CN110738380A - Thermal load control method, device and system - Google Patents
Thermal load control method, device and system Download PDFInfo
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Abstract
The invention discloses heat load control methods, devices and systems, wherein the method comprises the steps of obtaining a climate grade, a room temperature set value, a room temperature reference value and historical data before the corresponding moment of the current environment, wherein the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, predicting a heat load to be provided in the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, and adjusting an actual heat load value according to the predicted value.
Description
Technical Field
The invention relates to the field of heating, in particular to heat load control methods, devices and systems.
Background
In addition, , the heat supply industry has the characteristics of high energy consumption, high emission, high investment and low efficiency, namely three high low, multivariable systems closely related to the change of the weather are adopted as the heat supply system, the working condition of the system operation is very complex, the traditional load prediction mode basically predicts the area, the heat preservation coefficient and the weather condition of a building, the deviation of the result obtained by the theoretical calculation of heating ventilation and the actual condition is very large, the energy waste is caused, the amount of heat to be supplied to residents at different temperatures every day is , no accurate quantitative analysis methods exist, and a scientific and practical heat supply operation management means is lacked, so that the heat consumption on the same day is predicted through the room temperature, the climate grade and the historical operation data of the user, the indoor temperature of the user is automatically regulated and controlled, and accurate control of heat supply is realized.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides heat load control methods, devices and systems, which are used for at least solving the technical problem of low accuracy of a heat load control quantitative analysis method in the related art.
According to aspects of the embodiment of the invention, the heat load control method is characterized by comprising the steps of obtaining a climate grade and a room temperature set value under the current environment and historical data before the current environment corresponds to the current environment, predicting a heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, and adjusting an actual heat load value according to the predicted value, wherein the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value.
Optionally, the obtaining the climate grade in the current environment includes: acquiring the forecast temperature, radiation condition and wind speed in the current environment; correcting the forecasted temperature according to the radiation condition and the wind speed to obtain the climate temperature; and determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relation between the climate temperature and the climate grade.
Optionally, before determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relationship between the climate temperature and the climate grade, the method further includes: determining the corresponding temperature difference between two adjacent climate grades; and determining the corresponding relation between the climate temperature and the climate grade according to the temperature difference.
Optionally, predicting the thermal load to be provided in the current environment according to the climate level, the room temperature setting value, and the historical data, and obtaining a predicted value includes: acquiring a room temperature set value under the current environment; according to the room temperature set value, searching whether historical heat load data meeting the following preset conditions exist in the historical data, wherein the preset conditions comprise: the historical climate grade is the same as the climate grade under the current environment, and the difference between the historical room temperature reference value and the historical room temperature set value is within a preset difference range; and under the condition that the conditions are all found to be met, taking the found historical heat load data as the predicted value.
Optionally, after finding whether historical heat load data meeting the following predetermined conditions exists in the historical data, the method further includes, when meeting the predetermined conditions is found, acquiring historical heat load data meeting the predetermined conditions, adjusting historical heat load data meeting the predetermined conditions, and taking the adjusted heat load data as the predicted value.
Optionally, the adjusting the historical thermal load data meeting the predetermined condition includes determining a difference amplitude of a parameter corresponding to the predetermined condition that is not met, obtaining an adjustment amount corresponding to the determined difference amplitude according to a corresponding relationship between the difference amplitude and the adjustment amount, and adjusting historical thermal load data meeting the predetermined condition according to the adjustment amount.
Optionally, after finding whether historical heat load data meeting the following preset conditions exist in the historical data, the method further includes finding out optimal historical data from the historical data under the condition that the conditions are not met, wherein the optimal historical data includes the historical data with the smallest difference between a historical room temperature reference value and a historical room temperature set value and the smallest difference between a historical climate grade and a climate grade under the current environment, adjusting the historical heat load data corresponding to the optimal historical data according to the difference between the historical room temperature reference value and the historical room temperature set value to obtain th adjustment data, and adjusting the th adjustment data according to the difference between the historical climate grade and the climate grade under the current environment to obtain the predicted value.
Optionally, after the actual thermal load value is adjusted according to the predicted value, the method further includes: determining the highest threshold and the lowest threshold of the room temperature reference value under the current environment; screening a plurality of collected room temperature reference values according to the highest threshold and the lowest threshold to obtain the room temperature reference value in the current environment; and storing the room temperature reference value, the climate grade, the room temperature set value and the actual thermal load value obtained after the actual thermal load value is adjusted according to the predicted value under the current environment as historical data.
Optionally, adjusting the actual thermal load value according to the predicted value includes: dividing the time period for adjustment to obtain a divided time period; and adjusting the actual heat load in the divided time period according to the predicted value in the divided time period.
According to aspects of the embodiment of the invention, heat load control devices are provided, and the heat load control devices comprise an obtaining module, a prediction module and an adjusting module, wherein the obtaining module is used for obtaining a climate grade, a room temperature set value and historical data before the current environment corresponding to the current environment, the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, the prediction module is used for predicting a heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, and the adjusting module is used for adjusting an actual heat load value according to the predicted value.
According to aspects of the embodiment of the invention, heat load control systems are provided, and the heat load control systems comprise a wireless router, a Programmable Logic Controller (PLC), a heat meter and an electric regulating valve , wherein the wireless router is used for obtaining a weather forecast under the current environment, the weather forecast is used for determining a climate grade under the current environment, the Programmable Logic Controller (PLC) is used for storing historical data before the corresponding moment of the current environment and predicting a heat load to be provided under the current environment according to the climate grade, a room temperature set value and the historical data to obtain a predicted value, the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, the heat meter is used for collecting an actual heat load value under the current environment, and the electric regulating valve is used for regulating the actual heat load value according to the predicted value.
In the embodiment of the invention, a mode of predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data is adopted, wherein the historical data comprises the historical climate grade, the historical room temperature reference value, the historical room temperature set value and the historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, a predicted value is obtained, the actual heat load value is adjusted according to the predicted value, the regulation and control of the indoor temperature of a user are achieved, and the purpose of accurately controlling the heating energy consumption is achieved, so that the technical effects of heat load control quantitative analysis methods with higher accuracy are provided, and the technical problem of low accuracy of the heat load control quantitative analysis methods in the related technologies is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and constitute a part of this application , illustrate embodiments of the invention and together with the description serve to explain the invention without limiting it.
FIG. 1 is a flow chart of thermal load control methods according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the system architecture components in accordance with a preferred embodiment of the present invention;
FIG. 3 is a schematic diagram of a room temperature calculation mode according to a preferred embodiment of the present invention;
FIG. 4 is a schematic diagram of a climate grade calculation mode according to a preferred embodiment of the present invention;
FIG. 5 is a schematic diagram of the thermal load prediction principle according to a preferred embodiment of the present invention;
FIG. 6 is a flow chart of a method of thermal load prediction according to a preferred embodiment of the present invention;
FIG. 7 is a schematic illustration of a predictive heat load distribution in accordance with a preferred embodiment of the present invention;
FIG. 8 is a schematic diagram of thermal load control devices according to an embodiment of the invention;
FIG. 9 is a schematic diagram of thermal load control systems according to an embodiment of the invention.
Detailed Description
For those skilled in the art to better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a partial embodiment of of the present invention, rather than a complete embodiment.
Furthermore, the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a series of steps or elements of is not necessarily limited to the expressly listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present invention, there are provided embodiments of a method of thermal load control, it being noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as sets of computer executable instructions and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flow chart of thermal load control methods according to an embodiment of the invention, as shown in fig. 1, the method comprising the steps of:
step S102, acquiring a climate grade and a room temperature set value under the current environment and historical data before the corresponding moment of the current environment, wherein the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value;
step S104, predicting the thermal load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value;
and step S106, adjusting the actual thermal load value according to the predicted value.
Through the steps, the climate grade, the room temperature set value and the historical data before the corresponding moment of the current environment are obtained, wherein the historical data comprise the historical climate grade, the historical room temperature reference value, the historical room temperature set value and the historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, the predicted value is obtained by predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data, the purpose of regulating and controlling the indoor temperature of the user and realizing accurate control of heating energy consumption is achieved by adjusting the actual heat load value according to the predicted value, and therefore the technical effect of providing heat load control quantitative analysis methods with higher accuracy is achieved, and the technical problem that the heat load control quantitative analysis methods in the related technology are low in accuracy is solved.
In the embodiment, the influence of the weather grade and the room temperature set value on the heat load is considered at the same time, the weather grade, the room temperature set value and historical data before the corresponding moment of the current environment are obtained, specifically, the heat load under the condition the same as or close to the current weather grade and the room temperature set value is searched from the historical data through the current weather grade and the room temperature set value, then the predicted heat load under the conditions of the current weather grade and the room temperature set value is predicted according to the heat load searched from the historical data, and the heat load prediction method based on the historical data is used for searching the heat load under the similar condition firstly, so that not only the accuracy of determination can be ensured, but also the calculation amount is reduced, the error is reduced, and the prediction speed is improved.
Optionally, the obtaining the climate grade in the current environment includes: acquiring a forecast temperature, a radiation condition and a wind speed in the current environment; correcting the forecasted temperature according to the radiation condition and the wind speed to obtain the climate temperature; and determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relation between the climate temperature and the climate grade.
The climate has no common parameters except for air temperature, generally adopts air temperature to represent climate degree, but actually, the air temperature is not uniform, the difference of the air temperature is larger in each condition, and the intensity of wind speed and the intensity of solar radiation influence the air temperature and further influence the dissipation degree of indoor heat.
Optionally, before determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relationship between the climate temperature and the climate grade, determining a corresponding temperature difference between two adjacent climate grades, and determining the corresponding relationship between the climate temperature and the climate grade according to the temperature difference, determining an air temperature span of the climate grade division, that is, the corresponding temperature difference between the two adjacent climate grades, and determining the corresponding relationship between the climate temperature and the climate grade, for example, the corresponding temperature difference between the two adjacent climate grades is 5 ℃, the climate temperature is 25 ℃, and determining which climate grade the climate temperature of 25 ℃ is under the condition that the temperature difference is 5 ℃, and according to the corresponding relationship, in combination with the obtained climate temperature, determining which climate grade the climate temperature belongs to.
Optionally, the predicting the thermal load to be provided in the current environment according to the climate level, the room temperature setting value, and the historical data, and obtaining the predicted value includes: acquiring a room temperature set value under the current environment; according to the room temperature set value, whether historical heat load data meeting the following preset conditions exist in the historical data or not is searched, wherein the preset conditions comprise: the historical climate grade is the same as the climate grade under the current environment, and the difference value between the historical room temperature reference value and the historical room temperature set value is within a preset difference value range; when the two conditions are found to be met, the historical heat load data which are the same as the current climate grade condition and the preset room temperature condition are found, and the found historical heat load data can be directly used as a predicted value.
However, in the actual case, when the current room temperature setting value is the same as the room temperature setting value in the historical data, the case that the two predetermined conditions are simultaneously satisfied is rare, after searching whether historical heat load data satisfying the following predetermined conditions exist in the historical data, only conditions may be satisfied, when searching satisfying the predetermined conditions, historical heat load data satisfying 0 the predetermined conditions is obtained, when the historical heat load data satisfying the predetermined conditions is adjusted, the adjusted heat load data is predicted, for example, when the climate grade is the same, the difference between the room temperature setting value in the historical data and the room temperature reference value exceeds the predetermined difference range, historical heat load data corresponding to the climate grade, the room temperature setting value and the room temperature reference value is extracted, and the historical heat load data is corrected, for example, when the room temperature setting value in the historical data is different from the room temperature reference value, for example, degrees of the difference between the room temperature setting value in the historical data and the room temperature reference value is adjusted, for example, when the adjustment of the room temperature setting value is equal to the room temperature setting value, the room temperature setting value is adjusted, the corresponding to degrees, the corresponding to the historical heat load data, when the current room temperature setting value is equal to 3526, the current temperature setting value, the difference is determined, the corresponding to be equal to the corresponding to the thermal load data, when the historical heat load data, the current thermal load data, the historical thermal load data is not equal to the thermal load data, otherwise, the current thermal load data, the corresponding to the thermal load data is found to the current thermal load data is found to the corresponding to the thermal load data, the thermal load data is found to be equal to the current thermal load data, the current thermal load data is found to the current thermal load data, the current thermal load data is found to the corresponding to the same, the current thermal load data is found to the current thermal load data, the current thermal load data is found to the corresponding thermal load data is found to the current thermal load data is found to the corresponding to the same, the corresponding thermal load data, the current thermal load data, the corresponding to.
In addition, in an actual situation, the case that the two preset conditions are not satisfied may also exist, optionally, in this embodiment, after searching whether historical heat load data satisfying the following preset conditions exist in historical data, the method further includes, when searching for the case that the above conditions are not satisfied, searching for optimal historical data from the historical data, where the optimal historical data includes the historical data in which a difference between a historical room temperature reference value and a historical room temperature set value is minimum and a difference between a historical climate grade and a climate grade in a current environment is minimum, adjusting the historical heat load data corresponding to the optimal historical data according to the difference between the historical room temperature reference value and the historical room temperature set value to obtain a th adjustment data, adjusting the th adjustment data according to the difference between the historical climate grade and the climate grade in the current environment to obtain a predicted value, adjusting the historical heat load data according to a proximity degree, adjusting the historical heat load data according to an adjustment relationship according to the adjustment relationship, where the adjustment relationship may be analyzed and determined by using the historical data, the above adjusting method may also be performed by using a combination of the above-described method, and the method may be performed by combining the above-described methods, and may include, and performing a correction of the above-described methods, and performing a correction method for correcting the above-described which may be performed by combining the above-described methods for correcting the historical heat load data when a comparison method for correcting a difference between the historical load data and a current climate grade correction method for correcting a current weather load data, and a current weather-based on the historical-described which may be performed according to obtain a weather-described which is performed by using a combination of the difference between the above-described which is performed in this example, and a weather-described which is performed.
Optionally, after the actual thermal load value is adjusted according to the predicted value, the method further includes: determining the highest threshold and the lowest threshold of the room temperature reference value under the current environment; screening a plurality of collected room temperature reference values according to the highest threshold and the lowest threshold to obtain room temperature reference values in the current environment; and storing the room temperature reference value, the climate grade, the room temperature set value and the actual thermal load value obtained after the actual thermal load value is adjusted according to the predicted value under the current environment as historical data.
The room temperature reference is determined by the room temperatures of a plurality of users, special useless data exist in a large number of user room temperatures, for example, the room temperature is too high due to leakage of a heating pipeline, so the embodiment sets the highest threshold and the lowest threshold for the room temperature reference value, screens a plurality of collected room temperature reference values according to the highest threshold and the lowest threshold to obtain the room temperature reference value in the current environment, and effectively improves the effectiveness of the room temperature reference value.
Optionally, adjusting the actual thermal load value according to the predicted value includes: dividing the time period for adjustment to obtain a divided time period; and adjusting the actual heat load in the divided time period according to the predicted value in the divided time period.
Since the climate level and the room temperature setting are in the change, the adjustment of the actual heat load in response is also changed, but the higher the adjustment frequency is, the higher the economic cost and the labor cost are, and the lower the adjustment frequency is, the poorer the user experience is, therefore in the embodiment, timing period division is adopted, the adjustment is performed according to the divided periods, the periods can be equal or unequal, the adjustment can be performed according to the actual conditions, for example, on the weekend, the residents are all at home, therefore, the appropriate division period shortening is selected to increase the adjustment frequency, for example, in the traditional festival such as spring festival, the division period shortening is considered to increase the adjustment frequency, for example, in the week , many people often go to work, the period of the residential area can be appropriately prolonged, and the adjustment efficiency can be effectively improved.
It should be noted that the present embodiment provides heat exchange station load prediction control methods based on the user room temperature and climate level as a preferred embodiment, and the preferred embodiment is described in detail below.
The main purpose of the preferred embodiment is to keep the room temperature of the user stable under different weather levels while ensuring the heating quality of the user. When the outdoor air temperature is higher, the heat of the heat exchange station is reduced; when the outdoor temperature is higher, the heat of the heat exchange station is improved. The method mainly comprises the following implementation modes: firstly, establishing a historical operation database which takes days as a unit and mainly comprises a climate grade, an actual user room temperature and an actual output heat load, analyzing according to the climate grade of the day and the user room temperature which needs to be kept in the actual operation process, analyzing and comparing with data in the historical database, directly extracting the output heat load as a predicted heat load of the day if the database contains the same climate grade and the same user room temperature, calculating the predicted heat load of the day according to a formula if the database does not contain the same climate grade and the same user room temperature, and distributing and outputting the heat load of the day according to three stages according to the change condition of the external temperature. And after the operation is finished, storing the corresponding data into the historical database the next day. The preferred embodiment can be used for an intelligent control system of the heat exchange station, the room temperature of a user is kept stable under the condition of climate condition change, the situation that the room temperature of the user is too high or too low is prevented, and energy is saved on the premise of ensuring heat supply quality.
The technical scheme of the preferred embodiment is mainly realized by the following modes:
fig. 2 is a schematic diagram of a system architecture composition according to a preferred embodiment of the present invention, as shown in fig. 2, the system architecture configuration composition:
the system comprises a room temperature sensor, a wireless router, a PLC (programmable logic controller), heat meters of the sub-grid and electric regulating valves of the sub-grid.
The system can realize the functions that a room temperature sensor is used for collecting the room temperature of a user, a wireless router is used as a communication receiver to receive the room temperature of the user and weather forecast, a PLC (programmable logic controller) is mainly used for storing and calculating data, heat meters in the sub-grid are used for collecting the actual output heat load of the heat exchange station, and electric regulating valves in the sub-grid are used for controlling the data heat load of the heat exchange station.
The main modules of the system comprise: the system comprises a wireless room temperature module, a climate grade module, a historical data module and a load distribution module. Each block will be described in detail below.
A wireless room temperature module: fig. 3 is a schematic diagram of a room temperature calculation method according to a preferred embodiment of the present invention, and as shown in fig. 3, the user room temperature is periodically transmitted to the PLC controller (every hour) in a wireless manner, and a user room temperature reference value is generated by calculation as an actual situation for determining the current user room temperature. Calculation mode of the reference value of the room temperature per hour: if the room temperature of the user is lower than the low value of the room temperature, the room temperature is abandoned, and no calculation is carried out; if the room temperature of the user is higher than the room temperature high value, the room temperature is abandoned, and the calculation is not involved; others are averaged between the room temperature low and high values. The calculation mode of the standard value of the room temperature on the same day is as follows: and taking the average number according to the reference value of the room temperature of each hour as the reference value of the room temperature of each day and as the actual room temperature condition of the user on the same day. The specific calculation mode is shown in the attached drawing.
A climate grade module: fig. 4 is a schematic diagram of a climate grade calculation method according to a preferred embodiment of the present invention, as shown in fig. 4, a weather forecast is wirelessly transmitted to a PLC controller, and the main collected parameters are: maximum temperature, minimum temperature, wind speed, cloudy and sunny conditions, real-time temperature and the like; the climate grades are divided according to 0.5 ℃ and the temperature ranges from minus 5 ℃ to plus 5 ℃. The temperature calculation mode is Tj to Tp + Tr + Tv, wherein Tp is the average temperature of the day; tr is the correction of solar radiation to air temperature, and Tv is the correction of wind speed to air temperature. The specific calculation mode is shown in the attached drawing;
a historical data module: the storage content of the historical data mainly comprises: outputting a daily user room temperature reference value, a daily user room temperature set value, a daily weather and climate grade and a daily actual heat load;
a load distribution module: after the heat load output of the day is predicted, the outdoor temperature condition is constantly changed, and the output load must be adjusted in time according to the outdoor temperature to ensure the stability of the room temperature of a user. According to the technical scheme, the total load of the day is distributed according to three time intervals, the distribution principle is that the average temperature of a certain time interval is calculated according to the external temperature, and the external temperature is determined through weather forecast.
The preferred embodiment further provides control methods of the above system, which specifically include the following steps:
step 1, a model establishing stage, wherein a diagram 5 is a schematic diagram of a heat load prediction principle according to a preferred embodiment of the invention, as shown in the diagram 5, the control method can normally and automatically perform load prediction on the premise that quantitative historical data models are established first, the specific model establishing method comprises the steps of manually controlling network electric valve opening degrees to control output heat loads, the operation time is from 8 am to 8 th a day, the specific actual output heat loads can be calculated through a heating and ventilation calculation formula according to the heat supply area of a heat exchange station, a heat preservation system of a building and the weather condition, after the operation is completed, the current user room temperature reference value, the current user room temperature set value, the current weather and climate grade and the current actual heat loads are stored in a historical database, the user complaints of the heat exchange station are analyzed, if the user complaints are not much or not, the output loads are considered to be excessive, the output heat loads are properly reduced in a manual mode, if the user complaints are considered to be too low, the output loads are properly increased in a manual mode, the appropriate output load is considered to be the most appropriate reference value, and the actual heat load is also selected as the most appropriate reference value, and the actual heat exchange station is obtained by taking the reference of the current heat load.
if both conditions are met, directly extracting the output daily load in the historical database as the thermal load of the current day;
if the climate grade is satisfied, and the difference between the room temperature reference set value and the room temperature reference exceeds plus or minus 0.5 ℃, extracting the output load in the historical database for calculation, wherein the temperature difference is 1 ℃ and the energy consumption difference is 10%;
if the climate conditions are not met and the difference between the room temperature reference set value and the room temperature reference is not more than plus or minus 0.5 ℃, extracting the output load in the historical database for calculation, wherein the climate grades are different by 1 grade, and the energy consumption is different by 5 percent;
if neither condition is satisfied, finding the optimal historical data: and adjusting the output load according to the room temperature difference of the historical data with the minimum room temperature reference set value and the minimum room temperature reference difference, and adjusting according to the difference of the climate grades after adjustment.
After the thermal load output of the current day is predicted, the output load is divided into the following load according to the weather forecast of the current dayFig. 7 is a schematic diagram of predicted heat load distribution according to a preferred embodiment of the present invention, and as shown in fig. 7, the method for distributing predicted heat load according to the preferred embodiment of the present invention includes firstly counting predicted heat load throughout the day, counting the predicted heat load according to a time-temperature diagram, generating a predicted temperature change curve after the counting is completed, such as a thick black dotted line in fig. 7, equally dividing the entire day into three periods, dividing the actual change trend of heat load within time according to the predicted heat load change trend into monotone intervals, such as time calculation values 2 to 10 in fig. 7, which are monotone increasing intervals, in which temperature increases straight in this interval , then connecting the highest temperature value and the lowest temperature value in the monotone interval, such as a thin dotted line in fig. 7, and calculating the equation of the theoretical dotted line, y ═ k1x + b, when calculating the predicted th period, i.e., the time calculated value 5 to 12 in fig. 7, from the equation of the theoretical dotted line, the theoretical temperatures at the starting and ending time points of the th period, i.e., the time calculated values 5 and 12, can be determined, if the period has the extreme point (maximum or minimum) of the predicted temperature change curve, the theoretical temperatures at the time points of the theoretical dotted line at the minimum and maximum values (or maximum and minimum values) are determined from the theoretical dotted line corresponding to the curve of the minimum (or maximum) and maximum (or minimum) values at the starting or ending time points, e.g., the th period in fig. 7, which includes the maximum of the predicted temperature change curve, from the theoretical dotted line corresponding to the curve of the minimum and maximum values at the starting or ending time points, the theoretical temperatures at the time points of the minimum and maximum values are determined, in fig. 7, the theoretical temperatures at the time points of the minimum and maximum values are corrected from the theoretical dotted line, the theoretical temperatures at the theoretical temperature at the maximum and the theoretical temperature at the time point are calculated as the theoretical temperature, and the theoretical temperature at the maximum and the theoretical temperature are corrected by the theoretical temperature, and the theoretical temperature at the theoretical temperature are calculated by the theoretical temperature distribution of the theoretical dotted line 2, and the theoretical temperature distribution.
For the second period and the third period in fig. 7 as an example, as shown in fig. 7, when the second period is the calculated time value 13 to 20, the predicted temperature change curve in the second period is monotonously decreased, the maximum value and the minimum value of the monotonously decreased predicted temperature change curve are calculated, namely, the temperature corresponding to the time calculation value 10 and the temperature corresponding to the time calculation value 25, the equation of the theoretical dotted line corresponding to the monotonically decreasing predicted temperature change curve can be calculated by the maximum value and the minimum value, then respectively substituting the starting time and the ending time in the second time period into the equation, solving the maximum theoretical temperature corresponding to the starting time and the minimum theoretical temperature corresponding to the ending time, an average temperature of the maximum theoretical temperature and the minimum theoretical temperature is then calculated, and the average temperature summed with the wind speed correction temperature and the solar radiation correction temperature is used as the dispense temperature for the second time period.
As shown in fig. 7, when the third time interval is from 21 to 28 times of the calculated time value, the minimum value of the predicted temperature change curve exists when the calculated time value is 25 times in the third time interval, so it is necessary to calculate the maximum value of the starting or ending time points, calculate the theoretical temperature corresponding to the starting time and the theoretical temperature corresponding to the ending time, respectively, take the maximum value of the two, obviously, the theoretical temperature corresponding to the starting time of the third time interval is relatively large, take the theoretical temperature corresponding to the starting time as the maximum value, calculate the maximum theoretical temperature corresponding to the starting time of the theoretical dotted line where the maximum value and the minimum value are located, and take the average temperature of the two, and the sum of the average temperature and the wind speed correction temperature and the solar radiation correction temperature is used as the distribution temperature of the third time interval.
As shown in FIG. 7, the distribution ratio of the heat load in this time period in the present embodiment is equal to the ratio of the distribution temperature in this time period to the sum of the distribution temperatures due to the three time periods, and the heat load of the heat exchange station is distributed according to the distribution of the heat load for the three time periods.
It should be noted that the distribution temperatures of the th time interval, the second time interval and the third time interval are different, and sometimes the distribution temperatures of the adjacent phases are different greatly and change quickly, but cannot be changed suddenly by controlling the change of the heat load of the heat exchange station in the actual operation process, therefore, in the time zone where the two adjacent time intervals are in contact, the distribution temperature is controlled to change slowly by controlling the output heat load of the heat exchange station.
The beneficial effects of the preferred embodiment are as follows:
1. the weather grade, the room temperature reference value and the historical data are used for predicting the load and adjusting the heat load based on the three factors, so that the condition that the room temperature of a user is too high or too low is prevented, and energy is saved.
2. On the basis of the basic model, the optimal heat load is calculated based on the system, the optimal operation heat load is optimized based on the client feedback, and historical optimal operation data is saved. The real-time data is combined with the historical optimal operation data to distribute the heat load, so that the regulation and control time is saved, and the comfort level and the satisfaction degree of customers are improved.
3. On the basis of determining the meteorological grade by the traditional meteorological average temperature, the solar radiation and the wind speed correction temperature are increased, because the smaller the solar radiation is, the larger the wind speed is, and the heat consumption is increased. The solar radiation and wind speed correction temperature are increased, the accuracy of the prediction and the accuracy of the heat supply quantity are improved, the waste of heat is prevented, and the comfort level and the satisfaction level of customers are improved.
4. The calculation mode of the reference value of the room temperature is favorable for preventing the reference value of the room temperature from being influenced by overhigh temperature, overlow fluctuation and large fluctuation
5. And the load is distributed according to time periods, so that the load is prevented from being suddenly changed.
Specific numerical values in the present preferred embodiment and the number of samples, specific gradation temperatures, and the number of gradations in fig. 3 and 4 are examples, and the present preferred embodiment will be described without limiting the present preferred embodiment.
FIG. 8 is a schematic diagram of thermal load control devices according to an embodiment of the invention, and as shown in FIG. 8, the thermal load control device 80 includes an acquisition module 82, a prediction module 84, and an adjustment module 86, which are described in detail as follows:
an obtaining module 82, configured to obtain a climate level, a room temperature setting value, and historical data before a time corresponding to a current environment, where the historical data includes: historical climate grade, historical room temperature reference value, historical room temperature set value, and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value; a prediction module 84, connected to the obtaining module 82, configured to predict a thermal load to be provided in the current environment according to the climate level, the room temperature setting value, and the historical data, so as to obtain a prediction value; and the adjusting module 86 is connected with the predicting module 84 and is used for adjusting the actual heat load value according to the predicted value.
According to the heat load control device 80, the obtaining module 82 obtains the climate grade and the room temperature set value in the current environment and the historical data before the corresponding moment of the current environment, wherein the historical data comprises historical load data corresponding to the historical climate grade and the historical room temperature set value, the predicting module 84 predicts the heat load to be provided in the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, and the adjusting module 86 adjusts the actual heat load value according to the predicted value to achieve the purposes of regulating and controlling the indoor temperature of the user and accurately controlling the heating energy consumption, so that heat load control quantitative analysis methods with higher accuracy are provided, and the technical problem of low accuracy of the heat load control quantitative analysis methods in the related technologies is solved.
Fig. 9 is a schematic diagram of thermal load control systems according to an embodiment of the present invention, and as shown in fig. 9, the thermal load control system 90 includes a wireless router 91, a programmable logic controller PLC92, a heat meter 93 and an electric regulating valve 94, which will be described in detail below:
the wireless router 91 is used for obtaining weather forecast under the current environment, wherein the weather forecast is used for determining the climate grade under the current environment, the programmable logic controller PLC92 is connected with the wireless router 91 and is used for storing historical data before the current environment corresponds to time and predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, wherein the historical data comprises a historical climate grade, a historical room temperature reference value, a historical room temperature set value and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value, the heat meter 93 is connected with the programmable logic controller PLC92 and is used for collecting the actual heat load value under the current environment, and the electric regulating valve 94 is connected with the heat meter 93 and is used for regulating the actual heat load value according to the predicted value.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed technology can be implemented in other manners, wherein the above-described device embodiments are merely illustrative, for example, the division of the units can be logical function divisions, and other divisions can be realized in practice, for example, multiple units or components can be combined or integrated into another systems, or features can be omitted or not executed, in another point, the shown or discussed coupling or direct coupling or communication connection between each other can be through interfaces, indirect coupling or communication connection of units or modules, and can be electric or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in places, or may also be distributed on multiple units.
In addition, the functional units in the embodiments of the present invention may be integrated into processing units, or each unit may exist alone physically, or two or more units are integrated into units.
Based on the understanding, the technical solution of the present invention, which is essentially or partially contributed to by the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in storage media, which includes several instructions for making computer devices (which may be personal computers, servers, or network devices) execute all or part of the steps of the methods described in the embodiments of the present invention.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (11)
1, A method for controlling thermal load, comprising:
acquiring the climate grade, the room temperature set value and historical data before the corresponding moment of the current environment, wherein the historical data comprises: historical climate grade, historical room temperature reference value, historical room temperature set value, and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value;
predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value;
and adjusting the actual heat load value according to the predicted value.
2. The method of claim 1, wherein obtaining the climate level for a current environment comprises:
acquiring the forecast temperature, radiation condition and wind speed in the current environment;
correcting the forecasted temperature according to the radiation condition and the wind speed to obtain the climate temperature;
and determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relation between the climate temperature and the climate grade.
3. The method according to claim 2, wherein before determining the climate grade corresponding to the obtained climate temperature according to the obtained climate temperature and the corresponding relationship between the climate temperature and the climate grade, the method further comprises:
determining the corresponding temperature difference between two adjacent climate grades;
and determining the corresponding relation between the climate temperature and the climate grade according to the temperature difference.
4. The method of claim 1, wherein predicting the thermal load to be provided in the current environment based on the climate level, the room temperature setting, and the historical data comprises:
acquiring a room temperature set value under the current environment;
according to the room temperature set value, searching whether historical heat load data meeting the following preset conditions exist in the historical data, wherein the preset conditions comprise: the historical climate grade is the same as the climate grade under the current environment, and the difference between the historical room temperature reference value and the historical room temperature set value is within a preset difference range;
and under the condition that the conditions are all found to be met, taking the found historical heat load data as the predicted value.
5. The method of claim 4, after searching whether there is historical heat load data in the historical data that satisfies the following predetermined condition, further comprising:
acquiring historical heat load data meeting the predetermined condition when meeting the predetermined condition is found;
the historical thermal load data of that satisfies the predetermined condition is adjusted, and the adjusted thermal load data is used as the predicted value.
6. The method of claim 5, wherein adjusting historical thermal load data that satisfies the predetermined condition comprises:
determining the difference amplitude of the parameters corresponding to the unsatisfied preset conditions;
obtaining the adjustment amount corresponding to the determined difference amplitude according to the corresponding relation between the difference amplitude and the adjustment amount;
and adjusting the historical heat load data meeting the preset condition according to the adjustment amount.
7. The method of claim 4, after searching whether there is historical heat load data in the historical data that satisfies the following predetermined condition, further comprising:
under the condition that the conditions are not met, finding out optimal historical data from the historical data, wherein the optimal historical data comprises the following steps: the difference between the historical room temperature reference value and the historical room temperature set value is minimum, and the historical data with the minimum difference between the historical climate grade and the climate grade under the current environment are obtained;
according to the difference value between the historical room temperature reference value and the historical room temperature set value, adjusting the historical heat load data corresponding to the optimal historical data to obtain th adjustment data;
and adjusting the th adjustment data according to the difference between the historical climate grade and the climate grade under the current environment to obtain the predicted value.
8. The method of claim 1, after adjusting the actual thermal load value according to the predicted value, further comprising:
determining the highest threshold and the lowest threshold of the room temperature reference value under the current environment;
screening a plurality of collected room temperature reference values according to the highest threshold and the lowest threshold to obtain the room temperature reference value in the current environment;
and storing the room temperature reference value, the climate grade, the room temperature set value and the actual thermal load value obtained after the actual thermal load value is adjusted according to the predicted value under the current environment as historical data.
9. The method of any of claims 1-8, wherein adjusting an actual thermal load value according to the predicted value comprises:
dividing the time period for adjustment to obtain a divided time period;
and adjusting the actual heat load in the divided time period according to the predicted value in the divided time period.
10, A thermal load control device, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring the climate grade, the room temperature set value and historical data before the current environment corresponding moment, and the historical data comprises: historical climate grade, historical room temperature reference value, historical room temperature set value, and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value;
the prediction module is used for predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value;
and the adjusting module is used for adjusting the actual thermal load value according to the predicted value.
A thermal load control system of the type 11, , comprising:
the wireless router is used for acquiring a weather forecast under the current environment, wherein the weather forecast is used for determining the climate grade under the current environment;
the PLC is used for storing historical data before the corresponding moment of the current environment, predicting the heat load to be provided under the current environment according to the climate grade, the room temperature set value and the historical data to obtain a predicted value, wherein the historical data comprises: historical climate grade, historical room temperature reference value, historical room temperature set value, and historical load data corresponding to the historical climate grade, the historical room temperature reference value and the historical room temperature set value;
the heat meter is used for acquiring an actual heat load value under the current environment;
and the electric regulating valve is used for regulating the actual thermal load value according to the predicted value.
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