CN118208766A - Heating system adjusting method and system based on coal-to-electricity equipment - Google Patents
Heating system adjusting method and system based on coal-to-electricity equipment Download PDFInfo
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Abstract
The invention relates to the technical field of intelligent heat supply management, and particularly discloses a heat supply system adjusting method and system based on coal-to-electricity equipment, wherein the method comprises the steps of acquiring historical heat supply temperature of each resident based on authority possessed by default, and determining resident characteristics according to the historical heat supply temperature; clustering households based on household features, and synchronously calculating average features as labels of each type of households; for each family, randomly correcting the heat supply parameters of at least one family based on the authority of the family, and acquiring feedback information uploaded by the corresponding family; and adjusting the heat supply parameters of various households at regular time based on the feedback information. According to the method, the heat supply temperature of the households is obtained, the heat supply temperature is analyzed, the characteristics of the households are extracted, the households are clustered, a plurality of households are selected randomly for each type of households, heuristic autonomous adjustment is carried out, if default permission is obtained, heat supply parameters are sent to the same type of households, and the scheme can greatly optimize the resource utilization rate macroscopically.
Description
Technical Field
The invention relates to the technical field of intelligent heat supply management, in particular to a heat supply system adjusting method and system based on coal-to-electricity equipment.
Background
The heating system based on coal-to-electricity conversion is to change the traditional coal-fired heating system into an electric heating system. Heating system based on electric power, its advantage lies in: advanced control technology and automation system can be integrated, and intelligent monitoring, remote management and the like can be realized.
Most of the existing coal-fired central heating systems supply heat continuously, and larger resource waste can be caused when the heat supply period is interrupted. Some users choose private heating modes, such as air conditioners, which have better adjustability and are controlled by the users themselves, in view of cost performance. However, some users often forget to adjust, and most users only feel untimely to adjust, so that the adjusting frequency is low, and a large resource waste is easily caused in the adjusting frequency.
Therefore, providing an intelligent control scheme to improve the resource utilization rate is a technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The invention aims to provide a heating system adjusting method and system based on coal-to-electricity equipment, so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
In a first aspect of the invention, there is provided a heating system adjustment method based on a coal to electricity plant, the method comprising:
Acquiring the historical heat supply temperature of each resident based on the authority possessed by default, and determining the resident characteristics by the historical heat supply temperature;
clustering households based on the household features, and synchronously calculating average features as labels of each type of households;
for each family, randomly correcting the heat supply parameters of at least one family based on the authority of the family, and acquiring feedback information uploaded by the corresponding family;
Adjusting heat supply parameters of various households at regular time based on feedback information;
the step of acquiring the historical heat supply temperature of each resident based on the authority possessed by default and determining the resident characteristics by the historical heat supply temperature comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
Further, the dimensionless treatment process comprises the following steps:
; in the/> Is the temperature after dimensionless treatment,/>For the value needing dimensionless treatment in the historical heat supply temperature,/>For maximum in the historical heating temperature,/>A minimum value in the historical heating temperature;
The calculation process of the accumulated change amount is as follows:
; in the/> In the traversal process, the first position is followed by the second positionCumulative change between position of individual element and initial position,/>For increment, the increment step is 1; /(I)Is the first/>, after the initial positionElement value of individual element,/>Is the first/>, after the initial positionElement values of the individual elements.
Further, the step of clustering households based on the household features and synchronously calculating average features as labels of each class of households includes:
sequentially selecting two households, reading household characteristics of the two households, and calculating the difference degree of the household characteristics;
Acquiring the space distance between any two households, and correcting the space distance based on the difference degree to obtain the difference distance between the two households;
k-means clustering households based on the difference distances;
and calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
Further, the calculation process of the difference distance is as follows:
; in the/> Respectively represent a resident/>For resident/>And resident/>Difference distance between/>For resident/>And resident/>Spatial distance between/>For the degree of difference,/>For resident/>Resident characteristics of (1) and resident/>Is characterized in (1) >Time difference at individual positions,/>For resident/>Corresponding element number and resident/>Corresponds to the maximum of the number of elements.
Further, for each type of resident, the step of randomly correcting the heating parameter of at least one resident based on the authority of the resident, and obtaining the feedback information uploaded by the corresponding resident includes:
receiving a heating parameter adjusting authority granted by a resident;
acquiring optimal heating temperatures in the historical heating temperatures of all households;
Randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
satisfaction with each of the correction scales is received in real-time for the resident feedback.
Further, the step of adjusting the heating parameters of each resident at regular time based on the feedback information comprises:
calculating satisfaction average values of feedback of similar households;
Selecting the maximum value of the correction proportion of the satisfaction mean value reaching the preset satisfaction threshold value, and obtaining the maximum correction proportion;
and adjusting the heating parameters of the same household based on the optimal heating temperature and the maximum correction proportion.
In a second aspect of the present invention, there is also provided a heating system adjustment system based on a coal to electricity plant, the system comprising:
the resident characteristic extraction module is used for acquiring the historical heat supply temperature of each resident based on the authority possessed by default, and determining resident characteristics according to the historical heat supply temperature;
The resident clustering module is used for clustering the residents based on the resident characteristics, and synchronously calculating average characteristics as labels of each type of resident;
the heat supply optimization module is used for randomly correcting heat supply parameters of at least one resident based on the authority of the resident in a default mode for each type of resident to acquire feedback information uploaded by the corresponding resident;
the heat supply adjusting module is used for adjusting heat supply parameters of various households at regular time based on the feedback information;
the method for determining the resident characteristics based on the historical heat supply temperature of each resident based on the authority of the default comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
Further, the resident clustering module includes:
The difference degree calculating unit is used for sequentially selecting two households, reading household characteristics of the two households and calculating the difference degree of the household characteristics;
the difference distance calculation unit is used for obtaining the space distance between any two households, correcting the space distance based on the difference degree, and obtaining the difference distance between the two households;
The clustering execution unit is used for carrying out K-means clustering on households based on the difference distance;
The average characteristic calculating unit is used for calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
Further, the heating optimization module includes:
The permission receiving unit is used for receiving the heat supply parameter adjusting permission granted by the resident;
The standard calculation unit is used for acquiring the optimal heating temperature in the historical heating temperatures of all households;
the parameter correction unit is used for randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
And the feedback information receiving unit is used for receiving satisfaction degree of each correction proportion fed back by the households in real time.
Further, the heating regulation module includes:
the average value calculation unit is used for calculating satisfaction average values of feedback of the same family;
The proportion inquiry unit is used for selecting the maximum value of the correction proportion of which the satisfaction average value reaches a preset satisfaction threshold value to obtain the maximum correction proportion;
and the proportion application unit is used for adjusting the heat supply parameters of the same resident based on the optimal heat supply temperature and the maximum correction proportion.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the heat supply temperature of the households is obtained, the heat supply temperature is analyzed, the characteristics of the households are extracted, the households are clustered, a plurality of households are randomly selected for each type of households, heuristic autonomous adjustment is performed, if default permission is obtained, corresponding heat supply parameters are sent to the same type of households, and the adjustment scheme can macroscopically optimize the resource utilization rate.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is a flow chart diagram of a method of regulating a heating system based on a coal-to-electricity plant.
Fig. 2 is a block diagram of a heating system regulation system based on a coal-to-electricity plant.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a flow chart of a heating system adjusting method based on a coal-to-electricity device, and in an embodiment of the invention, a heating system adjusting method based on a coal-to-electricity device includes:
step S100: acquiring the historical heat supply temperature of each resident based on the authority possessed by default, and determining the resident characteristics by the historical heat supply temperature;
The technical scheme of the invention is directed to a heating system based on electric power, which can be regarded as a centralized air conditioner with an adjusting function, and because a resident can adjust the required temperature according to own requirements, the heating temperature of each resident at each moment is recorded and used as a historical heating temperature, the historical heating temperature is analyzed, and the characteristics of the resident can be extracted.
Step S200: clustering households based on the household features, and synchronously calculating average features as labels of each type of households;
the household characteristics reflect the habit of the heat supply requirement of each household in the energy supply process, and are used as the labels of the households; the households are clustered based on the household characteristics, the same or similar households can be classified into one category, and when the households are clustered, average characteristics are calculated according to the household characteristics of the same category of households and used as labels of the households.
Step S300: for each family, randomly correcting the heat supply parameters of at least one family based on the authority of the family, and acquiring feedback information uploaded by the corresponding family;
For each family, a plurality of households are selected, heating parameters of the selected households are adjusted according to average characteristics of the households and the queried optimal heating temperature, the aim of the process is to actively adjust the heating process of the households, for example, the temperature of the households is 18 ℃ for a long time, the energy consumption of the households is high at 18 ℃, the execution main body of the method adjusts the households to 19 ℃ based on the pre-acquired authority, if the households can accept (even the reverberation can be better, only because of operation problems, the households are unwilling to adjust the temperature at a high frequency), resources are saved compared with the temperature before adjustment in a macroscopic sense, and the saving amount can be very large when the households are more and the time is prolonged.
Regarding the optimal heating temperature, which belongs to default data, the most comfortable temperature of the human body in different stages can be regarded as the optimal heating temperature, such as 23 ℃.
With respect to the heating parameters, the heating parameters are the working processes of the heating party for the working parameters of the energy supply device when a certain temperature is reached.
Regarding feedback information, the feedback information is transmitted by a resident for characterizing the satisfaction of the resident with the energy supply parameter adjustment process; in general, if the resident does not perform temperature adjustment for a long time, the satisfaction degree becomes higher and higher, if the temperature is adjusted, a negative value is determined according to the adjustment amplitude, and the satisfaction degree is adjusted.
Step S400: adjusting heat supply parameters of various households at regular time based on feedback information;
The same family of households is the same or similar, and some households are satisfied with enough heating parameters, and the method can be applied to other households in the same family, which is the meaning of step S400.
The step of acquiring the historical heat supply temperature of each resident based on the authority possessed by default and determining the resident characteristics by the historical heat supply temperature comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
In the technical scheme of the invention, the basic flow classifies the same or similar households into one category, which is based on the characteristics of the households already extracted; therefore, the extraction process of the resident features is very important, and the above disclosure discloses a resident feature extraction scheme, which is specifically described as follows:
Receiving a heat supply regulation request sent by a resident, sending a permission acquisition request to the resident, and receiving permission fed back by the resident, wherein the permission is used for inquiring the temperature of the resident at different moments and is called historical heat supply temperature; the historical heat supply temperature is generally between 16 ℃ and 30 ℃, and based on the historical heat supply temperature, data processing is carried out on the historical heat supply temperature to obtain dimensionless data; counting the dimensionless data according to the time sequence to obtain an array, which is called a heat supply array; the sequence number in the array corresponds to time, and the element value is dimensionless data.
Traversing the array by a preset window function, detecting the change condition of each value in the array in real time, determining mutation data, wherein the mutation data reflects the regulation condition of a resident on the temperature, marking one moment when the regulation amplitude is large enough, and counting a plurality of moments to obtain a moment array which is taken as the resident characteristic; the resident characteristics extracted by the application are irrelevant to the amplitude of each adjustment and only relevant to whether the adjustment is carried out.
It should be noted that, regarding whether or not the heating adjustment request can be received, although some of the control rights of the air conditioner are handed over from the viewpoint of the resident, there is a high possibility that the electricity fee will be reduced in terms of the resource utilization rate, and thus the resident does not always have a contradictory emotion.
Specifically, the dimensionless treatment process comprises the following steps:
; in the/> Is the temperature after dimensionless treatment,/>For the value needing dimensionless treatment in the historical heat supply temperature,/>For maximum in the historical heating temperature,/>A minimum value in the historical heating temperature;
The calculation process of the accumulated change amount is as follows:
; in the/> In the traversal process, the first position is followed by the second positionCumulative change between position of individual element and initial position,/>For increment, the increment step is 1; /(I)Is the first/>, after the initial positionElement value of individual element,/>Is the first/>, after the initial positionElement values of the individual elements.
The dimensionless treatment process is very simple, namely the temperature is converted into the range of 0 to 100; the calculation process of the accumulated variation is complex, and the concrete description is as follows:
first, an initial position is determined, and based on the initial position, data is continuously queried backwards, which is automatically increased Realization, the/>The element positions and the initial positions of the elements form a section, the weight determined by a Gaussian distribution function is introduced into the section, and the centerline of the Gaussian distribution function adopts/>Position, i.e. when calculating the cumulative change amount, tail element amount (th/>The positions) are most influenced, the difference (analog to derivative) at each position is accumulated based on the Gaussian distribution function, the adjustment amplitude of the resident in the period can be obtained through accumulation, if the difference is not adjusted, the difference is always zero, and the accumulated change is also zero.
With respect to step S200 in the foregoing, the step of clustering households based on the household features, and synchronously calculating average features as labels of each class of households includes:
Sequentially selecting two households, reading household characteristics of the two households, and calculating the difference degree between the two household characteristics;
Acquiring the space distance between any two households, and correcting the space distance based on the difference to obtain the difference distance between the two households;
k-means clustering households based on the difference distances;
and calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
Firstly, calculating differences among households, clustering the households based on the differences, and adopting a K-means clustering scheme for a clustering scheme; the most common difference adopts Euclidean distance, for example, the coordinates of households are obtained, the distance between the coordinates is calculated to represent the difference, but the scheme is feasible, but households with similar distances can only be gathered into one type, and similar households can not be gathered into one type.
In the technical scheme of the invention, the distance between households is optimized, the difference degree is calculated by the household characteristics, and the difference degree and the space distance are combined to determine the difference distance which can reflect the space distance and the difference condition of two households at the same time, so that the households are clustered, and the similarity of the households of the same type is higher.
Further, when the households are clustered, an average value is calculated according to the household characteristics of the households, which is called an average sign, and the average value is used as a label of each type of household.
Specifically, the calculation process of the difference distance is as follows:
; in the/> Respectively represent a resident/>For resident/>And resident/>Difference distance between/>For resident/>And resident/>Spatial distance between/>For the degree of difference,/>For resident/>Resident characteristics of (1) and resident/>Is characterized in (1) >Time difference at individual positions,/>For resident/>Corresponding element number and resident/>Corresponds to the maximum of the number of elements.
The difference distance is proportional to the difference degree, and the difference distance is proportional to the space distance, and the space distance is amplified by the difference degree in an understanding way, so that the amplification ratio is smaller as the difference degree is larger.
In this regard, regarding the variance calculation process, since the number of elements in the resident features may be different, when the resident features with different numbers of elements are faced, some zero values need to be inserted into the resident features with a smaller number, so that the number of elements in the two resident features is the same.
Regarding the step S300 in the foregoing, the step of, for each type of resident, randomly correcting the heating parameter of at least one resident based on the authority of the resident, and obtaining the feedback information uploaded by the corresponding resident includes:
receiving a heating parameter adjusting authority granted by a resident;
acquiring optimal heating temperatures in the historical heating temperatures of all households;
Randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
satisfaction with each of the correction scales is received in real-time for the resident feedback.
Step S300, the method execution main body remotely adjusts the heat supply parameters of each resident, which requires the resident to grant rights in advance, and the granted rights are heat supply parameter adjustment rights; when the heat supply parameter adjusting rights are provided, the optimal heat supply temperature in the historical heat supply temperatures of all households is obtained, the optimal heat supply temperature is a default known value, meanwhile, a plurality of correction ratios are determined, the current heat supply temperature of the households is obtained in specific correction, the difference value between the optimal heat supply temperature and the current heat supply temperature is calculated, the difference value is multiplied by the correction ratio to obtain an adjusting value, and the adjusting value is superimposed on the current heat supply temperature to enable the adjusting value to be close to the optimal heat supply temperature; the plurality of correction ratios correspond to a plurality of adjustment modes, and for each adjustment mode, satisfaction of one resident feedback is obtained, and the larger the correction ratio is, the more obvious the resident feel is, and the dissatisfaction is easy to occur.
Regarding the step S400 in the foregoing, the step of adjusting the heating parameters of each resident at regular time based on the feedback information includes:
calculating satisfaction average values of feedback of similar households;
Selecting the maximum value of the correction proportion of the satisfaction mean value reaching the preset satisfaction threshold value, and obtaining the maximum correction proportion;
and adjusting the heating parameters of the same household based on the optimal heating temperature and the maximum correction proportion.
For each family, calculating a satisfaction mean value when receiving the satisfaction fed back by the family, and when the satisfaction mean value reaches a preset satisfaction threshold value, considering that the family does not feel the corresponding correction proportion; and obtaining the maximum correction proportion of the satisfaction mean value reaching the preset satisfaction threshold value, and correcting the current temperature to the extent closest to the optimal heating temperature based on the maximum correction proportion.
It should be noted that, regarding the optimal heating temperature in the present application, it is not necessarily constant, and can be adjusted by the staff completely, for example, the temperature with the highest resource utilization rate or the most comfortable temperature can be selected, no matter what optimal heating temperature is adopted, the architecture provided by the present application can enable various households to approach to the optimal heating temperature, and the approach process is the important point of the present application.
Fig. 2 is a block diagram of a heating system adjusting system based on a coal-to-electricity device, and in an embodiment of the present invention, a heating system adjusting system based on a coal-to-electricity device, the system 10 includes:
a resident characteristic extraction module 11, configured to obtain a historical heating temperature of each resident based on the authority possessed by default, and determine resident characteristics from the historical heating temperature;
A resident clustering module 12, configured to cluster residents based on the resident features, and synchronously calculate average features as labels of each type of residents;
The heat supply optimizing module 13 is used for randomly revising heat supply parameters of at least one resident based on the authority of the resident in a default mode for each type of resident to acquire feedback information uploaded by the corresponding resident;
a heating adjustment module 14 for adjusting heating parameters of various households at regular time based on the feedback information;
the method for determining the resident characteristics based on the historical heat supply temperature of each resident based on the authority of the default comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
Further, the resident clustering module 12 includes:
The difference degree calculating unit is used for sequentially selecting two households, reading household characteristics of the two households and calculating the difference degree of the household characteristics;
the difference distance calculation unit is used for obtaining the space distance between any two households, correcting the space distance based on the difference degree, and obtaining the difference distance between the two households;
The clustering execution unit is used for carrying out K-means clustering on households based on the difference distance;
The average characteristic calculating unit is used for calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
Specifically, the heating optimization module 13 includes:
The permission receiving unit is used for receiving the heat supply parameter adjusting permission granted by the resident;
The standard calculation unit is used for acquiring the optimal heating temperature in the historical heating temperatures of all households;
the parameter correction unit is used for randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
And the feedback information receiving unit is used for receiving satisfaction degree of each correction proportion fed back by the households in real time.
Still further, the heating adjustment module 14 includes:
the average value calculation unit is used for calculating satisfaction average values of feedback of the same family;
The proportion inquiry unit is used for selecting the maximum value of the correction proportion of which the satisfaction average value reaches a preset satisfaction threshold value to obtain the maximum correction proportion;
and the proportion application unit is used for adjusting the heat supply parameters of the same resident based on the optimal heat supply temperature and the maximum correction proportion.
The functions which can be realized by the heating system adjusting method based on the coal-to-electricity equipment are all completed by computer equipment, the computer equipment comprises one or more processors and one or more memories, at least one program code is stored in the one or more memories, and the program code is loaded and executed by the one or more processors to realize the heating system adjusting method based on the coal-to-electricity equipment.
The processor takes out instructions from the memory one by one, analyzes the instructions, then completes corresponding operation according to the instruction requirement, generates a series of control commands, enables all parts of the computer to automatically, continuously and cooperatively act to form an organic whole, realizes the input of programs, the input of data, the operation and the output of results, and the arithmetic operation or the logic operation generated in the process is completed by the arithmetic unit; the Memory comprises a Read-Only Memory (ROM) for storing a computer program, and a protection system is arranged outside the Memory.
For example, a computer program may be split into one or more modules, one or more modules stored in memory and executed by a processor to perform the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program in the terminal device.
It will be appreciated by those skilled in the art that the foregoing description of the service device is merely an example and is not meant to be limiting, and may include more or fewer components than the foregoing description, or may combine certain components, or different components, such as may include input-output devices, network access devices, buses, etc.
The Processor may be a central processing unit (Central Processing Unit, CPU), other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the above-described terminal device, and which connects the various parts of the entire worker terminal using various interfaces and lines.
The memory may be used for storing computer programs and/or modules, and the processor may implement various functions of the terminal device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as an information acquisition template display function, a product information release function, etc.), and the like; the storage data area may store data created according to the use of the berth status display system (e.g., product information acquisition templates corresponding to different product types, product information required to be released by different product providers, etc.), and so on. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The modules/units integrated in the terminal device may be stored in a computer readable medium if implemented in the form of software functional units and sold or used as separate products. Based on this understanding, the present invention may implement all or part of the modules/units in the system of the above-described embodiments, or may be implemented by instructing the relevant hardware by a computer program, which may be stored in a computer-readable medium, and which, when executed by a processor, may implement the functions of the respective system embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or system capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
It should be noted that, in this document, the term "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A heating system adjustment method based on coal to electricity equipment, the method comprising:
Acquiring the historical heat supply temperature of each resident based on the authority possessed by default, and determining the resident characteristics by the historical heat supply temperature;
clustering households based on the household features, and synchronously calculating average features as labels of each type of households;
for each family, randomly correcting the heat supply parameters of at least one family based on the authority of the family, and acquiring feedback information uploaded by the corresponding family;
Adjusting heat supply parameters of various households at regular time based on feedback information;
the step of acquiring the historical heat supply temperature of each resident based on the authority possessed by default and determining the resident characteristics by the historical heat supply temperature comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
2. The method for adjusting a heating system based on coal-to-electricity equipment according to claim 1, wherein the dimensionless treatment process is as follows:
; in the/> Is the temperature after dimensionless treatment,/>For the value needing dimensionless treatment in the historical heat supply temperature,/>For maximum in the historical heating temperature,/>A minimum value in the historical heating temperature;
The calculation process of the accumulated change amount is as follows:
; in the/> In the traversal process, the first position is followed by the second positionCumulative change between position of individual element and initial position,/>For increment, the increment step is 1; /(I)Is the first/>, after the initial positionElement value of individual element,/>Is the first/>, after the initial positionElement values of the individual elements.
3. The method for adjusting a heating system based on a coal-to-electricity plant according to claim 2, wherein the step of clustering households based on the household characteristics and synchronously calculating average characteristics as labels of each type of household comprises:
sequentially selecting two households, reading household characteristics of the two households, and calculating the difference degree of the household characteristics;
Acquiring the space distance between any two households, and correcting the space distance based on the difference degree to obtain the difference distance between the two households;
k-means clustering households based on the difference distances;
and calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
4. A heating system adjustment method based on coal-to-electricity equipment according to claim 3, characterized in that the calculation process of the difference distance is:
; in the/> Respectively represent a resident/>For resident/>And resident/>Difference distance between/>For resident/>And resident/>Spatial distance between/>For the degree of difference,/>For householdsResident characteristics of (1) and resident/>Is characterized in (1) >Time difference at individual positions,/>For resident/>Corresponding element number and resident/>Corresponds to the maximum of the number of elements.
5. The method for adjusting a heating system based on a coal-to-electricity conversion apparatus according to claim 1, wherein the step of randomly correcting the heating parameters of at least one resident based on the authority of the resident of each type, and acquiring the feedback information uploaded by the corresponding resident comprises:
receiving a heating parameter adjusting authority granted by a resident;
acquiring optimal heating temperatures in the historical heating temperatures of all households;
Randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
satisfaction with each of the correction scales is received in real-time for the resident feedback.
6. The method for adjusting a heating system based on a coal-to-electricity plant according to claim 5, wherein the step of adjusting the heating parameters of each resident at regular time based on the feedback information comprises:
calculating satisfaction average values of feedback of similar households;
Selecting the maximum value of the correction proportion of the satisfaction mean value reaching the preset satisfaction threshold value, and obtaining the maximum correction proportion;
and adjusting the heating parameters of the same household based on the optimal heating temperature and the maximum correction proportion.
7. A heating system regulation system based on coal to electricity equipment, the system comprising:
the resident characteristic extraction module is used for acquiring the historical heat supply temperature of each resident based on the authority possessed by default, and determining resident characteristics according to the historical heat supply temperature;
The resident clustering module is used for clustering the residents based on the resident characteristics, and synchronously calculating average characteristics as labels of each type of resident;
the heat supply optimization module is used for randomly correcting heat supply parameters of at least one resident based on the authority of the resident in a default mode for each type of resident to acquire feedback information uploaded by the corresponding resident;
the heat supply adjusting module is used for adjusting heat supply parameters of various households at regular time based on the feedback information;
the method for determining the resident characteristics based on the historical heat supply temperature of each resident based on the authority of the default comprises the following steps:
Receiving a heat supply regulation request sent by a resident, and acquiring a data query authority;
Acquiring the historical heat supply temperature of each resident according to the data query authority, and carrying out dimensionless treatment on the historical heat supply temperature;
according to the time sequence, the dimensionless processed data are arranged to obtain a heat supply array;
Traversing a heating array by a preset window function, and calculating the accumulated variation;
when the accumulated variation reaches a preset variation threshold, marking the traversing endpoint time;
Counting the marked end point time to obtain a time array as the resident characteristic.
8. The coal-to-electricity plant-based heating system regulation system of claim 7, wherein the household clustering module comprises:
The difference degree calculating unit is used for sequentially selecting two households, reading household characteristics of the two households and calculating the difference degree of the household characteristics;
the difference distance calculation unit is used for obtaining the space distance between any two households, correcting the space distance based on the difference degree, and obtaining the difference distance between the two households;
The clustering execution unit is used for carrying out K-means clustering on households based on the difference distance;
The average characteristic calculating unit is used for calculating the average characteristic of the household characteristics of each type of household as the label of each type of household.
9. The coal-to-electricity plant-based heating system regulation system of claim 8, wherein the heating optimization module comprises:
The permission receiving unit is used for receiving the heat supply parameter adjusting permission granted by the resident;
The standard calculation unit is used for acquiring the optimal heating temperature in the historical heating temperatures of all households;
the parameter correction unit is used for randomly selecting households for each type of households, and correcting the heat supply parameters based on the optimal heat supply temperature and a preset correction proportion under the heat supply parameter adjustment authority;
And the feedback information receiving unit is used for receiving satisfaction degree of each correction proportion fed back by the households in real time.
10. The coal-to-electricity plant-based heating system regulation system of claim 8, wherein the heating regulation module comprises:
the average value calculation unit is used for calculating satisfaction average values of feedback of the same family;
The proportion inquiry unit is used for selecting the maximum value of the correction proportion of which the satisfaction average value reaches a preset satisfaction threshold value to obtain the maximum correction proportion;
and the proportion application unit is used for adjusting the heat supply parameters of the same resident based on the optimal heat supply temperature and the maximum correction proportion.
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