CN114198805B - Coal changes electricity heating management monitored control system based on cloud - Google Patents
Coal changes electricity heating management monitored control system based on cloud Download PDFInfo
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- CN114198805B CN114198805B CN202111508496.XA CN202111508496A CN114198805B CN 114198805 B CN114198805 B CN 114198805B CN 202111508496 A CN202111508496 A CN 202111508496A CN 114198805 B CN114198805 B CN 114198805B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1096—Arrangement or mounting of control or safety devices for electric heating systems
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
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- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D2200/00—Heat sources or energy sources
- F24D2200/06—Solid fuel fired boiler
- F24D2200/062—Coal fired boilers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D2200/00—Heat sources or energy sources
- F24D2200/08—Electric heater
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Abstract
The invention provides a coal-to-electricity heating management monitoring system based on cloud service, which comprises a cloud server, an intelligent gateway, a plurality of coal heating monitoring modules and a plurality of electric heating monitoring modules, wherein the coal heating monitoring modules and the electric heating monitoring modules are respectively in wireless connection with the cloud server through the intelligent gateway; the coal heat supply monitoring modules are used for collecting coal heat supply data of a plurality of coal heat supply users and transmitting the collected coal heat supply data to the cloud server through the wireless gateway.
Description
Technical Field
The invention relates to the technical field of heat supply assessment, in particular to a coal-to-electricity heat supply management monitoring system based on cloud service.
Background
The change of coal into electricity means that a traditional boiler using coal as fuel is replaced by a boiler mainly using clean energy such as electricity. There are two methods for changing electricity by media: replacing a common coal boiler with an electric boiler; or the coal boiler and the original heating ventilation system are all cut off, and heating facilities such as an electric heating film or a heating cable are changed. Taking the transformation of Beijing as an example, PM2.5 of Beijing has 6 important sources, namely soil dust, fire coal, biomass combustion, automobile exhaust and garbage incineration, industrial pollution and secondary inorganic aerosol, wherein the proportion of the fire coal is about 18 percent. The fire coal pollution has a great influence on the formation of haze weather. As is known, the total number of coal-to-electricity users in the whole market reaches 38.45 ten thousands of households through thirteen years of coal-to-electricity engineering.
In the prior art, in the process of changing coal into electricity, a common user does not know the benefits of changing coal into electricity in place, the purpose of persuasion is difficult to achieve only through oral propaganda of service personnel, the user cannot visually know the situation before and after changing coal into electricity, and meanwhile the conventional coal changing system is difficult to carry out overall management, so that the process of changing coal into electricity is hindered by certain technology.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a cloud service-based coal-to-electricity heating management monitoring system, which can visually compare the energy consumption and safety before and after changing the electricity into the coal and can improve the overall supervision after changing the electricity into the coal so as to solve the problem that the prior coal-to-electricity system is insufficient in the front and back comparison and the overall supervision.
In order to achieve the purpose, the invention is realized by the following technical scheme: a coal-to-electricity heating management monitoring system based on cloud services comprises a cloud server, an intelligent gateway, a plurality of coal heating monitoring modules and a plurality of electric heating monitoring modules, wherein the coal heating monitoring modules and the electric heating monitoring modules are respectively in wireless connection with the cloud server through the intelligent gateway;
the coal heat supply monitoring modules are used for acquiring coal heat supply data of a plurality of coal heat supply users and transmitting the acquired coal heat supply data to the cloud server through the wireless gateway;
the plurality of electric heating monitoring modules are used for acquiring electric heating data of a plurality of electric heating users and transmitting the acquired electric heating data to the cloud server through the wireless gateway;
the cloud server is used for comparing the obtained coal heat supply data with the obtained electric heat supply data to obtain coal heat supply and electric heat supply efficiency and safety comparison results, and transmitting the comparison results to the user terminal through the intelligent gateway.
Furthermore, a cloud database is configured in the cloud server, heat supply data of a plurality of coal heat supply users and heat supply data of electric heat supply users are stored in the cloud database, and the heat supply data of the coal heat supply users comprise the distance of coal heat supply pipelines, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment failure frequency of the coal heat supply users;
the heat supply data of the electric heat supply users comprise the distance of the electric heat supply pipelines, the indoor area of the electric heat supply users, the number of the electric heat supply pipelines and the equipment failure frequency of the electric heat supply users.
Furthermore, the coal heat supply monitoring module comprises a coal usage monitoring unit, a coal heat supply flow monitoring unit, a coal heat supply output temperature monitoring unit and a coal heat supply input temperature monitoring unit;
the coal usage monitoring unit is used for monitoring the total coal usage; the coal heat supply flow monitoring unit is used for monitoring the coal heat supply amount of a coal heat supply user; the coal heat supply output temperature monitoring unit is used for monitoring the coal heat supply output temperature; the coal heat supply input temperature monitoring unit is used for monitoring the temperature in the coal heat supply user room.
Furthermore, the electric heating monitoring module comprises an electric consumption monitoring unit, an electric heating output temperature monitoring unit and an electric heating input temperature monitoring unit;
the power consumption monitoring unit is used for monitoring the power consumption of the electric heat supply user; the electric heating output temperature monitoring unit is used for monitoring the output temperature of the electric heating equipment; the electric heating input temperature monitoring unit is used for monitoring the indoor temperature of an electric heating user.
Further, a model building module is configured inside the cloud server, and the model building module comprises a coal heat supply model building unit and an electric heat supply model building unit;
the coal heat supply model building unit is used for building a coal heat supply model, the coal heat supply model comprises a plurality of coal heat supply submodels, and the coal heat supply submodels are built on the basis of each coal heat supply user;
the electric heating model building unit is used for building an electric heating model, the electric heating model comprises a plurality of electric heating submodels, and the electric heating submodels are built on the basis of each electric heating user;
the coal heat supply model building unit is configured with a coal heat supply sub-model building strategy, and the coal heat supply sub-model building strategy comprises the following steps: classifying coal heat supply users based on the indoor areas of the coal heat supply users, classifying the coal heat supply users with the indoor areas smaller than a first area as first-stage coal heat supply users, and then classifying the coal heat supply users into grades once increasing the first threshold area;
calculating the coal heat supply efficiency and the coal heat supply safety of the coal heat supply users in each grade, and substituting the total coal usage amount, the coal heat supply output temperature and the indoor temperature of the coal heat supply users into a coal heat supply efficiency formula to obtain an actual coal consumption value;
and (3) bringing the distance of coal heat supply pipelines of coal heat supply users, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment fault frequency of the coal heat supply users into a coal heat supply safety formula to obtain a coal heat supply risk value.
Further, the coal heating efficiency formula is configured to:
wherein Pmsx is an actual coal consumption value, msz is a total coal usage amount, mgr is a coal heat supply amount, M1 is a conversion coefficient between the coal usage amount and the coal heat supply amount, tmsc is a coal heat supply output temperature, tmsr is a temperature in a coal heat supply user room, a1 is a coal consumption coefficient, a2 is a coal heat supply temperature conversion coefficient, and M1, a1 and a2 are all larger than zero;
the coal heat supply safety formula is configured as follows:
wherein, pmfx is coal heat supply risk value, jmgr is coal heat supply pipeline's distance, bmgl is coal heat supply pipeline quantity, smm is coal heat supply user's indoor area, pmg is coal heat supply user's equipment fault frequency, b1 is coal heat supply parameter conversion coefficient, b2 is coal heat supply fault conversion coefficient, and b1 and b2 are all greater than zero.
Further, the electric heating model building unit is configured with an electric heating electronic model building strategy, and the electric heating electronic model building strategy comprises: classifying the electric heating users based on the indoor areas of the electric heating users, classifying the electric heating users of which the indoor areas are smaller than a first area into first-stage electric heating users, and then classifying the electric heating users into grades once increasing the first threshold area;
calculating the electric heating efficiency and the electric heating safety of the electric heating users in each grade, and substituting the electricity consumption of the electric heating users, the output temperature of electric heating equipment and the indoor temperature of the electric heating users into an electric heating efficiency formula to obtain an electric actual consumption value;
and (3) bringing the distance of the electric heating pipelines of the electric heating users, the indoor area of the electric heating users, the number of the electric heating pipelines and the equipment fault frequency of the electric heating users into an electric heating safety formula to obtain an electric heating risk value.
Further, the electrical heating efficiency formula is configured to:
the method comprises the following steps that Pdsx is an electric actual consumption value, lyd is power consumption, tdsc is the output temperature of electric heating equipment, tdsr is the indoor temperature of an electric heating user, a3 is an electric consumption coefficient, a4 is an electric heating temperature conversion coefficient, and a3 and a4 are both larger than zero;
the power supply thermal safety formula is configured as follows:
wherein Pdfx is the electric heating risk value, and Jdgr is the distance of electric heating pipeline, and Bdgl is electric heating pipeline quantity, and Sdm is the indoor area of electric heating user, and Pdg is electric heating user's equipment fault frequency, and b3 is electric heating parameter conversion coefficient, and b4 is electric heating fault conversion coefficient, and b3 and b4 all are greater than zero.
Further, a comparison module is further configured inside the cloud server, and a comparison strategy is configured in the comparison module, and the comparison strategy includes: respectively randomly selecting data of coal actual consumption values and coal heat supply risk values of n groups of coal heat supply submodels from first-level coal heat supply users to ith-level coal heat supply users;
adding the selected actual coal consumption values of a plurality of groups to obtain a coal heat supply sampling consumption total value, and adding the selected coal heat supply risk values of the plurality of groups to obtain a coal heat supply sampling risk total value;
substituting the total value of the coal heat supply sampling consumption into a first consumption comparison formula to obtain a first consumption comparison value; substituting the total risk value of the coal heat supply sampling into a first risk comparison formula to obtain a first risk comparison value;
respectively and randomly selecting data of electric actual consumption values and electric heating risk values of n groups of electric heating sub-models from first-level electric heating users to ith-level electric heating users;
adding the selected groups of electric actual consumption values to obtain an electric heating sampling consumption total value, and adding the selected groups of electric heating risk values to obtain an electric heating sampling risk total value;
substituting the total value of the electric heating sampling consumption into a second consumption comparison formula to obtain a second consumption comparison value; substituting the total risk value of the electric heating sampling into a second risk comparison formula to obtain a second risk comparison value;
and sending the first consumption comparison value, the second consumption comparison value, the first risk comparison value and the second risk comparison value to the user terminal through the intelligent gateway.
Further, the first consumption comparison formula is configured to: pxh1= Zmxh × c1; the first risk alignment formula is configured to: pfx1= Zmfx × d1; the second consumption comparison formula is configured to: pxh2= Zdxh × c2; the second risk alignment formula is configured to: pfx2= Zdfx × d2; wherein Pxh1 is a first consumption comparison value, zmxh is a coal heat supply sampling consumption total value, c1 is a coal heat supply consumption total value comparison coefficient, pfx1 is a first consumption comparison value, zmfx is a coal heat supply sampling risk total value, d1 is a coal heat supply risk total value comparison coefficient, pxh2 is a second consumption comparison value, zdxh is an electric heat supply sampling consumption total value, c2 is an electric heat supply consumption total value comparison coefficient, pfx2 is a second consumption comparison value, zdfx is an electric heat supply sampling risk total value, d2 is an electric heat supply risk total value comparison coefficient, and c1, c2, d1 and d2 are respectively greater than zero.
The invention has the beneficial effects that: according to the invention, the coal heat supply data of the coal heat supply user before the coal is changed into electricity is acquired, the electricity heat supply data of the electricity heat supply user after the coal is changed into electricity is acquired, the acquired data is transmitted to the cloud server to be processed, the comparison result of the coal heat supply efficiency and the electricity heat supply efficiency is obtained, and the comparison result is transmitted to the user terminal through the intelligent gateway.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic diagram of the connection of the present invention to a user terminal;
FIG. 2 is a schematic block diagram of the present invention in a first embodiment;
fig. 3 is a schematic block diagram of the present invention according to the second embodiment.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
In a first embodiment, please refer to fig. 1 and 2, the coal-to-electricity heating management monitoring system based on cloud service includes a cloud server, an intelligent gateway, a plurality of coal heating monitoring modules and a plurality of electric heating monitoring modules, the plurality of coal heating monitoring modules and the plurality of electric heating monitoring modules are wirelessly connected to the cloud server through the intelligent gateway, respectively, and a cloud database is further configured in the cloud server and is used for storing basic heating parameter data of coal heating users and electric heating users. The cloud database stores heat supply data of a plurality of coal heat supply users and heat supply data of electric heat supply users, wherein the heat supply data of the coal heat supply users comprise the distance of coal heat supply pipelines, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment failure frequency of the coal heat supply users; the heat supply data of the electric heat supply users comprise the distance of the electric heat supply pipelines, the indoor area of the electric heat supply users, the number of the electric heat supply pipelines and the equipment failure frequency of the electric heat supply users.
The coal heat supply monitoring modules are used for acquiring coal heat supply data of a plurality of coal heat supply users and transmitting the acquired coal heat supply data to the cloud server through the wireless gateway; the coal heat supply monitoring module comprises a coal usage monitoring unit, a coal heat supply flow monitoring unit, a coal heat supply output temperature monitoring unit and a coal heat supply input temperature monitoring unit; the coal usage monitoring unit is used for monitoring the total coal usage amount, the coal usage monitoring unit is used for weighing the total coal weight in a weight weighing mode, and then the usage amount can be obtained by weighing the used weight; the coal heat supply flow monitoring unit is used for monitoring the coal heat supply amount of a coal heat supply user, the coal heat supply flow monitoring unit is carried out by adopting a heat supply flowmeter, and the heat supply is generally carried out by adopting a hot water supply mode; the coal heat supply output temperature monitoring unit is used for monitoring the coal heat supply output temperature; the coal heat supply input temperature monitoring unit is used for monitoring the indoor temperature of a coal heat supply user. The coal heat supply output temperature monitoring unit and the coal heat supply input temperature monitoring unit are monitored by adopting temperature sensors.
The plurality of electric heating monitoring modules are used for acquiring electric heating data of a plurality of electric heating users and transmitting the acquired electric heating data to the cloud server through the wireless gateway; the electric heating monitoring module comprises an electricity consumption monitoring unit, an electric heating output temperature monitoring unit and an electric heating input temperature monitoring unit; the power consumption monitoring unit is used for monitoring the power consumption of the electric heat supply user and adopts an ammeter for metering; the electric heating output temperature monitoring unit is used for monitoring the output temperature of electric heating equipment; the electric heating input temperature monitoring unit is used for monitoring the indoor temperature of an electric heating user. The electric heating output temperature monitoring unit and the electric heating input temperature monitoring unit are realized by adopting temperature sensors.
The cloud server is used for comparing the obtained coal heat supply data with the obtained electric heat supply data to obtain coal heat supply and electric heat supply efficiency and safety comparison results, and transmitting the comparison results to the user terminal through the intelligent gateway.
A model building module is configured in the cloud server, and the model building module comprises a coal heat supply model building unit and an electric heat supply model building unit;
the coal heat supply model building unit is used for building a coal heat supply model, the coal heat supply model comprises a plurality of coal heat supply submodels, and the coal heat supply submodels are built on the basis of each coal heat supply user;
the electric heating model building unit is used for building an electric heating model, the electric heating model comprises a plurality of electric heating submodels, and the electric heating submodels are built on the basis of each electric heating user;
the coal heat supply model building unit is configured with a coal heat supply sub-model building strategy, and the coal heat supply sub-model building strategy comprises the following steps: classifying coal heat supply users based on the indoor areas of the coal heat supply users, classifying the coal heat supply users of which the indoor areas are smaller than a first area into first-stage coal heat supply users, and then classifying the coal heat supply users once every increasing of a first threshold area;
calculating the coal heat supply efficiency and the coal heat supply safety of the coal heat supply users in each grade, and substituting the total coal usage amount, the coal heat supply output temperature and the indoor temperature of the coal heat supply users into a coal heat supply efficiency formula to obtain an actual coal consumption value;
and (3) bringing the distance of coal heat supply pipelines of coal heat supply users, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment failure frequency of the coal heat supply users into a coal heat supply safety formula to obtain a coal heat supply risk value.
The coal heating efficiency formula is configured as follows:
wherein Pmsx is an actual coal consumption value, msz is a total coal consumption amount, mgr is a coal heat supply amount, M1 is a conversion coefficient between the coal consumption amount and the coal heat supply amount, tmsc is a coal heat supply output temperature, tmsr is a temperature in a coal heat supply user room, a1 is a coal consumption coefficient, a2 is a coal heat supply temperature conversion coefficient, and M1, a1 and a2 are all larger than zero, the coal consumption data can be converted through a1, and the temperature related to coal heat supply can be converted through a2, so that the coal heat supply system can be formedAnd mutually converting the matched numerical values.
The coal heat supply safety formula is configured as follows:
the larger the equipment failure frequency of the coal heat supply user is, the larger the coal heat supply risk value is, wherein Pmfx is the coal heat supply risk value, jmgr is the distance of a coal heat supply pipeline, bmgl is the number of the coal heat supply pipelines, smm is the indoor area of the coal heat supply user, pmg is the equipment failure frequency of the coal heat supply user, b1 is a coal heat supply parameter conversion coefficient, b2 is a coal heat supply failure conversion coefficient, and both b1 and b2 are greater than zero, parameters related to coal heat supply can be converted through b1, coal heat supply failure data can be converted through b2, and numerical values which can be compared and calculated with each other are formed.
The electric heating model building unit is configured with an electric heating sub-model building strategy, and the electric heating sub-model building strategy comprises the following steps: classifying the electric heating users based on the indoor areas of the electric heating users, classifying the electric heating users of which the indoor areas are smaller than a first area into first-stage electric heating users, and then classifying the first-stage electric heating users once every increasing of a first threshold area;
calculating the electric heating efficiency and the electric heating safety of the electric heating users in each grade, and substituting the electricity consumption of the electric heating users, the output temperature of electric heating equipment and the indoor temperature of the electric heating users into an electric heating efficiency formula to obtain an electric actual consumption value;
and (3) bringing the distance of the electric heating pipelines of the electric heating users, the indoor area of the electric heating users, the number of the electric heating pipelines and the equipment fault frequency of the electric heating users into an electric heating safety formula to obtain an electric heating risk value.
The electric heating efficiency formula is configured to:
wherein Pdsx is the actual consumption value of electricity, lyd is the electricity consumption, tdsc is the output temperature of the electric heating equipment, tdsr is the indoor temperature of the electric heating user, a3 is the electricity consumption coefficient, and a4 isThe electric heating temperature conversion coefficient, a3 and a4 are both larger than zero, electricity consumption can be converted through a3, and the temperature difference between the output temperature and the input temperature related to electric heating can be converted through a4 to form a numerical value capable of being calculated mutually;
the power supply heat safety formula is configured as follows:
the big electric heating risk value that obtains when electric heat supply user's equipment failure frequency is big also big, wherein, pdfx is electric heat supply risk value, jdgr is the distance of electric heat supply pipeline, bdgl is electric heat supply pipeline quantity, sdm is electric heat supply user's indoor area, pdg is electric heat supply user's equipment failure frequency, b3 is electric heat supply parameter conversion coefficient, b4 is electric heat supply fault conversion coefficient, and b3 and b4 all are greater than zero, can convert the parameter formation of electric heat supply through b3 and can assorted numerical value, can convert electric heat supply fault data through b4 and form can assorted numerical value.
The cloud server is also internally provided with a screening and sending module, the screening and sending module is provided with a screening and sending strategy, and the screening and sending strategy comprises the following steps: the method comprises the steps of obtaining the indoor area of a coal heat supply user, then calling the coal actual consumption value and the coal heat supply risk value of the coal heat supply user which is in the same level as the coal heat supply user and the electricity actual consumption value and the electricity heat supply risk value of the electricity heat supply user from a cloud server, and sending the called data to the user terminal through an intelligent gateway. The indoor areas of users at the same level are similar, so that the coal heating data and the electric heating data which are selected at the same level have better referential property.
In the second embodiment, referring to fig. 1 and fig. 3, a comparison module is added in the cloud server on the basis of the first embodiment, compared with the first embodiment, data sampling for coal heat supply users and electric heat supply users is added in the second embodiment, and by sampling and summarizing the same type of data, the comparison rationality of the data of the coal heat supply users and the electric heat supply users can be improved, so that the consumption of the coal heat supply process and the electric heat supply process and the accuracy of safety comparison are improved.
The cloud server is internally provided with a comparison module, the comparison module is provided with a comparison strategy, and the comparison strategy comprises the following steps: respectively randomly selecting data of coal actual consumption values and coal heat supply risk values of n groups of coal heat supply submodels from first-level coal heat supply users to ith-level coal heat supply users;
adding the selected groups of actual coal consumption values to obtain a total coal heat supply sampling consumption value, and adding the selected groups of coal heat supply risk values to obtain a total coal heat supply sampling risk value;
substituting the total value of the coal heat supply sampling consumption into a first consumption comparison formula to obtain a first consumption comparison value; substituting the total risk value of the coal heat supply sampling into a first risk comparison formula to obtain a first risk comparison value;
respectively and randomly selecting data of electric actual consumption values and electric heating risk values of n groups of electric heating sub-models from first-level electric heating users to ith-level electric heating users; the total number of samples is thus the value of i multiplied by n. n is less than the number of data in the group with the minimum number in each group of data, and the sampling effectiveness is guaranteed.
Adding the selected groups of electric actual consumption values to obtain an electric heating sampling consumption total value, and adding the selected groups of electric heating risk values to obtain an electric heating sampling risk total value;
substituting the total electric heating sampling consumption value into a second consumption comparison formula to obtain a second consumption comparison value; substituting the total risk value of the electric heating sampling into a second risk comparison formula to obtain a second risk comparison value;
and sending the first consumption comparison value, the second consumption comparison value, the first risk comparison value and the second risk comparison value to the user terminal through the intelligent gateway.
The first consumption comparison formula is configured to: pxh1= Zmxh × c1; the first risk alignment formula is configured to: pfx1= Zmfx × d1; the second consumption comparison formula is configured to: pxh2= Zdxh × c2; the second risk alignment formula is configured to: pfx2= Zdfx × d2; wherein Pxh1 is a first consumption comparison value, zmxh is a coal heat supply sampling consumption total value, c1 is a coal heat supply consumption total value comparison coefficient, pfx1 is a first consumption comparison value, zmfx is a coal heat supply sampling risk total value, d1 is a coal heat supply risk total value comparison coefficient, pxh2 is a second consumption comparison value, zdxh is an electric heat supply sampling consumption total value, c2 is an electric heat supply consumption total value comparison coefficient, pfx2 is a second consumption comparison value, zdfx is an electric heat supply sampling risk total value, d2 is an electric heat supply risk total value comparison coefficient, and c1, c2, d1 and d2 are respectively greater than zero. The coal heat supply sampling total consumption value and the electric heat supply sampling total consumption value can be matched through c1 and c2, and the coal heat supply sampling total risk value and the electric heat supply sampling total risk value can be matched through d1 and d2, so that the coal heat supply sampling total consumption value and the electric heat supply sampling total risk value are compared.
The working principle is as follows: the coal heat supply monitoring modules can be used for acquiring coal heat supply data of a plurality of coal heat supply users, then the acquired coal heat supply data is transmitted to the cloud server through the wireless gateway, the electric heat supply monitoring modules can be used for acquiring electric heat supply data of a plurality of electric heat supply users, and then the acquired electric heat supply data is transmitted to the cloud server through the wireless gateway; the obtained coal heat supply data and the obtained electric heat supply data are compared through the cloud server, the coal heat supply and electric heat supply efficiency and safety comparison results are obtained, the comparison results are transmitted to the user terminal through the intelligent gateway, a coal power change user can timely and accurately know the coal actual consumption and the coal heat supply safety before changing the coal power into the electricity power and the electric actual consumption and the electric heat supply safety after changing the coal power into the electricity power, the careful understanding of the user on the coal power change is improved, the overall monitoring of a heat supply system after changing the coal power into the electricity power is improved, and the use safety of the user is guaranteed.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (5)
1. A coal-to-electricity heating management monitoring system based on cloud service is characterized in that a comparison system comprises a cloud server, an intelligent gateway, a plurality of coal heating monitoring modules and a plurality of electric heating monitoring modules, wherein the coal heating monitoring modules and the electric heating monitoring modules are respectively in wireless connection with the cloud server through the intelligent gateway;
the coal heat supply monitoring modules are used for acquiring coal heat supply data of a plurality of coal heat supply users and transmitting the acquired coal heat supply data to the cloud server through the wireless gateway;
the plurality of electric heating monitoring modules are used for acquiring electric heating data of a plurality of electric heating users and transmitting the acquired electric heating data to the cloud server through the wireless gateway;
the cloud server is used for comparing the obtained coal heat supply data with the obtained electric heat supply data to obtain a comparison result of the efficiency and the safety of the coal heat supply and the electric heat supply, and transmitting the comparison result to the user terminal through the intelligent gateway;
a cloud database is configured in the cloud server, heat supply data of a plurality of coal heat supply users and heat supply data of electric heat supply users are stored in the cloud database, and the heat supply data of the coal heat supply users comprise the distance of coal heat supply pipelines, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment failure frequency of the coal heat supply users;
the heat supply data of the electric heat supply users comprise the distance of electric heat supply pipelines, the indoor area of the electric heat supply users, the number of the electric heat supply pipelines and the equipment fault frequency of the electric heat supply users;
the coal heat supply monitoring module comprises a coal usage monitoring unit, a coal heat supply flow monitoring unit, a coal heat supply output temperature monitoring unit and a coal heat supply input temperature monitoring unit;
the coal usage monitoring unit is used for monitoring the total coal usage; the coal heat supply flow monitoring unit is used for monitoring the coal heat supply amount of a coal heat supply user; the coal heat supply output temperature monitoring unit is used for monitoring the coal heat supply output temperature; the coal heat supply input temperature monitoring unit is used for monitoring the temperature in the coal heat supply user room;
the electric heating monitoring module comprises an electricity consumption monitoring unit, an electric heating output temperature monitoring unit and an electric heating input temperature monitoring unit;
the power consumption monitoring unit is used for monitoring the power consumption of the electric heat supply user; the electric heating output temperature monitoring unit is used for monitoring the output temperature of electric heating equipment; the electric heating input temperature monitoring unit is used for monitoring the indoor temperature of an electric heating user;
a model building module is configured in the cloud server, and the model building module comprises a coal heat supply model building unit and an electric heat supply model building unit;
the coal heat supply model building unit is used for building a coal heat supply model, the coal heat supply model comprises a plurality of coal heat supply submodels, and the coal heat supply submodels are built on the basis of each coal heat supply user;
the electric heating model building unit is used for building an electric heating model, the electric heating model comprises a plurality of electric heating submodels, and the electric heating submodels are built on the basis of each electric heating user;
the coal heat supply model building unit is configured with a coal heat supply sub-model building strategy, and the coal heat supply sub-model building strategy comprises the following steps: classifying coal heat supply users based on the indoor areas of the coal heat supply users, classifying the coal heat supply users with the indoor areas smaller than a first area as first-stage coal heat supply users, and then classifying the coal heat supply users into grades once increasing the first threshold area;
calculating the coal heat supply efficiency and the coal heat supply safety of the coal heat supply users in each grade, and substituting the total coal usage amount, the coal heat supply output temperature and the indoor temperature of the coal heat supply users into a coal heat supply efficiency formula to obtain an actual coal consumption value;
the distance of coal heat supply pipelines of coal heat supply users, the indoor area of the coal heat supply users, the number of the coal heat supply pipelines and the equipment failure frequency of the coal heat supply users are brought into a coal heat supply safety formula to obtain a coal heat supply risk value;
the coal heating efficiency formula is configured as follows:
wherein Pmsx is an actual coal consumption value, msz is a total coal usage amount, mgr is a coal heat supply amount, M1 is a conversion coefficient between the coal usage amount and the coal heat supply amount, tmsc is a coal heat supply output temperature, tmsr is a temperature in a coal heat supply user room, a1 is a coal consumption coefficient, a2 is a coal heat supply temperature conversion coefficient, and M1, a1 and a2 are all larger than zero;
the coal heat supply safety formula is configured as follows:
wherein, pmfx is coal heat supply risk value, jmgr is coal heat supply pipeline's distance, bmgl is coal heat supply pipeline quantity, smm is coal heat supply user's indoor area, pmg is coal heat supply user's equipment fault frequency, b1 is coal heat supply parameter conversion coefficient, b2 is coal heat supply fault conversion coefficient, and b1 and b2 are all greater than zero.
2. The cloud service-based coal-to-electricity and heat supply management and monitoring system according to claim 1, wherein the electric heat supply model building unit is configured with an electric heat supply submodel building strategy, and the electric heat supply submodel building strategy comprises: classifying the electric heating users based on the indoor areas of the electric heating users, classifying the electric heating users of which the indoor areas are smaller than a first area into first-stage electric heating users, and then classifying the first-stage electric heating users once every increasing of a first threshold area;
calculating the electric heating efficiency and the electric heating safety of the electric heating users in each grade, and substituting the electricity consumption of the electric heating users, the output temperature of electric heating equipment and the indoor temperature of the electric heating users into an electric heating efficiency formula to obtain an electric actual consumption value;
and (3) bringing the distance of the electric heating pipelines of the electric heating users, the indoor area of the electric heating users, the number of the electric heating pipelines and the equipment fault frequency of the electric heating users into an electric heating safety formula to obtain an electric heating risk value.
3. The cloud service-based coal-to-electricity heating management and monitoring system according to claim 2, wherein the electricity heating efficiency formula is configured as follows:
the method comprises the following steps that Pdsx is an electric actual consumption value, lyd is power consumption, tdsc is the output temperature of electric heating equipment, tdsr is the indoor temperature of an electric heating user, a3 is an electric consumption coefficient, a4 is an electric heating temperature conversion coefficient, and a3 and a4 are both larger than zero;
the power supply heat safety formula is configured as follows:
the system comprises a plurality of electric heating pipelines, pdfx, jdgr, bdgl, sdm, pdg, b3, b4, and Pdfx and Jdgr, wherein Pdgr is an electric heating risk value, jdgr is a distance of the electric heating pipelines, bdgl is the number of the electric heating pipelines, sdm is an indoor area of an electric heating user, pdg is an equipment fault frequency of the electric heating user, b3 is an electric heating parameter conversion coefficient, b4 is an electric heating fault conversion coefficient, and b3 and b4 are both greater than zero.
4. The system according to claim 3, wherein a comparison module is further configured inside the cloud server, and a comparison strategy is configured in the comparison module, and the comparison strategy includes: respectively randomly selecting data of coal actual consumption values and coal heat supply risk values of n groups of coal heat supply submodels from first-level coal heat supply users to ith-level coal heat supply users;
adding the selected groups of actual coal consumption values to obtain a total coal heat supply sampling consumption value, and adding the selected groups of coal heat supply risk values to obtain a total coal heat supply sampling risk value;
substituting the total value of the coal heat supply sampling consumption into a first consumption comparison formula to obtain a first consumption comparison value; substituting the total risk value of the coal heat supply sampling into a first risk comparison formula to obtain a first risk comparison value;
respectively and randomly selecting data of electric actual consumption values and electric heating risk values of n groups of electric heating sub-models from first-level electric heating users to ith-level electric heating users;
adding the selected groups of electric actual consumption values to obtain an electric heating sampling consumption total value, and adding the selected groups of electric heating risk values to obtain an electric heating sampling risk total value;
substituting the total value of the electric heating sampling consumption into a second consumption comparison formula to obtain a second consumption comparison value; substituting the total risk value of the electric heating sampling into a second risk comparison formula to obtain a second risk comparison value;
and sending the first consumption comparison value, the second consumption comparison value, the first risk comparison value and the second risk comparison value to the user terminal through the intelligent gateway.
5. The cloud service-based coal-to-electricity heating management and monitoring system according to claim 4, wherein the first consumption comparison formula is configured to: pxh1= Zmxh × c1; the first risk alignment formula is configured to: pfx1= Zmfx × d1; the second consumption comparison formula is configured to:
pxh2= Zdxh × c2; the second risk alignment formula is configured to: pfx2= Zdfx × d2; wherein Pxh1 is a first consumption comparison value, zmxh is a coal heat supply sampling consumption total value, c1 is a coal heat supply consumption total value comparison coefficient, pfx1 is a first consumption comparison value, zmfx is a coal heat supply sampling risk total value, d1 is a coal heat supply risk total value comparison coefficient, pxh2 is a second consumption comparison value, zdxh is an electric heat supply sampling consumption total value, c2 is an electric heat supply consumption total value comparison coefficient, pfx2 is a second consumption comparison value, zdfx is an electric heat supply sampling risk total value, d2 is an electric heat supply risk total value comparison coefficient, and c1, c2, d1 and d2 are respectively greater than zero.
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