An optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal heat storage

Abstract

This invention discloses an optimization method for an electric-heat-gas multi-energy flow system considering inter-seasonal thermal storage, comprising the following steps: establishing an inter-seasonal thermal storage system model based on source-load data and price information of the electric-heat-gas multi-energy flow system; considering the operational planning constraints of the electric-heat-gas multi-energy flow system; and establishing a joint optimization model for the planning and operation of the electric-heat-gas multi-energy flow system considering inter-seasonal thermal storage. From a medium- to long-term operational perspective, this invention introduces inter-seasonal thermal storage technology to achieve inter-seasonal transfer of heat supply and joint optimization of planning and operation.

Description

Technical Field

[0001] This invention relates to an energy optimization method for multi-energy flow systems, and more particularly to an optimization method for an electric-thermal-gas multi-energy flow system that takes into account cross-seasonal thermal storage. Background Technology

[0002] With the continuous advancement of national new urbanization and the "dual carbon" target, urban energy systems are characterized by multi-energy flow coupling operation (electricity, heat, and gas) and high penetration rates of renewable energy sources such as wind and solar power, facing the development requirements of improving quality and efficiency as well as energy conservation and emission reduction. Influenced by factors such as meteorology and the market, there are resource endowments in the energy supply and demand of urban energy systems. Cross-seasonal energy storage technology can achieve large-scale energy time-series adjustment over a longer time scale and a wider spatial range, effectively addressing a series of problems caused by differences in wind and solar resource endowments and energy prices.

[0003] For urban energy systems, large-scale thermal storage technology has greater versatility and potential for widespread adoption. However, there are few reports on cross-seasonal thermal storage technology, and most studies focus on day-ahead optimization of small-scale thermal storage devices. Therefore, there is an urgent need to propose a new joint optimization method for the planning and operation of multi-energy flow systems (electricity, heat, and gas) that takes into account cross-seasonal thermal storage. Summary of the Invention

[0004] Purpose of the invention: To address the problems existing in the prior art, the purpose of this invention is to provide a joint optimization method for the planning and operation of an electric-heat-gas multi-energy flow system that takes into account cross-seasonal thermal storage. By taking into account the seasonal thermal supply and demand transfer capacity of large-scale thermal storage systems, the method controls the charging and releasing of heat in cross-seasonal thermal storage systems at different times, providing a new method and reference for cross-seasonal energy storage capacity planning and operation optimization of electric-heat-gas multi-energy flow systems.

[0005] Technical solution: The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage, as described in this invention, includes the following steps:

[0006] (1) Establish a cross-seasonal thermal storage system model;

[0007] (2) Establish operational planning constraints for multi-energy flow systems that consider electricity, heat and gas;

[0008] (3) A joint optimization model for the planning and operation of an electric-heat-gas multi-energy flow system that takes into account cross-seasonal thermal storage is proposed.

[0009] (4) Solve the above objective function to determine the planned capacity of the cross-seasonal thermal storage system, as well as the energy optimization scheduling results of the power subsystem, thermal subsystem and natural gas subsystem for each month.

[0010] Furthermore, the cross-seasonal thermal energy storage system model described in step (1) is based on the annual source-load data and price information of the electric-heat-gas multi-energy flow system, and satisfies the following constraints:

[0011] Heat balance constraints:

[0012]

[0013] In the formula, N i This represents the number of hours in the i-th time period; This represents the average power of the electric boiler during time period i, in MW. This represents the average power of the steam boiler during time period i, in MW. This represents the average power output of the combined heat and power unit during time period i, in MW. This represents the average power of the heat source during time period i, in MW. This represents the average power of the thermal load during time period i, in MW.

[0014] Constraints on the heat charge / discharge period:

[0015]

[0016]

[0017] In the formula, and Let be a set of 0-1 variables, representing the charging and discharging state of the BTES system during time period i;

[0018] Charge and discharge heat power constraints:

[0019]

[0020]

[0021]

[0022] In the formula, This represents the heat storage capacity of the BTES system during time period i, in MWh. and These represent the heat charge / discharge efficiency, respectively. and These represent the charge and discharge heat power during time period i, in MW; and These represent the heat storage of the BTES system at the beginning and end of the scheduling cycle, respectively, in MWh; This indicates the upper limit of the charge / discharge heat power, in MW;

[0023] Maximum planned capacity limit:

[0024]

[0025] In the formula, This indicates the planned thermal storage capacity of the BTES system, expressed in MWh. and These represent the upper and lower limits of the heat storage capacity of the BTES system during operation, respectively, in MWh.

[0026] Furthermore, in step (2), the operational planning constraints of the electric-heat-gas multi-energy flow system include the energy supply and demand balance constraints of the electric-heat-gas system, the energy interaction constraints with the outside of the town, the maintenance constraints of the cogeneration unit, and the operational constraints of the energy conversion and storage equipment.

[0027] Furthermore, the energy supply and demand balance constraints of the electric-heat-gas system include the energy supply and demand balance constraints of the power system, the energy supply and demand balance constraints of the heating system, and the energy supply and demand balance constraints of the natural gas system.

[0028] Furthermore, the energy interaction constraints with the outside of the town include electrical energy interaction constraints and natural gas energy interaction constraints.

[0029] Furthermore, the maintenance constraints for the combined heat and power unit include:

[0030] Maintenance period constraints:

[0031]

[0032]

[0033] In the formula, N i N represents the number of hours in the i-th time period; m,min and N m,max These represent the earliest and latest start times for the maintenance of the m-th combined heat and power unit; J min and J max These represent the earliest and latest times when a cogeneration unit can begin maintenance, respectively; τ m,i The variable is 0-1 and is used to characterize the start of maintenance of the cogeneration unit. A value of 1 indicates that the m-th unit starts maintenance in time period i.

[0034] Single maintenance duration constraint:

[0035]

[0036]

[0037] In the formula, τ represents the period during which the unit begins maintenance; N represents the number of hours required for the maintenance of the m-th combined heat and power unit; durIndicates the number of time periods required for maintenance; y m,i The variable T is a 0-1 value used to characterize the maintenance status of the cogeneration unit. A value of 1 indicates that the m-th cogeneration unit is under maintenance during time period i; a value of 0 indicates that the m-th cogeneration unit is not under maintenance during time period i. n This represents the number of time periods after clustering the time series data;

[0038] Maintenance and operation related constraints:

[0039]

[0040]

[0041] In the formula, N chp Indicates the number of combined heat and power (CHP) units in a multi-energy flow system in a town; It is a constant representing the upper limit of the capacity to simultaneously overhaul a combined heat and power unit; Let be a set of 0-1 variables representing the operating status of the m-th cogeneration unit during time period i.

[0042] Furthermore, the operational constraints of the energy conversion and storage equipment include the model and constraints of the gas storage facility, the model and constraints of the combined heat and power unit, the model and constraints of the gas boiler, the constraints of wind and solar power output, and the charging and discharging constraints of the battery and thermal storage tank.

[0043] Furthermore, in step (3), the overall objective function of the joint optimization of planning and operation is:

[0044] min(C cap +C ope )

[0045]

[0046]

[0047] In the formula, C cap C represents the annualized investment cost of the equipment. ope The annual operating cost of the planned urban multi-energy flow system; This indicates the thermal storage capacity of the thermal storage system, expressed in MWh. This indicates the unit investment cost of the thermal energy storage system, expressed in yuan / MWh; R B This represents the capital recovery factor, which is related to the equipment's lifespan n and the discount rate d.

[0048]

[0049] In the formula, C en C is the system's energy purchase cost; ma For operation and maintenance costs; Ccur Costs associated with curtailing wind and solar power; Cost of carbon emissions.

[0050] Furthermore, the operation and maintenance costs include the operation and maintenance costs of wind and solar power generators, energy conversion and coupling equipment, energy storage equipment, and leased gas storage facilities within the town; wherein, the operation and maintenance cost of the gas storage facility is expressed as the product of its unit volume filling and discharging cost and the filling and discharging gas volume:

[0051]

[0052] In the formula, T n This represents the number of time periods after clustering the time series data; K es K hs and K BTES These represent the operation and maintenance costs of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, electric boilers, batteries, thermal storage tanks, and inter-seasonal thermal storage systems, respectively, in yuan / MWh; K gas This indicates the cost of the gas storage facility's filling and releasing process, expressed in yuan / Sm. 3 ; and These represent the average operating power of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, and electric boilers during time period i, respectively, in MW; This represents the average gas filling and discharging rate of the gas storage facility during time period i, in units of Sm. 3 / h; and These represent the average charging / discharging power of the battery and the average charging / discharging power of the heat storage tank during time period i, respectively. and These represent the charge and discharge heat power during time period i, in MW.

[0053] Furthermore, the cost of wind and solar curtailment is expressed as the amount of curtailed electricity and carbon emissions multiplied by a corresponding unit economic penalty coefficient; although wind and solar power generation have near-zero carbon emissions during operation, their carbon emissions are converted to the operational phase to represent the carbon dioxide generated by the equipment itself during the production phase; the cost of wind and solar curtailment C cur :

[0054]

[0055] In the formula, T n N represents the number of time periods after clustering the time series data; i This represents the number of hours in the i-th time period; and The values ​​represent the curtailment costs of wind power and solar power, respectively, in yuan / MWh. and These represent the historical power output values ​​of wind and solar power generation during time period i, respectively, in MW; and These represent the average operating power of wind power and photovoltaic power generation during time period i, respectively, in MW.

[0056] Beneficial effects: Compared with the prior art, the present invention has the following significant progress: It introduces the seasonal heat supply and demand transfer capability of a large-scale thermal storage system into the electric-heat-gas multi-energy flow system. From the perspective of medium and long-term operation, by controlling the charging and releasing heat of the thermal storage system at different times, the heat supply and demand relationship is transferred, promoting energy conversion and interaction between various systems, improving the system's renewable energy absorption capacity, and reducing the overall operating cost of the system. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the process of the present invention;

[0058] Figure 2 This is a schematic diagram of energy flow according to an embodiment of the present invention;

[0059] Figure 3 This is a typical per-unit curve of daily energy supply and demand.

[0060] Figure 4 This invention presents the energy supply results of the power subsystem before and after planning.

[0061] Figure 5 This invention presents the energy demand results of the power subsystem before and after planning.

[0062] Figure 6 This is a comparison of the supply conditions of the thermal subsystem of the present invention;

[0063] Figure 7 This is a comparison of the requirements of the thermal subsystem of this invention;

[0064] Figure 8 This invention plans the natural gas purchase volume and gas storage operation status of the natural gas subsystem before and after implementation.

[0065] Figure 9 This invention describes the total gas supply of the natural gas subsystem before and after planning.

[0066] Figure 10 This invention describes the operational status of the hydrogen storage tanks in the natural gas subsystem before and after planning. Detailed Implementation

[0067] The technical solution of the present invention will be explained and described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage, as described in this invention, includes the following steps:

[0069] Step 1: Obtain annual source-load data and price information, and establish a cross-seasonal thermal storage system model;

[0070] The network topology information of the electric-heat-gas multi-energy flow system includes the network topology structure and node connection relationships of the electric, heat, and gas systems; the line type and length of the power system; the pipeline type and length of the heat system; and the pipeline type and length of the natural gas system. Typical representative day source-load data includes the per-unit load curves and benchmark values ​​for the electric load, heat load, and natural gas load on typical representative days; and the per-unit output curves and benchmark values ​​for photovoltaic power generation and wind power generation. Price information includes the electricity price, heat price, and gas price for users of the electric-heat-gas multi-energy flow system; the electricity purchase price from the power grid and the electricity purchase price from the gas turbine of the power subsystem; the gas purchase price from the natural gas subsystem of the heat subsystem; and the gas purchase price from the natural gas trading platform of the natural gas subsystem.

[0071] The constraints for the cross-seasonal thermal storage system model and operation planning include charging and releasing power constraints, heat balance constraints, charging and releasing time period constraints, and maximum planned capacity limits, namely:

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] In the formula, The heat storage of the BTES system during time period i is expressed in MWh. and These represent the heat charge / discharge efficiency, respectively. and Let i represent the charge and discharge heat power in time period i, in MW; and These represent the upper and lower limits of the heat storage capacity of the BTES system during operation, respectively, in MWh; and These represent the heat storage capacity of the BTES system at the beginning and end of the scheduling cycle, respectively, in MWh; Indicates the upper limit of charge / discharge power, in MW; and Let be a set of 0-1 variables, representing the charging and discharging state of the BTES system during time period i.

[0079] Step 2: Establish operational planning constraints for the multi-energy flow system involving electricity, heat, and gas;

[0080] The operational planning constraints for an electric-thermal-gas multi-energy flow system include:

[0081] (1) Planning constraints for cross-seasonal thermal storage systems:

[0082]

[0083] In the formula, and These represent the upper and lower limits of capacity planning for cross-seasonal thermal storage systems, respectively, in MWh; u B It is a 0-1 variable; when it is 1, it means planning the BTES system, and otherwise it means not planning.

[0084] (2) Energy balance constraint of electric heating gas:

[0085]

[0086] In the formula, Represents the average power of the electrical load during time period i, in MW; The average power of the thermal load during time period i, in MW; Sm represents the average rate of natural gas load during period i. 3 / h.

[0087] (3) Energy interaction constraints with the outside of the town:

[0088]

[0089]

[0090] In the formula, This refers to the electricity volume under medium- and long-term power contracts signed for urban multi-energy flow systems, in MWh. This indicates the upper limit of the transmission power of a substation, expressed in MW. Sm indicates the maximum rate at which natural gas can be purchased. 3 / h.

[0091] (4) Unit maintenance constraints

[0092] As the core coupling element connecting the three subsystems of electricity, heat, and gas, the reliable operation of the combined heat and power (CHP) unit is crucial for urban multi-energy flow systems.

[91] Assume that each cogeneration unit is overhauled once a year, and the overhaul period must meet certain requirements, namely:

[0093]

[0094]

[0095] In the formula, N m,min and N m,max These represent the earliest and latest start times for the maintenance of the m-th combined heat and power unit; J min and J max These represent the earliest and latest times when a cogeneration unit can begin maintenance, respectively; τ m,i The variable is 0-1 and is used to characterize the start of maintenance of the cogeneration unit. A value of 1 indicates that the m-th unit starts maintenance in time period i.

[0096] A single maintenance operation requires a certain amount of time. If the combined heat and power unit begins maintenance during time period τ, then:

[0097]

[0098]

[0099] In the formula, N represents the number of hours required for the maintenance of the m-th combined heat and power unit; dur Indicates the number of time periods required for maintenance; y m,i The value is a 0-1 variable used to characterize the maintenance status of the cogeneration unit. When the value is 1, it means that the m-th cogeneration unit is under maintenance during time period i; when the value is 0, it means that the m-th cogeneration unit is not under maintenance during time period i.

[0100] The number of cogeneration units that can be simultaneously maintained in a multi-energy flow system in a town is limited by maintenance capacity; therefore, the number of cogeneration units under maintenance must meet certain constraints. Furthermore, cogeneration units cannot be simultaneously under maintenance and in operation.

[0101]

[0102]

[0103] In the formula, N chp Indicates the number of combined heat and power (CHP) units in a multi-energy flow system in a town; It is a constant representing the upper limit of the capacity to simultaneously overhaul a combined heat and power unit; Let be a set of 0-1 variables representing the operating status of the m-th cogeneration unit during time period i.

[0104] (5) Equipment operating constraints

[0105] To ensure the safe operation of energy production, conversion, and storage equipment within urban areas, certain constraints must be met, namely...

[0106]

[0107] In the formula, and represents the historical power output of wind and solar power during time period i, in MW.

[0108] Step 3: Establish a joint optimization model for the planning and operation of an electric-heat-gas multi-energy flow system that takes into account cross-seasonal thermal storage;

[0109] The joint optimization model for planning and operation aims to minimize the sum of the annualized investment cost of the cross-seasonal thermal storage system and the annual operating cost of the electricity-heat-gas multi-energy flow system.

[0110] Establish the following objective function:

[0111] min(C cap +C ope )

[0112] Among them, C cap C represents the annualized investment cost of the equipment. ope The annual operating costs of the planned urban multi-energy flow system are expressed as follows:

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120] In the formula, The thermal storage capacity of the thermal storage system is expressed in MWh. R represents the unit investment cost of the thermal energy storage system, expressed in yuan / MWh; B The capital recovery factor is related to the equipment's lifespan (n) and the discount rate (d); C en C ma C cur and These represent the system's energy purchase cost, operation and maintenance cost, wind and solar curtailment cost, and carbon emission cost, respectively; T n N represents the number of time periods after clustering the time series data; i This represents the number of hours in the i-th time period; This represents the average power purchased from the upstream power grid during time period i, in MW. This represents the electricity purchase price from the upper-level power grid during time period i, expressed in yuan / MWh; Sm represents the gas purchase rate from the upstream gas network during time period i. 3 / h; This represents the gas purchase price from the upstream gas network during time period i, in yuan / Sm. 3 ; K bt K hst and K BTES These represent the operation and maintenance costs of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, electric boilers, batteries, thermal storage tanks, and inter-seasonal thermal storage systems, respectively, in yuan / MWh; K gas This indicates the cost of the gas storage facility's filling and releasing process, expressed in yuan / Sm. 3 ; and Let i represent the average operating power (MW) of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, and electric boilers during time period i. Sm represents the average gas filling and discharging rate of the gas storage facility during time period i. 3 / h; and Let i represent the average charge / discharge power of the battery and the average charge / discharge power of the heat storage tank during time period i, respectively, in MW; and These represent the curtailment costs of wind power and solar power, respectively, in yuan / MWh; and Represent the historical power output of wind and solar power during time period i, in MW; The unit emission cost of carbon dioxide is expressed in yuan / ton; and These represent the carbon emission coefficients of wind power, photovoltaic power, and substations, respectively, in t / MWh; The carbon emission factor of natural gas is expressed in t / Sm. 3 .

[0121] Step 4: Solve the above objective function to determine the joint optimization results of the planning and operation of the electric-thermal-gas multi-energy flow system that takes into account cross-seasonal thermal storage.

[0122] The joint optimization model for the planning and operation of the multi-energy flow system of electric-thermal-gas considering cross-seasonal thermal storage is a linear optimization problem under multiple constraints, which can be solved by various methods. For example, it can be built using the Yalmip platform and the optimization solver Gurobi can be called to obtain the result.

[0123] The annual source-load data of a certain region in East China was selected for analysis. The basic parameter settings include: (1) combining the typical daily source-load energy supply and demand per unit value curve and the source-load benchmark value to obtain the average output of wind and solar power and the average load of electricity, heat and gas for each hour; (2) the operating parameters of the coupling equipment and energy storage equipment are shown in Table 1; (3) the annual electricity purchase from the upstream power grid shall not exceed 280,000 MWh, the electricity purchase power shall not exceed 80 MW, and the gas purchase rate from the upstream gas grid shall not exceed 12,000 Sm. 3 / h; (4) Substation carbon emission coefficient 0.4tCO2 / MWh, wind power carbon emission coefficient 0.0276tCO2 / MWh, photovoltaic power carbon emission coefficient 0.0584tCO2 / MWh, natural gas carbon emission coefficient 5.61×10 -5 tCO2 / MJ, exchange rate is €1 = 7.27 yuan; (5) purchase price from the upstream power grid is 0.45 yuan / kWh, natural gas price takes seasonal fluctuations, spring price is 2.113 yuan / Sm 3 In summer, the price is 1.934 yuan / Sm. 3 The price in autumn is 1.936 yuan / Sm 3 In winter, the price is 3.272 yuan / sm 3 (6) The maintenance capacity of the combined heat and power unit is set at 1 unit, and the number of maintenance times per year is set at 1. (7) The upper limit of the volume of natural gas mixed with hydrogen is set at 20%. (8) The lower limit of the capacity planning of the cross-seasonal thermal storage system is set at 1000GJ, i.e. 278MWh. At the same time, in order to avoid the problem of land occupation caused by excessive thermal storage volume, the upper limit of the planned capacity should be set. Referring to the actual project, it is set at 6000MWh. Other detailed parameters are shown in Table 2. (9) The subsidy price of the electric hydrogen production system from the higher-level government is set at 0.25 yuan / kWh.

[0124] Table 1 Operating parameters of coupling equipment and energy storage equipment

[0125]

[0126]

[0127] Table 2 Detailed Planning Parameters for Seasonal Thermal Storage Systems

[0128]

[0129] The planning of the urban multi-energy flow system was realized by using the Yalmip platform and the Groubi solver, taking into account the cross-seasonal thermal storage and hydrogen production system. The planning and operation of the system were jointly optimized. The planning results are shown in Table 3.

[0130] Table 3 Planning Results

[0131] Configuration variables Configuration results Cross-seasonal thermal storage system capacity / MWh 6000 Electrolytic cell rated power / MW 1.4821 <![CDATA[Hydrogen storage tank gas storage capacity / Sm 3 > 33767

[0132] As shown in Table 3, the planned capacity of the inter-seasonal thermal storage system has reached its upper limit. This is mainly due to two reasons: (1) the technology of inter-seasonal thermal storage is relatively mature and the cost is low; (2) there is idle power in the heating devices of the urban multi-energy flow system. The energy flow relationship of the planned urban multi-energy flow system is as follows: Figure 2 As shown.

[0133] Depend on Figure 4 and Figure 5 It can be seen that since the cross-seasonal thermal storage system is in a heat release state from November 15 to March 15 of the following year, and in a heat charging state for the rest of the time, this alleviates the heating pressure in winter to a certain extent, and also reduces the degree of limitation on the power output capacity of the cogeneration unit due to the low heat demand in summer. Therefore, after considering the planning of cross-seasonal thermal storage and hydrogen production systems: (1) During June to August, the amount of electricity purchased from outside the plant will decrease significantly. After the cogeneration unit breaks through the heat output limit, the output of the cogeneration unit No. 2, which has a higher overall efficiency, will increase significantly. The advantage of the low minimum output limit of cogeneration unit No. 1 will no longer exist, and the output will decrease significantly. (2) During the peak season for heat demand, the electricity consumption of electric boilers will decrease due to the heat supply of the cross-seasonal energy storage system. (3) The overall trend of hydrogen production power consumption shows a certain degree of following the demand and price of natural gas and the overall resource endowment trend of clean energy. It shows the characteristics of "maximum in winter, followed by spring and autumn, and minimum in summer". This is mainly because hydrogen production can consume excess clean energy, mix it with natural gas, and reduce the demand for gas load. Among them, the electricity consumption of the hydrogen-generating device was the largest in January and December, both exceeding 1100MWh; (4) The consumption of wind power and photovoltaic power has increased to a certain extent, and the overall consumption of clean power has increased by 1688MWh. This is mainly due to the hydrogen-generating device. However, due to the high cost of the hydrogen-generating device, its configuration capacity is small, resulting in a small increase in the overall consumption of wind and solar power; (5) The introduction of the hydrogen-generating device has played a role in smoothing out the fluctuations of wind and solar power to a certain extent, so the total charging and discharging capacity of the battery has decreased.

[0134] Depend on Figure 6 and Figure 7It can be seen that after considering the planning of the cross-seasonal thermal storage and electric hydrogen production system: (1) The heating situation of the cogeneration unit and electric boiler is consistent with the results of the power subsystem, and will not be elaborated here; (2) The heat output of the gas boiler is generally reduced. During June to August, the main reason is that the introduction of the cross-seasonal thermal storage device allows the cogeneration unit to break through the heat output limit, thereby compressing the heat supply of the gas boiler during the summer. During the heating season, the heat supply of the gas boiler is also reduced due to the heat supply of the cross-seasonal thermal storage system; (3) The heat charge and release of the heat storage tank is generally reduced, especially during June to August. The reason for this phenomenon is that the surplus heat during this period is mainly stored for a long time through the cross-seasonal thermal storage device; (4) In order to avoid the cross-seasonal thermal storage system occupying too much land area, the planned capacity of the thermal storage system is relatively small compared with the heat storage demand. It is mainly used to alleviate the output coupling constraint of the cogeneration unit and absorb the surplus heat during the summer when the natural gas price is low and the electricity demand is high. The heat charge is very small during other periods of the non-heating season.

[0135] Depend on Figures 8 to 10 It can be seen that, after considering the planning of cross-seasonal thermal storage and electric hydrogen production systems: (1) Except for a slight decrease in the total energy supply of mixed hydrogen gas in February, thanks to the role of electric hydrogen production units in absorbing surplus clean electricity, the total energy supply of mixed hydrogen gas in urban multi-energy flow systems increased in other months, with the increase being more significant from June to August. This was mainly due to the increased gas demand of cogeneration units, which also led to an increase in the purchase of natural gas during the summer; (2) During the winter, the purchase of natural gas, the total gas supply from gas sources and gas storage facilities all decreased, mainly due to the supplementary energy supply role played by the electric hydrogen production system. Among them, the hydrogen consumption was the highest in December, reaching 2.96 × 10 5 Sm 3 The energy provided accounts for 1.45% of the total energy supplied by mixed hydrogen gas; (3) The gas storage facility stores gas in the summer when the gas consumption is low and the natural gas price is low, and releases gas in the winter when the gas consumption is high and the natural gas price is high, so as to realize the cross-seasonal transfer of gas load, reduce gas supply pressure and reduce costs; (4) The hydrogen storage tank of the electric hydrogen production system not only plays the role of buffering the gas flow, but also can adjust the amount of hydrogen entering and leaving, so as to realize the cross-month transfer of hydrogen energy supply and demand.

Claims

1. An optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage, characterized in that, Includes the following steps: (1) Establish a cross-seasonal thermal storage system model; the cross-seasonal thermal storage system model is based on the annual source-load data and price information of the electric-heat-gas multi-energy flow system, and meets the constraints of heat balance, charging and releasing time period, charging and releasing power and maximum planning capacity limit; (2) Establish operational planning constraints for multi-energy flow systems that consider electricity, heat and gas; The operational planning constraints of the electric-heat-gas multi-energy flow system include the energy supply and demand balance constraints of the electric-heat-gas system, the energy interaction constraints with the outside of the town, the maintenance constraints of the cogeneration unit, and the operational constraints of the energy conversion and storage equipment. (3) Establish a joint optimization model for the planning and operation of a multi-energy flow system of electricity, heat and gas that takes into account cross-seasonal thermal storage; (4) Solve the optimization model to determine the planned capacity of the cross-seasonal thermal storage system, as well as the energy optimization scheduling results of the power subsystem, thermal subsystem and natural gas subsystem for each month; Among them, the heat balance constraint is: In the formula, N i This represents the number of hours in the i-th time period; This represents the average power of the electric boiler during time period i, in MW. This represents the average power of the steam boiler during time period i, in MW. This represents the average power output of the combined heat and power unit during time period i, in MW. This represents the average power of the heat source during time period i, in MW. This represents the average power of the thermal load during time period i, in MW. Constraints on the heat charge / discharge period: In the formula, and Let be a set of 0-1 variables, representing the charging and discharging state of the BTES system during time period i; Charge and discharge heat power constraints: In the formula, This represents the heat storage capacity of the BTES system during time period i, in MWh. and These represent the heat charge / discharge efficiency, respectively. and These represent the charge and discharge heat power during time period i, in MW; and These represent the heat storage of the BTES system at the beginning and end of the scheduling cycle, respectively, in MWh; This indicates the upper limit of the charge / discharge heat power, in MW; Maximum planned capacity limit: In the formula, This indicates the planned thermal storage capacity of the BTES system, expressed in MWh. and These represent the upper and lower limits of the heat storage capacity of the BTES system during operation, respectively, in MWh; The maintenance constraints for the combined heat and power (CHP) units include: Maintenance period constraints: where N i denotes the number of hours in the ith time period; N m,min and N m,max denote the earliest and latest start-up time period of the mth cogeneration unit, respectively; J min and J max denote the earliest and latest time at which the cogeneration unit can start up, respectively; τ m,i is a 0-1 variable that represents the start-up action of the cogeneration unit, and takes the value of 1 if the mth cogeneration unit starts up in the ith time period. Single maintenance duration constraint: In the formula, τ represents the period during which the unit begins maintenance; N represents the number of hours required for the maintenance of the m-th combined heat and power unit; dur Indicates the number of time periods required for maintenance; y m,i The variable T is a 0-1 value used to characterize the maintenance status of the cogeneration unit. A value of 1 indicates that the m-th cogeneration unit is under maintenance during time period i; a value of 0 indicates that the m-th cogeneration unit is not under maintenance during time period i. n This represents the number of time periods after clustering the time series data; Maintenance and operation related constraints: In the formula, N chp Indicates the number of combined heat and power (CHP) units in a multi-energy flow system in a town; It is a constant representing the upper limit of the capacity to simultaneously overhaul a combined heat and power unit; Let be a set of 0-1 variables representing the operating status of the m-th cogeneration unit during time period i.

2. The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage as described in claim 1, characterized in that, The energy supply and demand balance constraints of the electric-heat-gas system include the energy supply and demand balance constraints of the power system, the energy supply and demand balance constraints of the heating system, and the energy supply and demand balance constraints of the natural gas system.

3. The operational planning constraints of the multi-energy flow system considering electricity, heat, and gas as described in claim 1, characterized in that, The energy interaction constraints with the outside of the town include electrical energy interaction constraints and natural gas energy interaction constraints.

4. The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage as described in claim 1, characterized in that, The operational constraints of the energy conversion and storage equipment include the model and constraints of the gas storage facility, the model and constraints of the combined heat and power unit, the model and constraints of the gas boiler, the constraints of wind and solar power output, and the energy charging and discharging constraints of the battery and thermal storage tank.

5. The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage as described in claim 1, characterized in that, In step (3), the overall objective function of the joint optimization of planning and operation is: min(C cap +C ope ) In the formula, C cap C represents the annualized investment cost of the equipment. ope The annual operating cost of the planned urban multi-energy flow system; This indicates the thermal storage capacity of the thermal storage system, expressed in MWh. This indicates the unit investment cost of the thermal energy storage system, expressed in yuan / MWh; R B This represents the capital recovery factor, which is related to the equipment's lifespan n and the discount rate d. In the formula, C en C is the system's energy purchase cost; ma For operation and maintenance costs; C cur Costs associated with curtailing wind and solar power; Cost of carbon emissions.

6. The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage as described in claim 5, characterized in that, The operation and maintenance costs include the operating and maintenance costs of wind and solar power generators, energy conversion and coupling equipment, energy storage equipment, and leased gas storage facilities within the town; wherein, the operation and maintenance cost of the gas storage facility is expressed as the product of the unit volume filling and releasing cost and the filling and releasing gas volume: In the formula, T n This represents the number of time periods after clustering the time series data; K es K hs and K BTES These represent the operation and maintenance costs of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, electric boilers, batteries, thermal storage tanks, and inter-seasonal thermal storage systems, respectively, in yuan / MWh; K gas This indicates the cost of the gas storage facility's filling and releasing process, expressed in yuan / Sm. 3 ;P i w P i p P i chp , and These represent the average operating power of wind power generation, photovoltaic power generation, combined heat and power units, gas boilers, and electric boilers during time period i, respectively, in MW; This represents the average gas filling and discharging rate of the gas storage facility during time period i, in units of Sm. 3 / h;P i es and These represent the average charging / discharging power of the battery and the average charging / discharging power of the heat storage tank during time period i, respectively. and These represent the charge and discharge heat power during time period i, in MW.

7. The optimization method for an electric-thermal-gas multi-energy flow system considering cross-seasonal thermal storage as described in claim 5, characterized in that, The cost of curtailing wind and solar power is expressed as the amount of curtailed electricity and carbon emissions multiplied by a corresponding unit economic penalty coefficient. Although wind and solar power generation have near-zero carbon emissions during operation, their carbon emissions are factored into the operational phase to represent the carbon dioxide generated by the equipment itself during production. The cost of curtailing wind and solar power, C... cur : In the formula, T n N represents the number of time periods after clustering the time series data; i This represents the number of hours in the i-th time period; and The values ​​represent the curtailment costs of wind power and solar power, respectively, in yuan / MWh. and P i pf P represents the historical power output of wind and solar power during time period i, in MW; i w and P i p These represent the average operating power of wind power and photovoltaic power generation during time period i, respectively, in MW.

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