Thermal power generating unit heat supply income calculation method and device and storage medium

Abstract

The invention discloses a thermal power generating unit heat supply income calculation method and device considering capacity electricity price influence and a storage medium, belongs to the technical field of coal-fired thermal power generating unit heat supply income calculation, solves the problem of how to accurately calculate the thermal power generating unit heat supply income, and develops a typical working condition thermal test according to actual thermal characteristics of a thermal power generating unit. Fitting a power-heat consumption reference model under unit rated parameters, correcting important thermodynamic system boundary parameters to obtain a power-heat consumption model under an operation state in a statistical period, calculating unit maximum power decrease and capacity electricity price loss caused by heat supply according to the power-heat consumption model, counting coal consumption, water supplementing amount and heat supply income in combination with positive balance, and calculating the power-heat consumption of the unit. The heat supply cost and income of the unit in the statistical period are accurately calculated, and economical operation of heat supply of the unit is scientifically and effectively guided; according to the method, the cost is low, most of data needed by calculation are daily operation parameters and statistical data of the unit, no fixed equipment cost exists, and only test cost exists.

Description

Technical Field

[0001] The present invention belongs to the technical field of calculation of heating revenue of coal-fired thermal power units, and relates to a method, device and storage medium for calculating heating revenue of thermal power units taking into account the influence of capacity electricity price. Background Art

[0002] The revenue from capacity electricity price is directly linked to the maximum output of the unit. For heating units, external heat transfer will reduce the available energy of the unit, reduce the maximum power generation of the unit, and reduce the revenue from capacity electricity price. The traditional thermal power unit heating economic calculation does not take into account the impact of capacity electricity price, which makes it difficult to truly reflect the revenue of thermal power unit heating and cannot effectively guide the heating decision and economic operation of the unit. Summary of the invention

[0003] The technical problem to be solved by the present invention is how to improve the accuracy of calculating the heating benefit of a thermal power unit.

[0004] The present invention solves the above technical problems through the following technical solutions:

[0005] The present invention provides a method for calculating the heat supply income of a thermal power unit, comprising the following steps:

[0006] S1. Determine the statistical period, select representative test conditions according to the unit power characteristics, and carry out steam turbine thermal efficiency test;

[0007] S2, a benchmark model of power-heat consumption under rated parameters of the fitting unit;

[0008] S3, using the boundary parameters of the thermal system during the statistical period to correct the power-heat consumption benchmark model, and obtain the power-heat consumption model under the operating state;

[0009] S4. Using the power-heat consumption model under the operating state to calculate the maximum power drop value of the unit and the capacity electricity fee reduction value caused by the heating of the unit;

[0010] S5. According to the coal data, water replenishment data, coal price and water production cost during the statistical period, the coal cost and water replenishment cost of the heating group are calculated, and then the total revenue of the heating group is calculated in combination with the heating income.

[0011] Furthermore, the method for determining the statistical period in step S1, selecting representative test conditions according to the power characteristics of the unit, and conducting the steam turbine thermal efficiency test is specifically as follows:

[0012] S11. Determine the statistical period as a month;

[0013] S12. According to the upper and lower limits of the unit power, select n representative test conditions. The powers of the selected n representative test conditions are recorded as: P1, P2, P3…P n;

[0014] S13. Carry out thermal efficiency test on the steam turbine of the unit at the selected n representative test operating points, and calculate the thermal efficiency of the steam turbine at each representative test operating point as η1, η2, η3…η n .

[0015] Furthermore, the method for fitting the power-heat consumption benchmark model under the rated parameters of the unit described in step S2 is specifically as follows:

[0016] S21. Calculate the heat consumption Q1, Q2, Q3…Q of representative test conditions n , the formula is as follows:

[0017] Q i =P i / η i

[0018] Among them, the value of i is 1, 2, 3...n;

[0019] S22. Power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows:

[0020]

[0021] In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

[0022]

[0023] Furthermore, the method described in step S3 of using the thermal system boundary parameters within the statistical period to correct the power-heat consumption benchmark model to obtain the power-heat consumption model under the operating state is specifically as follows:

[0024] S31. According to the parameter correction curve provided by the unit equipment manufacturer, the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period is obtained, and the correction coefficient of the thermal system boundary parameters to the power includes: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5;

[0025] S32. After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the operating state during the statistical period is obtained as follows:

[0026] Pc (Q)=f1·f2·f3·f4·f5·P(Q).

[0027] Furthermore, the method described in step S4 for calculating the maximum power drop value and capacity electricity fee reduction value of the unit caused by the heating of the unit by using the power-heat consumption model in the operating state is specifically as follows:

[0028] S41, according to the unit heating flow G h and the heating medium enthalpy H h , calculate the heat supply per unit time (hour) Q h , and calculate the maximum value Q of heat supply per unit time per day during the statistical period hm,d , the calculation formulas are as follows:

[0029] Q h =G h ·H h

[0030] Q hm,d =max{Q h}

[0031] S42, when the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows:

[0032] P r,d =P c (Q hm,d )

[0033] S43. Calculate the average maximum power drop value P for the month based on the daily maximum power drop value of the unit. r,m , the calculation formula is as follows:

[0034]

[0035] Where M represents the number of days in the month;

[0036] S44. Calculate the capacity electricity cost C caused by the maximum power drop of the unit during the statistical period c,m , the calculation formula is as follows:

[0037] C c,m =P r,m ·V c,m

[0038] Among them, V c,m It is the monthly capacity electricity price.

[0039] Furthermore, the method described in step S5 for calculating the group heating coal cost and water replenishment cost based on the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculating the group heating total revenue based on the heating income is as follows:

[0040] S51, based on the total standard coal consumption of the month m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows:

[0041] B Q,m =B m α m

[0042] S52, based on the average price of standard coal V f,m , calculate the unit heating coal cost C during the statistical period f,m , the calculation formula is as follows:

[0043] C f,m =B Q,m ·V f,m

[0044] S53, based on the statistical value of heating water supply in the current month C w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows:

[0045] C w,m =G w,m ·V w,m

[0046] S54. Calculate the heat supply income of the unit during the statistical period I Q,m , the calculation formula is as follows:

[0047] I Q,m =Q h ·t m ·V Q

[0048] Among them, t , is the heating duration during the statistical period, V Q is the unit price of heating;

[0049] S55. Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows:

[0050] R s,m =I Q,m -C c,m -C f,m -C w,m .

[0051] The present invention also provides a thermal power unit heat supply benefit calculation device, comprising: a thermal efficiency test module, a benchmark model fitting module, a correction module, a capacity electricity cost calculation module, and a total benefit calculation module;

[0052] The thermal efficiency test module is used to: determine the statistical period, select representative test conditions according to the unit power characteristics, and carry out the steam turbine thermal efficiency test;

[0053] The benchmark model fitting module is used to: fit the benchmark model of power-heat consumption under rated parameters of the unit;

[0054] The correction module is used to: use the boundary parameters of the thermal system during the statistical period to correct the power-heat consumption benchmark model to obtain the power-heat consumption model under the operating state;

[0055] The capacity electricity cost calculation module is used to: calculate the maximum power drop value of the unit and the capacity electricity cost reduction value caused by the heating of the unit by using the power-heat consumption model under the operating state;

[0056] The total revenue calculation module is used to calculate the group heating coal cost and water replenishment cost according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculate the total revenue of the group heating in combination with the heating income.

[0057] Furthermore, the method for determining the statistical period described in the thermal efficiency test module, selecting representative test conditions according to the unit power characteristics, and conducting the thermal efficiency test of the steam turbine is as follows:

[0058] 11) Determine the statistical period as monthly;

[0059] 12) According to the upper and lower limits of the unit power, n representative test conditions are selected. The powers of the selected n representative test conditions are recorded as: P1, P2, P3…P n ;

[0060] 13) At the selected n representative test operating points, the thermal efficiency test of the unit steam turbine is carried out, and the thermal efficiency of the steam turbine at each representative test operating point is calculated as η1, η2, η3…η n .

[0061] Furthermore, the method for fitting the power-heat consumption benchmark model under the rated parameters of the unit described in the benchmark model fitting module is specifically as follows:

[0062] 21) Calculate the heat consumption Q1, Q2, Q3…Q of representative test conditions n , the formula is as follows:

[0063] Q i =Pi / η i

[0064] Among them, the value of i is 1, 2, 3...n;

[0065] 22) Power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows:

[0066]

[0067] In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

[0068]

[0069] Furthermore, the method described in the correction module of correcting the power-heat consumption benchmark model using the thermal system boundary parameters during the statistical period to obtain the power-heat consumption model under the operating state is specifically as follows:

[0070] 31) According to the parameter correction curve provided by the unit equipment manufacturer, the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period is obtained, and the correction coefficient of the thermal system boundary parameters to the power includes: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5;

[0071] 32) After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the statistical period operation state is obtained as follows:

[0072] P c (Q)=f1·f2·f3·f4·f5·P(Q).

[0073] Furthermore, the method described in the capacity electricity cost calculation module for calculating the maximum power drop value of the unit and the capacity electricity cost reduction value caused by the heating of the unit using the power-heat consumption model under the operating state is specifically as follows:

[0074] 41) According to the unit heat flow G h and the heating medium enthalpy H h , calculate the heat supply per unit time (hour) Qx, and calculate the maximum heat supply per unit time per day during the statistical period Q hm,d , the calculation formulas are as follows:

[0075] Q h=G h ·H h

[0076] Q hm,d =max{Q h}

[0077] 42) When the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows:

[0078] P r,d =P c (Q hm,d )

[0079] 43) According to the daily maximum power drop value of the unit, calculate the average maximum power drop value P for the month r,m , the calculation formula is as follows:

[0080]

[0081] Where M represents the number of days in the month;

[0082] 44) Calculate the capacity electricity cost C caused by the maximum power reduction of the unit during the statistical period c,m , the calculation formula is as follows:

[0083] C c,m =P r,m ·V c,m

[0084] Among them, V c,m It is the monthly capacity electricity price.

[0085] Furthermore, the method described in the total revenue calculation module is as follows: according to the coal data, water replenishment data, coal price and water production cost during the statistical period, the method of calculating the total revenue of the heating group by calculating the coal cost and water replenishment cost of the heating group and then combining the heating income to calculate the total revenue of the heating group:

[0086] 51) Based on the total standard coal consumption for production in that month B m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows:

[0087] B Q,m =B m α m

[0088] 52) Based on the average price of standard coal V f,m, calculate the heating coal cost C of the unit during the statistical period f,m , the calculation formula is as follows:

[0089] C f,m =B Q,m ·V f,m

[0090] 53) According to the statistical value of heating water supply in the current month G w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows:

[0091] C w,m =G w,m ·V w,m

[0092] 54) Calculate the heat supply income of the unit during the statistical period I Q,m , the calculation formula is as follows:

[0093] I Q,m =Q h ·t m ·V Q

[0094] Among them, t m is the heating duration during the statistical period, V Q is the unit price of heating;

[0095] 55) Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows:

[0096] R s,m =I Q,m -C c,m -C f,m -C w,m .

[0097] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above-mentioned thermal power unit heating benefit calculation method, and the processor is configured to execute the program stored in the memory.

[0098] The present invention also provides a storage medium on which a computer program is stored. When the computer program is run by a processor, the steps of the above-mentioned method for calculating the heating revenue of a thermal power unit are executed.

[0099] The advantages of the present invention are:

[0100] The technical solution of the present invention carries out thermal tests under typical working conditions according to the actual thermal characteristics of the thermal power unit, fits the power-heat consumption benchmark model under the rated parameters of the unit, and corrects the boundary parameters of the important thermal system to obtain the power-heat consumption model under the operating state during the statistical period, and calculates the maximum power drop of the unit and the capacity electricity price loss caused by heating on this basis, and combines the positive balance statistical coal consumption, water replenishment and heating income to accurately calculate the heating cost and income of the unit during the statistical period, so as to scientifically and effectively guide the economic operation of the heating of the unit; the cost of the present invention is relatively low, and most of the data required for calculation are the daily operating parameters and statistical data of the unit, there is no fixed equipment cost, and only the test cost; in addition, the power-heat consumption model of the present invention, in addition to being used for calculating the economic indicators of heating of the unit, can also be used to guide the daily energy-saving operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 It is a flow chart of a method for calculating the heating revenue of a thermal power unit taking into account the influence of capacity electricity price according to the first embodiment of the present invention;

[0102] Figure 2 is the main steam temperature correction curve of the unit used in Embodiment 1 and Embodiment 2 of the present invention;

[0103] Figure 3 is the main steam pressure correction curve of the unit used in Embodiment 1 and Embodiment 2 of the present invention;

[0104] Figure 4 is the reheat temperature correction curve of the unit used in Embodiment 1 and Embodiment 2 of the present invention;

[0105] Figure 5 is the reheat pressure loss correction curve of the unit used in Embodiment 1 and Embodiment 2 of the present invention;

[0106] Figure 6 It is the back pressure correction curve of the unit used in Embodiment 1 and Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0107] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described in combination with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0108] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments:

[0109] Embodiment 1

[0110] like Figure 1 As shown, a method for calculating the heating revenue of a thermal power unit taking into account the influence of capacity electricity price provided in this embodiment includes the following steps:

[0111] Step 1: Determine the statistical period, select representative test conditions according to the unit power characteristics, and conduct steam turbine thermal efficiency tests

[0112] Step 1.1: Since capacity electricity prices are generally settled on a monthly basis, the statistical period is determined to be monthly.

[0113] Step 1.2: According to the upper and lower limits of the unit power, select several representative test conditions. The representative test conditions include but are not limited to the lowest power condition, the highest power condition, the common power condition, etc. The representative test condition should be the pure condensing condition. To ensure the representativeness of the conditions, the number of representative test conditions n should not be less than 3. The powers of the selected n representative test conditions are recorded as: P1, P2, P3...P n .

[0114] Step 1.3: At the selected n representative test operating points, carry out thermal efficiency test on the unit steam turbine according to the requirements of GB / T 8117 standard, and calculate the thermal efficiency of the steam turbine at each representative test operating point as η1, η2, η3…η n .

[0115] Step 2: Fit the power-heat consumption benchmark model under the rated parameters of the unit

[0116] Step 2.1, calculate the heat consumption Q1, Q2, Q3…Q of the representative test operating points n , the formula is as follows:

[0117] Q i =P i / η i

[0118] Among them, the value of i is 1, 2, 3...n.

[0119] Step 2.2: Fit the power-heat consumption of representative test operating points to obtain a benchmark model of power-heat consumption under rated boundary parameters of the unit.

[0120] Specifically, the power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows:

[0121]

[0122] In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

[0123]

[0124] Step 3: Use the boundary parameters of the thermal system during the statistical period to correct the power-heat consumption benchmark model to obtain the power-heat consumption model under the operating state.

[0125] Step 3.1, according to the parameter correction curve provided by the unit equipment manufacturer, obtain the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period, the correction coefficient of the thermal system boundary parameters to the power includes: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5.

[0126] Taking a conventional thermal power unit as an example, the parameter correction curve of the unit is as follows: Figure 2-Figure 6 As shown, the rated main steam temperature of the unit is T m,0 , rated main steam pressure is p m,0 , Rated reheat steam temperature is T r,0 , Rated reheat pressure loss is Rated back pressure is p b,0 .

[0127] Calculate the statistical average of the main steam temperature during the statistical period Statistical average of main steam pressure Statistical average of reheat steam temperature Statistical average of reheat pressure loss And the average value of backpressure statistics

[0128] According to the main steam temperature deviation during the statistical period check Figure 2 The main steam temperature correction curve shown in the figure obtains the power change rate ω1, and the calculation formula of the main steam temperature correction coefficient f1 is as follows:

[0129]

[0130] According to the main steam pressure deviation during the statistical period check Figure 3 The main steam pressure correction curve shown in the figure obtains the power change rate ω2, and the calculation formula of the main steam pressure correction coefficient f2 is as follows:

[0131]

[0132] According to the reheat temperature deviation during the statistical period check Figure 4 The reheat temperature correction curve shown in the figure obtains the power change rate ω3, and the calculation formula of the reheat temperature correction coefficient f3 is as follows:

[0133]

[0134] According to the reheat pressure loss deviation during the statistical period check Figure 5 The reheating pressure loss correction curve shown in the figure obtains the power change rate ω4, and the calculation formula of the reheating pressure loss correction coefficient f4 is as follows:

[0135]

[0136] According to the back pressure during the statistical period check Figure 6 The back pressure correction curve shown in the figure shows the power change rate ω5 obtained by back pressure, and the calculation formula of the back pressure correction coefficient f5 is as follows:

[0137]

[0138] Step 3.2: After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the statistical period operation state is obtained as follows:

[0139] P c (Q)=f1·f2·f3·f4·f5·P(Q).

[0140] Step 4: Use the power-heat consumption model under the operating state to calculate the maximum power drop value and capacity electricity fee reduction value of the unit caused by the heating of the unit

[0141] Step 4.1: According to the heating flow rate G of the unit h and the heating medium enthalpy H h , calculate the heat supply per unit time (hour) Q h , and calculate the maximum value Q of heat supply per unit time per day during the statistical period hm,d , the calculation formulas are as follows:

[0142] Q h =G h ·H h

[0143] Q hm,d =max{Q h}

[0144] Step 4.2: When the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows:

[0145] P r,d =P c (Q hm,d )

[0146] Step 4.3: Calculate the average maximum power drop value P for the month based on the daily maximum power drop value of the unit. r,m , the calculation formula is as follows:

[0147]

[0148] Where M represents the number of days in the month.

[0149] Step 4.4: Calculate the capacity electricity cost C caused by the maximum power drop of the unit during the statistical period c,m , the calculation formula is as follows:

[0150] C c,m =P r,m ·V c,m

[0151] Among them, V c,m It is the monthly capacity electricity price.

[0152] Step 5: Calculate the heating coal cost and water replenishment cost of the group according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculate the total heating income of the group in combination with the heating income

[0153] Step 5.1: Based on the total standard coal consumption B for production in that month m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows:

[0154] B Q,m =B m α m

[0155] Step 5.2: Based on the average price of standard coal V f,m , calculate the unit heating coal cost C during the statistical period f,m , the calculation formula is as follows:

[0156] C f,m =B Q,m ·V f,m

[0157] Step 5.3: According to the statistical value of heating water supply in the current month G w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows:

[0158] Cw,m =G w,m ·V w,m

[0159] Step 5.4: Calculate the heat supply income I of the unit during the statistical period Q,m , the calculation formula is as follows:

[0160] I Q,m =Q h ·t m ·V Q

[0161] Among them, t m is the heating duration during the statistical period, V Q The unit price for heating.

[0162] Step 5.5: Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows:

[0163] R s,m =I Q,m -C c,m -C f,m -C w,m .

[0164] Embodiment 2

[0165] The present embodiment provides a thermal power unit heat supply revenue calculation device taking into account the impact of capacity electricity price, comprising: a thermal efficiency test module, a benchmark model fitting module, a correction module, a capacity electricity cost calculation module, and a total revenue calculation module;

[0166] The thermal efficiency test module is used to determine the statistical period, select representative test conditions according to the unit power characteristics, and carry out the steam turbine thermal efficiency test. The specific method is as follows:

[0167] 11) Determine the statistical period as monthly;

[0168] 12) According to the upper and lower limits of the unit power, n representative test conditions are selected. The powers of the selected n representative test conditions are recorded as: P1, P2, P3…P n ;

[0169] 13) At the selected n representative test operating points, the thermal efficiency test of the unit steam turbine is carried out, and the thermal efficiency of the steam turbine at each representative test operating point is calculated as η1, η2, η3…η n .

[0170] The benchmark model fitting module is used to fit the benchmark model of power-heat consumption under the rated parameters of the unit, and the specific method is as follows:

[0171] 21) Calculate the heat consumption Q1, Q2, Q3…Q of representative test conditions n , the formula is as follows:

[0172] Q i =P i / η i

[0173] Among them, the value of i is 1, 2, 3...n;

[0174] 22) The power-heat consumption of representative test operating points is fitted to obtain a benchmark model of power-heat consumption under the rated boundary parameters of the unit.

[0175] Specifically, the power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows:

[0176]

[0177] In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

[0178]

[0179] The correction module is used to correct the power-heat consumption benchmark model using the thermal system boundary parameters during the statistical period to obtain the power-heat consumption model under the operating state. The specific method is as follows:

[0180] 31) According to the parameter correction curve provided by the unit equipment manufacturer, the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period is obtained. The correction coefficient of the thermal system boundary parameters to the power includes: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5.

[0181] Taking a conventional thermal power unit as an example, the parameter correction curve of the unit is as follows: Figure 2-Figure 6 As shown, the rated main steam temperature of the unit is T m,0 , rated main steam pressure is p m,0 , Rated reheat steam temperature is T r,0 , Rated reheat pressure loss is d pr,0 , rated back pressure is p b,0 .

[0182] Calculate the statistical average of the main steam temperature during the statistical period Statistical average of main steam pressure Statistical average of reheat steam temperature Statistical average of reheat pressure loss And the average value of backpressure statistics

[0183] According to the main steam temperature deviation during the statistical period check Figure 2 The main steam temperature correction curve shown in the figure obtains the power change rate ω1, and the calculation formula of the main steam temperature correction coefficient f1 is as follows:

[0184]

[0185] According to the main steam pressure deviation during the statistical period check Figure 3 The main steam pressure correction curve shown in the figure obtains the power change rate ω2, and the calculation formula of the main steam pressure correction coefficient f2 is as follows:

[0186]

[0187] According to the reheat temperature deviation during the statistical period check Figure 4 The reheat temperature correction curve shown in the figure obtains the power change rate ω3, and the calculation formula of the reheat temperature correction coefficient f3 is as follows:

[0188]

[0189] According to the reheat pressure loss deviation during the statistical period check Figure 5 The reheating pressure loss correction curve shown in the figure obtains the power change rate ω4, and the calculation formula of the reheating pressure loss correction coefficient f4 is as follows:

[0190]

[0191] According to the back pressure during the statistical period check Figure 6 The back pressure shown in the figure obtains the power change rate ω5, and the calculation formula of the back pressure correction coefficient f5 is as follows:

[0192]

[0193] 32) After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the statistical period operation state is obtained as follows:

[0194] P c (Q)=f1·f2·f3·f4·f5·P(Q).

[0195] The capacity electricity cost calculation module is used to calculate the maximum power drop value and capacity electricity cost reduction value of the unit caused by the heating of the unit using the power-heat consumption model under the operating state. The specific method is as follows:

[0196] 41) According to the unit heat flow G h and the heating medium enthalpy H h , calculate the heat supply per unit time (hour) Q h , and calculate the maximum value Q of heat supply per unit time per day during the statistical period hm,d , the calculation formulas are as follows:

[0197] Q h =G h ·H h

[0198] Q hm,d =max{Q h}

[0199] 42) When the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows:

[0200] P r,d =P c (Q hm,d )

[0201] 43) According to the daily maximum power drop value of the unit, calculate the average maximum power drop value P for the month r,m , the calculation formula is as follows:

[0202]

[0203] Where M represents the number of days in the month;

[0204] 44) Calculate the capacity electricity cost C caused by the maximum power reduction of the unit during the statistical period c,m , the calculation formula is as follows:

[0205] C c,m =P r,m ·V c,m

[0206] Among them, V c,m It is the monthly capacity electricity price.

[0207] The total revenue calculation module is used to calculate the heating coal cost and water replenishment cost of the group according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculate the total revenue of the heating group in combination with the heating income. The specific method is as follows:

[0208] 51) Based on the total standard coal consumption for production in that month B m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows:

[0209] B Q,m =B m α m

[0210] 52) Based on the average price of standard coal V f,m , calculate the unit heating coal cost C during the statistical period f,m , the calculation formula is as follows:

[0211] C f,m =B Q,m ·V f,m

[0212] 53) According to the statistical value of heating water supply in the current month G w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows:

[0213] C w,m =G w,m ·V w,m

[0214] 54) Calculate the heat supply income of the unit during the statistical period I Q,m , the calculation formula is as follows:

[0215] I Q,m =Q h ·t m ·V Q

[0216] Among them, t m is the heating duration during the statistical period, V Q is the unit price of heating;

[0217] 55) Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows:

[0218] R s,m =I Q,m -C c,m -C f,m -C w,m .

[0219] Embodiment 3

[0220] A storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for calculating the heating revenue of a thermal power unit taking into account the influence of capacity electricity price in embodiment 1.

[0221] Embodiment 4

[0222] An electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the method for calculating the heating revenue of a thermal power unit taking into account the impact of capacity electricity price in Example 1, and the processor is configured to execute the program stored in the memory.

[0223] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the heating income of a thermal power unit, characterized in that: The following steps are involved: S1. Determine the statistical period, select representative test conditions according to the unit power characteristics, and carry out steam turbine thermal efficiency test; S2, a benchmark model of power-heat consumption under rated parameters of the fitting unit; S3, using the boundary parameters of the thermal system during the statistical period to correct the power-heat consumption benchmark model, and obtain the power-heat consumption model under the operating state; S4. Using the power-heat consumption model under the operating state to calculate the maximum power drop value of the unit and the capacity electricity fee reduction value caused by the heating of the unit; S5. According to the coal data, water replenishment data, coal price and water production cost during the statistical period, the coal cost and water replenishment cost of the heating group are calculated, and then the total revenue of the heating group is calculated in combination with the heating income.

2. The method for calculating the heat supply income of a thermal power unit according to claim 1, characterized in that: The method for determining the statistical period in step S1, selecting representative test conditions according to the power characteristics of the unit, and conducting the steam turbine thermal efficiency test is specifically as follows: S11. Determine the statistical period as a month; S12. According to the upper and lower limits of the unit power, select n representative test conditions. The powers of the selected n representative test conditions are recorded as: P1, P2, P3…P n ; S13. Carry out thermal efficiency test on the steam turbine of the unit at the selected n representative test operating points, and calculate the thermal efficiency of the steam turbine at each representative test operating point as η1, η2, η3…η n .

3. The method for calculating the heat supply income of a thermal power unit according to claim 2, characterized in that: The method for fitting the power-heat consumption benchmark model under the rated parameters of the unit described in step S2 is specifically as follows: S21. Calculate the heat consumption Q1, Q2, Q3…Q of representative test conditions n , the formula is as follows: Q i =P i / η i Among them, the value of i is 1, 2, 3...n; S22. Power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows: In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

4. The method for calculating the heat supply income of a thermal power unit according to claim 3, characterized in that: The method described in step S3 of using the thermal system boundary parameters within the statistical period to correct the power-heat consumption benchmark model to obtain the power-heat consumption model under the operating state is specifically as follows: S31, according to the correction coefficient of the parameter correction curve provided by the unit equipment manufacturer, the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period is obtained, and the thermal system boundary parameters include: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5; S32. After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the operating state during the statistical period is obtained as follows: P c (Q)=f1·f2·f3·f4·f5·P(Q)。 5. The method for calculating the heat supply income of a thermal power unit according to claim 4, characterized in that: The method described in step S4 for calculating the maximum power drop value and capacity electricity fee reduction value of the unit caused by the heating supply of the unit by using the power-heat consumption model in the operating state is specifically as follows: S41, according to the unit heating flow G h and the heating medium enthalpy H h , calculate the heat supply per unit time Q h , and calculate the maximum value Q of heat supply per unit time per day during the statistical period hm,d , the calculation formulas are as follows: Q h =G h ·H h Q hm,d =max{Q h } S42, when the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows: P r,d =P c (Q m,d ) S43. Calculate the average maximum power drop value P for the month based on the daily maximum power drop value of the unit. r,m , the calculation formula is as follows: Where M represents the number of days in the month; S44. Calculate the capacity electricity cost C caused by the maximum power drop of the unit during the statistical period c,m , the calculation formula is as follows: C c,m =P r,m ·V c,m Among them, V c,m It is the monthly capacity electricity price.

6. The method for calculating the heat supply income of a thermal power unit according to claim 5, characterized in that: The method described in step S5 for calculating the heating coal cost and water replenishment cost of the group according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculating the total revenue of the heating group in combination with the heating income is as follows: S51, based on the total standard coal consumption of the month m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows: B Q,m =B m ·a m S52, based on the average price of standard coal V f,m , calculate the unit heating coal cost C during the statistical period f,m , the calculation formula is as follows: C f,m =B Q,m ·V f,m S53, based on the monthly heating water supply statistical value G w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows: C w,m =G w,m ·V w,m S54. Calculate the heat supply income of the unit during the statistical period I Q,m , the calculation formula is as follows: I Q,m =Q h ·t m ·V Q Among them, t m is the heating duration during the statistical period, V Q is the unit price of heating; S55. Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows: R s,m =I Q,m -C c,m -C f,m -C w,m 。 7. A device for calculating the heating income of a thermal power unit, characterized in that: include: Thermal efficiency test module, benchmark model fitting module, correction module, capacity electricity cost calculation module, total benefit calculation module; The thermal efficiency test module is used to: determine the statistical period, select representative test conditions according to the unit power characteristics, and carry out the steam turbine thermal efficiency test; The benchmark model fitting module is used to: fit the benchmark model of power-heat consumption under rated parameters of the unit; The correction module is used to: use the boundary parameters of the thermal system during the statistical period to correct the power-heat consumption benchmark model to obtain the power-heat consumption model under the operating state; The capacity electricity cost calculation module is used to: calculate the maximum power drop value of the unit and the capacity electricity cost reduction value caused by the heating of the unit by using the power-heat consumption model under the operating state; The total revenue calculation module is used to calculate the group heating coal cost and water replenishment cost according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculate the total revenue of the group heating in combination with the heating income.

8. The thermal power unit heat supply income calculation device according to claim 7, characterized in that: The method for determining the statistical period described in the thermal efficiency test module, selecting representative test conditions according to the unit power characteristics, and conducting the steam turbine thermal efficiency test is as follows: 11) Determine the statistical period as monthly; 12) According to the upper and lower limits of the unit power, n representative test conditions are selected. The powers of the selected n representative test conditions are recorded as: P1, P2, P3…P n ; 13) At the selected n representative test operating points, the thermal efficiency test of the unit steam turbine is carried out, and the thermal efficiency of the steam turbine at each representative test operating point is calculated as η1, η2, η3…η n .

9. The thermal power unit heat supply income calculation device according to claim 8, characterized in that: The method for fitting the power-heat consumption benchmark model under the rated parameters of the unit described in the benchmark model fitting module is as follows: 21) Calculate the heat consumption Q1, Q2, Q3…Q of representative test conditions n , the formula is as follows: Q i =P i / η i Among them, the value of i is 1, 2, 3...n; 22) Power-heat consumption of representative test operating points: (Q1, P1), (Q2, P2), (Q3, P3), ... (Q n ,P n ) The least square method is used to fit the cubic polynomial, and the power-heat consumption benchmark model under the rated boundary parameters of the unit is obtained as follows: In the formula, a j is the fitting coefficient, and the values ​​of j are 0, 1, 2, and 3, which are solved by the following system of equations:

10. The thermal power unit heat supply income calculation device according to claim 9, characterized in that: The method described in the correction module for correcting the power-heat consumption benchmark model using the thermal system boundary parameters during the statistical period to obtain the power-heat consumption model under the operating state is as follows: 31) According to the correction coefficient of the parameter correction curve provided by the unit equipment manufacturer, the correction coefficient of the thermal system boundary parameters to the power during the unit statistical period is obtained, and the thermal system boundary parameters include: main steam temperature correction coefficient f1, main steam pressure correction coefficient f2, reheat steam temperature correction coefficient f3, reheat pressure loss correction coefficient f4, back pressure correction coefficient f5; 32) After the thermal system boundary parameters are corrected, the power-heat consumption model of the unit under the statistical period operation state is obtained as follows: P c (Q)=f1·f2·f3·f4·f5·P(Q)。 11. The thermal power unit heat supply income calculation device according to claim 10, characterized in that: The method described in the capacity electricity cost calculation module for calculating the maximum power drop value of the unit and the capacity electricity cost reduction value caused by the heating of the unit by using the power-heat consumption model under the operating state is as follows: 41) According to the unit heat flow G h and the heating medium enthalpy H h , calculate the heat supply per unit time Q h , and calculate the maximum value Q of heat supply per unit time per day during the statistical period hm,d , the calculation formulas are as follows: Q h =G h ·H h Q hm,d =max{Q h } 42) When the unit is supplying heat, the steam-water working medium is extracted, the work done by the steam turbine is reduced, and the unit output decreases. According to the maximum amount of heat supplied per unit time per day by the unit, the power-heat consumption model under the operating state is used to calculate the maximum power reduction value P of the unit on that day. r,d , the calculation formula is as follows: P r,d =P c (Q hm,d ) 43) According to the daily maximum power drop value of the unit, calculate the average maximum power drop value P for the month r,m , the calculation formula is as follows: Where M represents the number of days in the month; 44) Calculate the capacity electricity cost C caused by the maximum power reduction of the unit during the statistical period c,m , the calculation formula is as follows: C c,m =P r,m ·V c,m Among them, V c,m It is the monthly capacity electricity price.

12. The thermal power unit heat supply income calculation device according to claim 11, characterized in that: The method described in the total revenue calculation module for calculating the coal cost and water replenishment cost of the heating group according to the coal data, water replenishment data, coal price and water production cost during the statistical period, and then calculating the total revenue of the heating group in combination with the heating income is as follows: 51) Based on the total standard coal consumption for production in that month B m and heating ratio α m Calculate the standard coal consumption for heating during the statistical period B Q,m , the calculation formula is as follows: B Q,m =B m ·a m 52) Based on the average price of standard coal V f,m , calculate the heating coal cost C of the unit during the statistical period f,m , the calculation formula is as follows: C f,m =B Q,m ·V f,m 53) According to the statistical value of heating water supply in the current month G w,m and unit water production cost V w,m , calculate the heating water replenishment cost C during the statistical period w,m , the calculation formula is as follows: C w,m =G w,m ·V w,m 54) Calculate the heat supply income of the unit during the statistical period I Q,m , the calculation formula is as follows: I Q,m =Q h ·t m ·V Q Among them, t m is the heating duration during the statistical period, V Q is the unit price of heating; 55) Calculate the total heating revenue R of the unit during the statistical period s,m , the calculation formula is as follows: R s,m =I Q,m -C c,m -C f,m -C w,m 。 13. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the method for calculating the heating revenue of a thermal power unit as described in any one of claims 1 to 6, and the processor is configured to execute the program stored in the memory.

14. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for calculating the heating revenue of a thermal power unit according to any one of claims 1 to 6 are executed.

Images