Virtual power plant low-carbon economic dispatching method considering cooperation of hydrogen energy storage and liquid air energy storage

Abstract

A virtual power plant low-carbon economic dispatching method considering cooperation of hydrogen energy storage and liquid air energy storage comprises the steps that firstly, a hydrogen energy storage model is established, hydrogen energy serves as extension of the electricity-to-gas technology, and part of natural gas is replaced with the electricity-to-hydrogen and hydrogen gas turbine technology; secondly, establishing a liquid air energy storage (LAES) model, and stabilizing the output fluctuation of the unit by using the high-capacity and long-period electricity storage and discharge capability of the LAES model; and finally, hydrogen energy storage and liquid air energy storage are brought into an overall optimization scheduling framework, an electricity-gas-heat-hydrogen multi-energy complementary virtual power plant (VPP) model is constructed, and an improved mixed grey wolf optimization algorithm is used for solving. According to the invention, various energy conversion and energy storage devices are coupled, and wind power and photovoltaic power can be flexibly scheduled in a cross-time manner and fully utilized through joint optimization scheduling, so that collaborative optimal configuration of internal multi-energy resources is realized, the operation cost of the system is reduced, and carbon emission is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system optimization scheduling, in particular to a virtual power plant low-carbon economic scheduling method considering hydrogen energy storage and liquid air energy storage coordination. BACKGROUND

[0002] With the global energy system accelerating towards low-carbon and sustainable development, the penetration rate of renewable energy in the power system is continuously increasing. However, new energy resources such as wind power and photovoltaic power have significant volatility and intermittency characteristics, which poses great challenges to the balanced scheduling of the power system. In addition, traditional fossil fuel power generation still accounts for a large proportion, and carbon emission constraints are becoming increasingly stringent, so it is urgent to promote the construction of green and low-carbon energy systems through new energy management and optimization scheduling technology. To cope with the uncertainty brought by high penetration of renewable energy and the lack of flexibility of the power system, virtual power plant (VPP) technology has emerged. Virtual power plant (VPP) aggregates and coordinates the scheduling of distributed energy (such as wind power, photovoltaic power, distributed gas power), adjustable load, energy storage units, etc., to realize unified optimization control and economic operation of distributed resources, improve system flexibility and renewable energy consumption capacity, and has become an important direction of smart grid construction. In VPP, the introduction of energy storage systems plays a key role in coping with new energy fluctuations, achieving power load balancing, and improving system robustness. Currently, although electrochemical energy storage has relatively fast response capability, it has high cost, limited service life, and insufficient long-term energy storage capacity, making it difficult to meet the multi-time scale scheduling requirements of the power system.

[0003] Hydrogen energy storage (HES) as a new type of energy storage technology realizes cross-time scale and cross-energy carrier energy conversion through water electrolysis, hydrogen storage, and hydrogen power generation, etc., and has the advantages of low carbon, long-term energy storage, and high flexibility, which has shown broad application prospects in power system scheduling optimization. At the same time, as a large-scale long-term energy storage technology, liquid air energy storage (LAES) has become an important technical means for friendly consumption of new energy due to its high energy density, strong regional adaptability, and high construction flexibility. LAES can effectively realize efficient storage and release of electric energy through air liquefaction storage and multi-stage heat recovery and energy recovery process, and is particularly suitable for addressing the problems of diurnal periodic load changes and seasonal supply and demand imbalances in the power system.

[0004] Existing researches mostly embed hydrogen energy storage into power system scheduling model alone, and have not fully explored the potential advantages of hydrogen energy storage and other energy storage technologies in coordination, and lack comprehensive consideration of the coordination optimization of multiple energy storage technologies. In fact, hydrogen energy storage has the advantages of fast response and high energy density, and is suitable for short-term peak shaving and fast frequency regulation. LAES has large capacity and long-term stable output capability, and is suitable for long-term peak shaving and smoothing of renewable energy output. The two types of energy storage technologies are highly complementary in physical characteristics and operation mechanism, and if coordinated scheduling is realized, the overall flexibility and economy of the virtual power plant can be significantly improved. SUMMARY

[0005] In order to study the influence of multi-energy complementation and energy storage coordination on power system scheduling, the present application proposes a virtual power plant low-carbon economic scheduling method considering the coordination of hydrogen energy storage and liquid air energy storage. The method couples multiple energy conversion and storage devices, optimizes and schedules them jointly, so that wind power and photovoltaic power can be flexibly scheduled across time periods and fully utilized, thereby realizing optimal configuration of internal multi-energy resources, reducing system operation cost and reducing carbon emissions.

[0006] The technical scheme adopted by the present application is as follows:

[0007] A virtual power plant low-carbon economic scheduling method considering the coordination of hydrogen energy storage and liquid air energy storage, comprising the following steps:

[0008] Step 1: Establish a hydrogen energy storage model, and use hydrogen energy as an extension of electric-to-gas technology to replace part of natural gas;

[0009] Step 2: Establish a liquid air energy storage model, and use its high-capacity and long-period charge and discharge capability to smooth the output fluctuation of the unit;

[0010] Step 3: Combine the hydrogen energy storage model established in step 1 and the liquid air energy storage model established in step 2 to construct a hydrogen energy storage and liquid air energy storage coordination model;

[0011] Step 4: Based on the hydrogen energy storage and liquid air energy storage coordination model established in step 3, incorporate it into the overall optimization scheduling framework, construct a "electricity-gas-heat-hydrogen" multi-energy complementary virtual power plant model, and use MATLAB simulation environment combined with GUROBI optimization solver for solution.

[0012] In step 1, hydrogen can be widely used in transportation fuel, clean energy for civil use, and residential heating, etc. Therefore, hydrogen energy storage is introduced into the virtual power plant, hydrogen energy is used as an extension of P2G, and mixed hydrogen natural gas is delivered to the natural gas market to reduce carbon emissions. The specific construction method of the hydrogen energy storage model is as follows:

[0013] 1) Electrolysis of water to produce hydrogen:

[0014]

[0015] In formula (1): Ht is the amount of hydrogen produced by electrolysis of water during the period t; P t P2H Pt is the power used for electrolysis of water to produce hydrogen during the period t; η P2H ηe is the efficiency of electrolysis of water to produce hydrogen.

[0016] 2) Fuel cell power generation:

[0017]

[0018] In formula (2): Ht is the amount of hydrogen actually consumed by the fuel cell during the period t; η H2P ηf is the efficiency of the fuel cell; P t P2H Pf is the output power of the fuel cell using hydrogen for power generation during the period t.

[0019] 3) Hydrogen gas turbine power generation:

[0020]

[0021] In formula (3): Ht is the amount of hydrogen used for hydrogen gas turbine power generation during the period t; η HGT ηg is the efficiency of the hydrogen gas turbine; P t HGT Pg is the power generation power of the hydrogen gas turbine during the period t.

[0022] 4) Dynamic management of hydrogen storage:

[0023]

[0024] In formula (4): Ht is the amount of hydrogen stored in the hydrogen storage tank during the period t; S H2,min , S H2,max H0, Hmin, and Hmax are the initial, minimum, and maximum hydrogen storage amounts, respectively; loss H2 loss is the loss rate during hydrogen storage; H0 is the amount of hydrogen produced by electrolysis of water during the initial period; H0 is the amount of hydrogen actually consumed by the fuel cell during the initial period; H0 is the amount of hydrogen used for hydrogen gas turbine power generation during the initial period; Ht-1 is the amount of hydrogen stored in the hydrogen storage tank during the period t-1; t represents a 24-hour period within a day.

[0025] In step 2, liquid air energy storage (LAES) is a new large-scale long-time energy storage technology that realizes efficient conversion and scheduling of electric energy by liquefying and storing air. LAES has advantages such as high energy density, safety, and flexible deployment. The specific construction method of the LAES model is as follows:

[0026] 1) Energy balance of energy storage state:

[0027]

[0028] In formula (5): are the LAES energy storage states of the initial period, the t period, and the t-1 period, respectively; is the initial energy storage amount; LAES charg,eff , LAES discharg,eff is the charge-discharge efficiency of LAES; loss is the energy loss proportion in the energy storage process of each period of charging (liquefaction); P t LAES,charge , P t LAES,discharge are the charge-discharge powers of the t period LAES.

[0029] 2) Charge-discharge power constraints:

[0030]

[0031] In formula (6): P LAES,charge,max , P LAES,discharge,max are the maximum charge-discharge powers of LAES;

[0032] 3) Energy storage capacity constraints:

[0033]

[0034] In formula (7): S LAES,max is the maximum energy storage capacity of LAES.

[0035] In step 3, in virtual power plant scheduling, hydrogen energy storage combined with LAES has obvious complementary advantages. The specific construction method of the hydrogen energy storage and liquid air energy storage coordination model is as follows:

[0036] 1) Response speed:

[0037] Hydrogen energy storage system: Using water electrolysis, fuel cells, and hydrogen gas turbine technology, its energy conversion and start-up speed is relatively fast, and it can quickly intervene when the power grid load fluctuates instantaneously to provide short-time high-power support.

[0038] LAES system: Due to the involvement of air liquefaction and expansion power generation process, the response time is relatively slow, but its design purpose is to balance the energy supply and demand gap in a long period of time.

[0039] 2) Energy storage sustainability:

[0040] Hydrogen energy storage: Although it has a fast response, its continuous output time is generally short due to losses in the electro-hydrogen conversion and multi-stage conversion process and the limitation of hydrogen storage capacity. It is more suitable for emergency and instantaneous regulation.

[0041] LAES: It has high energy capacity and low unit energy cost, making it suitable for storing large amounts of energy over long periods of time. It is also effective for cross-period load regulation and energy smoothing.

[0042] 3) Collaborative constraints:

[0043] P t P2H ≥synergy ratio ×P t LAES,charge (8);

[0044] In equation (8): P t P2H Synergy is the power used for hydrogen production via water electrolysis during time period t. ratio This is the proportional coefficient for coordinated operation. Therefore, through coordinated scheduling, the system can utilize hydrogen energy storage to meet rapid response requirements, while simultaneously using LAES to balance overall energy supply and demand across time periods. The two energy storage technologies complement each other, optimizing the scheduling effect.

[0045] The synergistic model of hydrogen energy storage and liquid air energy storage specifically includes formulas (1) to (8).

[0046] In step 4, to collect real-time operational data from each unit and combine it with electricity price trends, renewable energy generation and electricity / heat load forecasts, a multi-energy complementary virtual power plant model of "electricity-gas-heat-hydrogen" is established to flexibly schedule various energy sources such as electricity, heat, and hydrogen. This model enables the system to achieve stable and efficient peak shaving through coordinated regulation when renewable energy levels fluctuate, while also considering both low carbon emissions and economic benefits. The specific construction method is as follows:

[0047] (a): The minimum net cost of operating a VPP system is as follows:

[0048] obj = C F -I C +C WI +C H +C PG +C CS +C W +C M +C H2,OP -

[0049] R H2 +C H2,GT -RH2，GT +LAES cost (9); In equation (9): obj is the objective function, i.e., the minimum net cost of operating the VPP system; C F Cost of carbon capture power plants; I C For carbon trading revenue; C WI Costs related to waste incineration power plants; C H For natural gas procurement costs; C PG For P2G equipment operating costs; C CS Cost of carbon sequestration; C W For the operation and maintenance costs of wind power and photovoltaic systems; C M C is the cost of purchasing electricity in the energy market. H2,OP For the operating cost of hydrogen energy systems; R H2 For fuel cell revenue; C H2,GT For the operating cost of hydrogen gas turbines; R H2，GT For hydrogen gas turbine revenue; LAES cost This refers to the operating cost of a liquid air energy storage system.

[0050] The specific expressions for each part are as follows:

[0051] ①. Cost of carbon capture power plants:

[0052]

[0053] In formula (10): To measure electricity generation P t G The corresponding variable costs for fuel and maintenance, etc.; 0.04 (P t G ) 2 This is a secondary cost term, representing the non-linear impact of unit output and efficiency.

[0054] ②. Carbon trading market revenue:

[0055]

[0056] In equation (11): P t GN The net output of the carbon capture power plant during period t; The net emissions during period t must be deducted from the capture amount.

[0057] ③. Costs related to waste incineration power plants:

[0058]

[0059] In equation (12): P t WI The equivalent power output of the waste incineration power plant during time period t.

[0060] ④. Natural gas procurement cost:

[0061]

[0062] In the above formula: V represents the amount of carbon dioxide purchased during time period t; t BUY V represents the amount of natural gas purchased during time period t; t CHP V t GB These represent the amount of CHP and natural gas consumed by the boiler during time period t, respectively; V t P2G Let t be the equivalent demand of P2G syngas for natural gas. The amount of natural gas equivalent to the power generation from hydrogen fuel cells and hydrogen gas turbines.

[0063] ⑤. P2G equipment operating costs:

[0064]

[0065] In equation (15): P represents the amount of carbon dioxide purchased during time period t; t P2G Let t represent the energy consumption of the P2G device during time period t.

[0066] ⑥. Carbon sequestration costs:

[0067]

[0068] In equation (16): The amount of CO2 flowing into the flue gas storage tank during time period t.

[0069] ⑦. Operation and maintenance costs of wind power and photovoltaic systems:

[0070]

[0071] In equation (17): P t W P t V These represent the available output of wind power and solar power during time period t.

[0072] ⑧. Cost of purchasing electricity in the energy market:

[0073]

[0074] In equation (18): The market electricity price for period t; P t EM Electricity purchased during time period t.

[0075] 9. Operating costs of hydrogen energy systems:

[0076]

[0077] In equation (19): k H2P k is the cost coefficient for hydrogen production via electrolysis. H2S P is the hydrogen storage cost coefficient. t P2H The hydrogen production power of water electrolysis during time period t; The amount of hydrogen in the hydrogen storage tank during time period t.

[0078] ⑩. Fuel cell revenue:

[0079]

[0080] In equation (20): r H2 P represents the fuel cell revenue coefficient. t H2P Let t be the output power of the fuel cell using hydrogen to generate electricity during the time period. Operating costs and benefits of hydrogen gas turbines:

[0081]

[0082] In the above formula: k H2,GT r is the operating cost coefficient for hydrogen gas turbines. H2,GT P is the revenue coefficient for hydrogen gas turbines. t HGT The power output of the hydrogen gas turbine during time period t is the power generated by the hydrogen gas turbine.

[0083] Operating costs of liquid air energy storage systems:

[0084]

[0085] In equation (23): LAES oper,cost P represents the operating cost coefficient for LAES. t LAES,charge P t LAES,discharge These represent the charging and discharging power of LAES during time period t.

[0086] (II): The constraints of the VPP system are as follows:

[0087] 1. Constraints related to the CCPP-P2G model:

[0088] 1) Total energy consumption constraint:

[0089] P t C2P =P t P2G +Pt CC (twenty four);

[0090] In equation (24): P t C2P P represents the total energy consumption during time period t. t P2G The energy consumption of the P2G device (electric-to-gas equipment) during time period t; P t CC Let t represent the energy consumption of the carbon capture portion during time period t.

[0091] 2) Constraints on wind and solar power curtailment:

[0092] P t P2G =P t WA +P t VA (25);

[0093] In equation (25): P t WA P represents the "curtailed" power generated by the wind power system during time period t; t VA The power of "curtailed solar power" generated by the photovoltaic system during time period t.

[0094] 3) Energy consumption constraints for carbon capture:

[0095] P t CC =P t A +P t op (26);

[0096] In equation (26): P t A P represents the energy consumption of the stationary portion of the carbon capture system during time period t; t op The energy consumption of the stationary portion of the carbon capture system during time period t.

[0097] 4) Power constraints of carbon capture power plants:

[0098] P t GN =P t G -P t GC -P t Gα (27);

[0099] In equation (27): P t G P represents the equivalent total power generation output of the carbon capture power plant during time period t;t GC P represents the energy consumed by the carbon capture power plant for carbon capture during time period t; t Gα This represents the energy consumed during flue gas treatment in time period t.

[0100] 5) Constraints on CO2 capture and P2G utilization:

[0101]

[0102] In the above formula: The amount of CO2 captured by the CCPP–P2G system during time period t; V represents the total CO2 consumed by the P2G system. t P2G The volume of natural gas generated by the P2G system; η P2G The conversion efficiency of P2G equipment from electricity to gas.

[0103] 6) Operational constraints of carbon capture power plants:

[0104] 100≤P t G ≤400 (31);

[0105]

[0106] 15≤P t GC +P t WC +P t VC +P t WIC ≤P t C,max (33);

[0107]

[0108] In the above formula: P t G The equivalent power output of the carbon capture power plant during time period t; The total amount of CO2 captured during time period t;

[0109] P t GC P t WC P t VC P t WIC P represents the energy consumption provided for carbon capture by thermal power, wind power, photovoltaic power, and waste incineration power plants during time period t; t C,max This represents the maximum allowable energy consumption of the carbon capture system during time period t.

[0110] 7) P2G operational constraints:

[0111] 0≤P t P2G ≤200 (36);

[0112] In the formula: P t P2G The operating power of the P2G device during time period t.

[0113] 2. Constraints related to the electric and thermal energy storage models:

[0114] 1) Energy storage constraints:

[0115]

[0116] In equation (37): P represents the energy storage capacity of the battery at the end of time period t; t ESC P t ESD These represent the charging and discharging power of the energy storage system during time period t; η ESC η ESD These refer to the charging and discharging efficiencies of the energy storage system.

[0117] 2) Thermal energy storage constraints:

[0118]

[0119] In formula (38): The heat storage capacity at the end of time period t; These represent the charging and heat dissipation power of the electrical storage system during time period t; η TSC η TSD These refer to the charging and discharging efficiencies of thermal energy storage, respectively.

[0120] 3. Constraints related to the waste-to-energy power plant model:

[0121] 1) Energy consumption constraints for flue gas treatment:

[0122]

[0123] In equation (39): P t α Total energy consumption for treating flue gas generated by waste incineration power plants; The amount of flue gas generated by the waste incineration power plant and directly used for flue gas treatment during time period t; 1) The amount of flue gas extracted from the flue gas storage tank for flue gas treatment during time period t. 2) Operational constraints of the waste incineration power plant:

[0124] 60≤P t WI≤100 (40);

[0125]

[0126] 0.1×400≤V t WI,α ≤0.9×400 (44);

[0127] In the above formula: P t WI The output of the waste-to-energy power plant during period t; V t WI,α The amount of gas in the flue gas storage device during time period t; The amount of flue gas generated by the waste incineration power plant and directly used for flue gas treatment during time period t; The amount of flue gas flowing into the flue gas storage tank during time period t; The amount of flue gas extracted from the flue gas storage tank for flue gas treatment during time period t; This is for the output of the waste-to-energy power plant during the t-1 period; The amount of gas in the flue gas storage device during time period t-1.

[0128] 4. Constraints related to the joint operation model of carbon capture-waste incineration-wind power-photovoltaics:

[0129] The carbon capture power plant, a waste incineration power plant equipped with gas storage devices, and a wind / solar power system will operate in synergy. A portion of the wind and solar power generation will be used for the carbon capture system's energy consumption; another portion will be used for the flue gas treatment system, and the remaining electricity will be fed into the grid. The constraints are as follows:

[0130] P t CC =P t GC +P t WC +P t VC +P t WIC (45);

[0131] P t α =P t Vα +P t Wα +P t Gα +P t WIα (46);

[0132] P t W =P t WN +Pt WC +P t Wα (47);

[0133] P t V =P t VA +P t VN +P t VC +P t Vα (48);

[0134] P t WI =P t WIN +P t WIC +P t WIα (49);

[0135]

[0136] In the formula: P t CC P represents the energy consumption of the carbon capture portion during time period t; t GC P represents the energy consumption of the carbon capture power plant for the carbon capture process during time period t. t WC P represents the carbon capture energy consumption borne by the wind turbine components during time period t; t VC P represents the carbon capture energy consumption borne by the photovoltaic unit during time period t; t WIC The carbon capture energy consumption shared by the waste-to-energy incineration plant during period t; P t α P represents the energy consumption of the flue gas treatment section during time period t; t Vα P t Wα P t WIα P t Gα Energy consumption for flue gas treatment at photovoltaic, wind power, waste incineration power plants, and carbon capture power plants during time period t; P t WN P t VN P t WIN These represent the grid-connected power generation capacity of wind power, photovoltaic power, and waste incineration power plants during time period t; P t W P tV P t WI These represent the predicted output of wind power, photovoltaic power, and waste incineration power generation during time period t; P t VA The "curtailed" power generated by the photovoltaic system during time period t; e represents the net CO2 emissions of the carbon capture power plant during period t; g The amount of CO2 produced per unit of equivalent power output of a carbon capture power plant;

[0137] 5. Constraints related to the CHP and gas-fired boiler model:

[0138] 1) CHP unit constraints:

[0139] 0≤P t CHP ≤140 (51);

[0140]

[0141] In the above formula: P t CHP The electrical power output of the CHP unit during time period t; P represents the thermal power output of the CHP unit during time period t. t PH The total output power of the CHP unit during time period t; This represents the total output power of the CHP unit during the t-1 time period.

[0142] 2) Constraints on gas-fired boilers:

[0143]

[0144] In the above formula: The heat output power of the gas-fired boiler during time period t; This represents the heat output power of the gas-fired boiler during the t-1 time period.

[0145] 6. Power balance constraint:

[0146] P t GN +P t WIN +P t CHP +P t WN +P t VN +P t ESD +P t EM +P t H2P +P tHGT +P t LAES,discharge =P t P2G +P t EL +P t ESC +P t LAES,charge (56);

[0147] In equation (56): P t GN P represents the net output of the carbon capture power plant during period t; t WIN For the period t, the net output of the waste incineration power plant to the grid is P. t CHP P represents the output electrical power of the CHP unit during time period t. t WN and P t VN These represent the grid-connected power of wind power and photovoltaic units during time period t; P t ESD P represents the energy storage discharge power during time period t. t EM P represents the amount of electricity purchased from the grid during time period t; t H2P and P t HGT These represent the power generation of the fuel cell and the hydrogen gas turbine during time period t, respectively; P t LAES,discharge P represents the liquid air energy storage discharge power during time period t. t P2G P represents the electrical energy consumed by the P2G device during time period t; t EL P represents the electrical load during time period t; t ESC P is the charging power of the energy storage system during time period t. t LAES,charge The charging power of liquid air energy storage during time period t.

[0148] 7. Other relevant constraints:

[0149] The hydrogen energy storage model is shown in equations (1) to (4), the liquefied natural gas energy storage model is shown in equations (5) to (7), and the co-constraint is shown in equation (8).

[0150] This invention discloses a low-carbon economic dispatch method for virtual power plants that considers the synergy of hydrogen energy storage and liquid air energy storage. The beneficial effects are as follows: 1) This invention achieves efficient synergy between renewable energy, traditional generating units, and energy storage units by constructing an integrated "electricity-gas-heat-hydrogen" energy model. When wind power is abundant, the LAES (Liquid Air Storage) is charged, and wasted wind and solar power is converted into hydrogen for storage; during peak load periods, hydrogen gas turbines and the LAES work together to supply power, reducing dependence on purchased electricity and fossil fuels.

[0151] 2) In the collaborative model of this invention, the equivalent output of carbon capture power plants can be further smoothly adjusted, reducing the start-up and shutdown losses of traditional gas turbines; the integrated application of hydrogen energy storage and LAES not only reduces the system's dependence on purchased electricity and natural gas, but also reduces carbon emissions and increases carbon trading revenue, thereby maximizing the optimization of overall net cost.

[0152] 3) This invention combines the “fast radius” regulation capability of hydrogen energy storage with the “long radius” cross-time valley leveling capability of LAES, forming a three-level energy storage synergy framework of short-term, medium-term and long-term, which not only meets the high requirements of the power system for flexibility and reliability, but also maximizes the economic and environmental value of renewable energy. Attached Figure Description

[0153] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0154] Figure 1 This is a graph showing the energy consumption of carbon capture.

[0155] Figure 2 This is a graph showing CO2 emissions and treatment volumes.

[0156] Figure 3 This is a schematic diagram of the operating status of a hydrogen energy storage system.

[0157] Figure 4 This is a schematic diagram of the charging and discharging of a liquid air energy storage system at different time periods.

[0158] Figure 5 This is a schematic diagram of HES and LAES operating in tandem.

[0159] Figure 6 A diagram illustrating the power output of waste-to-energy plants and the electricity purchased from the energy market.

[0160] Figure 7 This is a graph showing the change in energy consumption for flue gas treatment over time.

[0161] Figure 8 This is a graph showing the heat load and output of each heating unit.

[0162] Figure 9 This is a diagram showing the storage and release power and energy status of an energy storage device.

[0163] Figure 10 This is a comparison chart of carbon capture and carbon emissions.

[0164] Figure 11 A comparison chart of the output of carbon capture power plants and CHP units.

[0165] Figure 12 This is a chart comparing carbon trading revenue with VPP net costs.

[0166] Figure 13 This is a flowchart of the system scheduling process. Detailed Implementation

[0167] A low-carbon economic dispatch method for virtual power plants that considers the synergy between hydrogen energy storage and liquid air energy storage includes the following steps:

[0168] Step S1: Establish a hydrogen energy storage model, using hydrogen energy as an extension of the power-to-gas technology to replace part of the natural gas.

[0169] Step S2: Establish a liquid air energy storage model to smooth out the output fluctuations of the unit by utilizing its high capacity and long-term storage and discharge capabilities.

[0170] Step S3: Combining the hydrogen energy storage model from Step S1 and the liquid air energy storage model from Step S2, construct a collaborative model for hydrogen energy storage and liquid air energy storage.

[0171] Step S4: Incorporate the hydrogen energy storage and liquid air energy storage collaborative model from Step S3 into the overall optimization scheduling framework, construct a "electricity-gas-heat-hydrogen" multi-energy complementary virtual power plant model, and solve it using the MATLAB simulation environment combined with the GUROBI optimization solver.

[0172] Example:

[0173] To verify the effectiveness of the proposed low-carbon economic dispatch model for a virtual power plant (VPP) considering the synergy of hydrogen energy storage and liquid air energy storage, a typical VPP system in a certain region was selected for simulation. This system includes the following units and devices: a carbon capture power plant, a P2G unit, a P2H unit, a hydrogen gas turbine, a CHP unit, a LAES unit, a gas-fired boiler, a hydrogen storage tank, a fuel cell, a waste incineration power plant, a wind power plant, and a photovoltaic power plant. All data were compiled, and the parameters of each unit are shown in Table 1.

[0174] Table 1 Parameters of each unit

[0175]

[0176]

[0177] Based on the results of optimized scheduling, the energy consumption for carbon capture, as well as CO2 emissions and processing capacity, are as follows: Figure 1 , Figure 2 As shown. The energy storage capacities of hydrogen and liquefied natural gas are respectively as follows. Figure 4 , Figure 5 As shown. The output of waste incineration power plants, the amount of electricity purchased from the energy market, and the energy consumption for flue gas treatment are as follows: Figures 6-7 As shown in the figure. The heat load, output of each heating unit, and the storage and release power and stored energy of the energy storage device are respectively as follows: Figures 8-9 As shown.

[0178] Depend on Figure 1 It is known that during periods 1 to 7, due to higher wind power output and lower electricity load demand, the dispatch results show that maintaining a low output level for the carbon capture power plant is sufficient to meet load requirements. This indicates that during this period, the large amount of surplus electricity generated by wind power is mainly used to drive the liquid air energy storage (LAES) system, resulting in lower operating power consumption and flue gas treatment energy consumption for the carbon capture system, and consequently, a reduction in the overall CO2 capture volume. Simultaneously, CO2 emissions are very low during this period, demonstrating that during periods of abundant renewable energy, the system effectively utilizes waste wind power by reducing the operation of traditional generating units through energy storage technology.

[0179] Figure 2 The data shows CO2 emissions and capture volumes for each time period. During periods 1-7, due to lower output from carbon capture power plants, CO2 capture and emissions were essentially balanced, indicating that the system reduced the start-up of conventional units by absorbing curtailed wind and solar power through energy storage. However, during periods 10-13, increased electricity load forced carbon capture power plants to increase output, but capture volumes decreased, resulting in relatively higher emissions. Overall, this shows that the system relies on conventional units during high-load periods, but by shifting carbon capture energy consumption, carbon emissions were still partially reduced.

[0180] Figure 3 The operational status of the hydrogen energy storage system was fully demonstrated. For example, during the period from 10 to 15, when the electrical load suddenly increased and wind power output was insufficient, the system increased the power of water electrolysis to produce hydrogen and used fuel cells and hydrogen gas turbines to generate electricity, in order to quickly respond to load fluctuations. It can be seen that this supplementary power effectively alleviated the mismatch between new energy output and load demand, demonstrating the short-term adjustment capability of hydrogen energy storage.

[0181] Figure 4 The display shows the charging and discharging of the liquid air energy storage system during different time periods. From period 1 to 7, due to ample wind power, the system primarily charges, storing energy. From period 10 to 15, as the electrical load increases, the energy storage system begins to discharge, providing supplementary power to the grid, thus achieving peak shaving and valley filling across time periods. This process fully utilizes the long-term energy storage advantages of liquid air energy storage, ensuring a balance between grid supply and demand.

[0182] Figure 5 In this study, hydrogen energy storage and liquid air energy storage (LAES) each demonstrated their respective advantages across different time periods: hydrogen storage responded rapidly to short-term fluctuations (e.g., periods 1-9), while LAES provided continuous power over longer periods (e.g., periods 10-15). Together, they filled energy gaps at different time scales, reduced reliance on external power purchases, and optimized the utilization rate of energy storage resources.

[0183] Figure 6 The results show that the output of the waste-to-energy plant exhibits a highly stable characteristic, with its output power remaining largely within the rated operating range, and it does not participate in system load regulation or deep peak shaving. The energy market purchase volume drops to 0 in the collaborative model, meaning that the system did not purchase any electricity from the external grid within 24 hours. In other words, the collaborative operation of the hydrogen energy storage system and the liquid air energy storage system successfully achieved self-balancing of power supply and demand within the VPP, reducing the system's electricity purchase costs.

[0184] Figure 7 This demonstrates the change in flue gas treatment energy consumption over time. During low-load periods (e.g., periods 1-5), electricity prices are relatively cheap, so waste incineration processes the gas directly and uses photovoltaic power to adjust the storage tank level. During peak load periods (e.g., periods 10-15), newly generated or existing flue gas is stored in the storage tank without immediate processing. Until late at night (e.g., periods 22-23), the combustion unit still has a very small amount of flue gas that must be processed immediately (or the storage capacity is nearing its limit), so waste incineration processes the flue gas to prevent the storage tank from overloading. This shows that the system, through a strategy of "small-scale processing first – long-term full storage – late-night supplementary processing," shifts peak energy consumption to periods with lower energy consumption or abundant renewable resources, thus meeting environmental emission constraints while minimizing processing energy costs and equipment start-up and shutdown losses.

[0185] Figure 8 The operation of each heating unit was visually displayed. Data showed that during periods of high heat load, the gas-fired boilers undertook the main heating task; while during periods of high electricity load, the electrical output of the CHP units increased significantly, collaboratively completing the combined heat and power (CHP) task. This coordinated scheduling ensured that the system met the heat load while also maintaining stable grid operation, demonstrating that the system balanced electricity and heat demand through multi-energy complementarity.

[0186] Figure 9 This reflects the charging and discharging states of the electrical and thermal energy storage systems. During periods of ample wind power (e.g., periods 1-7), the electrical energy storage system primarily charges, while during peak load periods, it discharges to supplement the auxiliary system's power supply. Simultaneously, the thermal energy storage system regulates its charging and discharging based on changes in heat load, ensuring the stable operation of the heating network. These results demonstrate that energy storage systems play a crucial role in peak shaving and valley filling, reducing the pressure on the power grid and heating network.

[0187] To compare and analyze the impact of introducing hydrogen energy storage and liquefied air energy storage on the operating cost of the studied VPP, four comparison schemes were set up, as shown in Table 2.

[0188] Table 2 Four different VPP construction schemes

[0189]

[0190] Based on the four design schemes, the economic benefits, costs, and scheduling results of each aggregation unit were optimized and compared. The specific results are shown in Tables 3 and 4.

[0191] Table 3 Comparison of Benefits and Costs

[0192]

[0193] Table 4 Comparison of Scheduling Results

[0194]

[0195] 1) By Figure 10 and Figure 12 It can be seen that Scheme 2 has significant advantages over Scheme 1, which only includes basic units, in terms of carbon capture volume and carbon trading revenue, being 1108.5t and 238.34×10⁻⁶ higher, respectively. 2 This is mainly due to the introduction of hydrogen energy storage technology, which uses electricity-to-hydrogen equipment to convert surplus electricity into hydrogen, partially replacing natural gas for power generation. This reduces fossil fuel consumption, improves energy efficiency, and thus reduces system carbon emissions.

[0196] From a cost perspective, reduced natural gas consumption directly lowers fuel procurement costs, while decreased carbon emissions lead to higher carbon trading revenue. Figure 12 It can be seen that the dual factors resulted in a reduction of 510.54 × 10⁻⁶ in the net cost of VPP for Option 2 compared to Option 1. 2 This indicates that hydrogen energy storage provides an effective path to reduce the operating costs of virtual power plants and improve low-carbon efficiency. 2) Compared to Scheme 1, Scheme 3 involves liquefied air energy storage participating in peak shaving, smoothing the grid load; by Figure 11 It can be seen that the output of the carbon capture power plant was reduced by 460.8MW, which reduced the reliance on traditional units, indicating that liquefied air energy storage has a certain effect on smoothing the output fluctuations of the units.

[0197] 3) By Figure 11 It can be seen that, compared with Schemes 1, 2, and 3, Scheme 4 has the highest output of the CHP unit, at 5175MW, proving that liquid air energy storage and hydrogen energy storage are complementary in physical characteristics. The former is suitable for long-term energy storage and cross-period peak shaving, while the latter provides rapid response to compensate for short-term fluctuations, jointly improving system flexibility; at the same time, byFigure 12 As can be seen, VPP has the lowest net cost in Scheme 4, which reflects the economics of collaborative energy storage.

[0198] In summary, the synergistic operation framework of hydrogen energy storage and liquid air energy storage can reduce the net cost and carbon emissions of VPP, enable more efficient use of internal resources and optimize the energy structure, and enhance the VPP's ability to absorb clean energy and smooth load fluctuations.

Claims

1. A low-carbon economic dispatch method for a virtual power plant that considers the synergy of hydrogen energy storage and liquid air energy storage, characterized in that... Includes the following steps: Step 1: Establish a hydrogen energy storage model; Step 2: Establish a liquid air energy storage model to smooth out the output fluctuations of the unit; Step 3: Combining the hydrogen energy storage model established in Step 1 and the liquid air energy storage model established in Step 2, construct a collaborative model of hydrogen energy storage and liquid air energy storage; Step 4: Based on the hydrogen energy storage and liquid air energy storage collaborative model established in Step 3, construct and solve the "electricity-gas-heat-hydrogen" multi-energy complementary virtual power plant model.

2. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 1, characterized in that: In step 1, hydrogen energy storage is introduced into the virtual power plant, using hydrogen energy as an extension of P2G to supply hydrogen-blended natural gas to the natural gas market, thereby reducing carbon emissions. The hydrogen energy storage model specifically includes: 1) Hydrogen production by water electrolysis: In formula (1): P represents the amount of hydrogen produced by water electrolysis during time period t; t P2H η is the power used for hydrogen production via water electrolysis during time period t; P2H The efficiency of hydrogen production through water electrolysis; 2) Fuel cell power generation: In formula (2): η represents the actual amount of hydrogen consumed by the fuel cell during time period t; H2P For fuel cell efficiency; P t P2H The output power of the fuel cell generating electricity using hydrogen during time period t; 3) Hydrogen gas turbine power generation: In formula (3): η represents the amount of hydrogen used for power generation by the hydrogen gas turbine during time period t; HGT For hydrogen gas turbine efficiency; P t HGT The power generation capacity of the hydrogen gas turbine during time period t; 4) Dynamic management of hydrogen storage: In equation (4): The amount of hydrogen in the hydrogen storage tank during time period t; S H2,min S H2,max These represent the initial, minimum, and maximum hydrogen storage capacities, respectively; loss H2 This represents the loss rate during hydrogen storage. This represents the amount of hydrogen produced during the initial period through water electrolysis. This represents the actual amount of hydrogen consumed by the fuel cell during the initial period. The amount of hydrogen used for power generation by the hydrogen gas turbine in the initial period; The amount of hydrogen in the hydrogen storage tank during the t-1 time period; t represents the 24 time periods within a day.

3. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 2, characterized in that: In step 2, the liquid air energy storage model specifically includes: 1) Energy balance in energy storage state: In equation (5): The LAES energy storage status is shown for the initial period, period t, and period t-1, respectively. For initial energy storage; LAES charg,eff LAES discharg,eff The charge / discharge efficiency of LAES is divided into LAES and LAES. loss The percentage of energy loss during each period of energy storage for charging (liquefaction); P t LAES,charge P t LAES,discharge These represent the charging and discharging power of LAES during time period t; 2) Charge and discharge power constraints: In equation (6): P LAES,charge,max P LAES,discharge,max These are the maximum charge and discharge power of LAES, respectively. 3) Energy storage capacity limitations: In equation (7): S LAES,max This represents the maximum energy storage capacity of LAES.

4. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 3, characterized in that: In step 4, in order to collect real-time operating data of each unit and combine it with electricity price trends, renewable energy generation and electric heating load forecasts, and flexibly dispatch multiple energy sources such as electricity, heat, and hydrogen, a "electricity-gas-heat-hydrogen" multi-energy complementary virtual power plant model is established. The minimum net cost of operating the VPP system is as follows: obj=C F -I C +C WI +C H +C PG + C CS +C W +C M +C H2,OP - R H2 +C H2,GT -R H2，GT +LAES cost (9); In equation (9): obj is the objective function, i.e., the minimum net cost of operating the VPP system; C F Cost of carbon capture power plants; I C For carbon trading revenue; C WI Costs related to waste incineration power plants; C H For natural gas procurement costs; C PG For P2G equipment operating costs; C CS Cost of carbon sequestration; C W For the operation and maintenance costs of wind power and photovoltaic systems; C M C is the cost of purchasing electricity in the energy market. H2,OP For the operating cost of hydrogen energy systems; R H2 For fuel cell revenue; C H2,GT For the operating cost of hydrogen gas turbines; R H2，GT For hydrogen gas turbine revenue; LAES cost This refers to the operating cost of a liquid air energy storage system.

5. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 4, characterized in that: The specific expressions for each part of the objective function are as follows: ①. Cost of carbon capture power plants: In formula (10): To measure electricity generation P t G The corresponding variable costs for fuel and maintenance; 0.04(P t G ) 2 This is a secondary cost item, representing the non-linear impact of unit output and efficiency; ②. Carbon trading market revenue: In equation (11): P t GN The net output of the carbon capture power plant during period t; The net emissions during period t must be deducted from the capture amount; ③. Costs related to waste incineration power plants: In equation (12): P t WI The equivalent power output of the waste incineration power plant during time period t; ④. Natural gas procurement cost: In the above formula: Q t BUY V represents the amount of carbon dioxide purchased during time period t; t BUY V represents the amount of natural gas purchased during time period t; t CHP V t GB These represent the amount of CHP and natural gas consumed by the boiler during time period t, respectively; V t P2G Let t be the equivalent demand of P2G syngas for natural gas. The amount of natural gas equivalent to the power generation from hydrogen fuel cells and hydrogen gas turbines; ⑤. P2G equipment operating costs: In equation (15): P represents the amount of carbon dioxide purchased during time period t; t P2G The energy consumption of the P2G device during time period t; ⑥. Carbon sequestration costs: In equation (16): The amount of CO2 flowing into the flue gas storage tank during time period t; ⑦. Operation and maintenance costs of wind power and photovoltaic systems: In equation (17): P t W P t V These represent the available wind power and solar power output during time period t, respectively. ⑧. Cost of purchasing electricity in the energy market: In equation (18): The market electricity price for period t; P t EM Purchase electricity for period t; 9. Operating costs of hydrogen energy systems: In equation (19): k H2P k is the cost coefficient for hydrogen production via electrolysis. H2S P is the hydrogen storage cost coefficient. t P2H The hydrogen production power of water electrolysis during time period t; The amount of hydrogen in the hydrogen storage tank during time period t; ⑩. Fuel cell revenue: In equation (20): r H2 P represents the fuel cell revenue coefficient. t H2P The output power of the fuel cell generating electricity using hydrogen during time period t; Operating costs and benefits of hydrogen gas turbines: In the above formula: k H2,GT r is the operating cost coefficient for hydrogen gas turbines. H2,GT P is the revenue coefficient for hydrogen gas turbines. t HGT The power generation capacity of the hydrogen gas turbine during time period t; Operating costs of liquid air energy storage systems: In equation (23): LAES oper,cost P represents the operating cost coefficient for LAES. t LAES,charge P t LAES,discharge These represent the charging and discharging power of LAES during time period t.

6. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 5, characterized in that: VPP system constraints include constraints related to the CCPP-P2G model: 1) Total energy consumption constraint: P t C2P =P t P2G +P t CC (24); In equation (24): P t C2P P represents the total energy consumption during time period t. t P2G The energy consumption of the P2G device (electric-to-gas equipment) during time period t; P t CC Let t be the energy consumption of the carbon capture portion during time period t; 2) Constraints on wind and solar power curtailment: P t P2G =P t WA +P t VA (25); In equation (25): P t WA P represents the "curtailed" power generated by the wind power system during time period t; t VA The "curtailed" power generated by the photovoltaic system during time period t; 3) Energy consumption constraints for carbon capture: P t CC =P t A +P t op (26); In equation (26): P t A P represents the energy consumption of the stationary portion of the carbon capture system during time period t; t op The energy consumption of the stationary portion of the carbon capture system during time period t; 4) Power constraints of carbon capture power plants: P t GN =P t G -P t GC -P t Gα (27); In equation (27): P t G P represents the equivalent total power generation output of the carbon capture power plant during time period t; t GC P represents the energy consumed by the carbon capture power plant for carbon capture during time period t; t Gα The energy consumed during flue gas treatment in time period t; 5) Constraints on CO2 capture and P2G utilization: Q t CC =P t OP / 0.269 (28); In the above formula: The amount of CO2 captured by the CCPP–P2G system during time period t; V represents the total CO2 consumed by the P2G system. t P2G The volume of natural gas generated by the P2G system; η P2G The conversion efficiency of P2G equipment from electricity to gas; 6) Operational constraints of carbon capture power plants: 100≤P t G ≤400 (31)； 15≤P t GC +P t WC +P t VC +P t WIC ≤P t C,max (33); In the above formula: P t G The equivalent power output of the carbon capture power plant during time period t; The total amount of CO2 captured during time period t; P t GC P t WC P t VC P t WIC P represents the energy consumption provided for carbon capture by thermal power, wind power, photovoltaic power, and waste incineration power plants during time period t; t C,max This represents the maximum allowable energy consumption of the carbon capture system during time period t. 7) P2G operational constraints: 0≤P t P2G ≤200 (36)； In the formula: P t P2G The operating power of the P2G device during time period t.

7. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 6, characterized in that: The constraints of the VPP system also include constraints related to the electrical and thermal energy storage models: 1) Energy storage constraints: In equation (37): P represents the energy storage capacity of the battery at the end of time period t. t ESC P t ESD These represent the charging and discharging power of the energy storage system during time period t; η ESC η ESD These refer to the charging and discharging efficiencies of the energy storage system. 2) Thermal energy storage constraints: In equation (38): The heat storage capacity at the end of time period t; These represent the charging and heat dissipation power of the electrical storage system during time period t; η TSC η TSD These refer to the charging and discharging efficiencies of thermal energy storage, respectively.

8. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 7, characterized in that: The constraints of the VPP system also include constraints related to the waste-to-energy plant model: 1) Energy consumption constraints for flue gas treatment: In equation (39): P t α Total energy consumption for treating flue gas generated by waste incineration power plants; The amount of flue gas generated by the waste incineration power plant and directly used for flue gas treatment during time period t; The amount of flue gas extracted from the flue gas storage tank for flue gas treatment during time period t; 2) Operational constraints of waste incineration power plants: 60≤P t WI ≤100 (40)； 0.1×400≤V t WI,α ≤0.9×400 (44)； In the above formula: P t WI The output of the waste-to-energy power plant during period t; V t WI,α The amount of gas in the flue gas storage device during time period t; The amount of flue gas generated by the waste incineration power plant and directly used for flue gas treatment during time period t; The amount of flue gas flowing into the flue gas storage tank during time period t; The amount of flue gas extracted from the flue gas storage tank for flue gas treatment during time period t; This is for the output of the waste-to-energy power plant during the t-1 period; The amount of gas in the flue gas storage device during time period t-1.

9. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 8, characterized in that: The constraints related to the joint operation model of carbon capture-waste incineration-wind power-photovoltaics are as follows: The carbon capture power plant, a waste incineration power plant equipped with gas storage devices, and a wind / solar power system will operate in synergy; a portion of the wind and solar power generation will be used for the energy consumption of the carbon capture system; another portion will be used for the flue gas treatment system, and the remaining electricity will be fed into the grid; the constraints are as follows: P t CC =P t GC +P t WC +P t VC +P t WIC (45); P t α =P t Vα +P t Wα +P t Gα +P t WIα (46); P t W =P t WN +P t WC +P t Wα (47); P t V =P t VA +P t VN +P t VC +P t Vα (48); P t WI =P t WIN +P t WIC +P t WIα (49); In the formula: P t CC P represents the energy consumption of the carbon capture portion during time period t; t GC P represents the energy consumption of the carbon capture power plant for the carbon capture process during time period t. t WC P represents the carbon capture energy consumption borne by the wind turbine components during time period t; t VC P represents the carbon capture energy consumption borne by the photovoltaic unit during time period t; t WIC The carbon capture energy consumption shared by the waste-to-energy incineration plant during period t; P t α P represents the energy consumption of the flue gas treatment section during time period t; t Vα P t Wα P t WIα P t Gα Energy consumption for flue gas treatment at photovoltaic, wind power, waste incineration power plants, and carbon capture power plants during time period t; P t WN P t VN P t WIN These represent the grid-connected power generation capacity of wind power, photovoltaic power, and waste incineration power plants during time period t; P t W P t V P t WI These represent the predicted output of wind power, photovoltaic power, and waste incineration power generation during time period t; P t VA The "curtailed" power generated by the photovoltaic system during time period t; e represents the net CO2 emissions of the carbon capture power plant during period t; g The amount of CO2 generated per unit of equivalent power output of a carbon capture power plant.

10. The low-carbon economic dispatch method for a virtual power plant considering the synergy of hydrogen energy storage and liquid air energy storage as described in claim 9, characterized in that: Constraints related to the CHP and gas-fired boiler model include: 1) CHP unit constraints: 0≤P t CHP ≤140 (51)； In the above formula: P t CHP The electrical power output of the CHP unit during time period t; The thermal power output of the CHP unit during time period t; The total output power of the CHP unit during time period t; This represents the total output power of the CHP unit during the t-1 time period; 2) Constraints on gas-fired boilers: In the above formula: The heat output power of the gas-fired boiler during time period t; The heat output power of the gas-fired boiler during time period t-1; Electric power balance constraints include: In equation (56): P t GN P represents the net output of the carbon capture power plant during period t; t WIN For the period t, the net output of the waste incineration power plant to the grid is P. t CHP P represents the output electrical power of the CHP unit during time period t. t WN and P t VN These represent the grid-connected power of wind power and photovoltaic units during time period t; P t ESD P represents the energy storage discharge power during time period t. t EM P represents the amount of electricity purchased from the grid during time period t; t H2P and P t HGT These represent the power generation of the fuel cell and the hydrogen gas turbine during time period t, respectively; P t LAES,discharge P represents the liquid air energy storage discharge power during time period t. t P2G P represents the electrical energy consumed by the P2G device during time period t; t EL P represents the electrical load during time period t; t ESC P is the charging power of the energy storage system during time period t. t LAES,charge The charging power of liquid air energy storage during time period t.

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