Source and storage joint optimization configuration method and equipment based on park comprehensive energy model

Abstract

The present invention discloses a source-storage joint optimization configuration method and device based on a park comprehensive energy model, the method comprising: determining the total carbon emissions of multiple energy flows according to the carbon emissions corresponding to the park comprehensive energy model and the carbon emissions corresponding to the new energy units; constructing a cost objective function according to the total carbon emissions of multiple energy flows, the cost information corresponding to the park comprehensive energy model and the cost information corresponding to the new energy units, and constructing energy balance constraints according to the sub-model variables of the park comprehensive energy model and the park's daily historical load data; solving the cost minimum through the cost objective function based on the energy balance constraints to obtain a park comprehensive energy source-storage configuration plan, and performing source-storage optimization configuration according to the park comprehensive energy source-storage configuration plan. The present invention utilizes a compressed particle swarm algorithm to perform joint optimization configuration of new energy and energy storage through a cost objective function to reduce resource waste and help promote energy conservation and emission reduction.

Description

Technical Field

[0001] The present invention belongs to the technical field of comprehensive energy low-carbon optimization configuration, and in particular relates to a source-storage joint optimization configuration method and equipment based on a park comprehensive energy model. Background Art

[0002] Energy, as the driving force for human survival and social development and progress, has gradually received widespread attention in recent years. Traditional fossil energy has not only been severely consumed in recent centuries, but has also brought huge impacts on the earth's ecological environment. Faced with this series of problems, the energy structure of countries around the world has begun to transform towards low-carbon and zero-carbon directions, and vigorously advocated the use of clean energy.

[0003] The traditional energy system has a simple structure, a single energy form, serious environmental pollution, and lacks coordination and complementarity between multiple types of energy, resulting in low energy efficiency. In order to better explore the path of efficient and low-carbon development, scholars have conducted in-depth research on factors such as energy system structure, complementary characteristics between energy sources, and carbon emissions.

[0004] In the past, when measuring carbon emissions, only harmful gases emitted by equipment operation and combustion were considered, and almost no consideration was given to the carbon emissions of the equipment during its construction and dismantling, resulting in large errors in statistical emission data. The rational optimization of equipment capacity for multi-energy flow systems is related to the economic cost and emission reduction benefits of the system. Inappropriate capacity selection will not only increase the economic cost of the system, but also increase the pollutant emissions in the system. Therefore, how to reduce resource waste and carbon emissions has become an urgent problem to be solved.

[0005] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention The main purpose of the present invention is to provide a source-storage joint optimization configuration method and equipment based on a comprehensive energy model of a park, aiming to solve the technical problem of how to reduce resource waste and carbon emissions.

[0006] To achieve the above object, the present invention provides a source-storage joint optimization configuration method based on a comprehensive energy model of a park, and the source-storage joint optimization configuration method based on a comprehensive energy model of a park comprises: Determine the total carbon emissions of multiple energy flows according to the carbon emissions corresponding to the park comprehensive energy model and the carbon emissions corresponding to the new energy units, wherein the park comprehensive energy model is constructed by a combination of a cogeneration unit sub-model, an electric boiler sub-model, a gas boiler sub-model, a power-to-gas equipment sub-model and a multi-energy storage unit, wherein the multi-energy storage unit includes a battery sub-model, a heat storage sub-model and a gas storage sub-model; Constructing a cost objective function according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the park comprehensive energy model, and the cost information corresponding to the new energy unit; Constructing energy balance constraints based on sub-model variables of the park comprehensive energy model and the park's daily historical load data; Based on the energy balance constraint, the cost minimum is solved through the cost objective function to obtain a comprehensive energy source and storage configuration plan for the park, and the source and storage are optimized according to the comprehensive energy source and storage configuration plan for the park.

[0007] In addition, to achieve the above-mentioned objectives, the present invention also proposes a source-storage joint optimization configuration device based on a comprehensive energy model of a park, the device comprising: a memory, a processor, and a source-storage joint optimization configuration program based on a comprehensive energy model of a park stored in the memory and executable on the processor, the source-storage joint optimization configuration program based on a comprehensive energy model of a park configured to implement the source-storage joint optimization configuration method based on a comprehensive energy model of a park as described above.

[0008] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which is stored a source-storage joint optimization configuration program based on the comprehensive energy model of the park. When the source-storage joint optimization configuration program based on the comprehensive energy model of the park is executed by a processor, the source-storage joint optimization configuration method based on the comprehensive energy model of the park as described above is implemented.

[0009] The present invention first constructs a comprehensive energy model of the park according to a cogeneration unit sub-model, an electric boiler sub-model, a gas boiler sub-model, a power-to-gas equipment sub-model and a multi-energy storage unit. The comprehensive energy model of the park is constructed by combining the cogeneration unit sub-model, the electric boiler sub-model, the gas boiler sub-model, the power-to-gas equipment sub-model and the multi-energy storage unit. The multi-energy storage unit includes a battery sub-model, a heat storage sub-model and a gas storage sub-model. Then, the total carbon emissions of the multi-energy flows are determined according to the carbon emissions corresponding to the comprehensive energy model of the park and the carbon emissions corresponding to the new energy units. Then, according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the comprehensive energy model of the park and the cost information corresponding to the new energy units, and according to the sub-model variables of the comprehensive energy model of the park and the historical load data of the park during the day, an energy balance constraint condition is constructed. Finally, based on the energy balance constraint condition, a comprehensive energy source-storage configuration plan of the park is obtained through a cost objective function, and source-storage optimization configuration is performed according to the comprehensive energy source-storage configuration plan of the park. The present invention takes the energy cost, investment cost, carbon emission cost, and wind and solar power abandonment cost of the park's comprehensive energy model as multiple objectives, which can effectively improve the access capacity of new energy units and energy storage equipment, ensure the economy of the system while effectively reducing carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a structural schematic diagram of a source-storage joint optimization configuration device based on a park comprehensive energy model in a hardware operating environment involved in an embodiment of the present invention; Figure 2 It is a flow chart of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention; Figure 3 It is a schematic diagram of the structure of the integrated energy system of the first embodiment of the source-storage joint optimization configuration method based on the park integrated energy model of the present invention; Figure 4 It is a typical daily load and wind power per unit output curve diagram of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention; Figure 5 This is a comparison chart of system costs under four different situations of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention.

[0011] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0012] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0013] Reference Figure 1 , Figure 1 It is a schematic diagram of the structure of the source-storage joint optimization configuration equipment based on the park comprehensive energy model in the hardware operating environment involved in the embodiment of the present invention.

[0014] like Figure 1As shown, the source storage joint optimization configuration device based on the park comprehensive energy model may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-VolatileMemory, NVM), such as a disk storage. The memory 1005 may also be a storage system independent of the aforementioned processor 1001.

[0015] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the source-storage joint optimization configuration equipment based on the park comprehensive energy model, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0016] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a source-storage joint optimization configuration program based on a comprehensive energy model of a campus.

[0017] exist Figure 1 In the source-storage joint optimization configuration device based on the comprehensive energy model of the park shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the source-storage joint optimization configuration device based on the comprehensive energy model of the park of the present invention can be set in the source-storage joint optimization configuration device based on the comprehensive energy model of the park, and the source-storage joint optimization configuration device based on the comprehensive energy model of the park calls the source-storage joint optimization configuration program based on the comprehensive energy model of the park stored in the memory 1005 through the processor 1001, and executes the source-storage joint optimization configuration method based on the comprehensive energy model of the park provided in the embodiment of the present invention.

[0018] The embodiment of the present invention provides a source storage joint optimization configuration method based on a comprehensive energy model of a park, referring to Figure 2 , Figure 2It is a flow chart of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention.

[0019] In this embodiment, the source-storage joint optimization configuration method based on the park comprehensive energy model includes the following steps: Step S10: Determine the total carbon emissions of multiple energy flows according to the carbon emissions corresponding to the park's comprehensive energy model and the carbon emissions corresponding to the new energy units. The park's comprehensive energy model is constructed by a cogeneration unit sub-model, an electric boiler sub-model, a gas boiler sub-model, a power-to-gas equipment sub-model and a multi-energy storage unit combination. The multi-energy storage unit includes a battery sub-model, a heat storage sub-model and a gas storage sub-model.

[0020] It is easy to understand that the execution subject of this embodiment can be a comprehensive energy system (i.e., a multi-energy flow system) with functions such as data processing, network communication, and program running, or other computer equipment with similar functions, etc., and this embodiment is not limited.

[0021] In the specific implementation, refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an integrated energy system of the first embodiment of the source-storage joint optimization configuration method based on the park integrated energy model of the present invention. The input side supply source includes a natural gas source, a new energy unit (i.e., operating photovoltaics (Photovoltaic Cell, PV) and wind turbines (Wind Turbine, WT)) and an upper-level distribution network; the output side includes three load resources: electricity, gas, and heat; the energy storage units and energy conversion equipment in the transmission layer include gas boilers, electric boilers, combined heat and power units (CHP), and power-to-gas equipment (P2G).

[0022] In this implementation, it is necessary to construct a cogeneration unit sub-model, an electric boiler sub-model, a gas boiler sub-model, a power-to-gas equipment sub-model and a multi-energy storage unit.

[0023] The sub-model of the combined heat and power unit is:

[0024]

[0025] During operation, the rated power constraint and climbing constraint must be met:

[0026]

[0027] In the formula, P CHP is the output power of the cogeneration unit, in kW, H CHPis the thermal power output of the cogeneration unit, in kW, is the natural gas flow rate consumed, in m 3 / h, For energy conversion efficiency, is the calorific value of gas, is the thermoelectric ratio, The maximum value of the electric power output by the cogeneration unit; is the adjustment amount of the output power of the cogeneration unit, It is the climbing power limit of the cogeneration unit.

[0028] The model building parameters corresponding to the cogeneration unit sub-model include the electric power output of the cogeneration unit, the thermal power output of the cogeneration unit, the natural gas flow consumed, the energy conversion efficiency, the calorific value of the gas, the heat-to-electricity ratio, the maximum value of the electric power output of the cogeneration unit, the adjustment of the electric power output of the cogeneration unit and the climbing power limit of the cogeneration unit.

[0029] The electric boiler sub-model is:

[0030] In the formula, It is the thermal power output of the electric boiler when it is working, in kW. It is the electric power consumed by the electric boiler when it is working, in kW. The energy conversion efficiency of electric boilers is converted into electricity and heat.

[0031] The model building parameters corresponding to the electric boiler sub-model include the thermal power output when the electric boiler is working, the electric power consumed when the electric boiler is working, and the energy-to-electricity heat exchange efficiency of the electric boiler.

[0032] The gas boiler sub-model is:

[0033]

[0034] In the formula, It is the thermal power generated by the combustion of natural gas in a gas boiler, in kW. is the natural gas consumption flow rate of the gas boiler, in m 3 / h, is the thermal power output of the gas boiler, in kW, The gas-to-heat energy conversion efficiency of gas boilers.

[0035] The model building parameters corresponding to the gas boiler sub-model include the thermal power generated by the gas boiler burning natural gas, the natural gas consumption flow rate of the gas boiler, the output thermal power of the gas boiler and the gas-to-heat energy conversion efficiency of the gas boiler.

[0036] Power-to-Gas Plant Sub-Model:

[0037] Operation constraints:

[0038] In the formula, The power consumed by the power-to-gas equipment, in kW. is the electrical energy conversion efficiency coefficient of the power-to-gas equipment, The natural gas flow rate output by the power-to-gas equipment, in m 3 / h, It is the upper limit of the electric power consumption of the power-to-gas equipment.

[0039] The model building parameters corresponding to the power-to-gas equipment sub-model include the electrical power consumed by the power-to-gas equipment, the electrical energy conversion efficiency coefficient of the power-to-gas equipment, the natural gas flow output by the power-to-gas equipment, and the electrical power consumed by the power-to-gas equipment.

[0040] It should also be noted that the introduction of multi-energy storage devices in the integrated energy system can realize the transfer of energy in actual dimensions, improve energy utilization efficiency, reduce transportation facilities and production, and reduce system carbon emissions. The multi-energy storage unit includes a battery sub-model, a heat storage sub-model, and a gas storage sub-model, and its capacity and charge and discharge power constraints must be considered.

[0041] The battery sub-model is used to calculate the charge of the energy storage battery at the current moment according to the charge of the energy storage battery at the previous moment, the charging power and the discharging power of the energy storage battery at the current moment; the heat storage sub-model is used to calculate the heat power carried by the heat storage device at the current moment according to the heat power carried by the heat storage device at the previous moment, the heat storage power and the heat release power of the heat storage device at the current moment; the gas storage sub-model is used to calculate the natural gas capacity of the gas storage device at the current moment according to the natural gas capacity of the gas storage device at the previous moment, the stored natural gas volume of the gas storage device at the current moment and the released natural gas volume.

[0042] The battery sub-model is:

[0043]

[0044]

[0045]

[0046]

[0047] In the formula, is the charging power of the energy storage battery at time t, in kW, is the discharge power of the energy storage battery at time t, in kW, is the charging factor of the energy storage battery, is the discharge efficiency coefficient of the energy storage battery, is the charge of the energy storage battery at time t, is the charge of the energy storage battery at time t-1, is the minimum charge of the energy storage battery, The maximum charge of the energy storage battery; The model building parameters corresponding to the battery sub-model include the charging power of the energy storage battery at time t, the discharging power of the energy storage battery at time t, the charging coefficient of the energy storage battery, the discharge efficiency coefficient of the energy storage battery, the charge of the energy storage battery at time t, the charge of the energy storage battery at time t-1, the minimum charge of the energy storage battery and the maximum charge of the energy storage battery.

[0048] It should also be noted that It is used to limit the battery charging and discharging behaviors from occurring simultaneously.

[0049] The heat storage sub-model is:

[0050]

[0051] Similar to energy storage batteries, the following conditions must be met to ensure the stable operation of the thermal storage device:

[0052]

[0053] In the formula, is the heat storage power of the heat storage device at time t, in kW, is the heat release power of the heat storage device at time t, in kW, is the efficiency coefficient of heat storage of the heat storage device, is the efficiency coefficient of heat release of the heat storage device, is the thermal power carried by the heat storage device at time t, is the thermal power carried by the heat storage device at time t-1, is the minimum capacity of the heat storage device, is the maximum capacity of the heat storage device; The model building parameters corresponding to the heat storage sub-model include the heat storage power of the heat storage device at time t, the heat release power of the heat storage device at time t, the efficiency coefficient of heat storage of the heat storage device, the efficiency coefficient of heat release of the heat storage device, the heat power carried by the heat storage device at time t, the heat power carried by the heat storage device at time t-1, the minimum capacity of the heat storage device and the maximum capacity of the heat storage device.

[0054] The gas storage sub-model is:

[0055]

[0056] In the formula, is the amount of natural gas stored in the gas storage device at time t, in m 3 / h, is the amount of natural gas released by the gas storage device at time t, in m 3 / h, is the efficiency coefficient of the gas storage device, is the efficiency coefficient of the gas storage device release, is the natural gas capacity of the gas storage device at time t, is the natural gas capacity of the gas storage device at time t-1, is the minimum capacity of the gas storage device, is the maximum capacity of the gas storage device.

[0057] The model building parameters corresponding to the gas storage sub-model include the amount of natural gas stored in the gas storage device at time t, the amount of natural gas released by the gas storage device at time t, the efficiency coefficient of storage of the gas storage device, the efficiency coefficient of release of the gas storage device, the natural gas capacity of the gas storage device at time t, the natural gas capacity of the gas storage device at time t-1, the minimum capacity of the gas storage device and the maximum capacity of the gas storage device.

[0058] It should be understood that the carbon emissions of the integrated energy system over its entire life cycle can be divided into direct carbon emissions and indirect carbon emissions. Direct carbon emissions refer to carbon dioxide directly produced by burning fuels, while indirect carbon emissions refer to carbon emissions during the equipment construction process, as well as carbon emissions during the operation and maintenance process and the dismantling and recycling process. For new energy equipment and energy storage devices in the IES system, no direct carbon emissions will be generated during operation, so it is necessary to consider the carbon emissions during the construction and dismantling process. The carbon emissions during construction and dismantling depend on the capacity. The capacity of other equipment has been determined, so it is sufficient to consider the direct carbon emissions released by combustion during the operation stage.

[0059] It should also be noted that the operating carbon emissions between the cogeneration unit sub-model, the gas boiler sub-model and the power grid purchase amount are determined, and the carbon emissions corresponding to the multi-energy storage unit are determined; the operating carbon emissions and the carbon emissions corresponding to the multi-energy storage unit are used as the carbon emissions corresponding to the park's comprehensive energy model.

[0060] In this implementation, the carbon emissions of the new energy unit throughout its life cycle (the carbon emissions corresponding to the new energy unit) include the carbon dioxide generated during the construction process and the carbon dioxide generated during the demolition stage.

[0061] The carbon dioxide produced during the construction process is:

[0062] In the formula, It is the amount of CO2 generated during the construction of new energy equipment, in kg. For the construction phase Loss factor of the material; It is the conversion factor between standard unit electricity and energy consumption, unit is MJ / kW·h; For construction Carbon emission intensity of the material, in kg / t; The used The embodied energy intensity value of a material, in MJ / t; , The power consumption for this process is in kW·h / kW; , is the maximum installed capacity of photovoltaic and wind power, in kW; The carbon dioxide in the demolition process is:

[0063] In the formula, The amount of carbon dioxide emissions saved by recycling; , is the effective recovery rate of photovoltaic and wind power systems; , It is the carbon emission coefficient during the demolition process, and its unit is kg / kW·h.

[0064] In this embodiment, the carbon emissions of the energy storage equipment over its entire life cycle (i.e., the carbon emissions corresponding to the multi-energy storage unit) are calculated based on the average carbon emissions of batteries as a typical example, as there is little research on heat and gas storage in China. , including CO2 emissions during construction and demolition: The carbon dioxide emissions during the construction process are:

[0065] Where: The CO2 generated by the electricity required for the construction of the energy storage system, in kg. The electrical energy consumption for this process, unit: kW·h / kW. Maximum installed power for maximum energy storage.

[0066] The carbon dioxide emissions from the demolition process are:

[0067] Where: The carbon dioxide emissions from the energy storage device recovery process; It is the effective recovery rate of energy storage equipment after it is scrapped; It is the effective recovery carbon emission coefficient, and its unit is kg / kW.

[0068] Carbon emissions from other equipment in the integrated energy system (i.e., carbon emissions from the operation of the combined heat and power unit sub-model, gas boiler sub-model, and electricity purchased from the power grid) include carbon dioxide generated by the combustion of natural gas internal combustion engines and gas turbine boilers, and carbon dioxide generated by electricity purchased from the power grid:

[0069] Where: It represents the carbon dioxide generated during the operation of the multi-energy flow system, in kg. , is the electric power and thermal power generated by the cogeneration unit and the gas boiler at time t, in kW, The carbon emission coefficient corresponding to the electricity purchased from the power grid. It is the carbon dioxide emission coefficient of natural gas burned per unit of electricity. is the purchased electrical power at time t, in kW.

[0070] The value of equipment changes over time. Based on the equal annual value method, the annual discounted carbon emissions can be expressed as:

[0071]

[0072] Where: , is the discount rate for new energy units and energy storage equipment; , is the service life, in years.

[0073] Therefore, the total carbon emissions of the multi-energy flow system over its entire life cycle (i.e., the total carbon emissions of the multi-energy flow) are:

[0074] Step S20: constructing a cost objective function according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the park comprehensive energy model and the cost information corresponding to the new energy units.

[0075] Furthermore, a carbon trading cost function corresponding to the comprehensive energy model of the park is constructed according to the total carbon emissions of multiple energy flows; a cost target function is constructed according to the investment cost function, energy cost function, wind and solar power abandonment cost function and carbon trading cost function corresponding to the comprehensive energy model of the park.

[0076] In this embodiment, the cost objective function is:

[0077] in Including system investment cost , Energy cost , Carbon trading costs 2. Cost of curtailing wind and solar power .

[0078] Furthermore, the model construction cost information and the model operation and maintenance cost information are determined according to the cost information corresponding to the comprehensive energy model of the park, and the unit construction cost information and the unit operation and maintenance cost information are determined according to the cost information corresponding to the new energy unit; and an investment cost function is constructed according to the model construction cost information, the model operation and maintenance cost information, the unit construction cost information and the unit operation and maintenance cost information.

[0079] The system investment cost includes the equipment construction and operation and maintenance costs. The system construction cost change is determined by the capacity of new energy equipment and energy storage equipment. Considering that the system construction cost is mainly determined by the construction capacity of new energy and energy storage equipment, the expression is:

[0080] In the formula, Cost of equipment construction; is the equipment operation and maintenance cost.

[0081]

[0082] In the formula, , is the unit capacity construction cost of new energy equipment and energy storage equipment, in yuan / kW; , , , , , The unit operation and maintenance cost of new energy, energy storage, cogeneration unit, electric boiler, gas boiler, and power-to-gas equipment, in RMB / kW; Furthermore, the energy cost of the system includes the cost of natural gas consumption by the combined heat and power unit and gas boiler (i.e., natural gas consumption cost information) and the cost of purchasing and selling electricity from the distribution network (i.e., grid electricity cost information):

[0083]

[0084]

[0085] In the formula, is the scheduling period; It is the total time period of electricity purchase within the dispatch cycle; The real-time electricity price that the park purchases from the distribution network during the period; The real-time electricity price sold by the park to the distribution network during the period; is the electrical load; The purchase price for natural gas.

[0086] Furthermore, the system's carbon trading costs adopt an excess penalty mechanism. As the excess exceeds the range, the penalty price will also increase accordingly:

[0087] Where: is the carbon trading price; is the carbon emission quota of the multi-energy flow system, in kg; is the carbon emission quota that can be purchased by the multi-energy flow system at different penalty stages, in kg; is the carbon penalty factor; Furthermore, the cost of abandoning wind and solar power is:

[0088]

[0089]

[0090] Where: is the cost coefficient of wind and solar power abandonment, , The abandoned wind and solar power, , Indicates the proportion of wind turbines and photovoltaic units participating in system dispatch, , Provide real-time power for photovoltaic and wind power.

[0091] Step S30: constructing energy balance constraint conditions according to the sub-model variables of the park comprehensive energy model and the park's daily historical load data.

[0092] Furthermore, the processing method for constructing energy balance constraints based on the sub-model variables of the park's comprehensive energy model and the park's daily historical load data is to determine the historical electricity load, historical heat load and historical gas load based on the park's daily historical load data; based on the historical electricity load, historical heat load, historical gas load and wind power output curve (reference Figure 4 , Figure 4 The typical daily load and wind power per unit output curve of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention) determine the actual photovoltaic output and the actual wind power output; construct energy balance constraints according to the sub-model variables of the park comprehensive energy model, historical electricity load, historical heat load and historical gas load, the actual photovoltaic output and the actual wind power output; Energy balance constraints:

[0093]

[0094]

[0095]

[0096] In the formula, is the historical electricity load, is the historical heat load, is the historical gas load, For the actual output of photovoltaic For the actual output of wind power, Charging power for energy storage batteries, is the discharge power of the energy storage battery, is the purchased electrical power at time t, Selling electricity to the distribution network, is the amount of natural gas purchased, is the interconnection line interaction power, is the daily contact line interaction power, is the current contact line interaction power, It is the interactive power fluctuation of the interconnection line.

[0097] The sub-model variables of the park's comprehensive energy model are the model building parameters used when constructing the cogeneration unit sub-model, electric boiler sub-model, gas boiler sub-model, power-to-gas equipment sub-model and multi-energy storage unit.

[0098] Step S40: Based on the energy balance constraint, the cost minimum is solved through the cost objective function to obtain a comprehensive energy source and storage configuration plan for the park, and the source and storage are optimized according to the comprehensive energy source and storage configuration plan for the park.

[0099] It should be understood that based on the energy balance constraints, the minimum investment cost, the minimum energy cost, the minimum wind and solar power abandonment cost and the minimum carbon trading cost are calculated through the cost objective function; and the comprehensive energy source and storage configuration plan of the park is determined according to the minimum investment cost, the minimum energy cost, the minimum wind and solar power abandonment cost and the minimum carbon trading cost.

[0100] It should also be noted that when the minimum cost is calculated, the optimal value variables corresponding to each sub-model in the park's comprehensive energy model and the photovoltaic installation capacity and wind power installation capacity of the new energy units can be determined, and the optimal source and storage configuration plan (i.e., the park's comprehensive energy source and storage configuration plan) can be determined based on the optimal variables corresponding to each sub-model and the photovoltaic installation capacity and wind power installation capacity of the new energy units.

[0101] In this implementation, it is assumed that the historical load data of the multi-energy flow system in a typical day (T = 24h) is taken, the power balance of electricity, heat and gas is maintained in the entire dispatching cycle, and the new energy is output in per unit value. The typical day electrical heat load and new energy output curve are as follows: Figure 1 As shown in the figure, the life cycle of multi-energy flow equipment is unified as 20 years, the average annual discount rate of equipment is 6%, and the carbon emission quota of multi-energy flow system is = 400kg, the carbon emission quota that can be purchased by the multi-energy flow system at different penalty stages = 200 kg, primary fine price = 0.55 yuan / kg, penalty factor lc Take 1.2.

[0102] The real-time electricity price of the power grid and the cost of wind and solar curtailment are both based on the time-of-use electricity price shown in Table 1, which is divided into peak, flat and valley periods: peak period: 16:00 to 21:00, flat period: 7:00 to 16:00, and valley period: 21:00 to 24:00 and 0:00 to 7:00; the natural gas price is 3.45 yuan per cubic meter, which is converted into a calorific value of 0.364 yuan / kW·h; the rated capacity of CHP in the multi-energy flow system is 200kW, the rated capacity of EB is 150kW, the rated capacity of P2G is 100kW, and the upper and lower limits of interaction with the power grid are 400kW. Other relevant operation and cost parameters are shown in Table 2. Finally, the particle swarm optimization algorithm is used to verify the effectiveness of the multi-objective optimization model considering carbon emissions throughout the life cycle. The maximum number of iterations of the particle swarm algorithm is 100, the population size N is 50, the learning factors are 0.5 and 4 respectively, and the scheduling interval is 1 hour.

[0103] Table 1 Time-of-use electricity prices and wind and solar power curtailment prices at different time periods

[0104] Table 2 Relevant cost parameters of the park multi-energy flow system

[0105] refer to Figure 5 and Table 3, Figure 5 This is a comparison chart of system costs under four different situations of the first embodiment of the source-storage joint optimization configuration method based on the park comprehensive energy model of the present invention. Table 3 shows the configuration results under different schemes under situations 1-4.

[0106] Table 3 Optimization configuration results under different situations

[0107] Situations 1-4 represent the results of joint optimization configuration of new energy units without energy storage equipment and wind and solar units, with wind and solar units configured alone, and with energy storage equipment and energy storage equipment configured alone. It can be seen from the configuration results of Situations 1-4 that, compared with the results of Situations 2 and 3 with new energy units configured alone, the joint optimization configuration increases the access capacity of two low-carbon devices, new energy units and energy storage equipment, and effectively reduces the carbon emissions and new energy consumption rate of the multi-energy flow system. Compared with Situation 1, although Situation 4 has large construction and wind and solar abandonment costs, the carbon emission cost of Situation 1 without low-carbon equipment is 4671.61 yuan more than that of Situation 1. In Situation 2, there is no low-carbon equipment, which causes the gas turbine to be basically in full power throughout the day to meet the load demand, and the total system cost also increases by 5233 yuan. Compared with Situations 2 and 4, it can be seen that the access of energy storage equipment effectively reduces the abandonment of wind and solar power, and the energy storage equipment outputs at low times, saving the cost of purchasing energy, and reducing carbon emissions by 524.6kg. In comparison with Situations 2-3, Situation 4 achieves low-carbon economic optimization of the multi-energy flow system and verifies the effectiveness and feasibility of the joint optimization configuration of new energy units and energy storage equipment.

[0108] By comparing Situation 1 with other scenarios, it can be seen that if the multi-energy flow system is not equipped with new energy units and energy storage equipment, the carbon emissions of the multi-energy flow system will be very high, with a cost of up to 6,534.2 yuan. The total cost of the system is also the largest, up to 13,395.6 yuan, indicating that new energy equipment and energy storage are currently important means to build a low-carbon park. It is necessary to optimize the configuration of this when planning the multi-energy flow system.

[0109] In this embodiment, first, a comprehensive energy model of the park is constructed according to the cogeneration unit sub-model, the electric boiler sub-model, the gas boiler sub-model, the power-to-gas equipment sub-model and the multi-energy storage unit. The comprehensive energy model of the park is constructed by the combination of the cogeneration unit sub-model, the electric boiler sub-model, the gas boiler sub-model, the power-to-gas equipment sub-model and the multi-energy storage unit. Then, the total carbon emissions of the multi-energy flows are determined according to the carbon emissions corresponding to the comprehensive energy model of the park and the carbon emissions corresponding to the new energy units. Then, according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the comprehensive energy model of the park and the cost information corresponding to the new energy units, and according to the sub-model variables of the comprehensive energy model of the park and the daily historical load data of the park, an energy balance constraint condition is constructed. Finally, based on the energy balance constraint condition, the comprehensive energy source and storage configuration plan of the park is obtained through the cost objective function, and the source and storage are optimized according to the comprehensive energy source and storage configuration plan of the park. This embodiment takes the energy cost, investment cost, carbon emission cost, and wind and solar power abandonment cost of the park's comprehensive energy model as multiple objectives, which can effectively improve the access capacity of new energy units and energy storage equipment, ensure the economy of the system while effectively reducing carbon emissions.

[0110] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0111] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0112] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware data platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0113] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A source-storage joint optimization configuration method based on a comprehensive energy model of a park, characterized in that: The source-storage joint optimization configuration method based on the park comprehensive energy model comprises the following steps: Determine the total carbon emissions of multiple energy flows according to the carbon emissions corresponding to the park comprehensive energy model and the carbon emissions corresponding to the new energy units, wherein the park comprehensive energy model is constructed by a combination of a cogeneration unit sub-model, an electric boiler sub-model, a gas boiler sub-model, a power-to-gas equipment sub-model and a multi-energy storage unit, wherein the multi-energy storage unit includes a battery sub-model, a heat storage sub-model and a gas storage sub-model; Constructing a cost objective function according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the park comprehensive energy model, and the cost information corresponding to the new energy unit; Constructing energy balance constraints based on sub-model variables of the park comprehensive energy model and the park's daily historical load data; Based on the energy balance constraint, the cost minimum is solved through the cost objective function to obtain a comprehensive energy source and storage configuration plan for the park, and the source and storage are optimized according to the comprehensive energy source and storage configuration plan for the park.

2. The method according to claim 1, characterized in that The battery sub-model is used to calculate the charge of the energy storage battery at the current moment according to the charge of the energy storage battery at the previous moment, the charging power and the discharging power of the energy storage battery at the current moment; The heat storage sub-model is used to calculate the heat power carried by the heat storage device at the current moment according to the heat power carried by the heat storage device at the previous moment, the heat storage power and the heat release power of the heat storage device at the current moment; The gas storage sub-model is used to calculate the natural gas capacity of the gas storage device at the current moment according to the natural gas capacity of the gas storage device at the previous moment, the stored natural gas amount and the released natural gas amount of the gas storage device at the current moment.

3. The method according to claim 2, characterized in that The battery sub-model is: In the formula, is the charging power of the energy storage battery at time t, is the discharge power of the energy storage battery at time t, is the charging factor of the energy storage battery, is the discharge efficiency coefficient of the energy storage battery, is the charge of the energy storage battery at time t, is the charge of the energy storage battery at time t-1, is the minimum charge of the energy storage battery, It is the maximum charge of the energy storage battery.

4. The method according to claim 2, characterized in that The heat storage sub-model is: In the formula, is the heat storage power of the heat storage device at time t, is the heat release power of the heat storage device at time t, is the efficiency coefficient of heat storage of the heat storage device, is the efficiency coefficient of heat release of the heat storage device, is the thermal power carried by the heat storage device at time t, is the thermal power carried by the heat storage device at time t-1, is the minimum capacity of the heat storage device, is the maximum capacity of the heat storage device.

5. The method according to claim 2, characterized in that The gas storage sub-model is: In the formula, is the amount of natural gas stored in the gas storage device at time t, is the amount of natural gas released by the gas storage device at time t, is the efficiency coefficient of the gas storage device, is the efficiency coefficient of the gas storage device release, is the natural gas capacity of the gas storage device at time t, is the natural gas capacity of the gas storage device at time t-1, is the minimum capacity of the gas storage device, is the maximum capacity of the gas storage device.

6. The method according to any one of claims 1 to 5, characterized in that: Before the step of determining the total carbon emissions of multiple energy flows according to the carbon emissions corresponding to the park comprehensive energy model and the carbon emissions corresponding to the new energy units, the method includes: Determine the operating carbon emissions between the cogeneration unit submodel, the gas boiler submodel and the power grid purchased electricity, and determine the carbon emissions corresponding to the multi-energy storage unit; The carbon emissions corresponding to the park comprehensive energy model are determined based on the operating carbon emissions and the carbon emissions corresponding to the multi-energy storage unit.

7. The method according to claim 6, characterized in that The step of constructing a cost objective function according to the total carbon emissions of the multi-energy flows, the cost information corresponding to the park comprehensive energy model, and the cost information corresponding to the new energy unit includes: Determine the model construction cost information and the model operation and maintenance cost information according to the cost information corresponding to the park comprehensive energy model, and determine the unit construction cost information and the unit operation and maintenance cost information according to the cost information corresponding to the new energy unit; Constructing an investment cost function according to the model construction cost information, the model operation and maintenance cost information, the unit construction cost information and the unit operation and maintenance cost information; Determine natural gas consumption cost information corresponding to the cogeneration unit sub-model and the gas boiler sub-model; Constructing an energy cost function based on the natural gas consumption cost information and the grid electricity cost information; Constructing a carbon trading cost function corresponding to the park comprehensive energy model according to the total carbon emissions of the multi-energy flows; Construct a cost function for wind and solar power abandonment based on abandoned wind and solar power power, real-time photovoltaic output, and real-time wind power output; A cost objective function is constructed according to the investment cost function, the energy cost function, the carbon trading cost function and the wind and solar power abandonment cost function.

8. The method according to claim 7, characterized in that The step of constructing energy balance constraint conditions according to the sub-model variables of the park comprehensive energy model and the park's daily historical load data includes: Determine the historical electricity load, historical heat load and historical gas load based on the park's daily historical load data; Determine the actual photovoltaic output and the actual wind power output according to the historical electrical load, the historical thermal load, the historical gas load and the wind power unit output curve; Energy balance constraints are constructed based on the sub-model variables of the park comprehensive energy model, the historical electricity load, the historical heat load and the historical gas load, the actual photovoltaic output and the actual wind power output.

9. The method according to claim 8, characterized in that The step of solving the cost minimum through the cost objective function based on the energy balance constraint condition to obtain a comprehensive energy source storage configuration plan for the park includes: Based on the energy balance constraint, the minimum investment cost, the minimum energy cost, the minimum wind and solar power abandonment cost and the minimum carbon trading cost are calculated through the cost objective function; Determine the comprehensive energy source and storage configuration plan for the park based on the minimum investment cost, minimum energy consumption cost, minimum wind and solar power abandonment cost and minimum carbon trading cost.

10. A source-storage joint optimization configuration device based on a comprehensive energy model of a park, characterized in that: The device includes: a memory, a processor, and a source-reservoir joint optimization configuration processing program based on a comprehensive energy model of a park stored in the memory and executable on the processor, wherein the source-reservoir joint optimization configuration program based on a comprehensive energy model of a park is configured to implement the steps of the source-reservoir joint optimization configuration method based on a comprehensive energy model of a park as described in any one of claims 1 to 9.

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