Thermoelectric coupling thermal power and molten salt heat storage multi-time scale scheduling method and system

Abstract

The application discloses a thermal power and fused salt heat storage multi-time scale scheduling method and system coupled with a thermoelectricity, constructs a thermoelectricity coupling operation model on the basis of fused salt heat storage, realizes decoupling of thermal power and electricity through double-path adjustment of steam heat supply on the boiler side and electric heat supply on the power generation side, comprehensively considers factors of power generation income, auxiliary service compensation, heat storage operation and life cost and pollution emission cost, establishes a thermoelectricity coupling operation model under a set time scale, establishes an intra-day rolling optimization model, the objective function is to minimize the deviation of power generation power and load demand, the deviation of heat supply and heat load and the deviation of the initial time and the last time of intra-day and the day-ahead scheduling plan, carries out intra-day rolling optimization under the time scale according to the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the intra-day real-time thermal power load and new energy fluctuation obtained through prediction, and corrects the day-ahead scheduling plan in real time. The method can coordinate and optimize under the day-ahead and intra-day multi-time scale, and give consideration to economy and stability.

Description

Technical Field

[0001] This invention belongs to the field of power system optimization and dispatching technology. It relates to a multi-timescale dispatching method and system for thermoelectric coupled thermal power and molten salt thermal storage. Background Technology

[0002] As the traditional main power source, thermal power units need to be upgraded to improve their ability to absorb intermittent renewable energy sources such as wind and solar power. Common thermal power unit flexibility upgrade technologies include "rapid load change" retrofitting, which improves the unit's output regulation rate by optimizing boiler structure, control system and operating strategy, enabling it to respond more quickly to system load changes and compensate for the intermittency of renewable energy output.

[0003] While rapid load change retrofitting improves response speed, it comes at the cost of economic efficiency and equipment reliability, making it unsustainable for supporting a high proportion of renewable energy consumption. To overcome these issues, molten salt thermal energy storage retrofitting is gradually becoming an effective way to improve the flexibility of thermal power units. Molten salt thermal energy storage systems consist of storage tanks, heat exchangers, pumps, and piping systems. They offer advantages such as high-temperature stability (thermal efficiency can reach over 90%), low cost, and long service life, making them suitable for high-temperature steam systems in thermal power units.

[0004] During operation, the thermal storage system achieves the spatial and temporal transfer of thermal energy through the charging and discharging process:

[0005] The heat charging process: During periods of low load on thermal power units or when there is an oversupply of new energy sources, the excess heat power from the boiler and steam turbine is absorbed and stored in molten salt to reduce the minimum or excess output of thermal power.

[0006] Heat release process: During peak load or when the output of new energy sources is insufficient, stored heat energy is released. The high-temperature tank increases the steam intake of the steam turbine, and the low-temperature tank heats the feedwater to form high-temperature water that enters the boiler, thereby improving the output of thermal power and the heating capacity.

[0007] Existing research indicates that molten salt thermal storage retrofitting can achieve "thermal-electric decoupling" to a certain extent. That is, while maintaining stable thermal output of thermal power, the unit's peak-shaving capacity can be improved and coal consumption and mechanical losses can be reduced by adjusting the steam heating on the boiler side and the electric heating on the power generation side to affect the external power output and thermal output.

[0008] However, while existing molten salt thermal energy storage retrofits can improve the peak-shaving range of units, most studies only focus on the basic integration and operation of the thermal energy storage units, failing to fully explore the deep regulation capabilities of thermoelectric coupling, and failing to fully integrate the thermoelectric coupling mechanism. Furthermore, there is a lack of a unified optimization model between day-ahead economics and intraday real-time stability. This invention addresses this issue. Summary of the Invention

[0009] The purpose of this invention is to provide a multi-timescale scheduling method and system for thermoelectric coupled thermal power and molten salt thermal storage. It constructs a two-layer scheduling optimization model consisting of a day-ahead scheduling optimization model and an intraday rolling optimization model, and uniformly incorporates multi-dimensional factors such as power generation revenue, thermal storage cost, and environmental cost, so as to achieve a coordinated balance between economic efficiency, flexibility and stability under the fluctuation of new energy sources.

[0010] The technical solution to achieve the purpose of this invention is as follows:

[0011] A multi-timescale scheduling method for thermoelectric coupled thermal power and molten salt thermal storage includes the following steps:

[0012] Based on molten salt thermal storage, a thermoelectric coupled operation model is constructed, and thermoelectric power decoupling is achieved through dual-path regulation of steam heating on the boiler side and electric heating on the power generation side;

[0013] Taking into account factors such as power generation revenue, ancillary service compensation, thermal storage operation and life costs, and pollution emission costs, a day-ahead dispatch optimization model is established under a set time scale.

[0014] An intraday rolling optimization model is established, with the objective function being to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and renewable energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time.

[0015] In the preferred technical solution, based on molten salt thermal storage, the following are included:

[0016] Centered on thermal power units that have undergone molten salt thermal energy storage retrofitting, a high-temperature / low-temperature dual-loop molten salt thermal energy storage system is configured. This system consists of storage tanks, heat exchangers, pumps, and piping. The storage tanks store high-temperature molten salt, the heat exchangers transfer heat to the working fluid, and the pumps and piping system circulates the molten salt. In actual operation, the storage tanks are divided into high-temperature and low-temperature dual-loop storage tanks. The high-temperature storage tank is located between the boiler and the high-pressure tank of the steam turbine, while the low-temperature storage tank is located between the steam turbine's working cylinder and the boiler. The charging process occurs within the thermal power unit... During periods of low load or excess power generation, high-temperature and low-temperature thermal storage tanks absorb excess heat power from the boiler and steam turbine's working cylinders, transferring it to molten salt via heat exchangers and storing it in the storage tanks, thus reducing the minimum or excess output of thermal power plants. During peak load periods or when renewable energy output is insufficient, the storage tanks release the stored heat energy. The high-temperature storage tank increases the steam intake of the steam turbine, while the low-temperature storage tank heats liquid water to create high-temperature feedwater that enters the boiler, increasing thermal power output and heating. After molten salt thermal storage retrofitting, the thermal power units supply heat via boiler-side steam. and electric heating on the power generation side To meet the overall external heat load demand, achieve thermoelectric coupling, and regulate the peak and frequency of steam heating and electric heating power response, while smoothing out the real-time fluctuations of new energy units and loads during the day;

[0017] Through the molten salt thermal storage and heat release process, the thermal output of thermal power is realized. Without adjustment, change the steam supply on the boiler side. and the equivalent electrical output on the generator side This affects its external power output. and external electric heating .

[0018] In the preferred technical solution, the thermoelectric coupling operation model is constructed as follows:

[0019]

[0020] In the formula, / 、 / These represent the power stored / released by the high-temperature and low-temperature thermal storage systems during time period t, respectively. This represents the heat power transferred from the steam turbine to the generator during time interval t; , These represent the heat storage capacity of the high-temperature and low-temperature thermal storage systems at time t, respectively. or H , or L These are the heat loss rates of high-temperature and low-temperature thermal storage systems, respectively. or HC / or HD , or LC / or LD These refer to the thermal efficiency stored / released by high-temperature and low-temperature thermal storage systems, respectively. or coal For coal combustion thermal efficiency; for The amount of coal consumed at any given time; The calorific value of pulverized coal combustion; or ST For thermoelectric conversion efficiency, t for t The time interval of a period.

[0021] In the preferred technical solution, the objective function of the day-ahead scheduling optimization model is: to maximize the comprehensive operating revenue of thermal power plants within one day. fA As shown in the following formula:

[0022]

[0023] In the formula, U represents the complete set of all thermal power units participating in the dispatch. u For a specific thermal power unit in set U, The comprehensive power generation revenue of a single thermal power plant is calculated as follows:

[0024]

[0025] In the formula, This is the basic revenue from the sale of electricity by thermal power units; Compensation for thermal power units participating in deep peak-shaving ancillary services; The operating cost of thermal power units; For the flexibility and backup costs of thermal power units; The cost of pollution emissions from thermal power units; The comprehensive operating cost of molten salt thermal energy storage for thermal power units; This refers to the additional cost of purchasing heat when the thermal power unit's own heat supply is insufficient.

[0026] The calculation method for the renewable energy output cost to be borne is shown in the following formula:

[0027]

[0028] In the formula, T The total number of scheduling periods. Costs associated with curtailing solar / wind power; , and , These represent the maximum potential power generation capacity and the actual power generation capacity of wind power and photovoltaic power, respectively.

[0029] In the preferred technical solution, the day-ahead dispatch optimization model constraints for thermal power and new energy units include power balance, thermal power step ramp rate constraints under rapid load changes, thermal power unit power generation constraints, new energy power generation constraints, molten salt thermal storage system constraints, and thermal-electric coupling power constraints of thermal power units, as detailed below:

[0030] Power balance constraints include electrical power constraints and thermal power constraints;

[0031] The power balance constraint means that the total power generation capacity of thermal power units and new energy units must meet the load demand under different times and probabilities, that is:

[0032]

[0033] In the formula, In order to be in t Net electricity load demand over a time scale For thermal power units in t Equivalent electrical output on the generator side over a time scale For thermal power units in t External electric heating power over time scale For thermal power units in t Scheduling power requirements over a given time scale;

[0034] The thermal power balance constraint means that the thermal power unit after molten salt thermal storage modification meets the external heat load demand at different times through its own steam heating, electric heating, and purchased heat, that is:

[0035]

[0036] In the formula, For thermal power units in t Heat load demand over a time scale For thermal power units in t Boiler-side steam heating power on a time scale The difference between the thermal power output of the thermal power unit and the external heat load demand;

[0037] The constraint on the stepped ramp rate of thermal power plants under rapid load change conditions is as follows:

[0038]

[0039] In the formula, For thermal power units in t Load factor on a time scale and For thermal power units t Upper and lower limits of load factor on a time scale; m a , m b and m c The load rates of thermal power units are respectively t Lower limit benchmarks for different peak-shaving intervals on different time scales; For thermal power units in t Output over time scale r a , r b , r c These represent the maximum allowable rate of power change for the unit in different output ranges. a a, b, and c are the indices of the output range, respectively; Indicates the time interval of the scheduling model; Indicates the first x Lower limit of each output range; r x Indicates the first x The upper limit of the ramp rate for each output range;

[0040] The power generation constraints of thermal power units include upper and lower limits of unit output constraints and flexible reserve constraints, among which the flexible reserve constraints are as follows:

[0041]

[0042] In the formula, This represents the maximum thermal power output of the boiler side of the thermal power unit. and These are the upward and downward flexibility reserves for thermal power units, respectively. and These represent the upward and downward flexibility reserves of the thermal power units in interval n, respectively, for the previous time period. To achieve the minimum technical output of thermal power units;

[0043] Constraints on renewable energy generation:

[0044]

[0045] In the formula, m RE Minimum utilization rate for new energy generating units; m RE,d The percentage of the predicted output that can be reduced by new energy generating units per day; To provide actual power output for new energy generating units; Predicted power output for new energy generating units;

[0046] Constraints on molten salt thermal storage systems include capacity constraints and operational constraints of high- and low-temperature thermal storage systems.

[0047] Capacity constraints of high and low temperature thermal storage systems:

[0048]

[0049] In the formula, , They represent t Minimum and maximum thermal storage capacity of high-temperature systems over a given timescale; , They represent t Minimum and maximum thermal storage capacity of cryogenic systems over a timescale;

[0050] Operating constraints of high and low temperature thermal storage systems:

[0051]

[0052] In the formula, This indicates whether the thermal power unit is in operation. If it is in operation, the value is 1; otherwise, the value is 0. 、 and 、 These are 0-1 variables representing whether the high and low thermal storage systems are in the storage / release operating state, respectively. If they are in the operating state, the value is 1; otherwise, the value is 0. i HD and i LD The maximum heat transfer coefficient of high and low temperature thermal storage systems; and These are the maximum heat release power of the high- and low-temperature thermal storage systems, respectively.

[0053] Thermal power unit thermoelectric coupling power constraints:

[0054]

[0055] In the formula, , The minimum and maximum electric heating power of the thermal power unit after molten salt modification; This represents the maximum steam heating power of the thermal power unit after molten salt modification.

[0056] In the preferred technical solution, the objective function of the intraday rolling scheduling optimization model is calculated as follows:

[0057]

[0058]

[0059]

[0060]

[0061] In the formula, At a certain point in time t’ The total cost optimized when performing real-time scheduling; It is every real-time scheduling moment t The deviation between power generation capacity and net electricity load demand It is every real-time scheduling moment t Net electricity load demand; It is every real-time scheduling moment t The generator-side power output of the thermal power unit; It is every real-time scheduling moment t The thermal power units provide external electric heating; It is every real-time scheduling moment t The deviation between heating power and heat load demand; It is every real-time scheduling moment t The total system heat load; It is every real-time scheduling moment t Steam heating on the boiler side of the thermal power unit; It is every real-time scheduling moment t Thermal power units purchase heat from external sources; yes t = t’ and t = t’ + T’ The deviation between the current power generation capacity and the power generation plan. β 1, β 2, β 3 represents the weights of different objectives; and Each scheduling time is a separate event. t The planned values ​​for the generator-side power output and external heat supply of thermal power units.

[0062] In the preferred technical solution, the Big M method is used to process the absolute value of the deviation term, and the absolute value of the objective function under the time scale of the intraday rolling optimization model is solved, as follows:

[0063] The objective function is to minimize the deviation between power generation and load demand at each moment;

[0064] Introducing 0-1 variables , Each represents a real-time scheduling moment. t Whether the deviation between power generation and load demand is positive or negative, the following relationship must be satisfied between the two:

[0065]

[0066] After introducing a large positive number M, the original objective function is split into:

[0067]

[0068] The constraints are as follows:

[0069]

[0070] In the formula, , Represent t The positive and negative absolute values ​​of the deviation between power generation and load demand at any given time; when the deviation between power generation and load demand is positive... Take 1, Take 0, at this time It is a positive number. The value is 0; when the deviation between power generation and load demand is negative, Take 0, Take 1, at this time =0, It is a positive number; when the deviation between power generation and load demand is 0, The overall value is 0 due to the big M constraint;

[0071] right and The Big M method is used to solve for the absolute value of the deviation.

[0072] This invention also discloses a thermoelectric coupled thermal power and molten salt thermal storage multi-timescale scheduling system, comprising:

[0073] The thermoelectric coupling operation model construction module constructs a thermoelectric coupling operation model based on molten salt thermal storage, and achieves thermoelectric power decoupling through dual-path regulation of boiler-side steam heating and power generation-side electric heating;

[0074] The thermoelectric coupling operation model construction module comprehensively considers factors such as power generation revenue, ancillary service compensation, thermal storage operation and life cost, and pollution emission cost to establish a thermoelectric coupling operation model under a set time scale.

[0075] The intraday rolling optimization scheduling module establishes an intraday rolling optimization model. The objective function is to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and renewable energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time.

[0076] The present invention also discloses a computer storage medium storing a computer program thereon, wherein when the computer executes the computer program, it implements the multi-timescale scheduling method for thermoelectric coupling of thermal power and molten salt thermal storage as described in any of the above claims.

[0077] The present invention also discloses an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program stored in the memory. When the computer program is executed, it implements the multi-timescale scheduling method for thermoelectric coupling of thermal power and molten salt thermal storage as described in any of the above claims.

[0078] Compared with the prior art, the significant advantages of this invention are:

[0079] 1. Thermoelectric Coupling Modeling: A thermoelectric coupling operation model for thermal power units based on molten salt thermal storage retrofitting is proposed. This model utilizes dual-path regulation of boiler-side steam heating and generator-side electric heating to achieve flexible decoupling of thermal and electrical power, overcoming the limitations of traditional cogeneration's "heat-driven power generation" limitation. Through peak shaving and valley filling via thermal storage, frequent start-ups and shutdowns of thermal power units and coal consumption fluctuations are reduced, improving the overall system benefits.

[0080] 2. Deep Synergy Between Molten Salt Thermal Storage System and Thermal Power: A dual-loop molten salt thermal storage unit with both high and low temperatures is designed, and its operating characteristics are modeled in conjunction with the rapid load change constraints of the thermal power unit. This enhances the unit's peak-shaving capacity, reduces coal consumption and mechanical losses, and ensures operational reliability. The dual-loop molten salt thermal storage and thermoelectric coupling mechanism enables rapid power regulation, significantly improving the ability to track fluctuations in renewable energy sources. It also reduces mechanical losses caused by steep load increases in thermal power units and extends the lifespan of key components.

[0081] 3. Multi-timescale optimized scheduling framework: Construct a two-layer scheduling optimization model that combines day-ahead and intraday scheduling, and uniformly incorporate multi-dimensional factors such as power generation revenue, thermal storage costs, and environmental costs to achieve a coordinated balance between economic efficiency, flexibility, and stability under the fluctuation of new energy sources. Attached Figure Description

[0082] Figure 1 A flowchart of a multi-timescale scheduling method for thermoelectric coupled thermal power and molten salt thermal storage;

[0083] Figure 2 This is the energy flow diagram of the modified thermal power plant. Detailed Implementation

[0084] The principle of this invention is to construct a two-layer scheduling optimization model, namely a day-ahead scheduling optimization model and an intraday rolling optimization model, and to uniformly incorporate multi-dimensional factors such as power generation revenue, thermal storage costs, and environmental costs, so as to achieve a coordinated balance between economic efficiency, flexibility, and stability under the fluctuation of new energy sources.

[0085] Example:

[0086] like Figure 1 As shown, a multi-timescale scheduling method for thermoelectric coupled thermal power and molten salt thermal storage includes the following steps:

[0087] Based on molten salt thermal storage, a thermoelectric coupled operation model is constructed, and thermoelectric power decoupling is achieved through dual-path regulation of steam heating on the boiler side and electric heating on the power generation side;

[0088] Taking into account factors such as power generation revenue, ancillary service compensation, thermal storage operation and life costs, and pollution emission costs, a day-ahead dispatch optimization model is established under a set time scale.

[0089] An intraday rolling optimization model is established, with the objective function being to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and renewable energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time.

[0090] In another embodiment, a thermoelectrically coupled multi-timescale scheduling system for thermal power and molten salt thermal storage includes:

[0091] The thermoelectric coupling operation model construction module constructs a thermoelectric coupling operation model based on molten salt thermal storage, and achieves thermoelectric power decoupling through dual-path regulation of boiler-side steam heating and power generation-side electric heating;

[0092] The thermoelectric coupling operation model construction module comprehensively considers factors such as power generation revenue, ancillary service compensation, thermal storage operation and life cost, and pollution emission cost to establish a thermoelectric coupling operation model under a set time scale.

[0093] The intraday rolling optimization scheduling module establishes an intraday rolling optimization model. The objective function is to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and renewable energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time.

[0094] The following example illustrates the workflow of a thermoelectric coupled thermal power and molten salt thermal storage multi-timescale scheduling system, including the following steps:

[0095] S1. Based on molten salt thermal storage, a thermoelectric coupling operation model is constructed. Through dual-path regulation of steam heating on the boiler side and electric heating on the power generation side, flexible decoupling of thermoelectric power is achieved.

[0096] Centered on thermal power units that have undergone molten salt thermal energy storage retrofitting, a high-temperature / low-temperature dual-loop molten salt thermal energy storage system is configured. This system consists of storage tanks, heat exchangers, pumps, and piping. The storage tanks store high-temperature molten salt, the heat exchangers transfer heat to the working fluid, and the pumps and piping system circulates the molten salt. In actual operation, the storage tanks are divided into high-temperature and low-temperature dual-loop storage tanks. The high-temperature storage tank is located between the boiler and the high-pressure tank of the steam turbine, while the low-temperature storage tank is located between the steam turbine's working cylinder and the boiler. The charging process occurs within the thermal power unit... During periods of low load or excess power generation, high-temperature and low-temperature thermal storage tanks absorb excess heat power from the boiler and steam turbine's working cylinders, transferring it to molten salt via heat exchangers and storing it in the storage tanks, thus reducing the minimum or excess output of thermal power plants. During peak load periods or when renewable energy output is insufficient, the storage tanks release the stored heat energy. The high-temperature storage tank increases the steam intake of the steam turbine, while the low-temperature storage tank heats liquid water to create high-temperature feedwater that enters the boiler, increasing thermal power output and heating. After molten salt thermal storage retrofitting, the thermal power units supply heat via boiler-side steam. and electric heating on the power generation side To meet the overall external heat load demand, achieve thermoelectric coupling, and regulate the peak and frequency of steam heating and electric heating power response, while smoothing out the real-time fluctuations of new energy units and loads during the day;

[0097] Through the molten salt thermal storage and heat release process, the thermal output of thermal power is realized. Without adjustment, change the steam supply on the boiler side. and the equivalent electrical output on the generator side This affects its external power output. and external electric heating .

[0098] The modified thermal power energy flow diagram is as follows: Figure 2 .

[0099] When thermal power plants need to adjust their power output to meet fluctuating heat and electricity load demands, the output can be regulated through molten salt thermal storage. In this case, the operating model of the thermal power unit can be described as follows:

[0100]

[0101] In the formula, / 、 / These represent the power stored / released by the high-temperature and low-temperature thermal storage systems during time period t, respectively. This represents the heat power transferred from the steam turbine to the generator during time interval t; , These represent the heat storage capacity of the high-temperature and low-temperature thermal storage systems at time t, respectively. or H , or L These are the heat loss rates of high-temperature and low-temperature thermal storage systems, respectively. or HC , or HD , or LC , or LD The thermal efficiency stored / released by high-temperature and low-temperature thermal storage systems, respectively. or coal For coal combustion thermal efficiency; for The amount of coal consumed at any given time; The calorific value of pulverized coal combustion; or ST For thermoelectric conversion efficiency, t for t The time interval of a period.

[0102] S2. Establish a day-ahead scheduling optimization model, setting a time scale (e.g., 15 minutes), and comprehensively consider factors such as power generation revenue, ancillary service compensation, thermal storage operation and lifespan costs, and pollution emission costs.

[0103] The objective function of the current scheduling optimization model is: to maximize the comprehensive operating revenue of thermal power plants within one day. f A As shown in the following formula:

[0104]

[0105] In the formula, U represents the complete set of all thermal power units participating in the dispatch. u For a specific thermal power unit in set U, The comprehensive power generation revenue of a single thermal power plant is calculated as follows:

[0106]

[0107] In the formula, This is the basic revenue from the sale of electricity by thermal power units; Compensation for thermal power units participating in deep peak-shaving ancillary services; The operating cost of thermal power units; For the flexibility and backup costs of thermal power units; The cost of pollution emissions from thermal power units; The comprehensive operating cost of molten salt thermal energy storage for thermal power units; This refers to the additional cost of purchasing heat when the thermal power unit's own heat supply is insufficient.

[0108] When thermal power units cannot meet the net load demand of the power grid, new energy units can reduce their output. In this case, the thermal power units will have to bear certain additional costs. 。 The calculation method for the renewable energy output cost to be borne is shown in the following formula:

[0109]

[0110] In the formula, T represents the total number of scheduling periods. Costs associated with curtailing solar / wind power; , and , These represent the maximum potential power generation capacity and the actual power generation capacity of wind power and photovoltaic power, respectively.

[0111] (1) Comprehensive electricity sales revenue of thermal power units +

[0112] The comprehensive electricity sales revenue of thermal power units can be expressed as: + The sum is in the form of a sum. When the generating capacity of the unit exceeds the compensation benchmark, only the basic revenue remains from electricity sales. , can be represented as:

[0113]

[0114] In the formula, This represents the actual power generation capacity of the thermal power unit. C The electricity price is based on a unit of electricity generation, and thermal power units can obtain this revenue regardless of their power generation status.

[0115] When the generating capacity of the unit is less than the compensation benchmark, the revenue from the sale of electricity by the thermal power unit is divided by the basic revenue. In addition, it includes compensation revenue from participating in peak-shaving ancillary services. , It can be represented as:

[0116]

[0117]

[0118]

[0119] In the formula, Compensation for participating in peak-shaving ancillary services for each time period. This represents the maximum electrical output of the thermal power unit. C 1. C2 represents the unit electricity sales price based on different compensation benchmarks. If the generating capacity of the unit is less than the corresponding compensation benchmark, it can obtain this additional income. The power output load rate of thermal power units; m 1, m 2 represents the load factor benchmark corresponding to the first and second tiers of peak-shaving compensation; This is a seasonally related earnings adjustment factor.

[0120] (2) Operating costs of thermal power units

[0121] This cost calculation considers both conventional peak shaving and deep peak shaving scenarios for thermal power plants. In conventional peak shaving, operating costs only consider the coal consumption for power generation; in deep peak shaving, operating costs include not only the coal consumption for power generation but also the additional losses incurred by the thermal power units due to reduced output. Calculated using the following formula:

[0122]

[0123]

[0124] In the formula, The real-time operating cost of thermal power units; C coal This refers to the price per ton of coal. a RPR , b RPR , c RPR The coefficients are the fitting function coefficients for RPR loss. a DPR , b DPR These are the coefficients of the DPR loss fitting function.

[0125] (3) Flexibility standby cost of thermal power units

[0126] The formula for calculating the flexibility reserve cost of thermal power units is as follows:

[0127]

[0128] In the formula, , For thermal power units t The cost required to provide upward and downward flexibility reserves for the system at all times. Since the unit's rapid load ramp rate is divided into multiple stages, the corresponding flexibility reserves have different costs at different output stages of the unit. The specific calculation method can use existing methods, which will not be elaborated here.

[0129] (4) Pollution emission costs of thermal power units

[0130] The pollution emission costs of thermal power units are as follows:

[0131]

[0132] In the formula, , , These are the unit treatment cost, emission coefficient per unit power generation, and pollutant conversion coefficient for each pollutant from thermal power units. and The unit's pollution fitting coefficient; h For pollutant types, H The total number of pollutants considered in this model is particulate matter, SO2, and NO. x .

[0133] (5) Comprehensive operating cost of molten salt thermal energy storage for thermal power units

[0134] Thermal power units retrofitted with molten salt thermal energy storage include high / low temperature thermal energy storage systems, resulting in comprehensive operating costs, including operation and maintenance costs. and lifespan depreciation costs .

[0135]

[0136] Operating and maintenance costs of thermal energy storage systems

[0137] The thermal storage system incurs certain operation and maintenance costs during the charging and discharging process.

[0138]

[0139] In the formula, The cost of operation and maintenance of the thermal storage system; , These represent the power of the high-temperature thermal storage system releasing / storing heat at time t, respectively. , These represent the power of the low-temperature thermal storage system releasing / storing heat at time t.

[0140] Thermal storage system lifespan depletion cost

[0141] Thermal storage systems experience losses during charging and discharging, resulting in a reduced lifespan.

[0142]

[0143] In the formula, The investment and construction costs of the thermal storage system; The cycle life of the thermal storage system; , These are 0-1 variables representing whether the high-temperature and low-temperature thermal storage systems undergo a charge / discharge state transition at time t. If a charge / discharge state transition occurs, the value is 1; otherwise, it is 0.

[0144] (6) Purchased heat cost of thermal power units

[0145] Thermal power units retrofitted with molten salt thermal storage can output heat power externally. However, when these units cannot meet external heat load demands through steam and electric heating, they must purchase heat from external sources. The cost of purchased heat for thermal power units is... as follows:

[0146]

[0147] In the formula, C H,buy The unit price for heat purchased by thermal power units from external sources; This refers to the difference between the thermal power output of a thermal power unit and the external heat load demand.

[0148] The day-ahead dispatch optimization model for thermal power and renewable energy units includes constraints on power balance, thermal power step ramp rate under rapid load changes, thermal power generation constraints, renewable energy generation constraints, molten salt thermal storage system constraints, and thermal-electric coupling power constraints of thermal power units, as detailed below:

[0149] Power balance constraints include electrical power constraints and thermal power constraints;

[0150] The power balance constraint means that the total power generation capacity of thermal power units and new energy units must meet the load demand under different times and probabilities, that is:

[0151]

[0152] In the formula, In order to be in t Net electricity load demand over a time scale For thermal power units in t Equivalent electrical output on the generator side over a time scale For thermal power units in t External electric heating power over time scale For thermal power units in t Scheduling power requirements over a time scale.

[0153] The thermal power balance constraint means that the thermal power unit after molten salt thermal storage modification meets the external heat load demand at different times through its own steam heating, electric heating, and purchased heat, that is:

[0154]

[0155] In the formula, For thermal power units in t Heat load demand over a time scale For thermal power units in t Boiler-side steam heating power on a time scale This refers to the difference between the thermal power output of a thermal power unit and the external heat load demand.

[0156] The constraint on the stepped ramp rate of thermal power plants under rapid load change conditions is as follows:

[0157]

[0158] In the formula, For thermal power units in t Load factor on a time scale and For thermal power units t Upper and lower limits of load factor on a time scale; m a , m b and m c The load rates of thermal power units are respectively t The lower limit benchmark of the peak-shaving range on the time scale; For thermal power units in t Output over time scale r a , r b , r c These represent the maximum allowable power change rates of the unit in different output ranges, where a, b, and c are the indices of the output ranges. Indicates the time interval of the scheduling model; Indicates the first x Lower limit of each output range; r x Indicates the first x The upper limit of the gradient rate for each output range.

[0159] Thermal power unit generation constraints include upper and lower limits for unit output and flexible reserve constraints. Thermal power units in each... T A flexible reserve should be reserved to address potential uncertainties and power imbalances between operating output and load. The constraints for the flexible reserve are as follows:

[0160]

[0161] In the formula, This represents the maximum thermal power output of the boiler side of the thermal power unit. and These are the upward and downward flexibility reserves for thermal power units, respectively. and These represent the upward and downward flexibility reserves of the thermal power units in interval n, respectively, for the previous time period. To provide the minimum technical output for thermal power units.

[0162] Renewable energy generation is subject to constraints. When thermal power cannot meet power balance requirements, renewable energy generation can improve system output stability and operational economy by actively reducing some of its output. However, the output reduction by renewable energy in any given time period and within a single day cannot exceed specified limits.

[0163]

[0164] In the formula, m RE Minimum utilization rate for new energy generating units; m RE,d The percentage of the predicted output that can be reduced by new energy generating units per day; To provide actual power output for new energy generating units; It is predicted to contribute to the power output of new energy generating units.

[0165] Constraints on molten salt thermal storage systems include capacity constraints for high and low temperature thermal storage systems and operational constraints for high and low temperature thermal storage systems.

[0166] Capacity constraints of high and low temperature thermal storage systems:

[0167]

[0168] In the formula, , They represent t Minimum and maximum thermal storage capacity of high-temperature systems over a given timescale; , They represent t Minimum and maximum thermal storage capacity of cryogenic systems on a given timescale.

[0169] Operating constraints of high and low temperature thermal storage systems:

[0170]

[0171] In the formula, This indicates whether the thermal power unit is in operation. If it is in operation, the value is 1; otherwise, the value is 0. 、 and 、 These are 0-1 variables representing whether the high and low thermal storage systems are in the storage / release operating state, respectively. If they are in the operating state, the value is 1; otherwise, the value is 0. i HD and i LD The maximum heat transfer coefficient of high and low temperature thermal storage systems; and These represent the maximum heat release power of the high- and low-temperature thermal storage systems, respectively.

[0172] Thermal power units with thermoelectric coupling power constraints: After molten salt thermal storage retrofit, thermal power units can adjust steam heating and electric heating power through thermoelectric coupling to meet external heat load demands. The steam heating and electric heating power constraints of thermal power units are as follows:

[0173]

[0174] In the formula, , The minimum and maximum electric heating power of the thermal power unit after molten salt modification; This represents the maximum steam heating power of the thermal power unit after molten salt modification.

[0175] S3. Establish an intraday rolling optimization model, combining forecast information with minute-level time scales, to revise the day-ahead plan in real time, minimize power generation and net load, heating power and heat load, and plan deviations, and achieve load fluctuation tracking and real-time frequency regulation.

[0176] Based on the day-ahead scheduling optimization model, in order to feed back the real-time thermal power load and renewable energy fluctuations into the optimization model and scheduling scheme, the optimization scheduling results of the day-ahead scheduling optimization model under a set time scale are combined. The real-time thermal power load and renewable energy fluctuations are predicted by LSTM, and the rolling optimization is performed every minute under this time scale. The optimal scheduling scheme for the day is solved and corrected in real time to achieve the frequency regulation task and balance power fluctuations.

[0177] The intraday rolling dispatch optimization model does not require supply and demand balance at every moment. The objective function is to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations between the initial and final moments of the day and the day-ahead dispatch plan. The calculation is shown in the following formula:

[0178]

[0179]

[0180]

[0181]

[0182] In the formula, At a certain point in time t’ The total cost optimized for real-time scheduling; Δ t=1 / 15 h Δ t=1 / 60 h； It is every real-time scheduling moment t The deviation between power generation capacity and net electricity load demand It is every real-time scheduling moment t Net electricity load demand; It is every real-time scheduling moment t The generator-side power output of the thermal power unit; It is every real-time scheduling moment t The thermal power units provide external electric heating; It is every real-time scheduling moment t The deviation between heating power and heat load demand; It is every real-time scheduling moment t The total system heat load; It is every real-time scheduling moment t Steam heating on the boiler side of the thermal power unit; It is every real-time scheduling moment t Thermal power units purchase heat from external sources; yes t = t’ and t = t’ + T’ The deviation between the current power generation capacity and the power generation plan. β 1, β 2, β 3 represents the weights of different objectives; and Each scheduling time is a separate event. t The planned values ​​for the generator-side power output and external heat supply of thermal power units.

[0183] The constraints of the intraday rolling model at each time point are basically the same as those in the day-ahead scheduling model, including the thermal power step ramp rate constraint under rapid load change, thermal power unit power generation constraint, new energy power generation constraint, and molten salt thermal storage system constraint.

[0184] Since the objective function of the intraday rolling optimization model is to minimize the deviation, it is expressed as an absolute value term. To simplify the solution process and improve the efficiency of rolling optimization per minute, this model uses the Big M method to process the absolute value term of the deviation, as follows:

[0185] The objective function is to minimize the deviation between power generation and load demand at each moment.

[0186] First, introduce the 0-1 variables. , Each represents a real-time scheduling moment. t Whether the deviation between power generation and load demand is positive or negative, the following relationship must be satisfied between the two:

[0187]

[0188] After introducing a large positive number M, the original objective function is split into:

[0189]

[0190] The constraints are as follows:

[0191]

[0192] In the formula, , Represent t The positive and negative absolute values ​​of the deviation between power generation and load demand at any given time; when the deviation between power generation and load demand is positive... Take 1, Take 0, at this time It is a positive number. The value is 0; when the deviation between power generation and load demand is negative, Take 0, Take 1, at this time =0, It is a positive number; when the deviation between power generation and load demand is 0, The overall value is 0 due to the big M constraint;

[0193] right and The Big M method is used to solve for the absolute value of the deviation.

[0194] This invention proposes a modeling method for the operation of thermal power units that takes into account molten salt thermal storage retrofitting and thermoelectric coupling. It can form a scheduling framework for the coupling of thermal power and molten salt thermal storage, establish its operation model, give full play to the flexible regulation capability of molten salt thermal storage in the heat charging and releasing process and the decoupling advantage of thermoelectric coupling under dual-path heating, and further improve the peak-shaving capability, operational flexibility and renewable energy consumption level of the unit.

[0195] By optimizing the combined output of thermal power units and thermal storage units at two scheduling time scales—one day-ahead and one day-intraday—electrical and thermal power can quickly track load fluctuations while meeting heating demand, thereby reducing coal consumption and losses caused by frequent ramp-up and significantly improving the system's operational economy and safety.

[0196] A multi-timescale optimization model can be established that takes into account the constraints of thermal power ramping, thermal storage capacity limitations, and minimum utilization rate of new energy. Taking the coordinated operation of thermal power-molten salt thermal storage system and new energy units as the research object, the model maximizes the overall operating benefits within a day by comprehensively considering power generation revenue, ancillary service compensation, thermal storage operation and life costs, and environmental costs, thereby improving the overall benefits and operational reliability of the system.

[0197] In another embodiment, a computer storage medium stores a computer program thereon, wherein when the computer executes the computer program, it implements the thermoelectric coupling multi-timescale scheduling method for thermal power and molten salt thermal storage as described in any of the above embodiments.

[0198] In another embodiment, an electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor runs the computer program stored in the memory, wherein when the computer program is executed, it implements the thermoelectric coupling multi-timescale scheduling method for thermal power and molten salt thermal storage as described in any of the preceding embodiments.

[0199] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A multi-timescale scheduling method for thermoelectric coupled thermal power and molten salt thermal storage, characterized in that, Includes the following steps: Based on molten salt thermal energy storage, a thermoelectric coupling operation model is constructed, achieving decoupling of thermoelectric power through dual-path regulation of boiler-side steam heating and power generation-side electric heating; the molten salt thermal energy storage includes: Centered on thermal power units that have undergone molten salt thermal energy storage retrofitting, a high-temperature / low-temperature dual-loop molten salt thermal energy storage system is configured. This system consists of storage tanks, heat exchangers, pumps, and piping. The storage tanks store high-temperature molten salt, the heat exchangers transfer heat to the working fluid, and the pumps and piping system circulates the molten salt. In actual operation, the storage tanks are divided into high-temperature and low-temperature dual-loop storage tanks. The high-temperature storage tank is located between the boiler and the high-pressure tank of the steam turbine, while the low-temperature storage tank is located between the steam turbine's working cylinder and the boiler. The charging process occurs within the thermal power unit... During periods of low load or excess power generation, high-temperature and low-temperature thermal storage tanks absorb excess heat power from the boiler and steam turbine's working cylinders, transferring it to molten salt via heat exchangers and storing it in the storage tanks, thus reducing the minimum or excess output of thermal power plants. During peak load periods or when renewable energy output is insufficient, the storage tanks release the stored heat energy. The high-temperature storage tank increases the steam intake of the steam turbine, while the low-temperature storage tank heats liquid water to create high-temperature feedwater that enters the boiler, increasing thermal power output and heating. After molten salt thermal storage retrofitting, the thermal power units supply heat via boiler-side steam. and electric heating on the power generation side To meet the overall external heat load demand, achieve thermoelectric coupling, and regulate the peak and frequency of steam heating and electric heating power response, while smoothing out the real-time fluctuations of new energy units and loads during the day; Through the molten salt thermal storage and heat release process, the thermal output of thermal power is realized. Without adjustment, change the steam supply on the boiler side. and the equivalent electrical output on the generator side This affects its external power output. and external electric heating ; The thermoelectric coupling operation model is constructed as follows: In the formula, / 、 / These represent the power stored / released by the high-temperature and low-temperature thermal storage systems during time period t, respectively. This represents the heat power transferred from the steam turbine to the generator during time interval t; , These represent the heat storage capacity of the high-temperature and low-temperature thermal storage systems at time t, respectively. η H , η L These are the heat loss rates of high-temperature and low-temperature thermal storage systems, respectively. η HC / η HD , η LC / η LD These refer to the thermal efficiency stored / released by high-temperature and low-temperature thermal storage systems, respectively. η coal For coal combustion thermal efficiency; for The amount of coal consumed at any given time; The calorific value of pulverized coal combustion; η ST For thermoelectric conversion efficiency, t for t The time interval between periods; Taking into account factors such as power generation revenue, ancillary service compensation, thermal storage operation and lifespan costs, and pollution emission costs, a day-ahead dispatch optimization model is established under a given time scale. The objective function of the day-ahead dispatch optimization model is to maximize the comprehensive operating revenue of thermal power plants within one day. f A As shown in the following formula: In the formula, U represents the complete set of all thermal power units participating in the scheduling. u For a specific thermal power unit in set U, The comprehensive power generation revenue of a single thermal power plant is calculated as follows: In the formula, This constitutes the basic electricity sales revenue of thermal power units; Compensation for thermal power units participating in deep peak-shaving ancillary services; The operating cost of thermal power units; For the flexibility and backup costs of thermal power units; The cost of pollution emissions from thermal power units; The comprehensive operating cost of molten salt thermal energy storage for thermal power units; This refers to the additional cost of purchasing heat when the thermal power unit's own heat supply is insufficient. The costs of generating new energy power that must be borne; An intraday rolling optimization model is established, with the objective function being to minimize the deviations in power generation and load demand, heating and heat load, and the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and new energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time. The objective function of the intraday rolling scheduling optimization model is calculated as follows: In the formula, At a certain point in time t’ The total cost optimized when performing real-time scheduling; It is every real-time scheduling moment τ The deviation between power generation capacity and net electricity load demand It is every real-time scheduling moment τ Net electricity load demand; It is every real-time scheduling moment τ Electric output of the generator side of the thermal power unit; It is every real-time scheduling moment τ The thermal power units provide external electric heating; It is every real-time scheduling moment τ The deviation between heating power and heat load demand; It is every real-time scheduling moment τ The total system heat load; It is every real-time scheduling moment τ Steam heating on the boiler side of the thermal power unit; It is every real-time scheduling moment τ Thermal power units purchase heat from external sources; yes τ = t’ and τ = t’ + T’ The deviation between the current power generation capacity and the power generation plan. β 1, β 2, β 3 represents the weights of different objectives; and Each scheduling time is a separate event. τ The planned values ​​for the generator-side power output and external heat supply of thermal power units.

2. The method for multi-timescale scheduling of thermoelectric coupled thermal power and molten salt thermal energy storage according to claim 1, characterized in that, The cost of generating new energy that needs to be borne The calculation method is shown in the following formula: In the formula, T The total number of scheduling periods. Costs associated with curtailing solar / wind power; , and , These represent the maximum potential power generation capacity and the actual power generation capacity of wind power and photovoltaic power, respectively.

3. The method for multi-timescale scheduling of thermoelectric coupled thermal power and molten salt thermal energy storage according to claim 1, characterized in that, The day-ahead dispatch optimization model for thermal power and renewable energy units includes constraints on power balance, thermal power step ramp rate under rapid load changes, thermal power generation constraints, renewable energy generation constraints, molten salt thermal storage system constraints, and thermal-electric coupling power constraints of thermal power units, as detailed below: Power balance constraints include electrical power constraints and thermal power constraints; The power balance constraint means that the total power generation capacity of thermal power units and new energy units must meet the load demand under different times and probabilities, that is: In the formula, In order to be in t Net electricity load demand over a time scale For thermal power units in t Equivalent electrical output on the generator side over a time scale For thermal power units in t External electric heating power over time scale For thermal power units in t Scheduling power requirements over a time scale; The thermal power balance constraint means that the thermal power unit after molten salt thermal storage modification meets the external heat load demand at different times through its own steam heating, electric heating, and purchased heat, that is: In the formula, For thermal power units in t Heat load demand over a time scale For thermal power units in t Boiler-side steam heating power on a time scale The difference between the thermal power output of the thermal power unit and the external heat load demand; The constraint on the stepped ramp rate of thermal power plants under rapid load change conditions is as follows: In the formula, For thermal power units in t Load factor on a time scale and For thermal power units t Upper and lower limits of load factor on a time scale; μ a , μ b and μ c The load rates of thermal power units are respectively t Lower limit benchmarks for different peak-shaving intervals on different time scales; For thermal power units in t Output over time scale r a , r b , r c These represent the maximum allowable rate of power change for the unit in different output ranges. a a, b, and c are the indices of the output range, respectively; Indicates the time interval of the scheduling model; Indicates the first x Lower limit of each output range; r x Indicates the first x The upper limit of the ramp rate for each output range; The power generation constraints of thermal power units include upper and lower limits of unit output constraints and flexible reserve constraints, among which the flexible reserve constraints are as follows: In the formula, This represents the maximum thermal power output of the boiler side of the thermal power unit. and These are the upward and downward flexibility reserves for thermal power units, respectively. and These represent the upward and downward flexibility reserves of the thermal power units in interval n, respectively, for the previous time period. To achieve the minimum technical output of thermal power units; Constraints on renewable energy generation: In the formula, μ RE Minimum utilization rate for new energy units; μ RE,d The percentage of the predicted output that can be reduced by new energy generating units per day; To provide actual power output for new energy generating units; Predicted power output for new energy generating units; Constraints on molten salt thermal storage systems include capacity constraints and operational constraints of high- and low-temperature thermal storage systems. Capacity constraints of high and low temperature thermal storage systems: In the formula, , They represent t Minimum and maximum thermal storage capacity of high-temperature systems over a given timescale; , They represent t Minimum and maximum thermal storage capacity of cryogenic systems over a timescale; Operating constraints of high and low temperature thermal storage systems: In the formula, This indicates whether the thermal power unit is in operation. If it is in operation, the value is 1; otherwise, the value is 0. 、 and 、 These are 0-1 variables representing whether the high and low thermal storage systems are in the storage / release operating state, respectively. If they are in the operating state, the value is 1; otherwise, the value is 0. θ HD and θ LD The maximum heat transfer coefficient of high and low temperature thermal storage systems; and These are the maximum heat release power of the high- and low-temperature thermal storage systems, respectively. Thermal power unit thermoelectric coupling power constraints: In the formula, , The minimum and maximum electric heating power of the thermal power unit after molten salt modification; This represents the maximum steam heating power of the thermal power unit after molten salt modification.

4. The multi-timescale scheduling method for thermoelectric coupling of thermal power and molten salt thermal energy storage according to claim 1, characterized in that, The Big M method is used to process the absolute value of the deviation term, and the absolute value of the objective function of the intraday rolling optimization model at the time scale is solved as follows: The objective function is to minimize the deviation between power generation and load demand at each moment; Introducing variables , Each represents a real-time scheduling moment. τ Whether the deviation between power generation and load demand is positive or negative, the following relationship must be satisfied between the two: After introducing a large positive number M, the original objective function is split into: The constraints are as follows: In the formula, , Represent τ The positive and negative absolute values ​​of the deviation between power generation and load demand at any given time; when the deviation between power generation and load demand is positive... Take 1, Take 0, at this time It is a positive number. The value is 0; when the deviation between power generation and load demand is negative, Take 0, Take 1, at this time =0, It is a positive number; when the deviation between power generation and load demand is 0, The overall value is 0 due to the big M constraint; right and The Big M method is used to solve for the absolute value of the deviation.

5. A thermoelectric coupled thermal power and molten salt thermal storage multi-timescale scheduling system, characterized in that, A method for implementing the thermoelectric coupling multi-timescale scheduling of thermal power and molten salt thermal energy storage as described in any one of claims 1-4 includes: The thermoelectric coupling operation model construction module constructs a thermoelectric coupling operation model based on molten salt thermal storage, and achieves thermoelectric power decoupling through dual-path regulation of boiler-side steam heating and power generation-side electric heating; The thermoelectric coupling operation model construction module comprehensively considers factors such as power generation revenue, ancillary service compensation, thermal storage operation and life cost, and pollution emission cost to establish a thermoelectric coupling operation model under a set time scale. The intraday rolling optimization scheduling module establishes an intraday rolling optimization model. The objective function is to minimize the deviations in power generation and load demand, heating and heat load at each moment, as well as the deviations from the day-ahead scheduling plan at the initial and final moments of the day. Based on the day-ahead scheduling plan obtained from the day-ahead scheduling optimization model and the predicted intraday real-time heat and power load and renewable energy fluctuations, intraday rolling optimization is performed on a time scale to correct the day-ahead scheduling plan in real time.

6. A computer storage medium having a computer program stored thereon, characterized in that, When the computer executes the computer program, it implements the thermoelectric coupling multi-timescale scheduling method for thermal power and molten salt thermal storage as described in any one of claims 1-4.

7. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor runs the computer program stored in the memory. When the computer program is executed, it implements the multi-timescale scheduling method for thermoelectric coupling of thermal power and molten salt thermal storage as described in any one of claims 1-4.

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