 6000 300 heat storage tank 10000 (kWh) /

[0114] Table 2

[0115] Time Upper-level power grid price (yuan) Electricity sales price between parks (yuan) Wind power price (yuan) Energy storage electricity price (yuan) 0：00-7：00 0.31 0.19 0.25 0.25 8：00-11：00 0.64 0.42 0.53 0.53 12：00-23：00 1 0.67 0.84 0.84

[0116] Table 3

[0117]

[0118] Table 3 shows that, from a local comparison, the carbon markets in Cases 4 and 6 do not have free quotas. Compared with Case 6, Case 4 has higher leader profits and slightly lower follower profits. This is because the ORC electricity price of the leader in Case 4 is a time-of-use price, which is higher than the real-time price in Case 6, allowing the leader to obtain some additional profits. However, the amount of ORC electricity accepted by the carbon reduction equipment is less than that in Case 6, and 8,000 kg of greenhouse gases are still not captured on the dispatch day. In Cases 1-5, the upper-level grid is more responsible for accepting the small amount of traditional renewable energy that the virtual power plant cannot fully utilize. The park is less dependent on the upper-level grid, so it does not gain much benefit in the game, but only purchases renewable energy at a low price to reduce the purchase cost of electricity. In Cases 1, 2, 4, and 5, due to the existence of free quotas, after the unit achieves carbon emissions less than the free quota, it uses the surplus quota as income. A comparison of Cases 1 and 2 and Cases 4 and 5 shows that the more free quotas, the greater the net emissions.

[0119] Overall, in a master-slave game, as the leader's revenue decreases, net greenhouse gas emissions decrease. The zero-carbon operation achieved in Case 6 is due to the leader's increased incentives, namely, setting an ORC electricity price lower than the time-of-use electricity price and supplying it to the park's carbon equipment at a price lower than the park's electricity sales price. This allowed the park to accept more CSP electricity while also allowing more ORC electricity to be used as energy consumption to drive carbon equipment, achieving greenhouse gas control.

[0120] As shown above, the leader sets electricity and heat prices and incentive compensation as a non-empty set; the load participates in the game as a recipient of CSP power, while energy storage participates as a recipient of excess power from other power sources. The upper-level grid aims to reduce energy purchase costs and maximize power sales. These three factors are not in conflict with each other, and the follower's total revenue is determined by the maximum of the three, meaning each follower has a unique maximum. After the followers participate in decision-making, simulation results show that the leader's revenue also has a unique maximum. This demonstrates that the solution to the game strategy proposed in this invention is the optimal solution.

[0121] The present invention draws the following conclusions:

[0122] 1) The enthusiasm of followers to participate in the game is one of the key factors for achieving zero-carbon operation of virtual power plants, and the rationality of carbon responsibility allocation and green certificate income allocation is an important factor for followers to actively participate in the response. This paper uses the "positional fairness" rule of the average marginal carbon emission factor to allocate carbon responsibility and green certificate income. It not only takes refined carbon measurement and income measurement as the premise for formulating zero-carbon operation strategies, but also improves the enthusiasm of the load side to participate in carbon reduction;

[0123] 2) CSP power generation costs are higher than traditional renewable energy, but it retains flexibility. Saving the cost of mobilizing flexible resources is the advantage of CSP power stations. This paper uses ORC to improve the utilization rate of solar thermal energy and supplies it to carbon reduction equipment such as CCS and P2G at a price lower than that of all types of power sources. At the same time, the green certificate income generated by solar thermal power generation is allocated to the load side based on the "positional fairness" principle, thereby effectively reducing the power generation cost of CSP and improving its market competitiveness.

[0124] 3) Carbon trading is an economic means to guide low-carbon behavior. The number of free quotas directly affects the enthusiasm of both parties to participate in carbon trading. When free quotas and carbon benefits gradually decrease, this strategy takes into account the late stage of carbon market maturity, that is, when free quotas are zero, and increases the enthusiasm of both parties to accept CSP electricity by having CSP power stations participate in carbon trading.

[0125] Reference significance of the strategy proposed in this invention:

[0126] ORC power generation is the main part of CSP participating in carbon trading. In terms of waste heat utilization, ORC cycle medium and cycle conditions are important factors affecting the efficiency of heat and electricity conversion. It is also one of the keys to reduce the operating cost of CSP power station. The strategy of this paper is for subsequent energy Incorporating efficiency into the zero-carbon concept provides theoretical support.

[0127] According to a second aspect of an embodiment of the present invention, a zero-carbon scheduling system for a virtual power plant containing a solar thermal power station is provided that takes into account the game with multiple resources, including: a first module for executing step S1: dividing the parks included in the management and control of the virtual power plant containing the solar thermal power station into park 1, park 2, and park 3 according to different resources; establishing a game architecture between the virtual power plant containing the solar thermal power station and its internal multiple resources; taking the virtual power plant as the game leader, and the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper-level power grid as followers; the virtual power plant containing the solar thermal power station includes a power supply side, a load side, an energy storage side, and carbon utilization equipment; park 1 is a cold, heat, and electricity load combined supply type park, park 2 is a heat and electricity load combined supply type park, and park 3 is an electric load type park; a second module for executing step S2: establishing a solar thermal power station output model containing an organic Rankine cycle ORC, a solar collector mirror field HF, and a heat storage tank TES ; The third module is used to execute step S3: establish the CHP output model of the combined heat and power unit and the CCHP output model of the combined heat and power unit; establish the actual carbon emission model based on the CHP output model of the combined heat and power unit and the CCHP output model of the combined heat and power unit; and allocate the carbon responsibility on the power supply side to Park 1 and Park 2 through the position fair sharing rule; the fourth module is used to execute step S4: establish a carbon capture-power-to-gas coupling model; the fifth module is used to execute step S5: establish a carbon trading model and a green certificate income model after responsibility sharing; the sixth module is used to execute step S6, and construct a master-slave game model with one master and multiple slaves based on the output model of the solar thermal power station, the carbon capture-power-to-gas coupling model, the carbon trading model and the green certificate income model after responsibility sharing, with power balance as the constraint condition and the maximization of the benefits of the leader and followers as the goal; and solve the maximum benefits of the leader and follower in the master-slave game.

[0128] The specific embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

Claims

1. A zero-carbon scheduling method for a virtual power plant containing a solar thermal power station considering multi-resource game, characterized in that: The following steps are involved: Step S1: The parks included in the virtual power plant management and control including the solar thermal power station are divided into Park 1, Park 2, and Park 3 based on different resources; Establish a game architecture for a virtual power plant containing a solar thermal power station and its internal multiple resources; the virtual power plant is the game leader, and the users on the load side of the virtual power plant, the electric energy storage ESS on the energy storage side, and the upper-level power grid are followers; the virtual power plant containing a solar thermal power station includes a power supply side, a load side, an energy storage side, and carbon utilization equipment; Park 1 is a combined cooling, heating, and electricity load park, Park 2 is a combined heating and electricity load park, and Park 3 is an electricity load park; Step S2: establishing a CSP power plant output model including an organic Rankine cycle (ORC), a solar collector field (HF), and a thermal storage tank (TES); Step S3: Establish output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; establish an actual carbon emission model based on the output models for the combined heat and power (CHP) unit and the combined cooling, heating, and power (CCHP) unit; and allocate the carbon responsibility on the power supply side to Park 1 and Park 2 using the location-equitable allocation principle. Step S4, establishing a carbon capture-power-to-gas coupling model; Step S5: Establishing a carbon trading model and a green certificate income model after responsibility sharing; Step S6: Based on the CSP power station output model, the carbon capture-power-to-gas coupling model, the carbon trading model after responsibility sharing, and the green certificate revenue model, a master-slave game model with one master and multiple followers is constructed, with power balance as a constraint, the leader's goal being to achieve zero-carbon operation and maximize total revenue, and the follower's goal being to maximize revenue. The maximum revenue of the leader and follower in the master-slave game is then solved. The master-slave game model with one master and multiple followers, which takes power balance as a constraint condition, the leader's goal is to achieve zero-carbon operation and maximize total benefits, and the follower's goal is to maximize benefits, includes a leader's benefit model, a follower's benefit model, and constraints; The leader's profit model is specifically as follows: Where C Leader is the total benefit of the leader; C IES 、C NEW are the total revenues of gas-fired units and new energy units in the virtual power plant respectively; P i,PV (t), P i,CHP (t) are the ith PV and CHP outputs in period t, λ P2P ,λ CHP These are the unit prices for electricity sold by photovoltaic and gas-fired units respectively; is the thermal power of the nth GB device in period t; is the thermal power of the nth GT unit in period t; h P is the unit price of heat; air (t) is the cooling power during period t; λ e is the unit price of cooling power; C IDR for comprehensive demand response benefits; Cost of capturing greenhouse gases; g The cost of purchasing gas; The carbon cost borne by the combined heat and power (CHP) unit and the combined cooling, heating and power (CCHP) unit on the power supply side; f buy is the electricity purchase cost; C e,DR 、C h,DR are the electricity and heat benefits of the park users respectively; P i,WIND (t) is the wind power transmission power to the i-th park during period t; λ WT ,λ ORC are the unit prices of wind power and ORC electricity respectively; P CSP (t) is the CSP output during period t; P windess (t) is the power sold by wind power to the energy storage station; P WT,P2G (t) is the power supplied by wind power to P2G during period t; P WT,CCS (t) is the energy consumption of wind power supplied to CCS during period t; P ORC,CCS (t) is the electrical power supplied by ORC to CCS; P ORC,P2G (t) is the electrical power supplied by ORC to P2G; CSP ,λ csp are the unit electricity selling price and unit power generation cost of CSP respectively; B CSP It is the remaining green certificate income of the solar thermal power station after the apportionment.

2. The zero-carbon scheduling method for a virtual power plant containing a solar thermal power station taking into account multi-resource game according to claim 1 is characterized in that: The carbon trading model after responsibility sharing is as follows: Where: are the carbon costs borne by gas-fired units on the power supply side and the carbon costs borne by the load side; is the total cost of carbon emissions; k is the apportionment coefficient; λ is the carbon trading base price; α is the increase in reward and punishment prices; l is the interval length; D a The actual total carbon emissions are obtained based on the actual carbon emission model.

3. The zero-carbon scheduling method for a virtual power plant containing a solar thermal power station taking into account multi-resource game according to claim 1 is characterized in that: The green certificate income model after responsibility sharing is as follows: Where: G CSP is the total income of CSP; α CSP P is the selling price of green certificate; CSP (t) is the CSP output during period t; Δt is the step length of the scheduling period; B L,i The green certificate income allocated to the i-th park; k is the proportional coefficient of allocation; B CSP It is the remaining green certificate income of the solar thermal power station after the apportionment.

4. The zero-carbon scheduling method for a virtual power plant containing a solar thermal power station taking into account multi-resource game according to claim 1 is characterized in that: The follower's profit model is: maxC D =C ESS +C Grid +C L,DR ; Where C D is the total revenue of the followers; C ESS is the income of the energy storage station; C Grid Upper grid income; C L,DR is the total revenue of park users; P i,ch (t), P i,dis (t) are the charging and discharging power of the energy storage station to park i during period t; λ CESS P is the unit price of energy storage electricity; wind (t) is the charging power from the wind farm to the energy storage station during period t; P i,buy (t) is the power purchased by the i-th park from the upper power grid during period t; λ dis P is the electricity selling price of the upper power grid; windgrid (t) is the power purchased by the upper grid from the wind farm during period t; C e,DR The benefits of electricity users after participating in the response; C h,DR B is the benefit of heat users after participating in the response; L,i The green certificate income allocated to the i-th park; The carbon transaction cost borne by the load side after carbon responsibility sharing; WT The unit price of wind power sales.

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