Low-carbon energy storage configuration method and system considering synergistic operation of electric hydrogen hybrid energy storage

Abstract

The low-carbon energy storage configuration method and system considering the collaborative operation of electric-hydrogen hybrid energy storage comprise the following steps: establishing multi-energy flow balance constraints and device capacity and power upper and lower limit constraints; establishing an electric-hydrogen hybrid energy storage operation strategy, updating the multi-energy flow balance constraints based on the device start-stop state under the operation strategy; establishing an outer optimization scheduling model with the updated multi-energy flow balance constraints and device capacity and power upper and lower limit constraints as constraint conditions; establishing an inner optimization configuration model that comprehensively considers human comfort and maximizes new energy consumption; initializing a hybrid energy storage device configuration scheme, solving the outer optimization scheduling model, and obtaining an energy scheduling scheme; and determining the final configuration scheme by alternately fixing the configuration scheme and the energy scheduling scheme. Through the collaborative optimization configuration and scheduling of electric-hydrogen hybrid energy storage, the energy utilization efficiency is improved, carbon emissions are reduced, and user comfort is guaranteed, and low-carbon development and efficient new energy consumption are considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage configuration, and specifically relates to a low-carbon energy storage configuration method and system considering collaborative operation of electric-hydrogen hybrid energy storage. BACKGROUND

[0002] With the promotion of global energy transformation and low-carbon development, the demand for clean energy in industrial parks is increasing, and energy storage technology plays a key role in improving energy efficiency and promoting new energy consumption. Traditional energy storage configuration relies on lithium battery systems, and single energy storage method cannot meet the demand of industrial parks for efficient and low-carbon energy. Electric-hydrogen hybrid energy storage, as an emerging technology, combines the advantages of batteries and hydrogen energy, improves system flexibility and reliability, and helps to reduce carbon emissions. However, existing research has not fully considered the characteristics and application potential of electric-hydrogen hybrid energy storage, therefore, optimizing electric-hydrogen hybrid energy storage configuration has become an important issue in park energy management.

[0003] In the aspect of park energy storage configuration, the patent with publication number CN118735162A proposes a park energy storage configuration method considering energy storage available capacity attenuation, which calculates the energy storage life attenuation and the increase cost, combines with genetic algorithm to optimize the park energy storage configuration, improves the new energy consumption rate and the energy storage configuration precision. The patent with publication number CN117744938A considers economic, technical and robustness indexes in industrial park energy storage configuration, calculates the robustness index under uncertain scenarios, optimizes the energy storage configuration scheme, uses meta-heuristic algorithm to solve the optimization model, and obtains the energy storage configuration result with multi-objective balance. Existing park energy storage configuration mostly focuses on lithium battery application and optimization, ignoring the potential and advantages of electric-hydrogen hybrid energy storage. In the configuration and optimization of energy storage system, the traditional method fails to effectively combine the characteristics of electric-hydrogen hybrid energy storage.

[0004] For the electric hydrogen hybrid energy storage system, the existing energy storage configuration method includes: the patent with publication number CN119298133A provides a day-ahead optimization scheduling method and system for wind-solar-hydrogen storage off-grid operation system, proposes a day-ahead optimization scheduling method for wind-solar-hydrogen storage off-grid system, combines capacity configuration and scheduling model, adopts improved particle swarm algorithm to optimize system cost and operation efficiency, realizes optimization of mixed energy storage system charge-discharge time sequence, and has influence on optimization configuration and operation cost of wind-solar-hydrogen storage off-grid system; and Chinese patent CN119813275A discloses a capacity configuration method and device for electric-hydrogen hybrid energy storage system, constructs a flatness cost model and considers multiple constraints, improves the refinement of capacity allocation and the adaptability of power grid, solves the problems that the existing electric-hydrogen hybrid energy storage system capacity allocation is low in refinement, and the energy storage cannot meet the demand of power grid; in addition, the patent with publication number CN114977217A provides an electric-hydrogen hybrid energy storage system configuration method and device, adopts a multi-objective optimization model and a grey target decision, optimizes system cost and stability, and thus improves the problems of power loss, load fluctuation and voltage fluctuation in the system.

[0005] In summary, the existing technology mainly focuses on the charge-discharge time sequence and energy scheduling of the battery, lacks dynamic consideration of the SOC value of the electric energy storage system, and thus cannot flexibly adjust the charge-discharge strategy according to the actual state of the battery, resulting in low efficiency of the battery in the charge-discharge process; in addition, the existing technology cannot maximize the consumption rate of renewable energy, and it is difficult to realize efficient cooperation between new energy output and energy storage adjustment, thereby leading to the increase of carbon emissions. SUMMARY

[0006] In order to solve the technical problems of lacking dynamic consideration of the state of charge of the battery and being unable to maximize the consumption of new energy in the prior art, the present application provides a low-carbon energy storage configuration method and system considering the cooperative operation of electric-hydrogen hybrid energy storage. The method comprises: establishing multi-energy flow balance constraints and device capacity and power upper and lower limit constraints; establishing an electric-hydrogen hybrid energy storage operation strategy, updating the multi-energy flow balance constraints based on the device start-stop state under the operation strategy; establishing an outer optimization scheduling model with the updated multi-energy flow balance constraints and device capacity and power upper and lower limit constraints as constraint conditions; establishing an inner optimization configuration model that comprehensively considers human comfort and maximizes new energy consumption; initializing the configuration scheme of the hybrid energy storage device, solving the outer optimization scheduling model to obtain an energy scheduling scheme; and determining the final configuration scheme by alternately fixing the configuration scheme and the energy scheduling scheme. The present application realizes the improvement of energy utilization efficiency, the reduction of carbon emissions and the guarantee of user comfort through the cooperative optimization configuration and scheduling of electric-hydrogen hybrid energy storage, and takes into account low-carbon development and efficient consumption of new energy.

[0007] The present application adopts the following technical solutions.

[0008] This invention provides a low-carbon energy storage configuration method that considers the synergistic operation of hybrid electric and hydrogen energy storage, including:

[0009] S1. Construct a multi-energy flow model of the park's integrated energy system, and establish multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power.

[0010] S2. Establish an electric-hydrogen hybrid energy storage operation strategy, and update the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy.

[0011] S3. Using the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity and power in S1 as constraints, establish an outer-layer optimization scheduling model that maximizes the net benefit of the park's hybrid electric-hydrogen energy storage and minimizes carbon emissions.

[0012] S4. Establish an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources;

[0013] S5. Initialize the configuration scheme of the hybrid energy storage device, solve the outer layer optimization scheduling model, and obtain the energy scheduling scheme; by alternating between the fixed configuration scheme and the energy scheduling scheme, solve the outer layer optimization scheduling model and the inner layer optimization configuration model, update the configuration scheme and the energy scheduling scheme, and determine the final configuration scheme.

[0014] Preferably, in S1, the park's integrated energy system includes a power supply unit, a hydrogen supply unit, a heating unit, and a cooling unit. The power supply unit includes distributed photovoltaic and wind power renewable energy, hydrogen fuel cells, electric energy storage, and grid-purchased electricity. The heating unit includes a hydrogen boiler. The cooling unit includes an electrically driven ice storage air conditioner. The hydrogen supply system includes external hydrogen supply, hydrogen storage tanks, and hydrogen production equipment using an electrolyzer.

[0015] The multi-energy flow model of the park's integrated energy system includes energy balance constraints for power supply units, hydrogen supply units, heating units, and cooling units, as well as upper and lower power limits for equipment within each unit.

[0016] Preferably, in S2, the hybrid electric-hydrogen energy storage operation strategy is as follows:

[0017] When there is wind and / or solar curtailment in the park, the electrolytic cell equipment will be started based on the park's carbon emission intensity, and auxiliary energy storage charging will be provided.

[0018] When there is no wind or solar curtailment in the park, the start / stop status of the energy storage is set according to the state of charge of the energy storage.

[0019] Preferably, when wind curtailment and / or solar curtailment occur in the industrial park:

[0020] When the carbon emissions of the park exceed the set threshold, the electrolyzer equipment and ice storage air conditioning will be started, provided that the load demand is met; if the power of the electrolyzer equipment and / or the capacity of the hydrogen storage tank have reached the upper limit, the electric energy storage equipment and hydrogen fuel cells will be started and the electrolyzer equipment will be shut down; when the power of the electrolyzer equipment and the capacity of the hydrogen storage tank have not reached the upper limit, the electrolyzer equipment will operate normally.

[0021] If the carbon emissions of the park do not exceed the set threshold, the electrolyzer equipment will be started to produce hydrogen and the energy storage equipment will be started to charge. When the power of the electrolyzer equipment and / or the capacity of the hydrogen storage tank reach the upper limit, the electrolyzer equipment will be shut down and the ice storage air conditioner and hydrogen fuel cell will be turned on. If the power of the electrolyzer equipment and the capacity of the hydrogen storage tank do not reach the upper limit, the electrolyzer equipment will operate normally.

[0022] Preferably, when there is no wind or solar power curtailment in the park:

[0023] The energy storage device acquires the state of charge (SOC) in real time. When the SOC is within a predetermined range, the device remains on or off. When the SOC is less than the minimum value of the predetermined range, the device is activated to prevent the battery from continuing to discharge deeply. When the SOC is greater than the maximum value of the predetermined range, the device is deactivated.

[0024] Preferably, based on the equipment start-up and shutdown status under the operation strategy, the corresponding grid power purchase, fuel cell charging / discharging power, energy storage device charging / discharging power, electrolyzer power consumption, and ice storage air conditioning power consumption in the electrical balance condition of the multi-energy flow balance constraint are adjusted, and the electrolyzer hydrogen production power and fuel cell hydrogen consumption power in the thermal balance condition of the multi-energy flow balance constraint are adjusted.

[0025] Preferably, the objective function of the outer-layer optimization scheduling model in S3 is:

[0026] ;

[0027] In the formula, This indicates the annual net revenue of the park's integrated energy system; The annual comprehensive revenue of the park's integrated energy system includes revenue from electricity sales and hydrogen sales; For equipment operation and maintenance costs; The cost of purchasing electricity from the power grid; Cost of purchasing hydrogen from external sources; This is the sum of the cost of energy storage equipment depreciation and the cost of new energy storage configuration; Indicates carbon emissions; The penalty amount per unit of CO2 emissions; Carbon emission factors from purchasing electricity from the grid; The power purchased by the park from the grid at time t; T is the operation control cycle of the configuration method;

[0028] in, Calculate using the following formula:

[0029] ;

[0030] In the formula, This represents the charging and discharging power of the energy storage device at time t, with positive numbers indicating charging and negative numbers indicating discharging. Let t represent the hydrogen storage and release power of the hydrogen storage tank at time t, with positive numbers representing hydrogen storage and negative numbers representing hydrogen release; The cost of energy storage investment; Investment cost for hydrogen storage tanks; This refers to the depreciation factor for energy storage equipment. This refers to the depreciation factor for hydrogen storage tanks; and This refers to the number of electric energy storage and hydrogen storage tanks in the park's integrated energy system.

[0031] Preferably, the objective function of the inner-layer optimization configuration model in S4 is:

[0032] ;

[0033] The corresponding human comfort constraint function is:

[0034] ;

[0035] In the formula, This indicates the new energy absorption capacity of the park's integrated energy system; This refers to the output power of distributed wind power. This refers to the output power of distributed photovoltaic systems. This refers to the discharge power of the fuel cell. This represents the total electrical load on the demand side. This refers to the current indoor temperature. This represents the total cooling load on the demand side. This represents the total heat load on the demand side. For air quality; The specific heat capacity of air; Indicates the current time t The time difference with the previous moment.

[0036] Preferably, S5 includes:

[0037] S5.1 Initialize the configuration scheme of the hybrid energy storage device;

[0038] S5.2 transforms the multi-objective outer-layer optimization scheduling model into a single-objective outer-layer optimization scheduling model, substitutes the configuration scheme of hybrid energy storage devices into the model, and solves the energy scheduling scheme.

[0039] S5.3 transforms the multi-objective inner-layer optimization configuration model into a single-objective inner-layer optimization configuration model, substitutes the energy dispatch scheme into the model, and solves the configuration scheme of the hybrid energy storage device.

[0040] S5.4 Update the configuration scheme of the hybrid energy storage device and calculate the energy utilization rate under the energy dispatch scheme. When the difference in energy utilization rate under adjacent iterations is not less than the predetermined difference threshold, return to S5.2 to resolve the energy dispatch scheme and the configuration scheme of the hybrid energy storage device; otherwise, output the configuration scheme of the hybrid energy storage device at this time.

[0041] Preferably, S5.2 includes:

[0042] The multi-objective function of the outer-layer optimization scheduling model is converted into a single-objective function by weighting, resulting in the outer-layer optimization objective function. Based on multi-energy flow balance constraints and upper and lower limits of equipment capacity and power, multiple energy scheduling schemes are initialized. The outer-layer optimization objective function value of each energy scheduling scheme is calculated, and the two energy scheduling schemes with the largest function values ​​are selected. Parameters at multiple locations within the selected energy scheduling schemes are then swapped. For the swapped energy scheduling schemes, multiple locations within the selected schemes are selected, and perturbations are added to the parameters at these locations to generate new energy scheduling schemes. The corresponding outer-layer optimization objective function value is recalculated, and the energy scheduling scheme is updated. This process continues until a predetermined number of iterations is reached, at which point the energy scheduling scheme with the highest outer-layer optimization objective function value at that iteration count is output.

[0043] Another aspect of the present invention provides a low-carbon energy storage configuration system considering the synergistic operation of hybrid electric-hydrogen energy storage, comprising:

[0044] The constraint construction module constructs a multi-energy flow model of the park's integrated energy system, and establishes multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power.

[0045] The constraint update module establishes an operation strategy for hybrid electric-hydrogen energy storage and updates the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy.

[0046] The outer model construction module uses the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity and power in S1 as constraints to establish an outer optimization scheduling model that maximizes the net benefits of electric-hydrogen hybrid energy storage in the park and minimizes carbon emissions.

[0047] The inner-layer model construction module establishes an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources.

[0048] The configuration scheme solution module initializes the configuration scheme of the hybrid energy storage device, solves the outer layer optimization scheduling model, and obtains the energy scheduling scheme. By alternating between the fixed configuration scheme and the energy scheduling scheme, it solves the outer layer optimization scheduling model and the inner layer optimization configuration model, updates the configuration scheme and the energy scheduling scheme, and determines the final configuration scheme.

[0049] Compared with the prior art, the beneficial effects of the present invention include at least the following:

[0050] 1. This invention introduces dynamic monitoring and control of the state of charge (SOC) of the energy storage system into the electric-hydrogen hybrid energy storage operation strategy, enabling the energy storage device to flexibly respond to the fluctuations in renewable energy generation during different operating periods. This approach ensures that excess electricity is absorbed in a timely manner during periods of high renewable energy generation and released rationally during periods of low generation, thereby significantly improving the utilization rate of renewable energy and reducing wind and solar curtailment.

[0051] 2. The outer-layer optimization scheduling model of this invention aims to maximize the net benefits of energy storage and minimize carbon emissions. By increasing the proportion of renewable energy consumption and storage capacity, this method significantly reduces the overall carbon emission level of the system, enabling the electric hydrogen energy storage to achieve dynamic balance between load and energy supply during operation, and effectively reducing the system's dependence on high-carbon energy during peak electricity consumption.

[0052] 3. The inner-layer optimization configuration model of this invention incorporates a human comfort index during the optimization process, ensuring that the energy dispatch process satisfies the experience of park staff while fully absorbing renewable energy generation. This method can improve the utilization rate of new energy sources without sacrificing comfort, and avoid compensatory energy consumption caused by a decrease in comfort. Attached Figure Description

[0053] Figure 1 This is a flowchart illustrating a low-carbon energy storage configuration method considering the coordinated operation of hybrid electric and hydrogen energy storage provided in an embodiment of the present invention.

[0054] Figure 2 This is a schematic diagram of the electric-hydrogen hybrid energy storage operation strategy provided in an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0056] Example 1

[0057] This embodiment provides a low-carbon energy storage configuration method that considers the synergistic operation of hybrid electric and hydrogen energy storage, such as... Figure 1 As shown, the specific steps are as follows:

[0058] S1. Construct a multi-energy flow model of the park's integrated energy system, and establish multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power.

[0059] In S1, the main systems of the park include a power supply unit, a heating unit, a cooling unit, and a hydrogen supply unit. The power supply unit includes distributed photovoltaic and wind power renewable energy output, hydrogen fuel cells, electric energy storage, and grid power purchase. The heating unit uses hydrogen boilers to produce heat from hydrogen, using hydrogen as an energy source and converting it into heat energy. The hydrogen supply unit includes external hydrogen supply, hydrogen release from hydrogen storage tanks, and hydrogen production from electrolyzers. The cooling unit includes electrically driven ice storage air conditioning.

[0060] The multi-energy flow model of the park's integrated energy system includes multi-energy flow balance constraints for power supply, hydrogen supply, heating, and cooling units, as well as upper and lower limits for the capacity and power of equipment within each unit; the specific formula is expressed as follows:

[0061] ;

[0062] In the formula, the first equation represents the electrical equilibrium condition, and the second equation represents the thermal equilibrium condition. t For a specific moment; This refers to the output power of distributed wind power. This refers to the output power of distributed photovoltaic systems. for t Power purchased from the power grid at all times; This represents the start / stop status of grid-connected electricity sales; 1 indicates start and 0 indicates stop. This represents the charging / discharging power of the fuel cell; a positive number indicates charging, and a negative number indicates discharging. This represents the start / stop status of the fuel cell, with 1 for start and 0 for stop. This represents the total electrical load on the demand side. This refers to the charging / discharging power of the energy storage device; a positive number indicates charging, and a negative number indicates discharging. This indicates the start / stop status of the energy storage device; 1 represents start and 0 represents stop. This refers to the electrical power required for the electrolytic cell; This indicates the start / stop status of the electrolytic cell; 1 represents start and 0 represents stop. Power consumption for ice storage air conditioning; This indicates the start / stop status of the ice storage air conditioner; 1 represents start and 0 represents stop. for t The power to purchase hydrogen from external sources at all times; Hydrogen production power of the electrolyzer; Hydrogen power consumption for hydrogen fuel cells; The hydrogen charging / discharging power of the hydrogen storage tank; positive numbers represent hydrogen storage, and negative numbers represent hydrogen discharging. The heating capacity of the hydrogen boiler; This represents the total heat load on the demand side. The cooling capacity of the ice storage air conditioner; This represents the total cooling load on the demand side. q As a seasonal indicator, it is set to 0 in winter and 1 at other times; and respectively equipment Upper and lower limits of power; and respectively equipment The upper and lower limits of capacity.

[0063] S2. Establish an electric-hydrogen hybrid energy storage operation strategy, and update the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy.

[0064] In S2, the hybrid electric-hydrogen energy storage operation strategy is as follows:

[0065] See Figure 2 When wind and / or solar power curtailment occurs in the industrial park, the electrolytic cell equipment will be activated based on the park's carbon emission intensity, and auxiliary energy storage charging will be provided; specifically including:

[0066] When the carbon emissions of the industrial park exceed the set threshold, the electrolytic cell equipment will be started to fully absorb wind and solar energy, provided that the load demand is met. and ice storage air conditioning To absorb surplus wind and solar power; if the electrolyzer equipment power and / or hydrogen storage tank capacity have reached their upper limits, then start the electric energy storage equipment. and hydrogen fuel cells Shutting down the electrolytic cell equipment is Excess electricity will be converted, stored, or supplied to the load; the electrolyzer equipment will operate normally when the power of the electrolyzer equipment and the capacity of the hydrogen storage tank have not reached their upper limits; and the remaining electricity will be sold to the grid when the wind and solar power consumption reaches 95%.

[0067] If the carbon emissions of the industrial park do not exceed the set threshold, the electrolytic cell equipment will be started first. Hydrogen production is carried out, and the electric energy storage equipment is started. And appropriately charge the energy storage; when the power of the electrolyzer equipment and / or the capacity of the hydrogen storage tank reach the upper limit, shut down the electrolyzer equipment. Turn on the ice storage air conditioner and hydrogen fuel cells Convert excess electrical energy; if the power of the electrolyzer equipment and the capacity of the hydrogen storage tank have not reached the upper limit, the electrolyzer equipment is operated normally; when the wind and solar energy consumption reaches 95%, the electrolyzer equipment, electric energy storage and ice storage air conditioning that are in operation are shut down, and the remaining electrical energy is sold.

[0068] When there is no wind or solar curtailment in the industrial park, the start / stop status of the energy storage system is set according to its state of charge; specifically including:

[0069] The system acquires the state of charge (SOC) of the energy storage device in real time. When the SOC is within a predetermined range of 30% to 80%, the device's start / stop status remains unchanged. When the SOC falls below 30%, the device is activated. To prevent the battery from continuing to discharge deeply; when the state of charge of the energy storage device is greater than 80%, shut down the energy storage device. Avoid overcharging the battery to protect its lifespan.

[0070] Based on the equipment start-up and shutdown status under the operation strategy, adjust the corresponding grid power purchase, fuel cell charging / discharging power, energy storage device charging / discharging power, electrolyzer power consumption, and ice storage air conditioning power consumption in the electrical balance condition of the multi-energy flow balance constraint; and adjust the electrolyzer hydrogen production power and fuel cell hydrogen consumption power in the thermal balance condition of the multi-energy flow balance constraint.

[0071] The main optimization objective of this embodiment is to maximize the annual net revenue and minimize the carbon emissions of the park's integrated energy system. In order to obtain the optimal number of hybrid energy storage configurations, it is divided into an outer-layer optimization scheduling model and an inner-layer optimization configuration model.

[0072] S3. Using the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity and power in S1 as constraints, an outer-layer optimization scheduling model is established to maximize the net benefits of hybrid electric-hydrogen energy storage in the park and minimize carbon emissions.

[0073] The outer-layer optimization scheduling model is used to coordinate the energy allocation of the entire park, aiming to maximize the annual net benefit of the park's integrated energy system and minimize carbon emissions. The outer-layer optimization scheduling model is established using the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity power obtained in S1 as constraint functions. The objective function of the outer-layer optimization scheduling model is:

[0074] ;

[0075] In the formula, This indicates the annual net revenue of the park's integrated energy system; The annual comprehensive revenue of the park's integrated energy system mainly includes revenue from electricity sales and hydrogen sales; Indicates carbon emissions; The penalty amount per unit of CO2 emissions; Carbon emission factors from purchasing electricity from the grid; For equipment operation and maintenance costs; The cost of purchasing electricity from the power grid; Cost of purchasing hydrogen from external sources; T represents the depreciation cost of the energy storage equipment; T is the operating control cycle of the configuration method.

[0076] The specific formula for cost is expressed as follows:

[0077] ;

[0078] In the formula, For the operation and maintenance costs of distributed photovoltaic units; For the operation and maintenance costs of distributed photovoltaic units; For the operating cost of the electrolytic cell; For fuel cell operating costs; Operating costs for hydrogen boilers; The operating cost of ice storage air conditioning; The maintenance costs of each piece of equipment, of which This refers to distributed photovoltaic (PV) generators, distributed wind turbines, electrolyzers, hydrogen fuel cells, hydrogen boilers, and ice storage air conditioning equipment. The operating cost coefficients for the above equipment; The output power corresponding to the above devices; for Time-of-use pricing for electricity purchased from the grid at any given time; for The price of hydrogen purchased from external sources is constantly being monitored; The total operating cost of hybrid energy storage equipment; The cost of energy storage investment; Investment cost for hydrogen storage tanks; This refers to the depreciation factor for energy storage equipment. This refers to the depreciation factor for hydrogen storage tanks; , Regarding the number of energy storage devices and hydrogen storage tanks, it is assumed that the park already has 4 energy storage devices, of which , .

[0079] S4. Establish an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources.

[0080] The inner-layer optimization model considers the quantity and configuration of hybrid energy storage devices, aiming to maximize the absorption of new energy in the park through the collaborative work of these devices, and to ensure comfortable indoor temperatures through air conditioning regulation. The specific formula for the inner-layer optimization configuration model is expressed as follows:

[0081] ;

[0082] The corresponding human comfort constraint function is:

[0083] ;

[0084] In the formula, This indicates the new energy absorption capacity of the park's integrated energy system; This represents the total electrical load on the demand side. The current indoor temperature is in °C. The total cooling load on the demand side is expressed in kW, representing the cooling power supplied at time t. The total heat load on the demand side is expressed in kW, representing the heating power at time t. The mass of air, expressed in kg; is the specific heat capacity of air, expressed in kJ / (kg·℃); Indicates the current time t In this embodiment, the time difference from the previous moment is 1 hour.

[0085] S5. Initialize the configuration scheme of the hybrid energy storage device, solve the outer layer optimization scheduling model, and obtain the energy scheduling scheme; by alternating between the fixed configuration scheme and the energy scheduling scheme, solve the outer layer optimization scheduling model and the inner layer optimization configuration model, update the configuration scheme and the energy scheduling scheme, and determine the final configuration scheme.

[0086] S5.1 Initialize the configuration scheme of the hybrid energy storage device, that is, initialize the number of electrical energy storage devices and hydrogen storage tanks. x 0 and y 0 .

[0087] S5.2 transforms the multi-objective outer-layer optimization scheduling model into a single-objective outer-layer optimization scheduling model, substitutes the configuration scheme of hybrid energy storage devices into the model, and solves the energy scheduling scheme.

[0088] As a preferred implementation, the multi-objective function of the outer optimization scheduling model is transformed into a single-objective function by weighting, as shown in the following formula:

[0089] ;

[0090] In the formula, For the first k Energy scheduling schemes under a certain number of iterations Optimize the objective function for the outer layer; This is a weighting coefficient for carbon emissions, used to measure the importance of the benefits of the park's integrated energy system to carbon emissions;

[0091] Based on multi-energy flow balance constraints and upper and lower limits of equipment capacity power constraints, 20 energy dispatch schemes are initialized. The outer optimization objective function value of each energy dispatch scheme is calculated, and the two energy dispatch schemes with the largest function values ​​are selected. Parameters at multiple locations within the selected energy dispatch schemes are swapped. For the swapped energy dispatch schemes, multiple locations within the selected energy dispatch schemes are selected, and perturbations are added to the parameters at these locations to generate new energy dispatch schemes. The corresponding outer optimization objective function value is recalculated, and the energy dispatch schemes are updated. This process continues until a predetermined number of iterations is reached, at which point the energy dispatch scheme with the highest outer optimization objective function value at that iteration count is output.

[0092] S5.3 transforms the multi-objective inner-layer optimization configuration model into a single-objective inner-layer optimization configuration model, substitutes the energy dispatch scheme into the model, and solves the configuration scheme of the hybrid energy storage device.

[0093] As a preferred implementation, the multi-objective function of the inner optimization configuration model is transformed into a single-objective function by weighting, as shown in the following formula:

[0094] ;

[0095] In the formula, For the first k Configuration schemes for hybrid energy storage devices under a certain number of iterations; This represents the inner optimization objective function; This is a weighting coefficient for the depreciation cost of energy storage equipment, used to measure the importance of new energy consumption and the depreciation cost of energy storage equipment.

[0096] The methods for solving the configuration scheme of hybrid energy storage devices in this embodiment include, but are not limited to, integer linear programming, dynamic programming, particle swarm optimization, etc.

[0097] S5.4 updates the configuration scheme of the hybrid energy storage device and calculates the energy utilization rate under the energy dispatch scheme. If the difference in energy utilization rate between adjacent iterations is not less than a predetermined difference threshold, return to S5.2 to resolve the energy dispatch scheme and the configuration scheme of the hybrid energy storage device; otherwise, output the current configuration scheme of the hybrid energy storage device. The specific formula for calculating the energy utilization rate is as follows:

[0098] ;

[0099] In the formula, This indicates energy utilization rate.

[0100] Example 2

[0101] This embodiment provides a low-carbon energy storage configuration system considering hybrid electric-hydrogen energy storage, including:

[0102] The constraint construction module constructs a multi-energy flow model of the park's integrated energy system, and establishes multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power.

[0103] The constraint update module establishes an operation strategy for hybrid electric-hydrogen energy storage and updates the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy.

[0104] The outer model construction module uses the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity and power in S1 as constraints to establish an outer optimization scheduling model that maximizes the net benefits of electric-hydrogen hybrid energy storage in the park and minimizes carbon emissions.

[0105] The inner-layer model construction module establishes an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources.

[0106] The configuration scheme solution module initializes the configuration scheme of the hybrid energy storage device, solves the outer layer optimization scheduling model, and obtains the energy scheduling scheme. By alternating between the fixed configuration scheme and the energy scheduling scheme, it solves the outer layer optimization scheduling model and the inner layer optimization configuration model, updates the configuration scheme and the energy scheduling scheme, and determines the final configuration scheme.

[0107] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0108] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0109] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0110] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage, characterized in that, include: S1. Construct a multi-energy flow model of the park's integrated energy system, and establish multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power; wherein, the park's integrated energy system includes a power supply unit, a hydrogen supply unit, a heating unit, and a cooling unit; S2. Establish an electric-hydrogen hybrid energy storage operation strategy, and update the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy; the electric-hydrogen hybrid energy storage operation strategy is as follows: When the industrial park experiences wind and / or solar power curtailment, the electrolytic cell equipment will be activated based on the park's carbon emission intensity, and auxiliary energy storage charging will be provided; specifically: When the carbon emissions of the park exceed the set threshold, the electrolyzer equipment and ice storage air conditioning will be started, provided that the load demand is met; if the power of the electrolyzer equipment and / or the capacity of the hydrogen storage tank have reached the upper limit, the electric energy storage equipment and hydrogen fuel cells will be started and the electrolyzer equipment will be shut down; when the power of the electrolyzer equipment and the capacity of the hydrogen storage tank have not reached the upper limit, the electrolyzer equipment will operate normally. If the carbon emissions of the park do not exceed the set threshold, the electrolyzer equipment will be started to produce hydrogen and the energy storage equipment will be started to charge; when the power of the electrolyzer equipment and / or the capacity of the hydrogen storage tank reach the upper limit, the electrolyzer equipment will be shut down and the ice storage air conditioner and hydrogen fuel cell will be turned on; if the power of the electrolyzer equipment and the capacity of the hydrogen storage tank do not reach the upper limit, the electrolyzer equipment will operate normally. When there is no wind or solar curtailment in the industrial park, the start / stop status of the energy storage is set according to its state of charge; specifically: The system acquires the state of charge (SOC) of the energy storage device in real time. When the SOC is within a predetermined range, the device remains on or off. When the SOC is less than the minimum value of the predetermined range, the device is activated to prevent the battery from continuing to discharge deeply. When the SOC is greater than the maximum value of the predetermined range, the device is deactivated. S3. Using the updated multi-energy flow balance constraints and equipment capacity power upper and lower limit constraints as constraints, establish an outer-layer optimization scheduling model that maximizes the net benefit of the park's hybrid electric-hydrogen energy storage and minimizes carbon emissions. S4. Establish an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources; S5. Initialize the configuration scheme of the hybrid energy storage device, solve the outer layer optimization scheduling model, and obtain the energy scheduling scheme; by alternating between the fixed configuration scheme and the energy scheduling scheme, solve the outer layer optimization scheduling model and the inner layer optimization configuration model, update the configuration scheme and the energy scheduling scheme, and determine the final configuration scheme.

2. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 1, characterized in that: In S1, the power supply unit includes distributed photovoltaic and wind power renewable energy, hydrogen fuel cells, electric energy storage and grid power purchase; the heating unit includes a hydrogen boiler; the cooling unit includes an electrically driven ice storage air conditioner; and the hydrogen supply system includes external hydrogen supply, hydrogen storage tanks and electrolyzer hydrogen production equipment. The multi-energy flow model of the park's integrated energy system includes energy balance constraints for power supply units, hydrogen supply units, heating units, and cooling units, as well as upper and lower power limits for equipment within each unit.

3. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 1, characterized in that: Based on the equipment start-up and shutdown status under the operation strategy, adjust the corresponding grid power purchase, fuel cell charging / discharging power, energy storage device charging / discharging power, electrolyzer power consumption, and ice storage air conditioning power consumption in the electrical balance condition of the multi-energy flow balance constraint; and adjust the electrolyzer hydrogen production power and fuel cell hydrogen consumption power in the thermal balance condition of the multi-energy flow balance constraint.

4. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 1, characterized in that: The objective function of the outer-layer optimization scheduling model in S3 is: ； In the formula, This indicates the annual net revenue of the park's integrated energy system; The annual comprehensive revenue of the park's integrated energy system includes revenue from electricity sales and hydrogen sales; For equipment operation and maintenance costs; The cost of purchasing electricity from the power grid; Cost of purchasing hydrogen from external sources; This is the sum of the cost of energy storage equipment depreciation and the cost of new energy storage configuration; Indicates carbon emissions; The penalty amount per unit of CO2 emissions; Carbon emission factors from purchasing electricity from the grid; The power purchased by the park from the grid at time t; T is the operation control cycle of the configuration method; in, Calculate using the following formula: ； In the formula, This represents the charging and discharging power of the energy storage device at time t, with positive numbers indicating charging and negative numbers indicating discharging. Let t represent the hydrogen storage and release power of the hydrogen storage tank at time t, with positive numbers representing hydrogen storage and negative numbers representing hydrogen release; The cost of energy storage investment; Investment cost for hydrogen storage tanks; This refers to the depreciation factor for energy storage equipment. This refers to the depreciation factor for hydrogen storage tanks; and This refers to the number of electric energy storage and hydrogen storage tanks in the park's integrated energy system.

5. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 1, characterized in that: The objective function of the inner-layer optimal configuration model in S4 is: ； The corresponding human comfort constraint function is: ； In the formula, This indicates the new energy absorption capacity of the park's integrated energy system; This refers to the output power of distributed wind power. This refers to the output power of distributed photovoltaic systems. This refers to the discharge power of the fuel cell. This represents the total electrical load on the demand side. This refers to the current indoor temperature. This represents the total cooling load on the demand side. This represents the total heat load on the demand side. For air quality; The specific heat capacity of air; Indicates the current time t The time difference with the previous moment.

6. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 1, characterized in that: S5 includes: S5.1 Initialize the configuration scheme of the hybrid energy storage device; S5.2 transforms the multi-objective outer-layer optimization scheduling model into a single-objective outer-layer optimization scheduling model, substitutes the configuration scheme of hybrid energy storage devices into the model, and solves the energy scheduling scheme. S5.3 transforms the multi-objective inner-layer optimization configuration model into a single-objective inner-layer optimization configuration model, substitutes the energy dispatch scheme into the model, and solves the configuration scheme of the hybrid energy storage device. S5.4 Update the configuration scheme of the hybrid energy storage device and calculate the energy utilization rate under the energy dispatch scheme. When the difference in energy utilization rate under adjacent iterations is not less than the predetermined difference threshold, return to S5.2 to resolve the energy dispatch scheme and the configuration scheme of the hybrid energy storage device; otherwise, output the configuration scheme of the hybrid energy storage device at this time.

7. The low-carbon energy storage configuration method considering the synergistic operation of hybrid electric-hydrogen energy storage according to claim 6, characterized in that: S5.2 includes: The multi-objective function of the outer-layer optimization scheduling model is converted into a single-objective function by weighting, resulting in the outer-layer optimization objective function. Based on multi-energy flow balance constraints and upper and lower limits of equipment capacity and power, multiple energy scheduling schemes are initialized. The outer-layer optimization objective function value of each energy scheduling scheme is calculated, and the two energy scheduling schemes with the largest function values ​​are selected. Parameters at multiple locations within the selected energy scheduling schemes are then swapped. For the swapped energy scheduling schemes, multiple locations within the selected schemes are selected, and perturbations are added to the parameters at these locations to generate new energy scheduling schemes. The corresponding outer-layer optimization objective function value is recalculated, and the energy scheduling scheme is updated. This process continues until a predetermined number of iterations is reached, at which point the energy scheduling scheme with the highest outer-layer optimization objective function value at that iteration count is output.

8. A low-carbon energy storage configuration system considering the synergistic operation of hybrid electric-hydrogen energy storage, comprising the method described in any one of claims 1-7, characterized in that, include: The constraint construction module constructs a multi-energy flow model of the park's integrated energy system, and establishes multi-energy flow balance constraints and upper and lower limits constraints on equipment capacity and power. The constraint update module establishes an operation strategy for hybrid electric-hydrogen energy storage and updates the multi-energy flow balance constraints based on the equipment start-up and shutdown status under the operation strategy. The outer model construction module uses the multi-energy flow balance constraint updated in S2 and the upper and lower limits of equipment capacity and power in S1 as constraints to establish an outer optimization scheduling model that maximizes the net benefits of electric-hydrogen hybrid energy storage in the park and minimizes carbon emissions. The inner-layer model construction module establishes an inner-layer optimization configuration model that integrates human comfort and maximizes the consumption of new energy sources. The configuration scheme solution module initializes the configuration scheme of the hybrid energy storage device, solves the outer layer optimization scheduling model, and obtains the energy scheduling scheme. By alternating between the fixed configuration scheme and the energy scheduling scheme, it solves the outer layer optimization scheduling model and the inner layer optimization configuration model, updates the configuration scheme and the energy scheduling scheme, and determines the final configuration scheme.

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