Combined heat and power generation and energy storage collaborative configuration and optimized operation method based on market driving

Abstract

The invention provides a combined heat and power generation and energy storage collaborative configuration and optimized operation method based on market driving. The method comprises the following steps: step 1, constructing a heat and power storage integrated energy system structure; step 2, constructing an extraction condensing turboset model; 3, constructing a heat storage water tank model; 4, constructing a power market constraint and objective function; and 5, solving an objective function. According to the method, a system operation strategy is formulated in combination with market demands and energy prices, cooperative work of the combined heat and power generation system and the energy storage system is achieved, the energy utilization efficiency and the system stability are improved, and the system benefits are maximized.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and mainly to a market-driven method for coordinated configuration and optimized operation of cogeneration and energy storage. Background Art

[0002] In order to improve the accessibility of wind power resources to the grid, the northern region currently mainly adopts the method of installing energy storage devices on the wind farm side and using wind power heating, that is, adding heat storage devices, power storage devices or electric boilers to the original thermal power units to form a comprehensive energy system of thermal power storage. Connecting thermal energy storage equipment to cogeneration units is one of the effective measures to enhance the participation of cogeneration systems in grid peak regulation and auxiliary services. It can convert excess electricity during wind power peak periods into thermal energy for storage, and supply it to thermal users during wind power trough periods. The advantages of the combined complementarity of thermal power units are fully reflected, which effectively enhances the peak regulation capacity of the power system and improves the grid's ability to absorb intermittent renewable energy.

[0003] However, the existing technology has the following defects: (1) Traditional cogeneration systems focus only on the joint production of electricity and heat, and lack a mechanism to flexibly respond to electricity market demand, resulting in low system operation efficiency.

[0004] (2) Although energy storage technology can improve the flexibility and stability of the power system, it lacks integration with the cogeneration system and cannot fully realize the overall benefits of the system.

[0005] (3) Current cogeneration systems and energy storage systems often lack an overall coordinated optimization strategy and are unable to dynamically adjust their operating modes according to market demand and energy prices, resulting in waste of system resources and reduced efficiency. Summary of the invention

[0006] In response to the above problems, the present invention provides a market-driven method for coordinated configuration of cogeneration and energy storage. This method formulates a system operation strategy based on market demand and energy prices, realizes the coordinated operation of the cogeneration system and the energy storage system, improves energy utilization efficiency and system stability, and maximizes system benefits.

[0007] In order to achieve the above technical features, the purpose of the present invention is achieved as follows: a market-driven method for cogeneration and energy storage coordinated configuration and optimized operation, comprising the following steps: Step 1: construct a comprehensive energy system structure of thermal power and storage; Step 2, constructing a model of an extraction-condensing steam turbine unit; Step 3, constructing a hot water storage tank model; Step 4: construct power market constraints and objective functions; Step 5: Solve the objective function.

[0008] Preferably, the thermal power and storage integrated energy system in step 1 is composed of two energy networks, including a regional heating network and a power grid; wherein the user's heat demand is collaboratively supplied by the thermal power unit and the heat storage device, wherein part of the heat energy of the thermal power unit is stored in a hot water storage tank to provide adjustment space for the system.

[0009] Preferably, the system electrical and thermal balance relationship in step 1 is as follows: ; ; ; ; In the formula, for t Total power output of thermal power units during the period, MW; for t Electric load of thermal power units during the period, MW; for t Total thermal output of the unit during the period, MW; The thermal output that supplies the heat load for the unit during period t, MW; for t Thermal storage power of the hot water storage tank during the period, MW; The heat output stored in the hot water storage tank of the unit, MW; for t Heat release power of hot water storage tank during the period, MW; for t Heat load for the period, MW.

[0010] Preferably, the step 2 specifically includes: Step 2.1, construct the relationship model between the output power and input steam flow of the extraction condensing steam turbine: The relationship between the output power and input steam flow of the extraction condensing steam turbine is expressed as: (1); In the formula, G ( t ) is a steam turbine t The input steam flow rate at the moment, kg / s; P (t) is the steam turbine t Electric power at the moment, MW; is the generator efficiency, is the internal efficiency of the steam turbine, The efficiency of steam turbine machinery, heat dissipation, and self-use power loss; is the turbine inlet steam enthalpy, MJ / kg; is the exhaust enthalpy of the steam turbine, MJ / kg; The various efficiencies of the steam turbine are known. Assuming that the enthalpy drop of the steam turbine remains constant, the relationship between the output power of the steam turbine and the input steam flow rate can be simplified to a linear relationship, that is: (2); Among them, the definition is the electric power conversion coefficient; Step 2.2, build the boiler model: The main steam volume of the unit is controlled by controlling the fuel input. The mathematical relationship between thermal power and input fuel volume is as follows: (3); In the formula, F ( t )for t Enter the amount of fuel for the boiler at all times. for t Input the thermal power of the steam turbine at all times, and are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipe respectively; The thermal power input to the steam turbine can be obtained from the law of conservation of energy: (4); In the formula, G ( t )for t Main steam flow rate at the moment, kg / s; is the main steam specific enthalpy, MJ / kg; is the specific enthalpy of boiler feed water, MJ / kg; The relationship between the amount of fuel input to the boiler and the main steam flow rate is: (5); Assuming that the unit feed water specific enthalpy increase remains unchanged, the steam-fuel conversion coefficient is defined as: (6); It can be seen that there is a linear relationship between the amount of fuel input to the boiler and the main steam flow rate: (7); The amount of fuel input to the boiler has a maximum operating range constraint, namely: (8); In the formula, and are the upper and lower limits of the unit fuel input, MW; The boiler fuel ramping constraint is: (9); Where: and are the upper and lower maximum ramp powers of the unit fuel input, MW; Step 2.3, build the heat exchange station model: The extraction condensing thermal power unit mainly relies on the heat exchange station to exchange heat with the heat network, and the distribution system is mainly considered. When the extraction condensing unit extracts part of the steam for heating, according to the law of conservation of energy, the calculation method of its heating output is as follows: (10); (11); In the formula, for t Heating steam extraction flow rate at any moment, kg / s; is the specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobicity formed after the heat extraction steam completes the heat exchange, MJ / kg; Assuming that the specific enthalpy drop of the heating extraction steam remains unchanged, there is the following linear relationship between the heating extraction steam flow rate and the heating output of the unit: (12); In the formula, is the specific enthalpy drop of extraction steam for heating , MJ / kg; Step 2.4, extraction condensing steam turbine unit operating characteristics: The electrical output of the extraction condensing steam turbine unit is: (13); Where: and are the electric power conversion coefficients of the high-pressure, medium-pressure and low-pressure cylinders of the steam turbine respectively; Combining the above equations, we can get the feasible operating range of the extraction condensing steam turbine unit; The electric heating output under back pressure conditions are: (14); (15); In the formula, for the convenience of calculation, we define: ; In summary, the operating range of an extraction condensing steam turbine is mainly constrained by two factors: fuel input and heating steam extraction , and we can know that the upper and lower limits of the unit's electric heating output are: (16); ; when When , the lower limit of power output is determined by the minimum fuel quantity of the unit; when When , the lower limit of the electric output is the electric output of the unit under back pressure conditions with the same thermal output, that is: (17); The upper limit of the unit's electrical output is determined by the maximum amount of fuel, namely: (18); Where: F MAX is the maximum fuel quantity; It is the electrical output of the unit under pure condensing conditions; It is the thermal output of the unit under pure condensing conditions.

[0011] Preferably, the step 3 specifically includes: The “heat-to-electricity” constraint of thermal power units can be decoupled to a certain extent by adding a heat storage device to the unit. Its operation model is expressed as: (19); (20); (twenty one); In the formula, For the heat storage tank t Thermal storage capacity at the time, MWh; and They are t The heat absorption and release power and efficiency of the hot water storage tank within a certain period of time; The upper limit of heat storage capacity of the hot water tank, MWh; is the initial value of heat storage in the hot water tank, MWh; The heat storage and release efficiency of the hot water tank is subject to the following constraints: (twenty two); (twenty three); In the formula, and It is the maximum heat storage and release ratio of the hot water tank.

[0012] Preferably, the step 4 specifically includes: The optimization model is constructed with the goal of obtaining the highest revenue in the day-ahead market and the mFRR service market. The objective function is: (twenty four); In the formula, is the day-ahead market return, Energy compensation for ancillary services market, is the unit fuel cost; The calculation method of the day-ahead market return is: (25); In the formula, and is the winning bid price and bid volume in each period of the day-ahead market; The calculation formula for energy compensation is: (26); In the formula, and It is the settlement price of the up and down frequency adjustment market. and Bid volume for up and down frequency modulation market; The calculation method of unit fuel cost is: (27); In the formula, is the unit fuel cost; The relationship between the market bidding amount and the unit power output is: (28); In addition, there are upper and lower limits on the bidding volume in the ancillary services market, namely: (29); (30); and To assist the market bidding volume upper and lower limits, 0-1 decision variables and Whether the representative will participate in bidding in the up and down frequency modulation markets; The big-M method is used to linearize (17): (31); (32); (33); (34); (35); In the formula, M is a sufficiently large number, For big M Auxiliary 0-1 variable for the method.

[0013] Preferably, the step 5 specifically includes: After the constraints are linearized, this model is a mixed integer linear programming model, written as follows: (36).

[0014] The specific solution process of step 5 is: Step 5.1, start; Step 5.2, input the technical parameters of the thermal power unit and the hot water storage tank, and set the rated capacity; Step 5.3: Input the heat load data and electricity market price for each hour of the current typical day; set the upper and lower limits of the bidding amount; Step 5.4, determine whether all typical days are completed; if yes, proceed to step 5.5, if not, proceed to the next typical day and return to step 5.3; Step 5.5, call cplex to solve the optimization model, record the results and draw the graph; Step 5.6, end.

[0015] The present invention has the following beneficial effects: 1. The present invention constructs a joint operation scenario of thermal power units, electric heat conversion devices and heat storage devices. By constructing the operation characteristic model of each device and considering the thermoelectric coupling relationship between the devices, an overall operation characteristic model of the electric-heat-storage integrated energy system is established. In combination with the bidding and settlement methods of the day-ahead market and the frequency regulation auxiliary service market, and referring to the known electricity market prices, an operation optimization model of the cogeneration system participating in the electricity market is constructed. Compared with the unit output range before optimization, the flexibility is significantly increased, and the benefits obtained in the day-ahead market and the power regulation market are also increased to varying degrees.

[0016] 2. The present invention establishes an operation characteristic model of the integrated energy system of the combined extraction-condensing steam turbine unit and the hot water storage tank. Through the electric-thermal coupling relationship of each component of the system, and with a certain power market rule as the background, and with the highest revenue in the day-ahead market and the regulating power market as the objective function, a mixed integer linear optimization scheduling model for the participation of electric-thermal integrated energy in the power market is established, and the commercial solver cplex is called to solve the selected four typical days. By comparing the online power of the unit before and after optimization with the total revenue obtained by the system, it can be seen that the unit output range is greatly improved, the flexibility is significantly increased, and the revenue obtained in the day-ahead market and the regulating power market is also improved to varying degrees. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0018] Figure 1 This is the electric-thermal coupling relationship of the comprehensive energy system of the present invention. Figure 2 It is a schematic diagram of the steam turbine of the present invention.

[0019] Figure 3 It is a diagram of the thermal system structure of the present invention.

[0020] Figure 4 This is the output range of the thermal power unit of the present invention.

[0021] Figure 5 It is a flow chart of solving the example of the present invention. DETAILED DESCRIPTION

[0022] The present invention is described in detail below with reference to specific examples.

[0023] Due to the constraint of "electricity determined by heat" of thermal power units, in order to give priority to heating demand, the minimum power output of the units has to be increased, which affects the ability to absorb new energy. Configuring hot water storage tanks for thermal power units is one of the important methods to decouple the constraint of "electricity determined by heat", which can effectively reduce the forced output of the units. Configuring heat storage tanks is a prerequisite for installing heat storage devices in thermal power plants, and the capacity of hot water storage tanks has an important impact on improving the flexibility and economic operation of the system. Therefore, it is of great significance to optimize the heat storage capacity.

[0024] Based on this, the present invention provides a market-driven method for coordinated configuration and optimized operation of cogeneration and energy storage, including the following steps: Step 1: construct a comprehensive energy system structure of thermal power and storage; See also Figure 1 The electric heat storage integrated energy system consists of two energy networks, namely the regional heating network and the power grid. The heat demand of users is jointly supplied by the thermal power unit and the heat storage device. The electric heat coupling relationship between the three greatly improves the flexibility of the system. Part of the heat energy of the thermal power unit is stored in the hot water storage tank, providing adjustment space for the system.

[0025] The system electrical and thermal balance relationship is as follows: ; ; ; ; In the formula, for t Total power output of thermal power units during the period, MW; for t Electric load of thermal power units during the period, MW; for t Total thermal output of the unit during the period, MW; The thermal output that supplies the heat load for the unit during period t, MW; for t Thermal storage power of the hot water storage tank during the period, MW; The heat output stored in the hot water storage tank of the unit, MW; for tHeat release power of hot water storage tank during the period, MW; for t Heat load for the period, MW.

[0026] Step 2, constructing a model of an extraction-condensing steam turbine unit; See also Figure 2 Schematic diagram of a steam turbine.

[0027] Step 2.1, construct the relationship model between the output power and input steam flow of the extraction condensing steam turbine: The relationship between the output power and input steam flow of the extraction condensing steam turbine is expressed as: (1); In the formula, G ( t ) is a steam turbine t The input steam flow rate at the moment, kg / s; P (t) is the steam turbine t Electric power at the moment, MW; is the generator efficiency, is the internal efficiency of the steam turbine, The efficiency of steam turbine machinery, heat dissipation, and self-use power loss; is the turbine inlet steam enthalpy, MJ / kg; is the exhaust enthalpy of the steam turbine, MJ / kg; The various efficiencies of the steam turbine are known. Assuming that the enthalpy drop of the steam turbine remains constant, the relationship between the output power of the steam turbine and the input steam flow rate can be simplified to a linear relationship, that is: (2); Among them, the definition is the electric power conversion coefficient; Step 2.2, build the boiler model: The main steam volume of the unit can be controlled by controlling the fuel input. The mathematical relationship between thermal power and input fuel volume is as follows: (3); In the formula, F ( t )for t Enter the amount of fuel for the boiler at all times. for t Input the thermal power of the steam turbine at all times, and are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipe respectively; The thermal power input to the steam turbine can be obtained from the law of conservation of energy: (4); In the formula, G (t )for t Main steam flow rate at the moment, kg / s; is the main steam specific enthalpy, MJ / kg; is the specific enthalpy of boiler feed water, MJ / kg; The relationship between the amount of fuel input to the boiler and the main steam flow rate is: (5); Assuming that the unit feed water specific enthalpy increase remains unchanged, the steam-fuel conversion coefficient is defined as: (6); It can be seen that there is a linear relationship between the amount of fuel input to the boiler and the main steam flow rate: (7); The amount of fuel input to the boiler has a maximum operating range constraint, namely: (8); In the formula, and are the upper and lower limits of the unit fuel input, MW; The boiler fuel ramping constraint is: (9); Where: and are the upper and lower maximum ramp powers of the unit fuel input, MW; Step 2.3, build the heat exchange station model: See also Figure 3 For the thermal system, the extraction condensing thermal power unit mainly relies on the heat exchange station and the heat network for heat exchange, and the distribution system is mainly considered. When the extraction condensing unit extracts part of the steam for heating, according to the law of conservation of energy, the calculation method of its heating output is as follows: (10); (11); In the formula, for t Heating steam extraction flow rate at any moment, kg / s; is the specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobicity formed after the heat extraction steam completes the heat exchange, MJ / kg; Assuming that the specific enthalpy drop of the heating extraction steam remains unchanged, there is the following linear relationship between the heating extraction steam flow rate and the heating output of the unit: (12); In the formula, is the specific enthalpy drop of extraction steam for heating , MJ / kg; Step 2.4, extraction condensing steam turbine unit operating characteristics: The electrical output of the extraction condensing steam turbine unit is: (13); Where: and are the electric power conversion coefficients of the high-pressure, medium-pressure and low-pressure cylinders of the steam turbine respectively; Combining the above equations, we can get the feasible operating range of the extraction condensing steam turbine unit, which is: Figure 4 Middle quadrilateral ; The electric heating output under back pressure conditions are: (14); (15); In the formula, for the convenience of calculation, we define: ; In summary, the operating range of an extraction condensing steam turbine is mainly constrained by two factors: fuel input and heating steam extraction , and we can know that the upper and lower limits of the unit's electric heating output are: (16); ; when When , the lower limit of power output is determined by the minimum fuel quantity of the unit; when When , the lower limit of the electric output is the electric output of the unit under back pressure conditions with the same thermal output, that is: (17); The upper limit of the unit's electrical output is determined by the maximum amount of fuel, namely: (18); Where: F MAX is the maximum fuel quantity; It is the electrical output of the unit under pure condensing conditions; It is the thermal output of the unit under pure condensing conditions.

[0028] Step 3, constructing a hot water storage tank model; The “heat-to-electricity” constraint of thermal power units can be decoupled to a certain extent by adding a heat storage device to the unit. Its operation model is expressed as: (19); (20); (twenty one); In the formula, For the heat storage tank t Thermal storage capacity at the time, MWh; and They are t The heat absorption and release power and efficiency of the hot water storage tank within a certain period of time; The upper limit of heat storage capacity of the hot water tank, MWh; is the initial value of heat storage in the hot water tank, MWh; The heat storage and release efficiency of the hot water tank is subject to the following constraints: (twenty two); (twenty three); In the formula, and It is the maximum heat storage and release ratio of the hot water tank.

[0029] Step 4: construct power market constraints and objective functions; At present, my country's power market is in the early stage of construction. Therefore, the DK2 market rules of a certain power grid are used as the research background, and the optimization model is constructed with the goal of obtaining the highest profit in the day-ahead market and the mFRR service market. The objective function is: (twenty four); In the formula, is the day-ahead market return, Energy compensation for ancillary services market, is the unit fuel cost; The calculation method of the day-ahead market return is: (25); In the formula, and is the winning bid price and bid volume in each period of the day-ahead market; The calculation formula for energy compensation is: (26); In the formula, and It is the settlement price of the up and down frequency adjustment market. and Bid volume for up and down frequency modulation market; The calculation method of unit fuel cost is: (27); In the formula, is the unit fuel cost; The relationship between the market bidding amount and the unit power output is: (28); In addition, there are upper and lower limits on the bidding volume in the ancillary services market, namely: (29); (30); and To assist the market bidding volume upper and lower limits, 0-1 decision variables and Whether the representative will participate in bidding in the up and down frequency modulation markets; The big-M method is used to linearize (17): (31); (32); (33); (34); (35); In the formula, M is a sufficiently large number, It is an auxiliary 0-1 variable of the Big M method.

[0030] Step 5: Solve the objective function.

[0031] After the constraints are linearized, this model is a mixed integer linear programming model, written as follows: (36).

[0032] See also Figure 5 , program flowchart.

[0033] The specific solution process of step 5 is: Step 5.1, start; Step 5.2, input the technical parameters of the thermal power unit and the hot water storage tank, and set the rated capacity; Step 5.3: Input the heat load data and electricity market price for each hour of the current typical day; set the upper and lower limits of the bidding amount; Step 5.4, determine whether all typical days are completed; if yes, proceed to step 5.5, if not, proceed to the next typical day and return to step 5.3; Step 5.5, call cplex to solve the optimization model, record the results and draw the graph; Step 5.6, end.

Claims

1. A market-driven method for cogeneration and energy storage coordinated configuration and optimized operation, characterized in that: The following steps are involved: Step 1: construct a comprehensive energy system structure of thermal power and storage; Step 2, constructing a model of an extraction-condensing steam turbine unit; Step 3, constructing a hot water storage tank model; Step 4: construct power market constraints and objective functions; Step 5: Solve the objective function.

2. A market-driven method for cogeneration and energy storage coordinated configuration and optimized operation according to claim 1, characterized in that: In step 1, the thermal power and storage integrated energy system is composed of two energy networks, including a regional heating network and a power grid; wherein the user's heat demand is collaboratively supplied by the thermal power unit and the heat storage device, wherein part of the heat energy of the thermal power unit is stored in the hot water storage tank to provide adjustment space for the system.

3. A method for market-driven coordinated configuration and optimized operation of cogeneration and energy storage according to claim 2, characterized in that: The system electrical and thermal balance relationship in step 1 is as follows: ； ； ； ； In the formula, for t Total power output of thermal power units during the period, MW; for t Total electrical load of thermal power units during the period, MW; for t Total thermal output of the unit during the period, MW; The thermal output that supplies the heat load for the unit during period t, MW; for t Thermal storage power of the hot water storage tank during the period, MW; The heat output stored in the hot water storage tank of the unit, MW; for t Heat release power of hot water storage tank during the period, MW; for t Heat load for the period, MW.

4. The method for market-driven coordinated configuration and optimized operation of cogeneration and energy storage according to claim 3, characterized in that: The step 2 specifically includes: Step 2.1, construct the relationship model between the output power and input steam flow of the extraction condensing steam turbine: The relationship between the output power and input steam flow of the extraction condensing steam turbine is expressed as: （1）； In the formula, G ( t ) is a steam turbine t The input steam flow rate at the moment, kg / s; P (t) is the steam turbine t Electric power at the moment, MW; is the generator efficiency, is the internal efficiency of the steam turbine, The efficiency of steam turbine machinery, heat dissipation, and self-use power loss; is the turbine inlet steam enthalpy, MJ / kg; is the exhaust enthalpy of the steam turbine, MJ / kg; The various efficiencies of the steam turbine are known. Assuming that the enthalpy drop of the steam turbine remains constant, the relationship between the output power of the steam turbine and the input steam flow rate can be simplified to a linear relationship, that is: （2）； Among them, the definition is the electric power conversion coefficient; Step 2.2, build the boiler model: The main steam volume of the unit is controlled by controlling the fuel input. The mathematical relationship between thermal power and input fuel volume is as follows: （3）； In the formula, F ( t )for t Enter the amount of fuel for the boiler at all times. for t Input the thermal power of the steam turbine at all times, and are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipe respectively; The thermal power input to the steam turbine can be obtained from the law of conservation of energy: （4）； In the formula, G ( t )for t Main steam flow rate at the moment, kg / s; is the main steam specific enthalpy, MJ / kg; is the specific enthalpy of boiler feed water, MJ / kg; The relationship between the amount of fuel input to the boiler and the main steam flow rate is: （5）； Assuming that the unit feed water specific enthalpy increase remains unchanged, the steam-fuel conversion coefficient is defined as: （6）； It can be seen that there is a linear relationship between the amount of fuel input to the boiler and the main steam flow rate: （7）； The amount of fuel input to the boiler has a maximum operating range constraint, namely: （8）； In the formula, and are the upper and lower limits of the unit fuel input, MW; The boiler fuel ramping constraint is: （9）； Where: and are the upper and lower maximum ramp powers of the unit fuel input, MW; Step 2.3, build the heat exchange station model: The extraction condensing thermal power unit mainly relies on the heat exchange station to exchange heat with the heat network, and the distribution system is mainly considered. When the extraction condensing unit extracts part of the steam for heating, according to the law of conservation of energy, the calculation method of its heating output is as follows: （10）； （11）； In the formula, for t Heating steam extraction flow rate at any moment, kg / s; is the specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobicity formed after the heat extraction steam completes the heat exchange, MJ / kg; Assuming that the specific enthalpy drop of the heating extraction steam remains unchanged, there is the following linear relationship between the heating extraction steam flow rate and the heating output of the unit: （12）； In the formula, is the specific enthalpy drop of extraction steam for heating , MJ / kg; Step 2.4, extraction condensing steam turbine unit operating characteristics: The electrical output of the extraction condensing steam turbine unit is: （13）； Where: and are the electric power conversion coefficients of the high-pressure, medium-pressure and low-pressure cylinders of the steam turbine respectively; Combining the above equations, we can get the feasible operating range of the extraction condensing steam turbine unit; The electric heating output under back pressure conditions are: （14）； （15）； In the formula, for the convenience of calculation, we define: ; In summary, the operating range of an extraction condensing steam turbine is mainly constrained by two factors: fuel input and heating steam extraction , and we can know that the upper and lower limits of the unit's electric heating output are: （16）； ； when When the lower limit of power output is determined by the minimum fuel quantity of the unit; when When , the lower limit of the electric output is the electric output of the unit under back pressure conditions with the same thermal output, that is: （17）； The upper limit of the unit's electrical output is determined by the maximum amount of fuel, namely: （18）； Where: F MAX is the maximum fuel quantity; It is the electrical output of the unit under pure condensing conditions; It is the thermal output of the unit under pure condensing conditions.

5. A method for market-driven coordinated configuration and optimized operation of cogeneration and energy storage according to claim 4, characterized in that: The step 3 specifically includes: The "heat-to-electricity" constraint of thermal power units can be decoupled to a certain extent by adding a heat storage device to the unit. Its operation model is expressed as: （19）； （20）； （21）； In the formula, For the heat storage tank t Thermal storage capacity at the time, MWh; and They are t The heat absorption and release power and efficiency of the hot water storage tank within a certain period of time; The upper limit of heat storage capacity of the hot water tank, MWh; is the initial value of heat storage in the hot water tank, MWh; The heat storage and release efficiency of the hot water tank is subject to the following constraints: （22）； （23）； In the formula, and It is the maximum heat storage and release ratio of the hot water tank.

6. A market-driven method for cogeneration and energy storage coordinated configuration and optimized operation according to claim 5, characterized in that: The step 4 specifically includes: The optimization model is constructed with the goal of obtaining the highest revenue in the day-ahead market and the mFRR service market. The objective function is: （24）； In the formula, is the day-ahead market return, Energy compensation for ancillary services market, is the unit fuel cost; The calculation method of the day-ahead market return is: （25）； In the formula, and is the winning bid price and bid volume in each period of the day-ahead market; The calculation formula for energy compensation is: （26）； In the formula, and It is the settlement price of the up and down frequency modulation market. and Bid volume for up and down frequency modulation market; The calculation method of unit fuel cost is: （27）； In the formula, is the unit fuel cost; The relationship between the market bidding amount and the unit power output is: （28）； In addition, there are upper and lower limits on the bidding volume in the ancillary services market, namely: （29）； （30）； and To assist the market bidding volume upper and lower limits, 0-1 decision variables and Whether the representative will participate in bidding in the up and down frequency modulation markets; The big-M method is used to linearize (17): （31）； （32）； （33）； （34）； （35）； In the formula, M is a sufficiently large number, For big M Auxiliary 0-1 variable for the method.

7. A market-driven method for cogeneration and energy storage coordinated configuration and optimized operation according to claim 6, characterized in that: After the constraints in step 5 are linearized, the model is a mixed integer linear programming model, which is written in the following form: （36）。 8. A market-driven method for cogeneration and energy storage coordinated configuration and optimized operation according to claim 7, characterized in that: The specific solution process of step 5 is: Step 5.1, start; Step 5.2, input the technical parameters of the thermal power unit and the hot water storage tank, and set the rated capacity; Step 5.3: Input the heat load data and electricity market price for each hour of the current typical day; set the upper and lower limits of the bidding amount; Step 5.4, determine whether all typical days are completed; if yes, proceed to step 5.5, if not, proceed to the next typical day and return to step 5.3; Step 5.5, call cplex to solve the optimization model, record the results and draw the graph; Step 5.6, end.

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