Acquisition method based on load interval distribution of generating capacity of thermal power generating unit and application

Abstract

The invention discloses a thermal power generating unit generating capacity load interval distribution-based acquisition method and application, and the method comprises the steps: carrying out the preprocessing of a real-time data set F0 of an on-site generating set, and forming a set G0; establishing a six-level statistical index according to the load; determining conditions of the measuring points are set according to six-level statistical indexes; respectively configuring day, month and year attributes of each level of statistical index of a certain unit in the organization set H0; setting target values of four indexes including main steam temperature, main steam pressure, turbine rotating speed and generator load, searching real-time measuring point values corresponding to the four indexes in the set G0, and judging that the unit runs normally according to the set real-time measuring point values and the set target values. If yes, the daily, monthly and annual generating capacity of different loads of a certain unit or a certain level of organization mechanism is calculated respectively, and load interval distribution of unit-level and power plant-level electric quantity is correspondingly obtained according to organization mechanism dimension and time dimension generating data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of thermal power operation and maintenance, and particularly relates to a method for obtaining load interval distribution of power generation of a thermal power unit and application thereof. BACKGROUND

[0002] With the vigorous development of wind power and photovoltaic renewable energy, the grid-connection of new energy in large scale with unstable power generation determines that the power supply structure layout mainly with thermal power units will inevitably become the dominant complementary power supply. The conventional coordination control strategy cannot meet the higher requirement of the control quality of the power grid under ultra-low load of the unit, and the deep peak shaving capacity of the unit directly affects the on-grid competitiveness and profitability, which means that the stronger the deep regulation capacity is, the more considerable the grid compensation price income is, and it is of great significance to the work of reducing and eliminating losses for a company. In this case, a method for accurately and timely monitoring and statistically comparing the power generation proportion of a thermal power unit in different load intervals is urgently needed for a power generation enterprise. SUMMARY

[0003] In order to solve the problems in the prior art, the present application provides a method for obtaining load interval distribution of power generation of a thermal power unit, which can calculate and statistically the power generation of a unit in different load intervals in real time according to the real-time collected power generation load parameters of the unit, and provide a scientific and fast index obtaining method for the production management department, and timely monitor the operation of the unit.

[0004] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present application is as follows: the method for obtaining load interval distribution of power generation of a thermal power unit comprises the following steps: establishing statistical indexes, dividing the statistical indexes into six levels according to the load; and establishing target values of each statistical index based on the statistical indexes; establishing an organization relationship according to the organization level of the enterprise where the thermal power unit is located, forming an organization set H0, and respectively configuring the "day", "month", and "year" attributes of the six-level statistical index "I * " of one unit in the organization set H0, I * respectively corresponding to the "day", "month", and "year" attributes to form sets K D , K M , and K Y ; establishing power generation indexes at the unit level, which are respectively the daily power generation, monthly power generation, and annual power generation of the unit; based on the accurate "total power generation" attribute data of the unit, configuring the daily attribute K D of a certain index in the index set "I * " corresponding to a power plant or a certain period in the organization set H0, K D = the daily attribute K DThe sum of the calculation results forms the set O0, O1, O2, O3, and the indicator set "I" corresponding to a power plant or a period in the configuration organization set H0 * "The monthly attribute of an indicator in "K M " and year attribute "K Y ", calculate K by summing up the sets O0, O1, O2, and O3 M and K Y ; Based on the power generation data in the organizational dimension and the time dimension, the load range distribution of the power at the unit level and the power plant level is obtained.

[0005] Furthermore, obtaining accurate "total power generation" attribute data of the unit includes the following steps: By setting the upper and lower limits of the measurement point data or setting data processing rules, the real-time data set F0 collected by the on-site generator set is pre-processed to form the real-time data set G0 of the on-site generator set; Set target values ​​for four indicators for judging the normal operation of the unit; search for real-time measurement points corresponding to the four indicators in the real-time data set G0 of the on-site generator set; According to the actual situation of the application unit, establish organizational relationships in the data governance platform to form set H0; According to the actual needs of the application units in management and assessment, statistical indicators are established in the data governance platform. According to the load, they are divided into six levels of statistical indicators, forming sets I0, I1, I2, I3, I4, and I5; Establishing a measurement point judgment condition based on the statistical indicators, setting the measurement point judgment condition according to the six-level load statistical indicators to form sets J0, J1, J2, J3, J4, and J5; Configure the "day", "month", and "year" attributes of a unit indicator "I0, I1, I2, I3, I4, I5" in the organizational set H0 respectively, and form a set K corresponding to the "day", "month", and "year" attributes respectively. D , K M , K Y ; Establish unit-level power generation indicators, which have three attributes: daily, monthly, and annual, representing the daily power generation, monthly power generation, and annual power generation of the unit level respectively; Setting conditions for judging the normal operation of the unit, which are target values ​​of four indicators: main steam temperature, main steam pressure, turbine speed, and generator load, forming a set R1, R2, R3, and R4; Searching for real-time measurement points corresponding to the four indicators in the set G0 to form sets S1, S2, S3, and S4; Compare the set R1, R2, R3, R4 with the set S1, S2, S3, S4. When the real-time measurement point values ​​in the judgment conditions reach the simultaneous target values, the unit status is judged to be normal operation and subsequent calculations are performed; Configure the calculation logic of the statistical indicator attribute "daily power generation index" of a unit in the organizational set H0, and determine that when the data set G0 meets the measurement point judgment conditions J0, J1, J2, J3, J4, and J5 on the statistical day, the data set G0 is integrated and accumulated to obtain sets L1, L2, L3, and L4; calculate the monthly power generation attribute K of the same statistical indicator based on the daily power generation attribute M And the annual power generation attribute K Y ; Configure the "total power generation" attribute "K" of a unit in the organizational set H0 in the data governance platform. D The calculation logic of ": on the statistical day, the data set G0 is integrated and accumulated to form the set L5; For set K D The data is verified and the condition is met: L5-(L1+L2+L3+L4)≤T0, where T0 is the threshold set by the user based on the actual situation on site. In this case, the "total power generation" attribute data of the unit is calculated correctly.

[0006] Furthermore, the calculation logic of the statistical indicator attribute "daily power generation index" of a unit in the organizational set H0 is configured. When the data set G0 meets the measurement point judgment conditions "J0, J1, J2, J3, J4" on the statistical day, the data set G0 is integrated and accumulated to form sets L1, L2, L3, and L4. The details are as follows: Configure the attribute "K D The calculation logic of ": when the data set "G0" meets the "J0" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L0"; Configure the "30%~40% load power generation" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J1" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L1"; Configure the "40%~50% load power generation" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J2" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L2"; Configure the "50%~75% load power generation" attribute of a unit in the organization set H0.D The calculation logic of ": when the data set "G0" meets the "J3" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L3"; Configure the attribute "K D The calculation logic of " is: when the data set "G0" meets the "J4" condition on the statistical day, the data set G0 is integrated and accumulated to form the set L4.

[0007] Furthermore, the statistical indicators include power generation at loads below 30%, power generation at loads between 30% and 40%, power generation at loads between 40% and 50%, power generation at loads between 50% and 75%, power generation at loads above 75%, and total power generation.

[0008] Furthermore, the measuring point judgment conditions include: real-time load < 30% of the installed capacity, 30% of the installed capacity ≤ real-time load < 40% of the installed capacity, 40% of the installed capacity ≤ real-time load < 50% of the installed capacity, 50% of the installed capacity ≤ real-time load < 75% of the installed capacity, and 75% of the installed capacity ≤ real-time load.

[0009] Furthermore, the organizational structure relationship is specifically: group company level, regional company level, grassroots enterprise level, period level, and unit level, ultimately forming a set H0.

[0010] Furthermore, set the attribute "K D " is calculated automatically at 2:00 a.m. the next day to calculate the previous day's data. This avoids problems caused by data delays that may occur during on-site network transmission or data collection.

[0011] Furthermore, the monthly power generation attribute K of the same statistical indicator is calculated based on the daily power generation attribute. M , and annual power generation attribute K Y The details are as follows: S23, in the platform, configure the indicator set "I * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D Sum the results to form the set M0, M1, M2, M3; S24, in the platform, configure the indicator set "I * "Year attribute of a certain indicator" K Y ”:K Y = Current year attribute K D The sum is calculated and the results form the set N0, N1, N2, and N3.

[0012] Furthermore, the indicator set "I" corresponding to a power plant or a period in the organizational set H0 is configured according to the sets O0, O1, O2, and O3. * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D The sum of the calculation results forms the set P0, P1, P2, P3; the indicator set "I * "Year attribute of a certain indicator" K Y ”:K Y = Current year attribute K D The sum is calculated and the results form the set Q0, Q1, Q2, and Q3.

[0013] Compared with the prior art, the present invention has at least the following beneficial effects: the present invention calculates the specific power generation value of each load interval by applying an acquisition method based on the load interval distribution of the power generation of thermal power units, which can systematically evaluate the operating performance of the power generation unit, and adjust its operating strategy according to the current actual operating status of the unit and the power grid demand, guiding the power generation unit to continuously operate in the optimal state range with the highest efficiency, thereby improving the overall power generation efficiency, effectively reducing various cost consumptions during the operation process, and ultimately achieving the goal of maximizing the economic benefits of the power plant; at the same time, the method and its calculation results can also be used as a real-time monitoring tool for continuously tracking and monitoring the actual operation of the unit, and providing an important auxiliary evaluation means for evaluating the operating level and response ability of the operation duty officer when adjusting the load of the thermal power unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a screenshot of a bar chart showing the power generation percentages in each load range for three power plants in a certain month in a power company's production supervision system. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] The present invention provides a method for obtaining the load interval distribution of the power generation of a thermal power unit, comprising the following steps: S1, collects the real-time data of the on-site generator set monitoring points into the real-time database of the production control area to form a set A0; S2, using the data acquisition interface program deployed on the production control zone interface machine, reading the real-time measurement point data A0 in a zone real-time database through a data transmission protocol to form a set B0; S3, using the data sending software deployed on the production control zone interface machine to read the set B0 from the data acquisition interface program and send it to the virtual IP of the data transmission server in the management information zone in the horizontal isolation device to form a set C0; the horizontal isolation device is deployed between the production control zone and the management information zone and is used for realizing one-way data transmission in a non-network mode (physical isolation); according to the data communication direction, the power special horizontal one-way security isolation device is divided into a forward type and a reverse type. The forward security isolation device is used for one-way data transmission in a non-network mode from the production control zone to the management information zone. The example described in the present application adopts the forward type horizontal isolation device.

[0017] S4, using the data receiving software deployed in the data transmission server in the management information zone to read the set C0 from the virtual IP of the production control zone interface machine in the horizontal isolation device and store it into the real-time database in the management information zone to form a set D0; S5, using the data reading software deployed in the application server in the management information zone to read the set D0 in the real-time database to form a set E0; S6, reading the real-time measurement point data set E0 through the measurement point service adapted by the data governance platform and storing it in the platform backend to form a set F0; S7, using the measurement point governance function in the data governance software to perform data preprocessing on the set F0 by setting the high and low limit values of the measurement point data or self-defined data processing rules to form a set G0; S8, according to the actual situation of the application unit, establishing an organization relationship in the data governance platform, such as a group company level, a regional company level, a basic enterprise level, a period level, a unit level and the like, to finally form a set H0; S9, according to the actual needs of the application unit in management and assessment, establishing statistical indexes in the platform, for example, 30% below load power generation, 30%-40% load power generation, 40%-50% load power generation, 50%-75% load power generation, 75% above load power generation and total power generation, to form sets I0, I1, I2, I3, I4 and I5; S10, establishing a measurement point judgment condition in the platform: real-time load <30% unit installed capacity, 30% unit installed capacity ≤ real-time load <40% unit installed capacity, 40% unit installed capacity ≤ real-time load <50% unit installed capacity, 50% unit installed capacity ≤ real-time load <75% unit installed capacity and 75% unit installed capacity ≤ real-time load to form sets J0, J1, J2, J3 and J4; S11, configure the "day", "month", "year" attributes of the certain unit index "I * " (I0, I1, I2, I3, I4, I5) in the organization set H0 in the platform, forming sets K D , K M , K Y ; for example, establish a unit-level power generation index, which has three attributes of day, month, and year, representing the daily, monthly, and annual power generation of the unit level respectively; S12, set the conditions for judging the normal operation of the unit in the platform, mainly the target values of the four indexes of main steam temperature, main steam pressure, turbine speed, and generator load, forming sets R1, R2, R3, R4; S13, in G0, find the real-time measuring points corresponding to the above four indexes, forming sets S1, S2, S3, S4; S14, compare sets R1, R2, R3, R4 with sets S1, S2, S3, S4, when the real-time measuring point values in the judgment conditions meet the target values at the same time, it can be judged that the unit state is normal operation, and the subsequent calculation can be carried out; S15, in the platform, configure the calculation logic of the "K D " attribute of the certain unit "index 30% below load power generation" in the organization set H0: when the data set "G0" meets the "J0" condition on the statistical day, integrate and accumulate the data set "G0", forming set "L0"; S16, in the platform, configure the calculation logic of the "K D " attribute of the certain unit "30%~40% load power generation" in the organization set H0: when the data set "G0" meets the "J1" condition on the statistical day, integrate and accumulate the data set "G0", forming set "L1"; S17, in the platform, configure the calculation logic of the "K D " attribute of the certain unit "40%~50% load power generation" in the organization set H0: when the data set "G0" meets the "J2" condition on the statistical day, integrate and accumulate the data set "G0", forming set "L2"; S18, in the platform, configure the calculation logic of the "K D " attribute of the certain unit "50%~75% load power generation" in the organization set H0: when the data set "G0" meets the "J3" condition on the statistical day, integrate and accumulate the data set "G0", forming set "L3"; S19, in the platform, configure the calculation logic of the "K DThe calculation logic of ": when the data set "G0" meets the "J4" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L4"; S20, in the platform, configure the "total power generation" attribute "K D The calculation logic of ": on the statistical day, the data set "G0" is integrated and accumulated to form the set "L5"; S21, for the set “K D " is verified. If the conditions are met: L5-(L1+L2+L3+L4)<=T0, where T0 is the threshold set by the user based on the actual situation on site, the calculation is considered correct. S22, because there may be a certain data delay in on-site network transmission or data collection, set the attribute "K D " is calculated as the previous day's data automatically calculated at 2:00 a.m. the next day; S23, in the platform, configure the indicator set "I * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D Sum the results to form the set M0, M1, M2, M3; S24, in the platform, configure the indicator set "I * "Year attribute of a certain indicator" K Y ”:K Y = Current year attribute K D Sum the results to form sets N0, N1, N2, and N3; S25, in the platform, configure the indicator set "I * "Daily attribute of a certain indicator" K D ”:K D = Daily attribute K of thermal power units under the organization D Sum the results to form the set O0, O1, O2, O3; S26, in the platform, configure the indicator set "I * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D Sum the results to form the set P0, P1, P2, P3; S27, in the platform, configure the indicator set "I * "Year attribute of a certain indicator" K Y":K Y =yearly day attribute K D summed, the results forming the sets Q0, Q1, Q2, Q3.

[0018] As an embodiment, on the basis of the method described in the application, a front-end page is developed and designed, data is queried and exported according to the organizational structure dimension and the time dimension, and according to the requirements of users on the interface and functions, the power generation data of the unit level and the power plant level are displayed.

[0019] The method for obtaining the load interval distribution of the power generation of the thermal power unit has been tested in a supervision project of a power group branch, realizes automatic calculation on a smart supervision platform, and becomes an important means for the production management department to supervise the thermal power plant and carry out performance evaluation. Taking a regional company headquarters as an example, the implementation mode of the method is introduced as follows: 1) Collect and access the real-time production data of each subordinate power generation enterprise, and store them into the branch real-time database.

[0020] 2) The statistical program extracts historical data from the real-time database for online calculation at 1 o'clock in the morning every day, including: a) Collecting the all-day load archive data of different units on the statistical day; 3) Screening from the original data to remove obviously incorrect or jump data, forming valid data; 4) Classifying the data according to the load interval from the valid load data; 5) Accumulating points from the classified load archive data and storing them into different power measurement points; 6) Taking the maximum value of different power measurement points as the final power generation of the interval on the day, and storing it into the relational database; 7) Displaying on the front-end page.

[0021] Example 1, reference Figure 1 Based on the method described in the application, the user can arbitrarily select a date, query the power generation and its proportion under each load of each thermal power plant subordinate, and display the comparison with the same level power generation unit through a bar chart, which provides a basis for the user to master the overall production of each thermal power plant, provides an objective and effective means for the production management department to carry out the evaluation and benchmarking of the operation and maintenance level of the thermal power plant, and provides detailed and accurate basic data for the operation optimization of the power plant.

[0022] In the embodiment 2, based on the method of the present application, the power generation of each thermal power plant under each load and the proportion of the power generation can be used by the dispatcher in the regional dispatching center at any time. The dispatching center can be used for optimizing the dispatching instruction by analyzing the power generation load interval distribution of each thermal power generating unit in the large area, which can help to realize the optimization of the power grid dispatching in the large area, improve the reliability of the power grid operation, reduce the dispatching pressure, and help to improve the timeliness of the load response of each power generation unit.

[0023] In addition, the power generation load interval distribution of the thermal power generating unit obtained by the method of the present application can also be used for evaluating each power generation unit.

[0024] The present application can evaluate the performance of the power generating unit by calculating the power generation in each load interval based on the method for obtaining the power generation load interval distribution of the thermal power generating unit, adjust the operation strategy according to the actual situation, make the power generating unit operate in the best state, thereby improving the power generation efficiency, reducing the operation cost, and realizing the maximization of the economic benefit. The present application can also be used as an auxiliary means for real-time monitoring the operation of the unit and evaluating the adjustment of the thermal power generating unit by the operation operator.

[0025] The above content is only for illustrating the technical idea of the present application, and cannot limit the protection scope of the present application. Any modification made according to the technical idea of the present application on the basis of the technical scheme falls within the protection scope of the claims of the present application.

Claims

1. A method for obtaining load interval distribution of power generation of thermal power units, characterized in that: The following steps are involved: Establish statistical indicators, which are divided into six levels according to load; establish target values ​​for each level of statistical indicators based on the statistical indicators; Establish organizational relationships according to the organizational hierarchy of the enterprise where the thermal power generating units are located to form an organizational set H0, and configure the six-level statistical indicators of one of the units in the organizational set H0. * "Day", "Month", and "Year" attributes, I * Corresponding to the "day", "month", and "year" attributes, they form a set K D , K M , K Y ; Establish unit-level power generation indicators, namely daily power generation, monthly power generation and annual power generation; Based on the accurate "total power generation" attribute data of the unit, configure the indicator set "I" corresponding to a power plant or a period in the organizational set H0. * "Daily attribute of an indicator in"K D ”, K D = Daily attribute K of thermal power units under the organization D Sum and get the set O0, O1, O2, O3, and configure the index set "I" corresponding to a power plant or a period in the organizational set H0. * "The monthly attribute of an indicator in"K M " and year attribute "K Y ", calculate K by summing up the sets O0, O1, O2, and O3 M and K Y ; Based on the power generation data in the organizational dimension and the time dimension, the load range distribution of the power at the unit level and the power plant level is obtained.

2. The method for obtaining the load interval distribution based on the power generation capacity of thermal power units according to claim 1, characterized in that: Obtaining accurate "total power generation" attribute data for a unit includes the following steps: Preprocessing the real-time data set F0 collected from the on-site generator set by setting upper and lower limits of the measurement point data or setting data processing rules to form the real-time data set G0 of the on-site generator set; setting target values ​​for four indicators for judging the normal operation of the unit; and searching for real-time measurement points corresponding to the four indicators in the real-time data set G0 of the on-site generator set; According to the actual needs of the application units in management and assessment, statistical indicators are established in the data governance platform. According to the load, the statistical indicators are divided into six levels, forming sets I0, I1, I2, I3, I4, and I5. Based on the statistical indicators, the measurement point judgment conditions are established. According to the above six-level statistical indicators of the load, the measurement point judgment conditions are set to form sets J0, J1, J2, J3, J4, and J5. Configure the "day", "month", and "year" attributes of a unit indicator "I0, I1, I2, I3, I4, I5" in the organizational set H0 respectively, and form a set K corresponding to the "day", "month", and "year" attributes respectively. D , K M , K Y ; Establish unit-level power generation indicators, which have three attributes: daily, monthly, and annual, representing the daily power generation, monthly power generation, and annual power generation of the unit level respectively; Conditions for determining normal operation of the unit are set, where the conditions are target values ​​of four indicators: main steam temperature, main steam pressure, turbine speed, and generator load, forming a set R1, R2, R3, and R4; real-time measurement points corresponding to the four indicators are searched in the real-time data set G0 of the on-site generator unit to form a set S1, S2, S3, and S4; sets R1, R2, R3, and R4 are compared with sets S1, S2, S3, and S4, and when the values ​​of the real-time measurement points in the judgment conditions reach the simultaneous target values, the unit status is determined to be normal operation; Configure the calculation logic for the statistical indicator attribute "daily power generation index" of a unit in the organizational set H0. When the real-time data set G0 of the on-site generator unit meets the measurement point judgment conditions J0, J1, J2, J3, J4, and J5 on the statistical day, integrate and accumulate the data set G0 to obtain sets L1, L2, L3, and L4; calculate the monthly power generation attribute K of the same statistical indicator based on the daily power generation attribute. M And the annual power generation attribute K Y ; Configure the "total power generation" attribute "K D The calculation logic of " is: on the statistical day, the data set G0 is integrated and accumulated to form the set L5; D The data is verified and the condition is met: L5-(L1+L2+L3+L4)≤T0, where T0 is the threshold set by the user based on the actual situation on site. In this case, the "total power generation" attribute data of the unit is calculated correctly.

3. The method for obtaining the load interval distribution based on the power generation capacity of thermal power units according to claim 2, characterized in that: Configure the calculation logic for the statistical indicator attribute "Daily Power Generation Index" for a unit in the organizational set H0. When the data set G0 meets the measurement point judgment conditions "J0, J1, J2, J3, J4" on the statistical day, accumulate the points of the data set G0 to form the sets L1, L2, L3, and L4. The details are as follows: Configure the "Indicator load power generation below 30%" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J0" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L0"; Configure the "30%~40% load power generation" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J1" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L1"; Configure the "40%~50% load power generation" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J2" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L2"; Configure the "50%~75% load power generation" attribute of a unit in the organization set H0. D The calculation logic of ": when the data set "G0" meets the "J3" condition on the statistical day, the data set "G0" is integrated and accumulated to form the set "L3"; Configure the "Indicator load power generation above 75%" attribute of a unit in the organization set H0. D The calculation logic of " is: when the data set "G0" meets the "J4" condition on the statistical day, the data set G0 is integrated and accumulated to form the set L4.

4. The method for obtaining the load interval distribution based on the power generation capacity of thermal power units according to claim 2, characterized in that: The statistical indicators include power generation at loads below 30%, power generation at loads between 30% and 40%, power generation at loads between 40% and 50%, power generation at loads between 50% and 75%, power generation at loads above 75%, and total power generation.

5. The method for obtaining the load interval distribution based on the power generation of thermal power units according to claim 4, characterized in that: The measurement point judgment conditions include: real-time load < 30% of the installed capacity, 30% of the installed capacity ≤ real-time load < 40% of the installed capacity, 40% of the installed capacity ≤ real-time load < 50% of the installed capacity, 50% of the installed capacity ≤ real-time load < 75% of the installed capacity, and 75% of the installed capacity ≤ real-time load.

6. The method for obtaining load interval distribution based on power generation of thermal power units according to claim 1, characterized in that: The organizational structure relationships are specifically: group company level, regional company level, grassroots enterprise level, period level, and unit level, ultimately forming the set H0.

7. The method for obtaining load interval distribution based on power generation of thermal power units according to claim 1, characterized in that: Set the property "K D " is calculated automatically at 2:00 a.m. the next day based on the previous day's data.

8. The method for obtaining load interval distribution based on power generation of thermal power units according to claim 1, characterized in that: Calculate the monthly power generation attribute K of the same statistical indicator based on the daily power generation attribute M , and annual power generation attribute K Y The details are as follows: In the platform, configure the indicator set "I" corresponding to a unit in the organizational set H0. * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D Sum the results to form the set M0, M1, M2, M3; In the platform, configure the indicator set "I" corresponding to a unit in the organizational set H0. * "Annual attribute of a certain indicator" K Y ”:K Y = Current year attribute K D The sum is calculated and the results form the set N0, N1, N2, and N3.

9. The method for obtaining load interval distribution based on power generation of thermal power units according to claim 1, characterized in that: According to the sets O0, O1, O2, and O3, configure the indicator set "I" corresponding to a power plant or a period in the organizational set H0. * "Monthly attribute of a certain indicator" K M ”:K M = attribute K of the current month and day D The sum of the calculation results forms the set P0, P1, P2, P3; the indicator set "I" corresponding to a power plant or a period in the configuration organization set H0 * "Annual attribute of a certain indicator" K Y ”:K Y = Current year attribute K D The sum is calculated and the results form the set Q0, Q1, Q2, and Q3.

10. The method for obtaining the load interval distribution based on the power generation of thermal power units according to any one of claims 1 to 9, characterized in that: The obtained data of different power generation load intervals of thermal power units are used to evaluate the operation quality of each power generation unit and the economic performance indicators of each power generation unit.

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