Short-time scale low-carbon optimal scheduling method and system for island integrated energy system

Abstract

The invention belongs to the technical field of island integrated energy systems, and particularly discloses a short-time scale low-carbon optimal scheduling method and system for an island integrated energy system, and the method comprises the steps: constructing an electricity-hydrogen-heat multi-energy coupled island integrated energy system model; constructing a real-time stepped carbon transaction model based on the interval to which the carbon emission quota participating in the carbon emission transaction belongs by using an island integrated energy system model; on the basis of a real-time stepped carbon transaction model, deviation penalty of new energy prediction is considered, one day is divided into n scheduling cycles, n is an integer larger than 1, a target function is constructed with the highest total income of a system as an optimization target, the optimization target is solved, and an optimized scheduling result is obtained. According to the invention, wind energy, solar energy, wave energy, stored energy, a photo-thermal power station and other energy sources are co-scheduled with electricity, hydrogen and water loads to form a dynamically balanced energy system; and high consumption and low carbon emission are kept as far as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of island integrated energy systems, and in particular to a short-term low-carbon optimization scheduling method and system for island integrated energy systems. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] With the rapid development of new energy, clean energy such as wind power and solar energy has gradually become an important part of the global energy structure that cannot be ignored. The meteorological conditions on islands are complex, and the output of new energy is extremely unstable, which makes it difficult to absorb new energy. At the same time, it is difficult for islands to establish an interactive relationship with large land power grids, and the transmission power is limited. How to ensure the stable operation of island energy systems, improve energy utilization and reduce carbon emissions has become a technical problem that needs to be solved urgently. Traditional islands have less load and mostly use diesel generators for power supply, which will produce pollutants such as CO2, which is not conducive to the sustainable development of marine ecology.

[0004] In terms of system architecture design, the existing island integrated energy system usually isolates electricity, hydrogen, heat and other systems, does not take into account the coupling characteristics of multiple energy networks, only considers the electricity load, and does not consider the system construction of multiple loads coexisting; in terms of system optimization and scheduling, it is scheduled in hours and one day, but the output of island new energy fluctuates greatly, and the prediction of new energy based on the day-ahead time scale often cannot meet the accuracy requirements; at the same time, due to the weak interaction between islands and large power grids, wind power interruptions may cause the island system to fail to operate normally. In the current research on island energy systems, no research has been found to consider the problem of limited transmission power in the case of a sudden drop in wind power; in terms of operating conditions, it is difficult for islands to build an interactive relationship with large land power grids, and the problem of limited transmission power is not fully considered, and the system has poor robustness. In terms of carbon trading, most of the existing ones are fixed-price or ladder carbon trading based on the full scheduling cycle. However, fixed-price carbon trading is not conducive to promoting the consumption of new energy, and ladder carbon trading based on the full scheduling cycle often does not consider real-time performance. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a short-scale low-carbon optimization scheduling method and system for an island integrated energy system. It adopts an optimization scheduling method on a short-time scale within the day, and coordinates multiple energy sources such as wind energy, solar energy, wave energy and energy storage, solar thermal power stations, and electricity, hydrogen, and water loads. Carbon trading is carried out within each scheduling scale, and a hydrogen and water sales market is established to promote the consumption of new energy.

[0006] In some embodiments, the following technical solutions are adopted: A short-term low-carbon optimization scheduling method for an island integrated energy system, comprising: Construct an island integrated energy system model with multiple energy coupling of electricity, hydrogen and heat; Using the island integrated energy system model, a real-time ladder carbon trading model is constructed based on the interval to which the carbon emission quota participating in the carbon emission trading belongs; Based on the real-time stepped carbon trading model, the deviation penalty of new energy forecast is taken into account, a day is divided into n scheduling cycles, n is an integer greater than 1, and the maximum total system revenue is taken as the optimization goal. The objective function is constructed, the optimization goal is solved, and the optimized scheduling result is obtained.

[0007] As an optional solution, a model of an island integrated energy system with multi-energy coupling of electricity, hydrogen and heat is constructed, including: After the solar thermal power station converts the absorbed solar energy into thermal energy, part of the thermal energy is used to provide steam through the heat exchange device to drive the steam turbine generator to generate electricity, and the other part enters the heat storage device to cope with the volatility of energy output; The hydrogen produced by electrolysis will first meet the island's own load demand, and the rest will be sold in the hydrogen market; the fresh water produced by the seawater desalination device will first meet the island's own load demand, and the rest will be traded in the fresh water market; The island's power load is supplied by the superior power grid and new energy output; the total of new energy power generation and power grid purchases is equal to the sum of the island's power load, seawater electrolysis for hydrogen production, and seawater desalination equipment, achieving power balance between the power supply and power consumption ends.

[0008] As an optional solution, the amount of electricity purchased from the upper power grid is as follows: ; in, is the amount of electricity purchased from the upper power grid, is the total amount of wind power generation, is the total amount of wave energy generation, is the island power load, Transmission line transmission power limit, is the island hydrogen load, is the island freshwater load, It is the total power used by the CSP station to generate electricity.

[0009] As an optional solution, a real-time tiered carbon trading model is constructed, specifically: ; in, is the carbon trading floor price, T is the total number of scheduling scales within the day, and t represents the scheduling scale; is the step interval length of carbon trading, is the growth coefficient of carbon trading price, Represents the carbon emission quota participating in carbon emission trading within the tth scheduling scale.

[0010] As an alternative, carbon emission quotas participating in carbon emission trading Specifically: ; in, , , They are the carbon emission quotas for wind power generation, wave power generation and solar thermal power station power generation. is the carbon emission coefficient of thermal power generation, is the amount of electricity purchased from the power grid at time t; It is the actual total carbon emissions of the island’s integrated energy system.

[0011] As an optional option, the carbon emission quotas for wind power generation, wave power generation and solar thermal power station power generation are: ; ; ; in, is the carbon emission quota per kW, , , They are respectively the wind power generation power, wave power generation power and solar thermal power station power generation power at time t.

[0012] As an optional solution, the maximum total system revenue is taken as the optimization goal, and the objective function is constructed, specifically: ; ; ; in, , , , , , They are the total profit of the island integrated energy system in one day, the supply load income, the profit of hydrogen energy and fresh water participating in market transactions, the operating cost of the island integrated energy system in one day, the system maintenance cost and the penalty item for abandoning wind and solar power; Profits from carbon trading; , are the new energy forecast deviation penalty term and penalty coefficient respectively; , They are the intraday and day-ahead power forecast values ​​respectively.

[0013] In other embodiments, the following technical solutions are adopted: A short-term low-carbon optimization dispatching system for an island integrated energy system, comprising: Model building module, used to build an island integrated energy system model with electricity, hydrogen and heat multi-energy coupling; A carbon trading model building module is used to build a real-time ladder carbon trading model based on the interval to which the carbon emission quota participating in the carbon emission trading belongs by using the island comprehensive energy system model; The optimization scheduling module is used to divide a day into n scheduling cycles based on the real-time step-by-step carbon trading model, taking into account the deviation penalty of new energy prediction, and taking the maximum total system revenue as the optimization goal. The objective function is constructed, the optimization goal is solved, and the optimization scheduling result is obtained.

[0014] In other embodiments, the following technical solutions are adopted: A terminal device includes a processor and a memory, wherein the processor is used to implement instructions; the memory is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing the above-mentioned short-time scale low-carbon optimization scheduling method for the island integrated energy system.

[0015] In other embodiments, the following technical solutions are adopted: A computer-readable storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor of a terminal device and executing the above-mentioned short-time scale low-carbon optimization scheduling method for an island integrated energy system.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) In the island energy system, the present invention forms a dynamically balanced energy system by coordinating multiple energy sources such as wind energy, solar energy, wave energy and energy storage, solar thermal power stations, and electricity, hydrogen, and water loads. It can reasonably configure island new energy and loads, and build a hydrogen sales market to meet the normal operation of the system and maintain high consumption and low carbon emissions as much as possible.

[0017] (2) The present invention fully considers the problem of large fluctuations in renewable energy output and adopts an ultra-short time scale optimization scheduling method, with 15 minutes as the scheduling scale and 4 hours as a scheduling cycle. It can more accurately realize the scheduling of wind and solar power within a day; making the system better than the traditional day-ahead scheduling method in terms of renewable energy consumption, carbon emissions and system benefits.

[0018] (3) The present invention adopts real-time tiered carbon trading, conducts carbon trading within each scheduling scale, and constructs hydrogen and water sales markets; the more carbon emissions, the higher the tier height, the more new energy is consumed, the greater the profit obtained from carbon trading, and the better it can promote the consumption of new energy.

[0019] (4) The present invention fully considers the characteristics of new energy on islands, optimizes the scheduling strategy by flexibly utilizing the synergy of energy storage, solar thermal power stations, wind power, and wave power generation systems, and effectively overcomes the problem of low optimization scheduling accuracy of traditional island integrated energy systems. It also proposes an improved step-by-step carbon trading, which effectively increases the benefits of the system, promotes the consumption of new energy, reduces the carbon emissions of the system, and effectively reduces the transmission power required on the islands.

[0020] (5) The present invention takes into account the problem of limited transmission power on islands. During the peak load period, under the special working condition that the wind power output on islands drops to zero, the method of the present invention will significantly improve the new energy consumption rate, reduce carbon emissions, and increase system benefits. The most important thing is that the power required to be transmitted from the power grid during the island new energy failure is less than the traditional method; reducing the power transmission power of the power grid during the failure, thereby reducing the dependence on the power grid and ensuring that the system can operate stably during the failure.

[0021] Other features and advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a short-term low-carbon optimization scheduling method for an island integrated energy system in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of an island integrated energy system model with electricity-hydrogen-heat multi-energy coupling in an embodiment of the present invention; Figure 3 This is a schematic diagram comparing day-ahead scheduling and intraday scheduling. DETAILED DESCRIPTION

[0023] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0024] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0025] Embodiment 1 In one or more embodiments, a short-term low-carbon optimization scheduling method for an island integrated energy system is disclosed, combining Figure 1 , specifically including the following process: S101: Construct an island integrated energy system model with multiple energy couplings of electricity, hydrogen and heat.

[0026] Combination Figure 1 The electric-hydrogen-heat multi-energy coupled island integrated energy system model mainly includes: new energy power generation devices including wave power generation, island wind power and solar thermal power stations, upper power grid, electrolysis hydrogen production device, seawater desalination device, island load, thermal collector, steam turbine generator, heat storage device and carbon exchange.

[0027] The clean energy provided by wave power generation, island wind power and solar thermal power stations, and the electric energy provided by wave power generation and island wind power are respectively transmitted to the electrolysis hydrogen production device, seawater desalination device and island load; the upper-level power grid is connected to the electrolysis hydrogen production device, seawater desalination device and island load through transmission lines; after the solar thermal power station converts the absorbed solar energy into thermal energy, part of the thermal energy provides steam through the heat exchange device to drive the steam turbine generator to generate electricity; the other part enters the heat storage device to cope with the volatility of the island system energy output.

[0028] The hydrogen obtained from hydrogen electrolysis will first meet the island’s own load demand, and the rest will enter the hydrogen sales market for sale; the fresh water obtained from seawater desalination will first meet the island’s own load demand, and the rest will enter the water sales market for sale.

[0029] Specifically, a CSP plant collects solar thermal energy by reflecting it to a small area. The CSP plant first converts the absorbed solar energy into thermal energy: (1) Where: It is the heat energy converted from solar energy. is the photothermal conversion efficiency, is the area of ​​all reflectors, is the thermal radiation index.

[0030] After the solar thermal power station converts the absorbed solar energy into thermal energy, part of the thermal energy is used to provide steam through the heat exchange device to drive the steam turbine generator to generate electricity; the other part enters the heat storage device to cope with the volatility of the island system's energy output.

[0031] (2) (3) (4) Where: is the thermoelectric conversion efficiency, is the total power used by the CSP station for generating electricity. It is the power directly used for electricity generation in a CSP plant. To generate electricity for the heat storage device, The power directly stored in the CSP plant. and are the thermal power input and output of the heat storage device, and are the input and output efficiencies of the heat storage device respectively.

[0032] At the same time, CSP plants need to have output and ramp constraints: (5) In the formula, , are the total power used by the CSP station for power generation at time t and time t-1, respectively. and is the maximum and minimum power of thermoelectric conversion, and They are the upper and lower limits of the photothermal conversion ramp.

[0033] Secondly, the heat storage device also needs to be set with upper and lower limits.

[0034] (6) (7) In the formula, and are the upper and lower limits of the input power of the heat storage device, and are the upper and lower limits of the output power of the heat storage device respectively.

[0035] Finally, the heat capacity of the heat storage device remains consistent throughout the entire scheduling cycle, while ensuring that heat storage and heat release cannot occur at the same time.

[0036] (8) In the formula, and are the initial and final heat capacities of the entire dispatching cycle respectively; and Binary variables representing the charging and releasing of thermal energy of the heat storage device.

[0037] An electrolytic hydrogen production device is a device that uses electrical energy to decompose water into hydrogen and oxygen. It mainly produces hydrogen by electrolyzing seawater.

[0038] (9) In the formula, is the total power of hydrogen production by electrolysis of seawater, is the island hydrogen load, It is hydrogen that participates in market transactions.

[0039] Desalination equipment converts seawater into fresh water for human drinking or other uses by removing salt and other dissolved substances from seawater. There are two common seawater desalination technologies: reverse osmosis and multiple-effect distillation.

[0040] (10) In the formula, is the total power used for desalination, is the island freshwater load, It is fresh water that participates in market transactions.

[0041] The output of new energy is uncertain. In this embodiment, when the output of new energy cannot meet the island's electricity, hydrogen, and fresh water loads, electricity is purchased from the upper-level power grid.

[0042] (11) In the formula, is the total amount of wind power generated on the island, is the total amount of wave energy generation, is the island power load, is the amount of electricity purchased from the upper power grid, Transmit power limits for transmission lines.

[0043] In addition, in the island integrated energy system model of this embodiment, the total of wind power generation, solar thermal power station power generation, wave power generation, and power grid purchases must be equal to the sum of the island's electrical load, seawater electrolysis to produce hydrogen, and seawater desalination electricity consumption, so as to achieve power balance between the power supply end and the power consumption end.

[0044] (12) (13) (14) In the formula, and are the upper and lower limits of hydrogen production power, and They are the upper and lower limits of fresh water production power respectively; Electricity for producing hydrogen by electrolysis of seawater, electricity for desalination; To participate in the hydrogen market, , They are the lower and upper limits of electricity consumption for participating in the hydrogen market; To participate in the electricity consumption of the freshwater market, , They are the lower and upper limits of electricity consumption for participating in the freshwater market.

[0045] S102: Using the island integrated energy system model, a real-time step-by-step carbon trading model is constructed based on the interval to which the carbon emission quota participating in the carbon emission trading belongs.

[0046] For the island integrated energy system, its carbon emission quota mainly comes from free allocation, and in the carbon emission trading market, the electricity it purchases is not included in the carbon emission quota management. The carbon emission quota of the island energy system is: (15) In the formula, , , , They are system carbon emission quota, wind power generation, wave power generation and solar thermal power station carbon emission quota. is the carbon emission quota per kW, , , They are respectively the wind power generation power, wave power generation power and solar thermal power station power generation power at time t, and T is the scheduling period.

[0047] Carbon emission quotas for participating in carbon emission trading, specifically: (16) in, is the amount of electricity purchased from the power grid at time t, is the carbon emission coefficient of thermal power generation, It is the actual total carbon emissions of the island’s integrated energy system.

[0048] The step-by-step carbon trading is set as a piecewise function. As the carbon emission quota increases, the carbon price in the trading range also increases. Traditional step-by-step carbon trading is traded once a day, and the height of each step is the same, which has poor flexibility. The real-time carbon trading model proposed in this embodiment is: (17) in, is the carbon trading floor price, T is the total number of scheduling scales within the day, and t represents the scheduling scale; is the step interval length of carbon trading, is the growth coefficient of carbon trading price, Indicates the carbon emission quota participating in carbon emission trading within the tth scheduling scale. In this embodiment, every 15 minutes is a scheduling scale, every 4 hours is a scheduling cycle, and there are a total of 96 scheduling scales in a day, which are divided into 6 cycles for cyclic calculation.

[0049] This embodiment adopts real-time tiered carbon trading, conducts carbon trading within each ultra-short-term scheduling scale, and builds a hydrogen and water sales market; the more carbon emissions, the higher the tier height, the more new energy is consumed, the greater the profit from carbon trading, and the better it can promote the consumption of new energy.

[0050] S103: Based on the real-time step-by-step carbon trading model, the deviation penalty of new energy forecast is taken into consideration, and the ultra-short time-scale scheduling method is adopted. One day is divided into n scheduling cycles, where n is an integer greater than 1. The maximum total system revenue is taken as the optimization goal, and the objective function is constructed. The optimization goal is solved to obtain the optimized scheduling result.

[0051] Traditional day-ahead optimization is to predict the output and load of renewable energy sources on the day before. Figure 3 In (a), 1h is the dispatch scale, and the data given the day before is the output of renewable energy and the amount of electricity required by the load every hour; one day is a dispatch cycle, and the optimization results of the actual output of renewable energy, power purchase by the upper power grid, and the state change of the heat storage device for the next day are all given at one time. However, the output of renewable energy on islands fluctuates greatly, and the prediction of renewable energy based on the day-ahead time scale often cannot meet the accuracy requirements.

[0052] Combination Figure 3 (b) in the figure, the intraday optimization scheduling of this embodiment uses a shorter time scale for optimization scheduling, and the results are more accurate. Starting at 0:00 every day, a four-hour forecast of the output and load of new energy is given. 15min is the scheduling scale, and the data given within the day are the output of new energy and the power required by the load every 15 minutes; 4h is a scheduling cycle, and each day is divided into 6 cycles to give the optimization results of the output of new energy, power purchases from the upper power grid, and changes in the status of the heat storage device; this embodiment can more accurately realize the scheduling of wind and solar power through the intraday ultra-short-time scheduling strategy.

[0053] In this embodiment, the objective function is specifically: (18) (19) (20) (twenty one) (twenty two) (twenty three) in, , , , , , They are the total profit of the island in one day, the supply load income, the profit of hydrogen energy and fresh water participating in the market transaction, the operating cost of the island system in one day, the system maintenance cost and the penalty item for abandoning wind and solar power; , , They are electricity price, hydrogen price and fresh water price; , , They are the power generation cost coefficient of the CSP power station, the operating cost coefficient of the hydrogen production equipment, and the operating cost coefficient of the seawater desalination equipment; , , , They are the maintenance cost coefficients of the heat collection device, heat storage device, hydrogen pipeline, and water pipeline respectively; is the unit power penalty coefficient, is the predicted value, is the optimized utilization value.

[0054] In addition, the day-ahead dispatching benefit also needs to consider the new energy forecast deviation penalty, so the total day-ahead system benefit is (twenty four) (25) In the formula, , are the prediction error penalty term and penalty coefficient respectively, , They are the intraday and day-ahead power forecast values ​​respectively.

[0055] All of the above models can be implemented based on the MATLAB platform using the GUROBI solver in the YALMIP toolbox. The solver solves based on the given data, objective function and constraints to obtain the globally optimal scheduling result.

[0056] Through the ultra-short time scale dispatch strategy for the island integrated energy system, the synergy of energy storage, solar thermal power station, wind power and wave power generation system is flexibly utilized; at the same time, an improved real-time ladder carbon trading model is proposed, which is conducive to promoting the consumption of new energy; in the case of large fluctuations in the output of new energy, by flexibly utilizing the synergy of energy storage, solar thermal power station, wind power and wave power generation system, the dispatch strategy is optimized, which can effectively improve the dispatch accuracy and thus increase the system benefits, improve the consumption rate of new energy and reduce carbon emissions. At the same time, during the period of new energy failure on the island, the purchase of electricity from the power grid can be minimized, reducing the dependence on the power grid.

[0057] In order to verify the effect of the method of this embodiment, this embodiment sets two scenarios: Scenario 1 is the normal power supply of the new energy system; Scenario 2 is the failure and shutdown of all wind turbines within 1 hour during the peak load period.

[0058] Table 1 shows the comparison results between the method of this embodiment and the traditional method in scenario 1.

[0059] Table 1. Comparison of results in scenario 1

[0060] Combined with the analysis in Table 1, using the method of this embodiment, through the scheduling optimization of ultra-short time scale, the system has obvious optimization in new energy consumption rate, carbon emissions, and operating benefits. The overall new energy consumption rate increased by 0.0742%, and carbon emissions decreased from 533.5372kg to 378.55181kg, a year-on-year decrease of 29.048%. The overall operating efficiency increased by 6.11%. It can be seen that the proposed strategy reduces carbon emissions while improving the new energy consumption rate and system operating benefits, proving the effectiveness of the proposed method.

[0061] Table 2 shows the comparison results between the method of this embodiment and the traditional method in scenario 1.

[0062] Table 2. Comparison of results in scenario 2

[0063] Combined with the analysis in Table 2, when the new energy power supply fails, the proposed method can still effectively optimize the system's new energy consumption rate, carbon emissions and operating benefits. At the same time, the lower limit of the power transmission of the traditional method during the fault period is 1259.9kW, while the lower limit of the power transmission of the proposed method during the fault period is 1165.18kW, which is 7.52% lower, thereby ensuring that the system can maintain normal operation as much as possible in the event of a fault, reducing dependence on the upper power grid.

[0064] In scenario 2, the power transmission limit of the power grid is 1200kW. At this time, the traditional method of day-ahead optimization scheduling cannot be carried out. This is because the island integrated energy system is far away from the upper power grid and the transmission power is limited. When the new energy power supply fails, the system cannot obtain sufficient power grid support and the system will be out of power.

[0065] Since the wind power and wave power generation curves are inversely proportional to the load curve, and the power generation curve of the solar thermal power station is roughly the same as the load change trend. Therefore, in the method of this embodiment, during the peak load period, the fluctuation of new energy is effectively smoothed by flexibly dispatching the energy storage system. At night, the wind power output is large, while the load demand is small. The system uses excess new energy to produce fresh water and hydrogen, and puts it into the hydrogen and water sales market, which not only increases revenue, but also promotes the consumption of new energy.

[0066] In the early morning hours, the output of wind turbines and wave energy is low, so solar thermal power stations are used for power supply first. When wind and wave energy are sufficient, the system stores excess energy in the heat storage device.

[0067] Compared with traditional methods, the proposed method can more effectively deal with the scheduling accuracy problem caused by the large fluctuation of new energy by flexibly utilizing the solar thermal energy storage device on a short time scale, which can ensure the stable operation of the system and improve the robustness of the system. At the same time, it only purchases a large amount of electricity during the fault period, which has better economic benefits and promotes the consumption of new energy and reduces carbon emissions. The required transmission line transmission power is less than the traditional method, which is conducive to the stable operation of the system.

[0068] Embodiment 2 In one or more embodiments, a short-term low-carbon optimization scheduling system for an island integrated energy system is disclosed, comprising: Model building module, used to build an island integrated energy system model with electricity, hydrogen and heat multi-energy coupling; A carbon trading model building module is used to build a real-time ladder carbon trading model based on the interval to which the carbon emission quota participating in the carbon emission trading belongs by using the island comprehensive energy system model; The optimization scheduling module is used to divide a day into n scheduling cycles based on the real-time step-by-step carbon trading model, taking into account the deviation penalty of new energy prediction, and taking the maximum total system revenue as the optimization goal. The objective function is constructed, the optimization goal is solved, and the optimization scheduling result is obtained.

[0069] The specific implementation of the above modules is the same as that in Example 1 and will not be described in detail.

[0070] Embodiment 3 In one or more embodiments, a terminal device is disclosed, which includes a processor and a memory, the processor is used to implement instructions; the memory is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing the short-scale low-carbon optimization scheduling method for the island integrated energy system described in Example 1.

[0071] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0072] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0073] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software.

[0074] Embodiment 4 In one or more embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, wherein the instructions are suitable for being loaded by a processor of a terminal device and executing the short-time scale low-carbon optimization scheduling method for an island integrated energy system described in Example 1.

[0075] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A short-term low-carbon optimization scheduling method for an island integrated energy system, characterized in that: include: Construct an island integrated energy system model with multiple energy coupling of electricity, hydrogen and heat; Using the island integrated energy system model, a real-time ladder carbon trading model is constructed based on the interval to which the carbon emission quota participating in the carbon emission trading belongs; Based on the real-time stepped carbon trading model, the deviation penalty of new energy forecast is taken into account, a day is divided into n scheduling cycles, n is an integer greater than 1, and the maximum total system revenue is taken as the optimization goal. The objective function is constructed, the optimization goal is solved, and the optimized scheduling result is obtained.

2. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 1, characterized in that: Construct an island integrated energy system model with electricity, hydrogen and heat multi-energy coupling, including: After the solar thermal power station converts the absorbed solar energy into thermal energy, part of the thermal energy is used to provide steam through the heat exchange device to drive the steam turbine generator to generate electricity, and the other part enters the heat storage device to cope with the volatility of energy output; The hydrogen produced by electrolysis will first meet the island's own load demand, and the rest will be sold in the hydrogen market; the fresh water produced by the seawater desalination device will first meet the island's own load demand, and the rest will be traded in the fresh water market; The island's power load is supplied by the superior power grid and new energy output; the total of new energy power generation and power grid purchases is equal to the sum of the island's power load, seawater electrolysis for hydrogen production, and seawater desalination equipment, achieving power balance between the power supply and power consumption ends.

3. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 2, characterized in that: The specific amount of electricity purchased from the upper power grid is: ； in, is the amount of electricity purchased from the upper power grid, is the total amount of wind power generation, is the total amount of wave energy generation, is the island power load, Transmission line transmission power limit, is the island hydrogen load, is the island freshwater load, It is the total power used by the CSP station to generate electricity.

4. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 1, characterized in that: Construct a real-time tiered carbon trading model, specifically: ； in, is the carbon trading floor price, T is the total number of scheduling scales within the day, and t represents the scheduling scale; is the step interval length of carbon trading, is the growth coefficient of carbon trading price, Represents the carbon emission quota participating in carbon emission trading within the tth scheduling scale.

5. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 4, characterized in that: Carbon emission quotas participating in carbon emission trading Specifically: ； in, , , They are the carbon emission quotas for wind power generation, wave power generation and solar thermal power station power generation. is the carbon emission coefficient of thermal power generation, is the amount of electricity purchased from the power grid at time t; It is the actual total carbon emissions of the island’s integrated energy system.

6. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 5, characterized in that: The carbon emission quotas for wind power generation, wave power generation and solar thermal power station power generation are: ； ； ； in, is the carbon emission quota per kW, , , They are respectively the wind power generation power, wave power generation power and solar thermal power station power generation power at time t.

7. A short-term low-carbon optimization scheduling method for an island integrated energy system as claimed in claim 1, characterized in that: Taking the maximum total system revenue as the optimization goal, the objective function is constructed, which is as follows: ； ； ； in, , , , , , They are the total profit of the island integrated energy system in one day, the supply load income, the profit of hydrogen energy and fresh water participating in market transactions, the operating cost of the island integrated energy system in one day, the system maintenance cost and the penalty item for abandoning wind and solar power; Profits from carbon trading; , are the new energy forecast deviation penalty term and penalty coefficient respectively; , They are the intraday and day-ahead power forecast values ​​respectively.

8. A short-term low-carbon optimization dispatching system for an island integrated energy system, characterized in that: include: Model building module, used to build an island integrated energy system model with electricity, hydrogen and heat multi-energy coupling; A carbon trading model building module is used to build a real-time ladder carbon trading model based on the interval to which the carbon emission quota participating in the carbon emission trading belongs by using the island comprehensive energy system model; The optimization scheduling module is used to divide a day into n scheduling cycles based on the real-time step-by-step carbon trading model, taking into account the deviation penalty of new energy prediction, and taking the maximum total system revenue as the optimization goal. The objective function is constructed, the optimization goal is solved, and the optimization scheduling result is obtained.

9. A terminal device, comprising a processor and a memory, wherein the processor is used to implement instructions; and the memory is used to store multiple instructions, characterized in that: The instructions are suitable for being loaded by a processor and executing the short-time-scale low-carbon optimization scheduling method for an island integrated energy system as described in any one of claims 1-7.

10. A computer-readable storage medium storing a plurality of instructions, characterized in that: The instructions are suitable for being loaded by a processor of a terminal device and executing the short-time-scale low-carbon optimization scheduling method for an island integrated energy system as described in any one of claims 1-7.

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