Method, system, equipment and medium for measuring and calculating heating load and cooling load

Abstract

The invention discloses a method, a system and equipment for measuring and calculating a heating load and a cooling load, and a medium, and belongs to the technical field of load identification. According to the method, the relationship between the load and the air temperature under different industrial characteristics can be effectively mined by fitting the historical load data and the historical air temperature data, and the characteristics of the load and the air temperature can be more highlighted through the baseline load value and the critical temperature value; summer fitting load data, winter fitting load data, a cooling load proportion and a heating load proportion are calculated in combination with actually measured load data and actually measured air temperature data, the influence of air temperature on the load data itself can be fully considered, and adjustment is carried out according to the cooling load proportion and the heating load proportion; the method can avoid the excessive deviation between the heating load and the cooling load and the actual condition, can solve the technical problem of low accuracy of measuring and calculating the heating load and the cooling load in the prior art, and improves the accuracy of the cooling load and the heating load.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of load identification, and particularly relates to a heating load and cooling load calculation method, system, device and medium. BACKGROUND

[0002] With the popularity of new energy grid connection and distributed power supply equipment, the load characteristics of the current power system present diversity and randomness. The most prominent power load at present is heating load and cooling load. The heating load refers to the heat load required for maintaining indoor temperature through temperature regulating equipment (such as air conditioning heating, electric heating, boiler, etc.). The cooling load refers to the additional power load generated when temperature regulating equipment (such as air conditioning refrigeration, electric fan, etc.) is concentratedly used. The heating load accounts for a large proportion in the winter load demand of the power system, while the cooling load accounts for a large proportion in the summer load demand of the power system, which jointly determines the additional power demand of the power system during summer and winter. Therefore, the calculation of heating load and cooling load can provide a basis for power dispatching and power resource allocation of the power system in winter and summer.

[0003] At present, the calculation of heating load and cooling load mainly includes time series analysis method and load curve comparison method. The time series analysis method is to analyze the seasonality, trend and periodicity of load data through time series analysis of historical load data, and finally identify and separate the cooling load and heating load. The load curve comparison method is to select the typical load curve of spring and autumn as the basic load curve, and calculate the difference between the actual load curve and the basic load curve as the cooling load and heating load. However, the load curve comparison method ignores the temperature fluctuations in different periods, resulting in low calculation accuracy of cooling load and heating load. The time series analysis method excessively focuses on the influence of load data itself and ignores the influence of other external factors, also resulting in low calculation accuracy of cooling load and heating load. Therefore, there is an urgent need for a heating load and cooling load calculation method, system, device and medium to solve the defects of the prior art. SUMMARY

[0004] The present application aims to provide a heating load and cooling load calculation method, system, device and medium to solve the technical problem of low accuracy of heating load and cooling load calculation in the prior art. By constructing a load-temperature relationship curve, the heating load and cooling load are calculated in combination with the baseline load value, critical temperature value, cooling load proportion and heating load proportion, thereby improving the accuracy of heating load and cooling load.

[0005] To solve the above technical problems, the present application embodiment provides a heating load and cooling load calculation method, comprising:

[0006] Obtaining historical load data, historical temperature data, measured load data and measured temperature data of a to-be-measured calculation region;

[0007] Fitting the historical load data and the historical temperature data to obtain a load-temperature relationship curve, a baseline load value and a critical temperature value of each industry in the to-be-measured calculation region;

[0008] Based on the load-temperature relationship curve and the critical temperature value, combined with the measured load data and the measured temperature data, summer fitting load data and winter fitting load data of each industry in the to-be-measured calculation region are obtained;

[0009] Based on the summer fitting load data, the winter fitting load data and the baseline load value, a cooling load ratio and a heating load ratio of each industry in the to-be-measured calculation region are determined;

[0010] Based on the cooling load ratio and the heating load ratio of each industry in the to-be-measured calculation region, combined with the measured load data, the heating load and the cooling load of the to-be-measured calculation region are obtained.

[0011] It can be understood that, compared with the prior art, the present application can effectively mine the relationship between load and temperature under different industry characteristics by fitting the historical load data and the historical temperature data to obtain the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-measured calculation region. The baseline load value and the critical temperature value can highlight the characteristics of load and temperature. Combined with the measured load data and the measured temperature data to calculate the summer fitting load data, the winter fitting load data, the cooling load ratio and the heating load ratio, the influence of temperature on the load data itself can be fully considered, and the cooling load ratio and the heating load ratio can be adjusted to avoid large deviation between the heating load and the cooling load and the actual value, ensuring the robustness of the heating load and the cooling load, thereby improving the accuracy of the cooling load and the heating load.

[0012] As a preferred scheme, the fitting of the historical load data and the historical temperature data to obtain the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-measured calculation region specifically comprises:

[0013] According to the preset industry category and the date category, the historical load data and the historical temperature data are processed to obtain historical working day daily average load data, historical working day daily maximum temperature data, historical working day daily minimum temperature data, historical non-working day daily average load data, historical non-working day daily maximum temperature data and historical non-working day daily minimum temperature data of each industry in the to-be-measured calculation region;

[0014] fitting the historical weekday average daily load data, the historical weekday daily maximum temperature data, the historical weekday daily minimum temperature data, the historical non-weekday average daily load data, the historical non-weekday daily maximum temperature data, and the historical non-weekday daily minimum temperature data, a load-temperature relationship curve of each industry in the to-be-tested calculation region is obtained;

[0015] Based on the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-tested calculation region are calculated.

[0016] The preferred embodiment divides the historical load data and the historical temperature data by industry category and date category (weekdays and non-weekdays), which can separate the load characteristics between different industries, weekdays and non-weekdays, eliminate the interference of data mixing, and thus capture more accurate characteristic relationship between load and temperature, thereby improving the accuracy of the load-temperature relationship curve, the baseline load value and the critical temperature value, and further improving the accuracy of the subsequent calculation of the cooling load and the heating load.

[0017] As a preferred embodiment, the fitting of the historical weekday average daily load data, the historical weekday daily maximum temperature data, the historical weekday daily minimum temperature data, the historical non-weekday average daily load data, the historical non-weekday daily maximum temperature data, and the historical non-weekday daily minimum temperature data to obtain the load-temperature relationship curve of each industry in the to-be-tested calculation region specifically includes:

[0018] According to the historical weekday average daily load data and the historical weekday daily maximum temperature data, a weekday load-daily maximum temperature scatter plot of each industry is constructed;

[0019] According to the historical weekday average daily load data and the historical weekday daily minimum temperature data, a weekday load-daily minimum temperature scatter plot of each industry is constructed;

[0020] According to the historical non-weekday average daily load data and the historical non-weekday daily maximum temperature data, a non-weekday load-daily maximum temperature scatter plot of each industry is constructed;

[0021] According to the historical non-weekday average daily load data and the historical non-weekday daily minimum temperature data, a non-weekday load-daily minimum temperature scatter plot of each industry is constructed;

[0022] Based on a preset nonlinear least squares method, a piecewise quadratic function is used to respectively perform curve fitting on each of the weekday load-daily maximum temperature scatter plots, and a weekday load-daily maximum temperature relationship curve of each industry in the to-be-tested calculation region is obtained.

[0023] Based on the preset nonlinear least squares method, a segmented quadratic function is used to perform curve fitting on each of the non-working day load maximum temperature scatter plot, to obtain a non-working day load maximum temperature relationship curve of each industry in the to-be-calculated region.

[0024] Based on the preset nonlinear least squares method, a segmented quadratic function is used to perform curve fitting on each of the working day load minimum temperature scatter plot, to obtain a working day load minimum temperature relationship curve of each industry in the to-be-calculated region.

[0025] Based on the preset nonlinear least squares method, a segmented quadratic function is used to perform curve fitting on each of the non-working day load minimum temperature scatter plot, to obtain a non-working day load minimum temperature relationship curve of each industry in the to-be-calculated region.

[0026] Based on the working day load maximum temperature relationship curve, the non-working day load maximum temperature relationship curve, the working day load minimum temperature relationship curve and the non-working day load minimum temperature relationship curve of each industry in the to-be-calculated region, as the load temperature relationship curve of each industry in the to-be-calculated region.

[0027] The preferred scheme can capture the correlation between load and temperature from different angles by constructing different scatter plots and selecting a segmented quadratic function as a fitting function, and performing optimal parameter fitting by using a nonlinear least squares method, so that the obtained load temperature relationship curve can more accurately describe the complex characteristics of load changes with temperature for different industries under different date categories, thereby providing an accurate basis for subsequent identification of baseline load values and critical temperature values, and further improving the accuracy of subsequent calculation of cooling load and heating load.

[0028] As a preferred scheme, based on the load temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region are calculated, specifically including:

[0029] Based on the minimum point in the working day load maximum temperature relationship curve of each industry in the to-be-calculated region, a first working day baseline load value and a working day critical maximum temperature value of each industry in the to-be-calculated region are determined.

[0030] Based on the minimum point in the non-working day load maximum temperature relationship curve of each industry in the to-be-calculated region, a first non-working day baseline load value and a non-working day critical maximum temperature value of each industry in the to-be-calculated region are determined.

[0031] Based on the minimum point in the working day load minimum temperature relationship curve of each industry in the to-be-calculated region, a second working day baseline load value and a working day critical minimum temperature value of each industry in the to-be-calculated region are determined.

[0032] determining a second non-working day baseline load value and a non-working day critical minimum temperature value of each industry in the to-be-calculated region based on a minimum point in the non-working day load-minimum temperature relationship curve of each industry in the to-be-calculated region;

[0033] taking the first working day baseline load value, the first non-working day baseline load value, the second working day baseline load value and the second non-working day baseline load value of each industry in the to-be-calculated region as the baseline load value of each industry in the to-be-calculated region;

[0034] taking the working day critical maximum temperature value, the non-working day critical maximum temperature value, the working day critical minimum temperature value and the non-working day critical minimum temperature value of each industry in the to-be-calculated region as the critical temperature value of each industry in the to-be-calculated region.

[0035] The preferred solution can realize dynamic solving of the baseline load value and the critical temperature value by obtaining the minimum point in the curve, ensure that the baseline load value and the critical temperature value are more in line with the actual situation, and thus improve the accuracy of subsequent heating load and cooling load.

[0036] As a preferred solution, the obtaining of the summer fitting load data and the winter fitting load data of each industry in the to-be-calculated region based on the load-temperature relationship curve and the critical temperature value, in combination with the measured load data and the measured temperature data, specifically includes:

[0037] dividing the measured load data and the measured temperature data to obtain an industry actual load value and an industry actual temperature of each industry in the to-be-calculated region;

[0038] obtaining a season interval and a date category to which the industry actual load value belongs;

[0039] when the season interval to which the industry actual load value belongs is summer, screening the load-temperature relationship curve and the critical temperature value based on the season interval and the date category to obtain a summer load-temperature relationship curve parameter and a critical maximum temperature threshold of each industry;

[0040] calculating the summer fitting load data of each industry in the to-be-calculated region based on the industry actual temperature, the summer load-temperature relationship curve and the critical maximum temperature threshold;

[0041] when the season interval to which the industry actual load value belongs is winter, screening the load-temperature relationship curve and the critical temperature value based on the season interval and the date category to obtain a winter load-temperature relationship curve parameter and a critical minimum temperature threshold of each industry;

[0042] Based on the industry actual air temperature, winter load air temperature relationship curve parameters and critical minimum air temperature threshold, the winter fitting load data of each industry in the to-be-calculated region is calculated.

[0043] The preferred embodiment dynamically performs load fitting through seasonal intervals and date categories, uses a critical maximum temperature threshold in summer and a critical minimum air temperature threshold in winter, so that the summer fitting load and the winter fitting load can more accurately reflect the actual load situation, thereby providing a more realistic data basis for subsequent calculation of cooling load and heating load, and improving the accuracy of the cooling load and the heating load.

[0044] As a preferred embodiment, the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region are determined based on the summer fitting load data, the winter fitting load data and the baseline load value, specifically including:

[0045] When the seasonal interval to which the industry actual load value belongs is summer, the baseline load value is filtered based on the seasonal interval and the date category to obtain the summer baseline load value of each industry;

[0046] The summer fitting load data and the summer baseline load value of each industry are respectively subtracted, and the subtraction result is divided by the summer fitting load data to obtain the cooling load proportion of each industry in the to-be-calculated region;

[0047] When the seasonal interval to which the industry actual load value belongs is winter, the baseline load value is filtered based on the seasonal interval and the date category to obtain the winter baseline load value of each industry;

[0048] The winter fitting load data and the winter baseline load value of each industry are respectively subtracted, and the subtraction result is divided by the winter fitting load data to obtain the heating load proportion of each industry in the to-be-calculated region.

[0049] The preferred embodiment selects different baseline load values based on different seasonal categories, which can improve the accuracy of the cooling load proportion and the heating load proportion, and further improve the accuracy of the subsequent cooling load and heating load.

[0050] As a preferred embodiment, the cooling load and the heating load of the to-be-calculated region are obtained based on the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region and the measured load data, specifically including:

[0051] The cooling load proportion of each industry in the to-be-calculated region is multiplied by the measured load data to obtain the cooling load of each industry in the to-be-calculated region;

[0052] multiply the heating load proportion of each industry in the to-be-measured region with the measured load data respectively, to obtain the heating load of each industry in the to-be-measured region;

[0053] sum the cooling load of each industry in the to-be-measured region, to obtain the cooling load of the to-be-measured region;

[0054] sum the heating load of each industry in the to-be-measured region, to obtain the heating load of the to-be-measured region.

[0055] The preferred embodiment adjusts the cooling load proportion and the heating load proportion, can avoid that the heating load and the cooling load are too large from the actual deviation, ensures the robustness of the heating load and the cooling load, and thus improves the accuracy of the cooling load and the heating load.

[0056] Correspondingly, the embodiment of the present application provides a heating load and cooling load measuring and calculating system, comprising a data acquisition module, a load-air temperature relationship curve fitting module, a fitted load calculation module, a load proportion calculation module and a load measuring and calculating module.

[0057] The data acquisition module is used to acquire historical load data, historical air temperature data, measured load data and measured air temperature data of a to-be-measured region.

[0058] The load-air temperature relationship curve fitting module is used to fit the historical load data and the historical air temperature data, to obtain a load-air temperature relationship curve of each industry in the to-be-measured region, a baseline load value and a critical temperature value.

[0059] The fitted load calculation module is used to acquire summer fitted load data and winter fitted load data of each industry in the to-be-measured region based on the load-air temperature relationship curve and the critical temperature value, in combination with the measured load data and the measured air temperature data.

[0060] The load proportion calculation module is used to determine a cooling load proportion and a heating load proportion of each industry in the to-be-measured region based on the summer fitted load data, the winter fitted load data and the baseline load value.

[0061] The load measuring and calculating module is used to obtain the heating load and the cooling load of the to-be-measured region based on the cooling load proportion and the heating load proportion of each industry in the to-be-measured region, in combination with the measured load data.

[0062] Correspondingly, the embodiment of the present application provides a terminal device, comprising:

[0063] one or more processors;

[0064] a memory, coupled to the processor, storing one or more programs;

[0065] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for calculating heating load and cooling load as described above.

[0066] Correspondingly, the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for calculating heating load and cooling load as described above. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 A step flow chart of the method for calculating heating load and cooling load provided by the embodiment of the present application;

[0068] Figure 2 A schematic diagram of the highest temperature curve of working day load of residential electricity industry provided by the embodiment of the present application;

[0069] Figure 3 A schematic diagram of the lowest temperature curve of working day load of residential electricity industry provided by the embodiment of the present application;

[0070] Figure 4 A structural schematic diagram of the system for calculating heating load and cooling load provided by the embodiment of the present application. DETAILED DESCRIPTION

[0071] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

[0072] Embodiment one

[0073] In order to solve the technical problem of low accuracy of heating load and cooling load calculation in the prior art, please refer to Figure 1 , Figure 1 The step flow chart of the method for calculating heating load and cooling load provided by the embodiment of the present application comprises steps S101 to S105.

[0074] Step S101: obtaining historical load data, historical temperature data, measured load data and measured temperature data of a region to be calculated.

[0075] In an optional embodiment, the sensor is set to collect the air temperature value and the electricity load data every 15 minutes, a total of 96 points, and collect the air temperature value of the to-be-calculated region in the past two years to obtain historical air temperature data, further collect the electricity load data of the to-be-calculated region in the past two years to obtain historical load data, collect the air temperature value of the to-be-calculated region in the current calculation day to obtain measured load data, and collect the electricity load data of the to-be-calculated region in the current calculation day to obtain measured load data.

[0076] In an optional embodiment, after obtaining the historical load data, the historical air temperature data, the measured load data and the measured air temperature data of the to-be-calculated region, the missing values of the historical load data, the historical air temperature data, the measured load data and the measured air temperature data can be filled in, and the abnormal values can be processed.

[0077] Step S102: fitting the historical load data and the historical air temperature data to obtain the load-air temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region.

[0078] In this embodiment, the fitting of the historical load data and the historical air temperature data to obtain the load-air temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region specifically includes:

[0079] According to the preset industry category and date category, the historical load data and the historical air temperature data are processed to obtain the historical working day average load data, the historical working day daily maximum air temperature data, the historical working day daily minimum air temperature data, the historical non-working day average load data, the historical non-working day daily maximum air temperature data and the historical non-working day daily minimum air temperature data of each industry in the to-be-calculated region;

[0080] The historical working day average load data, the historical working day daily maximum air temperature data, the historical working day daily minimum air temperature data, the historical non-working day average load data, the historical non-working day daily maximum air temperature data and the historical non-working day daily minimum air temperature data are fitted to obtain the load-air temperature relationship curve of each industry in the to-be-calculated region.

[0081] Based on the load-air temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region are calculated.

[0082] The embodiment can separate the load characteristics of different industries, weekdays and non-weekdays by dividing the historical load data and historical temperature data by industry category and date category (weekdays and non-weekdays), eliminate the interference of mixed data, and thus capture more accurate feature relationship between the load and the temperature, thereby improving the accuracy of the load-temperature relationship curve, the baseline load value and the critical temperature value, and further improving the accuracy of the cooling load and the heating load in subsequent calculation.

[0083] In the embodiment, the historical weekday daily average load data, the historical weekday daily maximum temperature data, the historical weekday daily minimum temperature data, the historical non-weekday daily average load data, the historical non-weekday daily maximum temperature data and the historical non-weekday daily minimum temperature data are fitted to obtain the load-temperature relationship curve of each industry in the to-be-calculated region, and the fitting specifically includes:

[0084] According to the historical weekday daily average load data and the historical weekday daily maximum temperature data, a weekday load maximum temperature scatter plot of each industry is constructed;

[0085] According to the historical weekday daily average load data and the historical weekday daily minimum temperature data, a weekday load minimum temperature scatter plot of each industry is constructed;

[0086] According to the historical non-weekday daily average load data and the historical non-weekday daily maximum temperature data, a non-weekday load maximum temperature scatter plot of each industry is constructed;

[0087] According to the historical non-weekday daily average load data and the historical non-weekday daily minimum temperature data, a non-weekday load minimum temperature scatter plot of each industry is constructed;

[0088] Based on a preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each of the weekday load maximum temperature scatter plots to obtain a weekday load maximum temperature relationship curve of each industry in the to-be-calculated region;

[0089] Based on a preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each of the non-weekday load maximum temperature scatter plots to obtain a non-weekday load maximum temperature relationship curve of each industry in the to-be-calculated region;

[0090] Based on a preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each of the weekday load minimum temperature scatter plots to obtain a weekday load minimum temperature relationship curve of each industry in the to-be-calculated region;

[0091] Based on the preset nonlinear least squares method, a segmented quadratic function is used to respectively perform curve fitting on each of the non-working day load minimum temperature scatter plots, to obtain a non-working day load minimum temperature relationship curve of each industry in the to-be-calculated region.

[0092] Based on the working day load maximum temperature relationship curve, the non-working day load maximum temperature relationship curve, the working day load minimum temperature relationship curve and the non-working day load minimum temperature relationship curve of each industry in the to-be-calculated region, as the load temperature relationship curve of each industry in the to-be-calculated region.

[0093] In this embodiment, by constructing different scatter plots and selecting a segmented quadratic function as a fitting function, and by using a nonlinear least squares method to perform optimal parameter fitting, the correlation between load and temperature is captured from different angles, so that the obtained load temperature relationship curve can more accurately describe the complex characteristics of load changes with temperature for different industries under different date categories, thereby providing an accurate basis for subsequent identification of baseline load values and critical temperature values, and further improving the accuracy of subsequent cooling load and heating load calculations.

[0094] In this embodiment, based on the load temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region are calculated, specifically including:

[0095] Based on the minimum point in the working day load maximum temperature relationship curve of each industry in the to-be-calculated region, a first working day baseline load value and a working day critical maximum temperature value of each industry in the to-be-calculated region are determined;

[0096] Based on the minimum point in the non-working day load maximum temperature relationship curve of each industry in the to-be-calculated region, a first non-working day baseline load value and a non-working day critical maximum temperature value of each industry in the to-be-calculated region are determined;

[0097] Based on the minimum point in the working day load minimum temperature relationship curve of each industry in the to-be-calculated region, a second working day baseline load value and a working day critical minimum temperature value of each industry in the to-be-calculated region are determined;

[0098] Based on the minimum point in the non-working day load minimum temperature relationship curve of each industry in the to-be-calculated region, a second non-working day baseline load value and a non-working day critical minimum temperature value of each industry in the to-be-calculated region are determined;

[0099] The first working day baseline load value, the first non-working day baseline load value, the second working day baseline load value and the second non-working day baseline load value of each industry in the to-be-calculated region are taken as the baseline load value of each industry in the to-be-calculated region.

[0100] The critical maximum temperature value on weekdays, the critical maximum temperature value on non-weekdays, the critical minimum temperature value on weekdays, and the critical minimum temperature value on non-weekdays for each industry in the region to be measured are taken as the critical temperature value for each industry in the region to be measured.

[0101] This embodiment achieves dynamic solution for baseline load and critical temperature values ​​by obtaining the minimum point in the curve, ensuring that the baseline load and critical temperature values ​​are more consistent with the actual situation, thereby improving the accuracy of subsequent calculations on heating and cooling loads.

[0102] In one optional embodiment, the historical daily average load data is obtained by summing and averaging the electricity load values ​​belonging to the same day in the historical load data; the historical daily maximum temperature data is obtained by summing and averaging the temperature values ​​collected by each sensor for the same collection date in the historical temperature data; the historical daily minimum temperature data is obtained by summing and averaging the temperature values ​​collected by each sensor; then, preset industry categories are defined as: primary industry, secondary industry, tertiary industry, and residential electricity consumption, and date categories are defined as: weekdays and non-working days; then, the historical daily minimum temperature data, historical daily maximum temperature data, and historical daily average load data are classified according to industry category and date category to obtain the historical weekday daily average load data, historical weekday daily maximum temperature data, and historical weekday daily minimum temperature data for each industry in the area to be measured. Low temperature data, historical average daily load data for non-working days, historical daily maximum temperature data for non-working days, and historical daily minimum temperature data for non-working days are collected. Then, using temperature on the horizontal axis and load (expressed as power in kW) on the vertical axis, and with each scatter plot data point representing the same collection date, scatter plots of maximum working day load temperature, minimum working day load temperature, maximum working day load temperature, and minimum working day load temperature are plotted for each industry. Next, curve fitting is performed based on a preset nonlinear least squares method and a piecewise quadratic function to obtain the working day load temperature relationship curves, non-working day load temperature relationship curves, working day load temperature relationship curves, and minimum working day load temperature relationship curves for each industry in the area to be measured, thus obtaining the load-temperature relationship curves for each industry in the area to be measured. Further details can be found in the following references. Figure 2 and Figure 3 , Figure 2 This is a schematic diagram of the relationship between weekday load and peak temperature in the residential electricity industry, provided as an embodiment of the present invention. Figure 3 This invention provides a schematic diagram of the relationship between weekday load and minimum temperature in the residential electricity industry; as shown in the embodiment of the invention. Figure 2 and Figure 3As shown, the horizontal axis represents air temperature, and the vertical axis represents load (expressed as power in kW). The blue dots represent the actual load, i.e. Figure 2 and Figure 3 The data consists of historical average daily load data for working days. Using nonlinear least squares method and piecewise quadratic function fitting, a fitted curve can be obtained. The fitted curve is... Figure 2 The middle section shows the relationship between work load and maximum temperature. Figure 3 The curve in the middle represents the relationship between the working day load and the minimum temperature.

[0103] It should be noted that nonlinear least squares (NLS) is a mathematical optimization method used to estimate the parameters of nonlinear models. Its core objective is to find the optimal parameter estimates by minimizing the sum of squared residuals between the observed data and the model's predicted values. A piecewise quadratic function is a function whose domain is defined by combining different quadratic function expressions across different intervals.

[0104] In an optional embodiment, the minimum point is defined as the inflection point of a piecewise quadratic function, that is, the inflection point on the curve of the relationship between load and temperature on weekdays, the curve of the relationship between load and temperature on non-weekdays, the curve of the relationship between load and temperature on weekdays and the curve of the relationship between load and temperature on non-weekdays are their respective minimum points. Since there is a strong correlation between load and temperature in the power system, the inflection point on the curve of the relationship between load and temperature on weekdays, the curve of the relationship between load and temperature on non-weekdays, the curve of the relationship between load and temperature on weekdays and the curve of the relationship between load and temperature on non-weekdays is usually only one for each curve. If there is a curve with at least two inflection points, the inflection point with the smallest ordinate value is taken as the minimum point of that curve.

[0105] Further, the minimum point in the workday load maximum temperature relationship curve of each industry in the to-be-calculated region is obtained, and the abscissa value of the minimum point is taken as the workday critical maximum temperature value of each industry in the to-be-calculated region, and the ordinate value is taken as the first workday baseline load value of each industry in the to-be-calculated region. In this way, the minimum point in the non-workday load maximum temperature relationship curve of each industry in the to-be-calculated region is obtained, and the abscissa value of the minimum point is taken as the non-workday critical maximum temperature value of each industry in the to-be-calculated region, and the ordinate value is taken as the first non-workday baseline load value of each industry in the to-be-calculated region. The minimum point in the workday load minimum temperature relationship curve of each industry in the to-be-calculated region is obtained, and the abscissa value of the minimum point is taken as the workday critical minimum temperature value of each industry in the to-be-calculated region, and the ordinate value is taken as the second workday baseline load value of each industry in the to-be-calculated region. The minimum point in the non-workday load minimum temperature relationship curve of each industry in the to-be-calculated region is obtained, and the abscissa value of the minimum point is taken as the non-workday critical minimum temperature value of each industry in the to-be-calculated region, and the ordinate value is taken as the second non-workday baseline load value of each industry in the to-be-calculated region.

[0106] As shown in Figure 2 and Figure 3 In Figure 2 , the first workday baseline load value of the residential electricity industry obtained based on the minimum point is 1.97e+7 kW, and the workday critical maximum temperature value is 23.71℃; in Figure 3 , the second workday baseline load value of the residential electricity industry obtained based on the minimum point is 2.01e+7 kW, and the workday critical minimum temperature value is 19.82℃.

[0107] Step S103: Based on the load-temperature relationship curve and the critical temperature value, the measured load data and the measured temperature data are combined to obtain the summer fitting load data and the winter fitting load data of each industry in the to-be-calculated region.

[0108] In this embodiment, the summer fitting load data and the winter fitting load data of each industry in the to-be-calculated region are obtained based on the load-temperature relationship curve and the critical temperature value, and the measured load data and the measured temperature data, and specifically include:

[0109] The measured load data and the measured temperature data are divided to obtain the industry actual load value and the industry actual temperature of each industry in the to-be-calculated region.

[0110] The season interval and the date category to which the industry actual load value belongs are obtained.

[0111] When the actual load value of the industry belongs to the summer season, the load-temperature relationship curve and critical temperature value are filtered based on the season and date category to obtain the summer load-temperature relationship curve parameters and critical maximum temperature threshold for each industry.

[0112] Based on the actual temperature of the industry, the summer load-temperature relationship curve, and the critical maximum temperature threshold, calculate the summer fitted load data for each industry in the region to be measured;

[0113] When the actual load value of the industry belongs to the winter season, the load-temperature relationship curve and critical temperature value are filtered based on the season and date category to obtain the winter load-temperature relationship curve parameters and critical minimum temperature threshold for each industry.

[0114] Based on the actual temperature of the industry, the parameters of the winter load-temperature relationship curve, and the critical minimum temperature threshold, the winter fitted load data for each industry in the region to be measured are calculated.

[0115] This embodiment dynamically fits the load by seasonal intervals and date categories. The critical maximum temperature threshold is used in summer, and the critical minimum temperature threshold is used in winter. This makes the fitted load in summer and winter more realistic, thus providing a more accurate data basis for the subsequent calculation of heating and cooling loads, thereby improving the accuracy of heating and cooling loads.

[0116] In an optional embodiment, the measured load data and measured temperature data are divided to obtain the actual industrial load value P for each industry in the area to be measured. 实际,j And the actual temperature of the industry, which includes the actual maximum temperature and the actual minimum temperature of the industry; then obtain the seasonal interval and date category of the actual load value of the industry; the seasonal interval includes summer interval and winter interval, and the date category includes weekday and non-working day;

[0117] When the belonging seasonal interval is summer, the actual highest temperature of the industry is selected as the actual temperature of the industry at this time, and when the belonging seasonal interval is winter, the actual lowest temperature of the industry is selected as the actual temperature of the industry at this time, according to the belonging date category and the belonging seasonal interval, the load temperature relationship curve and the critical temperature value are screened, specifically, the belonging date category is used to screen the fitting curve of whether it is a weekday or a non-working day, if it is a weekday, the corresponding weekday load highest temperature relationship curve and the weekday load lowest temperature relationship curve of the industry are screened first; if it is a non-working day, the corresponding non-working day load highest temperature relationship curve and the non-working day load lowest temperature relationship curve of the industry are screened first; the belonging seasonal interval is used to screen the fitting interval of whether it is the highest temperature or the lowest temperature, if it is summer, the non-working day load highest temperature relationship curve and the weekday load highest temperature relationship curve are screened, if it is winter, the non-working day load lowest temperature relationship curve and the weekday load lowest temperature relationship curve are screened; therefore, according to the belonging seasonal interval and the belonging date category, one relationship curve can be screened from the four relationship curves, and then according to the relationship curve, the corresponding fitting curve function (since the previous step uses the nonlinear least square method for fitting, the fitting curve function parameters can be obtained, which is called summer load temperature relationship curve parameters in summer, and winter load temperature relationship curve parameters in winter) can be obtained, and the temperature value corresponding to the fitting curve load value of the relationship curve (which is called the critical highest temperature threshold in summer, and the critical lowest temperature threshold in winter) is extracted again;

[0118] Further, for the measurement day t and the industry j, in summer, the actual temperature of the industry is set as the actual highest temperature of the industry x 最高 , the critical highest temperature threshold is set as x 临界最高,j , the summer load temperature relationship curve parameters are set as α j and β j ; then compare the actual temperature of the industry x 最高 and the critical highest temperature threshold x 临界最高,j , according to the comparison result, the summer fitting load data P 夏季拟合,j is calculated, and the calculation formula of the summer fitting load data P 夏季拟合,j is as follows:

[0119] P 夏季拟合,j =α j (x-x 临界最高,j ) 2 +β j x 最高 ≥x 临界最高,j ;

[0120] P 夏季拟合,j =P 实际,j x 最高 <x临界最高,j ;

[0121] In winter, the actual industrial air temperature is set as the actual minimum air temperature x 最低 , the critical minimum air temperature threshold is set as x 临界最低j , the winter load air temperature relationship curve parameter is set as γ j and δ j ; then the actual minimum air temperature x 最低 of the industry and the critical minimum air temperature threshold set as x 临界最低j are compared, the winter fitting load data P 冬季拟合,j is calculated according to the comparison result, and the calculation formula of the winter fitting load data P 冬季拟合,j is as follows:

[0122] P 冬季拟合,j = γ j (x-x 临界最低,j ) 2 + δ j x 最低 ≥ x 临界最低,j ;

[0123] P 冬季拟合,j = P 实际,j x 最低 < x 临界最低,j .

[0124] Step S104: determining the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region based on the summer fitting load data, the winter fitting load data and the baseline load value.

[0125] In this embodiment, the determination of the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region based on the summer fitting load data, the winter fitting load data and the baseline load value specifically includes:

[0126] When the season interval to which the actual industrial load value belongs is summer, the baseline load value is filtered based on the season interval and the date category, to obtain the summer baseline load value of each industry;

[0127] The summer fitting load data and the summer baseline load value of each industry are subtracted respectively, and the subtraction result is divided by the summer fitting load data, to obtain the cooling load proportion of each industry in the to-be-calculated region;

[0128] When the season interval to which the actual industrial load value belongs is winter, the baseline load value is filtered based on the season interval and the date category, to obtain the winter baseline load value of each industry;

[0129] The winter fitted load data and the winter baseline load value of each industry are subtracted respectively, and the difference is divided by the winter fitted load data, to obtain the heating load proportion of each industry in the to-be-tested region.

[0130] The embodiment selects different baseline load values based on different seasonal categories, which can improve the accuracy of the cooling load proportion and the heating load proportion, and further improve the accuracy of the subsequent cooling load and heating load.

[0131] In an optional embodiment, as described in the screening of the above optional embodiment, the date category is used to screen the fitted curve of whether it is a weekday or a non-weekday, if it is a weekday, the corresponding weekday load highest temperature relationship curve and the weekday load lowest temperature relationship curve of the industry are screened first; if it is a non-weekday, the corresponding non-weekday load highest temperature relationship curve and the non-weekday load lowest temperature relationship curve of the industry are screened first; the seasonal interval is used to screen the fitted interval of whether it is the highest temperature or the lowest temperature, if it is summer, the non-weekday load highest temperature relationship curve and the weekday load highest temperature relationship curve are screened, if it is winter, the non-weekday load lowest temperature relationship curve and the weekday load lowest temperature relationship curve are screened; therefore, according to the seasonal interval and the date category, one relationship curve can be screened from the four relationship curves, and then according to the relationship curve, the corresponding fitted curve function (since the previous step uses the nonlinear least squares method for fitting, the fitted curve function parameters can be obtained, which are called summer load temperature relationship curve parameters in summer, and winter load temperature relationship curve parameters in winter) can be obtained, and the fitted curve load value of the relationship curve (which is called summer baseline load value in summer, and winter baseline load value in winter) is extracted therefrom;

[0132] Further, the calculation formula of the cooling load proportion is specifically:

[0133]

[0134] The calculation formula of the heating load proportion is:

[0135]

[0136] In the above formula, ω 降温,j is the cooling load proportion of the industry j; P 夏季拟合,j is the summer fitted load data of the industry j; P 夏季基线,j is the summer baseline load value of the industry j; ω 取暖,j is the heating load proportion of the industry j; P 冬季拟合,j is the winter fitted load data of the industry j; P 冬季基线,j is the winter baseline load value of the industry j.

[0137] In an optional embodiment, for the part of the industry, when the temperature is lower, the load-temperature fitting curve is a horizontal straight line, thus, if P 夏季拟合,j is negative, ω 降温,j is set to 0, and if P 冬季拟合,j is negative, ω 取暖,j is set to 0.

[0138] Step S105: Based on the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region, the measured load data is combined to obtain the heating load and the cooling load of the to-be-calculated region.

[0139] In this embodiment, based on the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region, the measured load data is combined to obtain the heating load and the cooling load of the to-be-calculated region, specifically including:

[0140] The cooling load proportion of each industry in the to-be-calculated region is multiplied by the measured load data to obtain the cooling load of each industry in the to-be-calculated region;

[0141] The heating load proportion of each industry in the to-be-calculated region is multiplied by the measured load data to obtain the heating load of each industry in the to-be-calculated region;

[0142] The cooling loads of each industry in the to-be-calculated region are summed to obtain the cooling load of the to-be-calculated region;

[0143] The heating loads of each industry in the to-be-calculated region are summed to obtain the heating load of the to-be-calculated region.

[0144] In this embodiment, the cooling load proportion and the heating load proportion are adjusted, which can avoid that the heating load and the cooling load have a large deviation from the actual value, and ensure the robustness of the heating load and the cooling load, thereby improving the accuracy of the cooling load and the heating load.

[0145] In an optional embodiment, the calculation formula of the cooling load of each industry is specifically:

[0146] P 降温,j = P 实际,j × ω 降温,j ;

[0147] The calculation formula of the heating load of each industry is specifically:

[0148] P 取暖,j = P 实际,j × ω 取暖,j ;

[0149] The cooling load of each industry is summed up to obtain the cooling load P of the region to be calculated 降温 :

[0150] P 降温 =∑P 降温,j ;

[0151] The heating load of each industry is summed up to obtain the heating load P of the region to be calculated 取暖 :

[0152] P 取暖 =∑P 取暖,j .

[0153] The embodiment can effectively mine the relationship between the load and the temperature under the characteristics of different industries by fitting the historical load data and the historical temperature data to obtain the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the region to be calculated, and can highlight the characteristics of the load and the temperature through the baseline load value and the critical temperature value. In combination with the measured load data and the measured temperature data, the summer fitting load data, the winter fitting load data, the cooling load ratio and the heating load ratio are calculated, the influence of the temperature on the load data itself can be fully considered, and the adjustment is made through the cooling load ratio and the heating load ratio, so that the actual deviation of the heating load and the cooling load can be avoided to be too large, the robustness of the heating load and the cooling load is ensured, and the accuracy of the cooling load and the heating load is improved.

[0154] Embodiment two

[0155] Please refer to Figure 4 , Figure 4 The structure diagram of a heating load and cooling load measurement and calculation system provided by the embodiment of the application, comprising: a data acquisition module 201, a load-temperature relationship curve fitting module 202, a fitting load calculation module 203, a load ratio calculation module 204 and a load measurement and calculation module 205.

[0156] The data acquisition module 201 is used to acquire the historical load data, the historical temperature data, the measured load data and the measured temperature data of the region to be calculated.

[0157] The load-temperature relationship curve fitting module 202 is used to fit the historical load data and the historical temperature data to obtain the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the region to be calculated.

[0158] In the embodiment, the load-temperature relationship curve fitting module 202 comprises a load-temperature relationship curve fitting unit.

[0159] The load-air temperature relationship curve fitting unit is configured to process the historical load data and the historical air temperature data according to preset industrial categories and date categories, to obtain historical daily average load data of working days, historical daily maximum air temperature data of working days, historical daily minimum air temperature data of working days, historical daily average load data of non-working days, historical daily maximum air temperature data of non-working days, and historical daily minimum air temperature data of non-working days of each industry in the to-be-tested calculation region;

[0160] The historical daily average load data of working days, the historical daily maximum air temperature data of working days, the historical daily minimum air temperature data of working days, the historical daily average load data of non-working days, the historical daily maximum air temperature data of non-working days, and the historical daily minimum air temperature data of non-working days are fitted to obtain a load-air temperature relationship curve of each industry in the to-be-tested calculation region.

[0161] Based on the load-air temperature relationship curve, a baseline load value and a critical temperature value of each industry in the to-be-tested calculation region are calculated.

[0162] In this embodiment, the load-air temperature relationship curve fitting unit includes a load-air temperature relationship curve fitting subunit.

[0163] The load-air temperature relationship curve fitting subunit is configured to construct a working day load-daily maximum air temperature scatter plot of each industry according to the historical daily average load data of working days and the historical daily maximum air temperature data of working days.

[0164] The load-air temperature relationship curve fitting subunit is configured to construct a working day load-daily minimum air temperature scatter plot of each industry according to the historical daily average load data of working days and the historical daily minimum air temperature data of working days.

[0165] The load-air temperature relationship curve fitting subunit is configured to construct a non-working day load-daily maximum air temperature scatter plot of each industry according to the historical daily average load data of non-working days and the historical daily maximum air temperature data of non-working days.

[0166] The load-air temperature relationship curve fitting subunit is configured to construct a non-working day load-daily minimum air temperature scatter plot of each industry according to the historical daily average load data of non-working days and the historical daily minimum air temperature data of non-working days.

[0167] Based on a preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each working day load-daily maximum air temperature scatter plot, to obtain a working day load-daily maximum air temperature relationship curve of each industry in the to-be-tested calculation region.

[0168] Based on a preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each non-working day load-daily maximum air temperature scatter plot, to obtain a non-working day load-daily maximum air temperature relationship curve of each industry in the to-be-tested calculation region.

[0169] Based on the preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each of the working day load minimum temperature scatter diagrams, to obtain a working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region;

[0170] Based on the preset nonlinear least square method, a piecewise quadratic function is used to perform curve fitting on each of the non-working day load minimum temperature scatter diagrams, to obtain a non-working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region;

[0171] Based on the working day load maximum temperature relationship curve, the non-working day load maximum temperature relationship curve, the working day load minimum temperature relationship curve and the non-working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region, a load temperature relationship curve of each industry in the to-be-measured calculation region is obtained.

[0172] In the embodiment, the load temperature relationship curve fitting unit comprises a baseline load value and critical temperature value calculation subunit.

[0173] The baseline load value and critical temperature value calculation subunit is configured to determine a first working day baseline load value and a working day critical maximum temperature value of each industry in the to-be-measured calculation region based on a minimum value point in the working day load maximum temperature relationship curve of each industry in the to-be-measured calculation region.

[0174] The baseline load value and critical temperature value calculation subunit is configured to determine a first non-working day baseline load value and a non-working day critical maximum temperature value of each industry in the to-be-measured calculation region based on a minimum value point in the non-working day load maximum temperature relationship curve of each industry in the to-be-measured calculation region.

[0175] The baseline load value and critical temperature value calculation subunit is configured to determine a second working day baseline load value and a working day critical minimum temperature value of each industry in the to-be-measured calculation region based on a minimum value point in the working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region.

[0176] The baseline load value and critical temperature value calculation subunit is configured to determine a second non-working day baseline load value and a non-working day critical minimum temperature value of each industry in the to-be-measured calculation region based on a minimum value point in the non-working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region.

[0177] The baseline load value and critical temperature value calculation subunit is configured to determine a second non-working day baseline load value and a non-working day critical minimum temperature value of each industry in the to-be-measured calculation region based on a minimum value point in the non-working day load minimum temperature relationship curve of each industry in the to-be-measured calculation region.

[0178] The critical temperature values of each industry in the to-be-calculated region are obtained by taking the working day critical maximum temperature value, the non-working day critical maximum temperature value, the working day critical minimum temperature value and the non-working day critical minimum temperature value of each industry in the to-be-calculated region as the critical temperature values of each industry in the to-be-calculated region.

[0179] The fitting load calculation module 203 is configured to obtain the summer fitting load data and the winter fitting load data of each industry in the to-be-calculated region based on the load-air temperature relationship curve and the critical temperature values, in combination with the measured load data and the measured air temperature data.

[0180] In this embodiment, the fitting load calculation module 203 includes a fitting load calculation unit.

[0181] The fitting load calculation unit is configured to divide the measured load data and the measured air temperature data to obtain the industrial actual load value and the industrial actual air temperature of each industry in the to-be-calculated region.

[0182] The season interval and the date category to which the industrial actual load value belongs are obtained.

[0183] When the season interval to which the industrial actual load value belongs is summer, the load-air temperature relationship curve and the critical temperature values are screened based on the season interval and the date category to obtain the summer load-air temperature relationship curve parameters and the critical maximum air temperature threshold value of each industry.

[0184] The summer fitting load data of each industry in the to-be-calculated region is calculated based on the industrial actual air temperature, the summer load-air temperature relationship curve and the critical maximum air temperature threshold value.

[0185] When the season interval to which the industrial actual load value belongs is winter, the load-air temperature relationship curve and the critical temperature values are screened based on the season interval and the date category to obtain the winter load-air temperature relationship curve parameters and the critical minimum air temperature threshold value of each industry.

[0186] The winter fitting load data of each industry in the to-be-calculated region is calculated based on the industrial actual air temperature, the winter load-air temperature relationship curve parameters and the critical minimum air temperature threshold value.

[0187] The load proportion calculation module 204 is configured to determine the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region based on the summer fitting load data, the winter fitting load data and the baseline load value.

[0188] In this embodiment, the load proportion calculation module 204 includes a load proportion calculation unit.

[0189] The load ratio calculation unit is configured to, when the seasonal interval to which the industrial actual load value belongs is summer, screen the baseline load value based on the seasonal interval and the date category to obtain a summer baseline load value of each industry;

[0190] The summer fitted load data and the summer baseline load value of each industry are respectively subtracted, and the subtraction result is divided by the summer fitted load data to obtain a cooling load ratio of each industry in the to-be-measured region;

[0191] When the seasonal interval to which the industrial actual load value belongs is winter, the baseline load value is screened based on the seasonal interval and the date category to obtain a winter baseline load value of each industry;

[0192] The winter fitted load data and the winter baseline load value of each industry are respectively subtracted, and the subtraction result is divided by the winter fitted load data to obtain a heating load ratio of each industry in the to-be-measured region.

[0193] The load calculation module 205 is configured to, based on the cooling load ratio and the heating load ratio of each industry in the to-be-measured region, combine the measured load data to obtain the heating load and the cooling load of the to-be-measured region.

[0194] In this embodiment, the load calculation module 205 includes a load calculation unit.

[0195] The load calculation unit is configured to multiply the cooling load ratio of each industry in the to-be-measured region by the measured load data to obtain the cooling load of each industry in the to-be-measured region.

[0196] The heating load ratio of each industry in the to-be-measured region is multiplied by the measured load data to obtain the heating load of each industry in the to-be-measured region.

[0197] The cooling loads of each industry in the to-be-measured region are summed to obtain the cooling load of the to-be-measured region.

[0198] The heating loads of each industry in the to-be-measured region are summed to obtain the heating load of the to-be-measured region.

[0199] The embodiment can effectively mine the relationship between the load and the temperature under different industrial characteristics by fitting historical load data and historical temperature data to obtain the load-temperature relationship curve of each industry in the to-be-tested calculation region, the baseline load value and the critical temperature value, and can highlight the characteristics of the load and the temperature through the baseline load value and the critical temperature value. In combination with the measured load data and the measured temperature data, summer fitting load data, winter fitting load data, cooling load proportion and heating load proportion are calculated, the influence of the temperature on the load data itself can be fully considered, and the cooling load proportion and the heating load proportion are adjusted, so that the actual deviation of the heating load and the cooling load can be avoided, the robustness of the heating load and the cooling load is ensured, and the accuracy of the cooling load and the heating load is improved.

[0200] Embodiment three

[0201] On the basis of the above-mentioned embodiment of the heating load and the cooling load calculation method, the embodiment three of the present application provides a terminal device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the heating load and the cooling load calculation method of the embodiment of the present application is realized.

[0202] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.

[0203] The terminal device can be a desktop computer, a notebook computer, a palm computer and a cloud server, etc. The terminal device can include, but is not limited to, a processor and a memory.

[0204] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The processor is a control center of the terminal device, and connects all parts of the terminal device through various interfaces and lines.

[0205] On the basis of the above-mentioned method embodiment, the computer readable storage medium provided by the embodiment of the application includes a stored computer program, wherein, when the computer program runs, the device where the computer readable storage medium is located is controlled to execute the method for calculating the heating load and the cooling load according to any one of the above-mentioned method embodiments of the application.

[0206] The modules / units integrated in the device / terminal equipment, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of each method embodiment can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable file or some intermediate form, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0207] To sum up, the embodiment of the present application can effectively mine the relationship between load and temperature under different industrial characteristics by fitting historical load data and historical temperature data to obtain the load-temperature relationship curve of each industry in the to-be-tested calculation area, the baseline load value and the critical temperature value, and can highlight the characteristics of load and temperature through the baseline load value and the critical temperature value; in combination with the measured load data and the measured temperature data, summer fitting load data, winter fitting load data, cooling load proportion and heating load proportion are calculated, the influence of temperature on the load data itself can be fully considered, and the robustness of the heating load and the cooling load can be ensured by adjusting the cooling load proportion and the heating load proportion, so that the actual deviation of the heating load and the cooling load is avoided to be too large, thereby improving the accuracy of the cooling load and the heating load.

[0208] The above-described specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application, and it should be understood that the above-described only specific embodiments of the present application, and not used to limit the protection scope of the present application. It is particularly pointed out that, for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for calculating heating load and cooling load, characterized by, The method comprises the following steps: obtaining historical load data, historical temperature data, measured load data and measured temperature data of a to-be-calculated region; fitting the historical load data and the historical temperature data to obtain a load-temperature relationship curve, a baseline load value and a critical temperature value of each industry in the to-be-calculated region; based on the load-temperature relationship curve and the critical temperature value, combining the measured load data and the measured temperature data, obtaining summer fitting load data and winter fitting load data of each industry in the to-be-calculated region; based on the summer fitting load data, the winter fitting load data and the baseline load value, determining the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region; based on the cooling load proportion and the heating load proportion of each industry in the to-be-calculated region, combining the measured load data, obtaining the heating load and the cooling load of the to-be-calculated region.

2. The method for calculating heating load and cooling load as described in claim 1, characterized in that, The fitting of the historical load data and the historical temperature data to obtain the load-temperature relationship curve, the baseline load value and the critical temperature value of each industry in the to-be-calculated region comprises the following steps: processing the historical load data and the historical temperature data according to a preset industry category and a date category to obtain historical daily load data of working days, daily maximum temperature data of working days, daily minimum temperature data of working days, historical daily load data of non-working days, daily maximum temperature data of non-working days and daily minimum temperature data of non-working days of each industry in the to-be-calculated region; fitting the historical daily load data of working days, the daily maximum temperature data of working days, the daily minimum temperature data of working days, the historical daily load data of non-working days, the daily maximum temperature data of non-working days and the daily minimum temperature data of non-working days to obtain the load-temperature relationship curve of each industry in the to-be-calculated region; based on the load-temperature relationship curve, calculating the baseline load value and the critical temperature value of each industry in the to-be-calculated region.

3. The method for calculating heating load and cooling load as described in claim 2, characterized in that, The fitting of the historical daily load data of working days, the daily maximum temperature data of working days, the daily minimum temperature data of working days, the historical daily load data of non-working days, the daily maximum temperature data of non-working days and the daily minimum temperature data of non-working days to obtain the load-temperature relationship curve of each industry in the to-be-calculated region comprises the following steps: constructing a working day load maximum temperature scatter plot of each industry according to the historical daily load data of working days and the daily maximum temperature data of working days; constructing a working day load minimum temperature scatter plot of each industry according to the historical daily load data of working days and the daily minimum temperature data of working days; constructing a non-working day load maximum temperature scatter plot of each industry according to the historical daily load data of non-working days and the daily maximum temperature data of non-working days; constructing a non-working day load minimum temperature scatter plot of each industry according to the historical daily load data of non-working days and the daily minimum temperature data of non-working days; Based on the preset nonlinear least squares method, the piecewise quadratic function is used to fit the curve of each said working day load highest temperature scatter diagram, and the working day load highest temperature relationship curve of each industry in the said to be measured and calculated region is obtained; Based on the preset nonlinear least squares method, the piecewise quadratic function is used to fit the curve of each said non-working day load highest temperature scatter diagram, and the non-working day load highest temperature relationship curve of each industry in the said to be measured and calculated region is obtained; Based on the preset nonlinear least squares method, the piecewise quadratic function is used to fit the curve of each said working day load lowest temperature scatter diagram, and the working day load lowest temperature relationship curve of each industry in the said to be measured and calculated region is obtained; Based on the preset nonlinear least squares method, the piecewise quadratic function is used to fit the curve of each said non-working day load lowest temperature scatter diagram, and the non-working day load lowest temperature relationship curve of each industry in the said to be measured and calculated region is obtained; Based on the working day load highest temperature relationship curve, the non-working day load highest temperature relationship curve, the working day load lowest temperature relationship curve and the non-working day load lowest temperature relationship curve of each industry in the said to be measured and calculated region, the load temperature relationship curve of each industry in the said to be measured and calculated region is obtained.

4. The method for calculating heating load and cooling load as described in claim 3, characterized in that, Based on the minimum point in the working day load highest temperature relationship curve of each industry in the said to be measured and calculated region, the first working day baseline load value and the working day critical highest temperature value of each industry in the said to be measured and calculated region are determined; Based on the minimum point in the non-working day load highest temperature relationship curve of each industry in the said to be measured and calculated region, the first non-working day baseline load value and the non-working day critical highest temperature value of each industry in the said to be measured and calculated region are determined; Based on the minimum point in the working day load lowest temperature relationship curve of each industry in the said to be measured and calculated region, the second working day baseline load value and the working day critical lowest temperature value of each industry in the said to be measured and calculated region are determined; Based on the minimum point in the non-working day load lowest temperature relationship curve of each industry in the said to be measured and calculated region, the second non-working day baseline load value and the non-working day critical lowest temperature value of each industry in the said to be measured and calculated region are determined; The first working day baseline load value, the first non-working day baseline load value, the second working day baseline load value and the second non-working day baseline load value of each industry in the said to be measured and calculated region are taken as the baseline load value of each industry in the said to be measured and calculated region; The working day critical highest temperature value, the non-working day critical highest temperature value, the working day critical lowest temperature value and the non-working day critical lowest temperature value of each industry in the said to be measured and calculated region are taken as the critical temperature value of each industry in the said to be measured and calculated region. Based on the load temperature relationship curve and the critical temperature value, combined with the measured load data and the measured temperature data, the summer fitting load data and the winter fitting load data of each industry in the said to be measured and calculated region are obtained, specifically including:

5. The method for calculating heating load and cooling load as described in claim 4, characterized in that, ​ The measured load data and the measured air temperature data are divided to obtain an industrial actual load value and an industrial actual air temperature of each industry in the to-be-tested calculation region; An interval of a season to which the industrial actual load value belongs and a date category to which the industrial actual load value belongs are obtained; When the interval of the season to which the industrial actual load value belongs is summer, the load-air temperature relationship curve and the critical temperature value are screened based on the interval of the season and the date category to obtain a summer load-air temperature relationship curve parameter and a critical maximum air temperature threshold of each industry; Based on the industrial actual air temperature, the summer load-air temperature relationship curve and the critical maximum air temperature threshold, summer fitting load data of each industry in the to-be-tested calculation region are calculated; When the interval of the season to which the industrial actual load value belongs is winter, the load-air temperature relationship curve and the critical temperature value are screened based on the interval of the season and the date category to obtain a winter load-air temperature relationship curve parameter and a critical minimum air temperature threshold of each industry; Based on the industrial actual air temperature, the winter load-air temperature relationship curve parameter and the critical minimum air temperature threshold, winter fitting load data of each industry in the to-be-tested calculation region are calculated.

6. The method for calculating heating load and cooling load as described in claim 5, characterized in that, The summer fitting load data, the winter fitting load data and the baseline load value are used to determine a cooling load ratio and a heating load ratio of each industry in the to-be-tested calculation region, and the determination specifically includes: When the interval of the season to which the industrial actual load value belongs is summer, the baseline load value is screened based on the interval of the season and the date category to obtain a summer baseline load value of each industry; The summer fitting load data and the summer baseline load value of each industry are subtracted respectively, and the subtraction result is divided by the summer fitting load data to obtain a cooling load ratio of each industry in the to-be-tested calculation region; When the interval of the season to which the industrial actual load value belongs is winter, the baseline load value is screened based on the interval of the season and the date category to obtain a winter baseline load value of each industry; The winter fitting load data and the winter baseline load value of each industry are subtracted respectively, and the subtraction result is divided by the winter fitting load data to obtain a heating load ratio of each industry in the to-be-tested calculation region.

7. The method for calculating heating load and cooling load as described in claim 1, characterized in that, The cooling load ratio and the heating load ratio of each industry in the to-be-tested calculation region are combined with the measured load data to obtain a heating load and a cooling load of the to-be-tested calculation region, and the combination specifically includes: The cooling load ratio of each industry in the to-be-tested calculation region is multiplied by the measured load data to obtain a cooling load of each industry in the to-be-tested calculation region; The heating load ratio of each industry in the to-be-tested calculation region is multiplied by the measured load data to obtain a heating load of each industry in the to-be-tested calculation region; The cooling loads of each industry in the to-be-tested calculation region are summed to obtain a cooling load of the to-be-tested calculation region; The heating loads of each industry in the to-be-tested calculation region are summed to obtain a heating load of the to-be-tested calculation region.

8. A system for measuring and calculating heating and cooling loads, characterized by, The summer fitting load data, the winter fitting load data and the baseline load value are used to determine a cooling load ratio and a heating load ratio of each industry in the to-be-tested calculation region, and the determination specifically includes: When the interval of the season to which the industrial actual load value belongs is summer, the baseline load value is screened based on the interval of the season and the date category to obtain a summer baseline load value of each industry; The summer fitting load data and the summer baseline load value of each industry are subtracted respectively, and the subtraction result is divided by the summer fitting load data to obtain a cooling load ratio of each industry in the to-be-tested calculation region; When the interval of the season to which the industrial actual load value belongs is winter, the baseline load value is screened based on the interval of the season and the date category to obtain a winter baseline load value of each industry; The winter fitting load data and the winter baseline load value of each industry are subtracted respectively, and the subtraction result is divided by the winter fitting load data to obtain a heating load ratio of each industry in the to-be-tested calculation region. The cooling load ratio and the heating load ratio of each industry in the to-be-tested calculation region are combined with the measured load data to obtain a heating load and a cooling load of the to-be-tested calculation region, and the combination specifically includes: The cooling load ratio of each industry in the to-be-tested calculation region is multiplied by the measured load data to obtain a cooling load of each industry in the to-be-tested calculation region; The heating load ratio of each industry in the to-be-tested calculation region is multiplied by the measured load data to obtain a heating load of each industry in the to-be-tested calculation region; The cooling loads of each industry in the to-be-tested calculation region are summed to obtain a cooling load of the to-be-tested calculation region; The heating loads of each industry in the to-be-tested calculation region are summed to obtain a heating load of the to-be-tested calculation region. The data acquisition module, the load-air temperature relationship curve fitting module, the fitted load calculation module, the load proportion calculation module and the load measurement module; The data acquisition module is configured to acquire historical load data, historical air temperature data, measured load data and measured air temperature data of a region to be measured and calculated; The load-air temperature relationship curve fitting module is configured to fit the historical load data and the historical air temperature data to obtain a load-air temperature relationship curve, a baseline load value and a critical temperature value of each industry in the region to be measured and calculated; The fitted load calculation module is configured to acquire summer fitted load data and winter fitted load data of each industry in the region to be measured and calculated based on the load-air temperature relationship curve and the critical temperature value, in combination with the measured load data and the measured air temperature data; The load proportion calculation module is configured to determine a cooling load proportion and a heating load proportion of each industry in the region to be measured and calculated based on the summer fitted load data, the winter fitted load data and the baseline load value; The load measurement module is configured to obtain the heating load and the cooling load of the region to be measured and calculated based on the cooling load proportion and the heating load proportion of each industry in the region to be measured and calculated, in combination with the measured load data.

9. A terminal device, comprising: The computer program is executed by the processor to implement the method for measuring and calculating the heating load and the cooling load according to any one of claims 1 to 7. The computer program is executed by the processor to implement the method for measuring and calculating the heating load and the cooling load according to any one of claims 1 to 7. ​ ​ 10. A computer-readable storage medium having stored thereon a computer program, characterized in that, ​

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