A market-driven combined heat and power and energy storage collaborative configuration and optimized operation method

Abstract

The application provides a market-driven combined heat and power and energy storage collaborative configuration and optimization operation method, which comprises the following steps: step 1, constructing a combined heat and power and energy storage integrated energy system structure; step 2, constructing an extraction condensing steam turbine unit model; step 3, constructing a heat storage water tank model; step 4, constructing an electric power market constraint and a target function; and step 5, solving the target function. The method combines market demand and energy prices to formulate a system operation strategy, realizes the collaborative work of a combined heat and power system and an energy storage system, improves energy utilization efficiency and system stability, and maximizes system benefits.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy storage technology, and mainly relates to a market-driven combined heat and power and energy storage collaborative configuration and optimized operation method. BACKGROUND

[0002] In order to improve the on-grid ability of wind power resources, the method of installing energy storage devices at the wind farm side and using wind power heating is mainly adopted in the northern region at present, that is, a heat storage device, an electric storage device or an electric boiler is added to the original heat and power unit to form a heat and power storage mixed comprehensive energy system. The access of heat storage equipment in the combined heat and power unit is one of the effective measures to improve the participation of the combined heat and power system in the peak regulation and auxiliary services of the power grid, which can convert the excess power at the wind power peak period into heat energy for storage, and supply it to the heat users at the wind power valley period. The advantages of joint complementation of the heat and power unit are thus fully reflected, thereby effectively enhancing the peak regulation capability of the power system and improving the accommodation capability of the power grid for intermittent renewable energy.

[0003] However, the existing technology has the following defects:

[0004] (1) The traditional combined heat and power system only focuses on the joint production of electricity and heat, lacks a mechanism for flexible response to power market demand, and thus has low system operation efficiency.

[0005] (2) Although the energy storage technology can improve the flexibility and stability of the power system, it lacks sufficient integration in collaborative operation with the combined heat and power system, and thus cannot fully exert the overall benefits of the system.

[0006] (3) The current combined heat and power system and energy storage system often lack overall collaborative optimization strategies, and thus cannot dynamically adjust the operation mode according to market demand and energy prices, resulting in waste of system resources and reduction of benefits. SUMMARY

[0007] In view of the above problems, the present application provides a market-driven combined heat and power and energy storage collaborative configuration method, which formulates system operation strategies in combination with market demand and energy prices, realizes the collaborative work of the combined heat and power system and the energy storage system, improves the energy utilization efficiency and system stability, and maximizes the system benefits.

[0008] In order to realize the above technical features, the purpose of the present application is realized as follows: a market-driven combined heat and power and energy storage collaborative configuration and optimized operation method, comprising the following steps:

[0009] Step 1, constructing a heat and power storage comprehensive energy system structure;

[0010] Step 2, constructing an extraction condensing steam turbine unit model;

[0011] Step 3: Construct a hot water storage tank model;

[0012] Step 4: Construct the electricity market constraints and objective function;

[0013] Step 5: Solve for the objective function.

[0014] Preferably, the integrated thermal power and energy storage system in step 1 consists of two energy networks: a district heating network and a power grid. The user's heat demand is supplied by the thermal power unit and the thermal storage device in a coordinated manner. Part of the thermal energy of the thermal power unit is stored in the hot water storage tank to provide regulation space for the system.

[0015] Preferably, the system's electrothermal balance relationship in step 1 is as follows:

[0016] ;

[0017] ;

[0018] ;

[0019] ;

[0020] In the formula, for t Total electrical output of the thermal power unit during the time period, in MW; for t Electric load of thermal power units during the period, in MW; for t Total thermal output of the unit during the period, MW; The portion of the heat output (MW) that supplies heat load to the unit during time period t; for t Thermal storage capacity of the hot water storage tank during a given time period, in MW; The heat output of the unit stored in the hot water tank, MW; for t Heat release capacity of hot water storage tank during a given period, in MW; for t Heat load for a given period, in MW.

[0021] Preferably, step 2 specifically includes:

[0022] Step 2.1: Construct a model showing the relationship between the output power and input steam flow rate of the extraction condensing steam turbine:

[0023] The relationship between the output power and the input steam flow rate of the extraction condensing steam turbine is expressed as follows:

[0024] (1);

[0025] In the formula, G (t ) is a steam turbine t is the input steam flow at the moment, kg / s; P (t) is the electric power at the moment, MW; t is the generator efficiency, is the internal efficiency of the steam turbine, is the mechanical, radiation, and self-power loss efficiency of the steam turbine; is the steam turbine inlet enthalpy, MJ / kg; is the steam turbine exhaust enthalpy, MJ / kg;

[0026] The output power of the steam turbine and the input steam flow are linearly related, assuming that the enthalpy drop of the steam turbine remains constant, i.e.:

[0027] (2);

[0028] wherein the electric power conversion coefficient is defined as

[0029] Step 2.2, constructing a boiler model:

[0030] The main steam flow of the unit is controlled by controlling the fuel input, and the mathematical relationship between the thermal power and the input fuel is as follows:

[0031] (3);

[0032] wherein, F ( t ) is the fuel input to the boiler at the moment, t is the thermal power input to the steam turbine at the moment, and t are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipeline, respectively; The thermal power input to the steam turbine can be obtained from the law of conservation of energy:

[0033]

[0034] (4);

[0035] wherein, G ( t ) is the main steam flow at the moment, kg / s; t is the specific enthalpy of the main steam, MJ / kg; is the specific enthalpy of the boiler feed water, MJ / kg; The relationship between the fuel input to the boiler and the main steam flow can be obtained as follows:

[0036] ​​​​​

[0037] (5);

[0038] Assuming the feedwater enthalpy increase remains constant, the steam-fuel conversion factor is defined as:

[0039] (6);

[0040] A linear relationship can be found between the fuel quantity input to the boiler and the main steam flow rate:

[0041] (7);

[0042] The amount of fuel input to the boiler is subject to a maximum operating range constraint, namely:

[0043] (8);

[0044] In the formula, and These represent the upper and lower limits of the unit's fuel input, in MW.

[0045] The boiler fuel ramp-up constraint is:

[0046] (9);

[0047] In the formula: and These represent the maximum ramp power (MW) of the unit's fuel input.

[0048] Step 2.3, Construct the heat exchange station model:

[0049] Extraction-condensing cogeneration units primarily rely on heat exchange stations and heating networks for heat exchange. Considering the distribution system, when an extraction-condensing unit supplies heat by extracting a portion of steam, its heating output is calculated according to the law of conservation of energy as follows:

[0050] (10);

[0051] (11);

[0052] In the formula, for t Real-time steam extraction flow rate for heating, kg / s; The specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobic layer formed after heat exchange by steam extraction for heating, in MJ / kg;

[0053] Assuming the enthalpy drop of the heating extraction steam ratio remains constant, the following linear relationship exists between the heating extraction steam flow rate and the unit's heating output:

[0054] (12);

[0055] where, is the enthalpy drop of heat supply extraction steam , MJ / kg;

[0056] Step 2.4, extraction steam turbine unit operating characteristics:

[0057] The electric output of the extraction steam turbine unit is:

[0058] (13);

[0059] where, and are the electric power conversion coefficients of the high-pressure cylinder, the medium-pressure cylinder and the low-pressure cylinder of the steam turbine, respectively;

[0060] The feasible operating range of the extraction steam turbine unit can be obtained by combining the above equations;

[0061] The electric heat output under the back pressure condition is:

[0062] (14);

[0063] (15);

[0064] where, for the convenience of calculation, it is defined that: ;

[0065] From the above, the operating range of the extraction steam turbine is mainly constrained by two factors, namely the fuel input and the heat supply extraction steam , and it can be known that the upper and lower limits of the electric heat output of the unit are:

[0066] (16);

[0067] ;

[0068] When , the lower limit of the electric output is determined by the minimum fuel amount of the unit; when , the lower limit of the electric output is the electric output under the back pressure condition of the unit under the same heat output, that is:

[0069] (17);

[0070] The upper limit of the electric output of the unit is determined by the maximum fuel amount, that is:

[0071] (18);

[0072] where, F MAXFor the maximum fuel quantity; For the electric output of the unit under the pure condensing condition; For the thermal output of the unit under the pure condensing condition.

[0073] Preferably, the step 3 specifically includes:

[0074] The "heat determines electricity" constraint of the thermoelectric unit can be decoupled to a certain extent by adding a heat storage device in the unit, and the operation model is represented as:

[0075] (19);

[0076] (20);

[0077] (21);

[0078] In the formula, is the heat storage capacity of the heat storage tank at t time, MWh; and are the heat absorption and release power of the heat storage water tank and the efficiency within t time, respectively; is the upper limit of the heat storage of the heat storage water tank, MWh; is the initial value of the heat storage of the heat storage water tank, MWh;

[0079] The heat storage and release efficiency of the heat storage water tank is subject to the following constraints:

[0080] (22);

[0081] (23);

[0082] In the formula, and are the maximum heat storage and release ratio of the heat storage water tank.

[0083] Preferably, the step 4 specifically includes:

[0084] The optimization model is constructed with the goal of obtaining the highest income in the day-ahead market and the mFRR service market. Then the objective function is:

[0085] (24);

[0086] In the formula, is the day-ahead market income, is the energy compensation of the ancillary service market, is the unit fuel cost;

[0087] Wherein, the calculation method of the day-ahead market income is:

[0088] (25);

[0089] where, and are the winning price and the bid quantity of each period in the day-ahead market;

[0090] The calculation formula of energy compensation is:

[0091] (26);

[0092] where, and are the settlement price of the up and down frequency regulation market, and are the bid quantity of the up and down frequency regulation market;

[0093] The calculation method of unit fuel cost is:

[0094] (27);

[0095] where, is the unit fuel cost;

[0096] The relationship between the market bid quantity and the unit power output is:

[0097] (28);

[0098] In addition, the auxiliary service market has an upper and lower limit of the bid quantity, i.e.:

[0099] (29);

[0100] (30);

[0101] and are the upper and lower limits of the auxiliary market bid quantity, and 0-1 decision variable and represent whether to participate in the bid of the up and down frequency regulation market;

[0102] The linearization of (17) is carried out using the big M method:

[0103] (31);

[0104] (32);

[0105] (33);

[0106] (34);

[0107] (35);

[0108] wherein, M is a sufficiently large number, is large M auxiliary 0-1 variable.

[0109] Preferably, the step 5 specifically comprises:

[0110] After linearization of the constraints, the model is a mixed integer linear programming model, written in the following form:

[0111] (36).

[0112] The specific solving process of the step 5 is as follows:

[0113] Step 5.1, start;

[0114] Step 5.2, input the technical parameters of the heat and power unit and the heat storage tank, and set the rated capacity;

[0115] Step 5.3, input the current typical day hourly heat load data and the power market price; set the upper and lower limits of the bidding amount;

[0116] Step 5.4, judge whether all typical days are completed; if yes, go to step 5.5, if not, go to the next typical day and return to step 5.3;

[0117] Step 5.5, call cplex to solve the optimization model, record the results and draw the graph;

[0118] Step 5.6, end.

[0119] The present application has the following beneficial effects:

[0120] 1. The present application constructs the combined operation situation of the heat and power unit, the electric-heat conversion device and the heat storage device. By constructing the operation characteristic model of each device, considering the heat and power coupling relationship between the devices, establishing the overall operation characteristic model of the electric-heat-storage comprehensive energy system, combining the bidding and settlement mode of the day-ahead market and the frequency regulation auxiliary service market, referring to the known power market price, the present application constructs the operation optimization model of the combined heat and power system participating in the power market, which greatly improves the unit output range and significantly increases the flexibility compared to the optimization before, and the income obtained in the day-ahead market and the regulation power market is also increased by different degrees.

[0121] 2, The application establishes a comprehensive energy system operation characteristic model combined with an extraction condensing steam turbine unit and a heat storage water tank, through the electric-thermal coupling relationship of each component of the system, and taking a certain electricity market rule as the background, taking the highest income obtained in the day-ahead market and the regulation power market as the objective function, a mixed integer linear optimization scheduling model of the electric-thermal comprehensive energy participating in the electricity market is established, and a commercial solver cplex is called to solve four selected typical days. Compared the online power of the unit before and after optimization with the total income obtained by the system, it can be seen that the unit output range is greatly improved, the flexibility is significantly increased, and the income obtained in the day-ahead market and the regulation power market is also increased by different amplitudes. BRIEF DESCRIPTION OF DRAWINGS

[0122] The application will be further described below in combination with the drawings and examples.

[0123] Figure 1 is the electric-thermal coupling relationship of the comprehensive energy system of the application.

[0124] Figure 2 is a schematic diagram of the steam turbine of the application.

[0125] Figure 3 is a heat supply system structure diagram of the application.

[0126] Figure 4 is the output range of the thermal power unit of the application.

[0127] Figure 5 is a flow chart of the example solution of the application. DETAILED DESCRIPTION

[0128] The application will be described in detail below in combination with specific examples.

[0129] Due to the "heat determines electricity" constraint of the thermal power unit, in order to preferentially ensure the heat supply demand, the minimum electric output of the unit has to be increased, which affects the accommodation capacity of new energy. Configuring a heat storage water tank for the thermal power unit is one of the important methods to decouple the "heat determines electricity" constraint, which can effectively reduce the forced output of the unit. Configuring the heat storage tank is the premise of installing the heat storage device in the thermal power plant, and the capacity of the heat storage water tank has important influence on improving the flexibility and economic operation of the system, therefore, optimizing the heat storage capacity has important significance.

[0130] Based on this, the application provides a market-driven cogeneration and energy storage collaborative configuration and optimization operation method, including the following steps:

[0131] Step 1, build a thermal power storage comprehensive energy system structure;

[0132] Referring to Figure 1The integrated energy system of electricity, heat, and energy storage consists of two energy networks: a district heating network and a power grid. The user's heat demand is supplied by the combined operation of the thermal power unit and the thermal storage device. The electrothermal coupling relationship among the three greatly improves the system's flexibility. Part of the thermal energy of the thermal power unit is stored in the hot water storage tank, providing the system with adjustment capacity.

[0133] The system's electrothermal balance relationship is as follows:

[0134] ;

[0135] ;

[0136] ;

[0137] ;

[0138] In the formula, for t Total electrical output of the thermal power unit during the time period, in MW; for t Electrical load of thermal power units during a given time period, in MW; for t Total thermal output of the unit during the period, MW; The portion of the heat output (MW) that supplies heat load to the unit during time period t; for t Thermal storage capacity of the hot water storage tank during a given time period, in MW; The heat output of the unit stored in the hot water tank, MW; for t Heat release capacity of hot water storage tank during a given period, in MW; for t Heat load during a given time period, in MW.

[0139] Step 2: Construct a model of an extraction-condensing steam turbine unit;

[0140] See Figure 2 This is a schematic diagram of a steam turbine.

[0141] Step 2.1: Construct a model showing the relationship between the output power and input steam flow rate of the extraction condensing steam turbine:

[0142] The relationship between the output power and the input steam flow rate of the extraction condensing steam turbine is expressed as follows:

[0143] (1);

[0144] In the formula, G ( t ) is a steam turbine t The input steam flow rate at any given time, in kg / s; P (t) is the steam turbinet Electric power at any given time, in MW; For generator efficiency, This refers to the internal efficiency of the steam turbine. This is to reduce the efficiency of steam turbine mechanical, heat dissipation, and self-use power loss. The enthalpy of the steam inlet to the turbine is expressed in MJ / kg. The exhaust enthalpy of the steam turbine is expressed in MJ / kg.

[0145] Given that all efficiencies of the steam turbine are known, and 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, namely:

[0146] (2);

[0147] Among them, the definition The power conversion factor;

[0148] Step 2.2, Construct the boiler model:

[0149] The main steam output of the unit can be controlled by controlling the fuel input. The mathematical relationship between thermal power and input fuel output is as follows:

[0150] (3);

[0151] In the formula, F ( t )for t Input the amount of fuel for the boiler at all times. for t The thermal power of the steam turbine is constantly input. and These are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipes, respectively.

[0152] The thermal power input to the steam turbine can be obtained from the law of conservation of energy:

[0153] (4);

[0154] In the formula, G ( t )for t Main steam flow rate at any given time, kg / s; The main steam specific enthalpy, MJ / kg; Specific enthalpy of boiler feedwater, MJ / kg;

[0155] By combining the equations, the relationship between the fuel input to the boiler and the main steam flow rate can be obtained as follows:

[0156] (5);

[0157] Assuming the feedwater enthalpy increase remains constant, the steam-fuel conversion factor is defined as:

[0158] (6);

[0159] A linear relationship can be found between the fuel quantity input to the boiler and the main steam flow rate:

[0160] (7);

[0161] The amount of fuel input to the boiler is subject to a maximum operating range constraint, namely:

[0162] (8);

[0163] In the formula, and These represent the upper and lower limits of the unit's fuel input, in MW.

[0164] The boiler fuel ramp-up constraint is:

[0165] (9);

[0166] In the formula: and These represent the maximum ramp power (MW) of the unit's fuel input.

[0167] Step 2.3, Construct the heat exchange station model:

[0168] See Figure 3 As a thermal system, extraction-condensing cogeneration units mainly rely on heat exchange stations and heating networks for heat exchange. Considering the distribution system, when an extraction-condensing unit supplies heat by extracting a portion of steam, its heating output is calculated according to the law of conservation of energy as follows:

[0169] (10);

[0170] (11);

[0171] In the formula, for t Real-time steam extraction flow rate for heating, kg / s; The specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobic layer formed after heat exchange by steam extraction for heating, in MJ / kg;

[0172] Assuming the enthalpy drop of the heating extraction steam ratio remains constant, the following linear relationship exists between the heating extraction steam flow rate and the unit's heating output:

[0173] (12);

[0174] where, is the enthalpy drop of heat supply extraction steam , MJ / kg;

[0175] Step 2.4, extraction steam turbine unit operating characteristics:

[0176] The electric output of the extraction steam turbine unit is:

[0177] (13);

[0178] where, and are the electric power conversion coefficients of the high-pressure cylinder, the medium-pressure cylinder and the low-pressure cylinder of the steam turbine, respectively;

[0179] The simultaneous equations above can obtain the feasible operating range of the extraction steam turbine unit, i.e. Figure 4 the middle quadrilateral ;

[0180] The electric and heat outputs under the back pressure condition are:

[0181] (14);

[0182] (15);

[0183] where, for the convenience of calculation, it is defined that: ;

[0184] From the above, the operating range of the extraction steam turbine is mainly restricted by two factors, i.e. the fuel input and the heat supply extraction steam , and it can be known that the upper and lower limits of the electric and heat outputs of the unit are:

[0185] (16);

[0186] ;

[0187] When , the lower limit of the electric output is determined by the minimum fuel amount of the unit; when , the lower limit of the electric output is the electric output under the back pressure condition of the unit with the same heat output, i.e.

[0188] (17);

[0189] The upper limit of the electric output of the unit is determined by the maximum fuel amount, i.e.

[0190] (18);

[0191] where, FMAX Maximum fuel quantity; This refers to the electrical output of the unit under pure condensing conditions. This refers to the thermal output of the unit under pure condensing conditions.

[0192] Step 3: Construct a hot water storage tank model;

[0193] The "heat-driven power generation" constraint of a thermal power unit can be decoupled to some extent by adding a thermal storage device to the unit. Its operating model is expressed as follows:

[0194] (19);

[0195] (20);

[0196] (twenty one);

[0197] In the formula, For the heat storage tank in t Heat storage capacity at any given time, in MWh; and They are respectively t The heat absorption and release power and efficiency of the hot water storage tank within a given time period; The upper limit of thermal storage in the hot water tank, MWh; The initial value of heat storage in the hot water tank is MWh;

[0198] The heat storage and release efficiency of hot water storage tanks is subject to the following constraints:

[0199] (twenty two);

[0200] (twenty three);

[0201] In the formula, and This represents the maximum heat storage and release ratio of the hot water storage tank.

[0202] Step 4: Construct the electricity market constraints and objective function;

[0203] Currently, my country's electricity market is in its early stages of development. Therefore, this study uses the DK2 market rule of a certain power grid as the research background, and constructs an optimization model with the objective of maximizing revenue in both the day-ahead market and the mFRR service market. The objective function is:

[0204] (twenty four);

[0205] In the formula, For the recent market gains, To provide energy compensation for the ancillary services market, For the unit's fuel cost;

[0206] Where the daily market return is calculated as:

[0207] (25);

[0208] Where, And are the winning price and the bid quantity of each period of the day-ahead market;

[0209] The energy compensation is calculated as:

[0210] (26);

[0211] Where, And are the up and down regulation market settlement price, And are the up and down regulation market bid quantity;

[0212] The unit fuel cost is calculated as:

[0213] (27);

[0214] Where, is the unit fuel cost;

[0215] The relationship between the market bid quantity and the unit power output is:

[0216] (28);

[0217] In addition, the auxiliary service market has an upper and lower limit of the bid quantity, i.e.,

[0218] (29);

[0219] (30);

[0220] And are the upper and lower limits of the auxiliary market bid quantity, and 0-1 decision variable And represent whether to participate in the bid of the up and down regulation market;

[0221] The linearization of (17) is performed using the Big-M method:

[0222] (31);

[0223] (32);

[0224] (33);

[0225] (34);

[0226] (35);

[0227] where M is a sufficiently large number, is the auxiliary 0-1 variable for the big M method.

[0228] Step 5, objective function solving.

[0229] After linearization of the constraints, the model is a mixed integer linear programming model, which can be written as follows:

[0230] (36).

[0231] See Figure 5 , program block diagram.

[0232] The specific solving process of step 5 is as follows:

[0233] Step 5.1, start;

[0234] Step 5.2, input the technical parameters of the heat engine unit and the heat storage tank, and set the rated capacity;

[0235] Step 5.3, input the current typical day hourly heat load data and power market price; set the upper and lower limits of the bid amount;

[0236] Step 5.4, judge whether all typical days are completed; if yes, go to step 5.5, if no, go to the next typical day and return to step 5.3;

[0237] Step 5.5, call cplex to solve the optimization model, record the results and draw the graph;

[0238] Step 5.6, end.

Claims

1. A market-driven method for the coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage, characterized in that, Includes the following steps: Step 1: Construct the integrated thermal power storage energy system structure; Step 2: Construct a model of an extraction-condensing steam turbine unit; Step 2.1: Construct a model showing the relationship between the output power and input steam flow rate of the extraction condensing steam turbine: The relationship between the output power and the input steam flow rate of the extraction condensing steam turbine is expressed as follows: （1）； In the formula, G ( t ) is a steam turbine t The input steam flow rate at any given time, in kg / s; P (t) is the steam turbine t Electric power at any given time, in MW; For generator efficiency, The internal efficiency of the steam turbine. This is to reduce the efficiency of steam turbine mechanical, heat dissipation, and self-use power loss. The enthalpy of the steam inlet to the turbine is expressed in MJ / kg. The exhaust enthalpy of the steam turbine is expressed in MJ / kg. Given that all efficiencies of the steam turbine are known, and 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, namely: （2）； Among them, the definition The power conversion factor; Step 2.2, Construct the boiler model: The main steam output of the unit is controlled by controlling the fuel input. The mathematical relationship between thermal power and input fuel quantity is as follows: （3）； In the formula, F ( t )for t Input the amount of fuel for the boiler at all times. for t The thermal power of the steam turbine is constantly input. and These are the thermal efficiency of the boiler and the thermal efficiency of the boiler pipes, 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 any given time, kg / s; The main steam specific enthalpy, MJ / kg; Specific enthalpy of boiler feedwater, MJ / kg; By combining the equations, the relationship between the fuel input to the boiler and the main steam flow rate can be obtained as follows: （5）； Assuming the feedwater enthalpy increase remains constant, the steam-fuel conversion factor is defined as: （6）； A linear relationship can be found between the fuel input to the boiler and the main steam flow rate: （7）； The amount of fuel input to the boiler is subject to a maximum operating range constraint, namely: （8）； In the formula, and These represent the upper and lower limits of the unit's fuel input, in MW. The boiler fuel ramp-up constraint is: （9）； In the formula: and These represent the maximum ramp power (MW) of the unit's fuel input. Step 2.3, Construct the heat exchange station model: Extraction-condensing cogeneration units primarily rely on heat exchange stations and heating networks for heat exchange. Considering the distribution system, when an extraction-condensing unit supplies heat by extracting a portion of steam, its heating output is calculated according to the law of conservation of energy as follows: （10）； （11）； In the formula, for t Real-time steam extraction flow rate for heating, kg / s; The specific enthalpy of the extracted heating steam, MJ / kg; The specific enthalpy of the hydrophobic layer formed after heat exchange by steam extraction for heating, in MJ / kg; Assuming the enthalpy drop of the heating extraction steam ratio remains constant, the following linear relationship exists between the heating extraction steam flow rate and the unit's heating output: （12）； In the formula, Enthalpy drop of steam extraction for heating MJ / kg; Step 2.4, Operating characteristics of extraction-condensing steam turbine units: The electrical output of the extraction condensing steam turbine unit is: （13）； In the formula: and These are the power conversion coefficients for the high-pressure, intermediate-pressure, and low-pressure cylinders of the steam turbine, respectively. By combining the above equations, the feasible operating range of the extraction condensing steam turbine unit can be obtained. The electric heating outputs under back pressure conditions are as follows: （14）； （15）； In the formula, for ease of calculation, the following definition is used: ; In summary, the operating range of extraction condensing steam turbines is mainly constrained by two factors: fuel input. and heating steam extraction volume Therefore, the upper and lower limits of the unit's electrothermal output can be determined as follows: （16）； ； when At that time, the lower limit of electrical output is determined by the unit's minimum fuel quantity; when At that time, the lower limit of electrical output is the electrical output of the unit under the back pressure condition with the same thermal output, that is: （17）； The upper limit of the unit's electrical output is determined by the maximum fuel quantity, that is: （18）； In the formula: F MAX Maximum fuel quantity; This refers to the electrical output of the unit under pure condensing conditions. This refers to the thermal output of the unit under pure condensing conditions. Step 3: Construct a hot water storage tank model; Step 4: Construct the electricity market constraints and objective function; Step 5: Solve for the objective function.

2. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 1, characterized in that, In step 1, the integrated thermal power and energy storage system consists of two energy networks: a district heating network and a power grid. The user's heat demand is supplied by the thermal power unit and the thermal storage device. Part of the thermal energy of the thermal power unit is stored in the hot water storage tank to provide regulation space for the system.

3. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 2, characterized in that, The electrothermal balance relationship of the system in step 1 is as follows: ； ； ； ； In the formula, for t Total electrical output of the thermal power unit during the time period, in MW; for t Total electrical load of the thermal power unit during the period, in MW; for t Total thermal output of the unit during the period, MW; The portion of the heat output (MW) that supplies heat load to the unit during time period t; for t Thermal storage capacity of the hot water storage tank during a given time period, in MW; The heat output of the unit stored in the hot water tank, MW; for t Heat release capacity of hot water storage tank during a given period, in MW; for t Heat load during a given time period, in MW.

4. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 1, characterized in that, Step 3 specifically includes: The "heat-driven power generation" constraint of a thermal power unit can be decoupled to some extent by adding a thermal storage device to the unit. Its operating model is expressed as follows: （19）； （20）； （21）； In the formula, For the heat storage tank in t Heat storage capacity at any given time, in MWh; and They are respectively t The heat absorption and release power and efficiency of the hot water storage tank within a given time period; The upper limit of thermal storage in the hot water tank, MWh; The initial value of heat storage in the hot water tank is MWh; The heat storage and release efficiency of hot water storage tanks is subject to the following constraints: （22）； （23）； In the formula, and This represents the maximum heat storage and release ratio of the hot water storage tank.

5. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 4, characterized in that, Step 4 specifically includes: If the optimization model is constructed with the objective of maximizing returns in both the day-to-day market and the mFRR service market, then the objective function is: （24）； In the formula, For the recent market gains, To compensate for the energy needs of the ancillary services market, For the unit's fuel cost; The method for calculating day-to-day market returns is as follows: （25）； In the formula, and This represents the winning bid prices and bid volumes for various time periods in the market prior to the current day. The formula for calculating energy compensation is: （26）； In the formula, and The settlement price for the up-and-down frequency modulation market. and For the bidding volume in the up and down frequency modulation market; The method for calculating the fuel cost of the generating unit is as follows: （27）； In the formula, Unit fuel cost; The relationship between market bidding volume and unit power output is as follows: （28）； In addition, the ancillary services market has upper and lower limits on the amount of bids, namely: （29）； （30）； and To assist in determining the upper and lower limits of market bid volume, 0-1 decision variables and This indicates whether the representative will participate in bidding for the up- and down-frequency modulation market. Linearize (17) using the Big M method: （31）； （32）； （33）； （34）； （35）； In the formula, M For a sufficiently large number, For the great M Auxiliary 0-1 variables of the law.

6. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 5, characterized in that, After the constraints are linearized in step 5, this model becomes a mixed-integer linear programming model, written in the following form: （36）。 7. The market-driven method for coordinated configuration and optimized operation of combined heat and power (CHP) and energy storage as described in claim 6, characterized in that, The specific solution process for step 5 is as follows: Step 5.1, Begin; 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 hourly heat load data and electricity market price for a typical current day; set the upper and lower limits for the bid quantity; Step 5.4: Determine whether all typical days have been completed; if yes, proceed to step 5.5; if no, 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 plot them; Step 5.6, End.

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