CN117575846A - Energy comprehensive service platform based on Internet of things - Google Patents
Energy comprehensive service platform based on Internet of things Download PDFInfo
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Abstract
The invention provides an energy comprehensive service platform based on the Internet of things, which comprises the following steps: the system comprises an application layer, a service layer, a data layer, a network layer and an equipment layer, wherein the equipment layer collects data and stores the data in the data layer through the network layer, the service layer analyzes the data in the data layer and uploads the data to the application layer with the same data standard and interface protocol, and the service layer realizes the analysis of public building energy consumption, the analysis of industrial energy consumption and the analysis of classified energy consumption; the process of analyzing the energy consumption of the public building comprises comprehensive and sub-term statistical analysis of various energy consumption of the public building in a specific past time period, analysis of variation trend of each energy consumption, analysis of energy consumption of each system and analysis of energy consumption of unit area, and by carrying out detailed analysis on the energy consumption of the building, the part or subsystem with high energy consumption can be found and improved, so that the energy efficiency of the whole building is improved.
Description
Technical Field
The invention relates to the technical field of comprehensive energy service, in particular to an comprehensive energy service platform based on the Internet of things.
Background
At present, the requirements of comprehensively improving the social energy efficiency level, promoting clean energy consumption, establishing a multi-element supply system, and promoting technical innovation, industrial innovation and business model innovation by taking green low carbon as a direction and promoting the formation of widely-cooperated energy ecology are met; at present, in order to adapt to the development of the sustainable development of energy, in response to strategic deployment of energy services, related enterprise companies push out intelligent service platforms capable of providing required functional applications and data information for energy users. However, most of the above intelligent platforms are single service platforms, which can only provide unilateral demand information for energy users, for example, can provide related services for energy users in the aspect of internet of vehicles service, and can provide related functions for energy users in the aspect of power demand. It can be seen that the energy users need to access more specialized service platforms if they want to obtain the resource information in all aspects. Therefore, the existing service platform cannot provide different requirements for different services for energy users; therefore, the invention provides an energy comprehensive service platform based on the Internet of things.
Disclosure of Invention
In order to solve the above problems, the present invention provides an energy comprehensive service platform based on the internet of things, so as to more exactly solve the above problems.
The invention is realized by the following technical scheme:
the invention provides an energy comprehensive service platform based on the Internet of things, which comprises the following steps: the system comprises an application layer, a service layer, a data layer, a network layer and an equipment layer, wherein the equipment layer collects data and stores the data in the data layer through the network layer, the service layer analyzes the data in the data layer and unifies data standards and interface protocols to upload the data to the application layer, and the service layer realizes the analysis of public building energy consumption, the analysis of industrial energy consumption and the analysis of classified energy consumption;
the process of analyzing the energy consumption of the public building comprises comprehensive and subentry statistical analysis, each energy consumption change trend analysis, each system energy consumption analysis and unit area energy consumption analysis of various energy consumption of the public building in a specific past time period;
analyzing the public building by adopting a building energy consumption analysis model, wherein the building energy consumption analysis model comprises the following components:
collecting historical energy consumption data of a building, wherein the historical energy consumption data comprises various energy consumption data of electricity, water, fuel gas and cold and hot energy sources, and the energy consumption data comprises daily, monthly or yearly energy consumption;
collecting design data, environmental data and electrical layout schemes of a building;
according to the design data, the environment data and the building structure, the exterior wall materials, the window types, the outdoor temperature, the humidity, the solar radiation and the equipment power information in the electrical layout scheme of the building, a thermal energy model of the building is obtained by using a preset thermodynamic mathematical model to perform thermal energy calculation and modeling treatment, and the thermal energy model is used for describing the heat distribution, the heat transmission and the interaction with the external environment inside the building.
Further, the energy comprehensive service platform based on the internet of things, the building energy consumption analysis model further comprises:
dividing the building into a plurality of subsystems, calculating energy consumption levels of different parts in the building by considering heat transmission and temperature variation difference in each subsystem, setting a building as X and n parts respectivelyThe thermal energy model in the building is:
；
wherein the method comprises the steps ofIs energy consumption and outputs energy, < >>Is the total energy in the air, +.>Is heat conduction energy, +.>Other energy;
according to the principle of heat conduction:
；
is the unit energy consumption of the building, < >>Is the heat inside the building, < >>Is the average temperature in the building, +.>Is the average temperature outside the building, and a is the sum of the interior spaces of the building.
Furthermore, the energy comprehensive service platform based on the Internet of things takes the interior of a building as a unified whole, the temperature distribution of each area in the interior of the building is uniform, and the energy consumption range of public building energy consumption information is comprehensively calculated;
the calculation formulas of the heat quantity are as follows:
；
；
where W is the ventilation, cpp is the air heat capacity, ft is the reduction coefficient, B is the exterior wall area, B is the heat difference per unit area, G is the solar radiation, fi is the solar gain coefficient of the glass, and S is the area of the glass.
Further, the energy comprehensive service platform based on the internet of things aims at finding out the parts needing improvement due to the fact that the heat conductivity coefficients of different parts in a building at different times and temperatures are different:
the method comprises the steps that a preset node analysis network is adopted to analyze thermal energy data of each part of a building in temperature and time respectively in two-dimensional coordinates, and the thermal energy data identified in the two-dimensional coordinates are gradient ascending or gradient descending;
judging whether the thermal energy data of one part of the building rises or falls along with the gradient of the adjacent part;
if yes, calculating the influence weight of heat conduction between adjacent parts, and reconstructing a two-dimensional coordinate to calibrate the heat conductivity coefficient of the part;
and judging whether the part needs to be improved according to whether the heat conductivity coefficient meets the preset requirement.
Further, the energy comprehensive service platform based on the internet of things can conduct heat to the part bearing low heat when being heated unevenly in a building, and the prior function of the interaction strength of the two is as follows:
；
wherein the method comprises the steps ofRepresenting a part of a building, < >>Representation and->Is->Representing the interaction strength of the two;
the interaction intensity is related to the heat quantity:
；
p is the difference in heat quantity between the two,and->Respectively indicate->And->K is the derivative of heat with respect to time or temperature, nt and mt each represent +.>And->The gradient of the gradient rise or gradient fall in the coordinates.
Further, the energy comprehensive service platform based on the internet of things, the industrial energy consumption analysis comprises:
comprehensive and itemized statistical analysis of various energy consumption: calculating statistics of comprehensive and fractional consumption of electricity, water, fuel gas and cold and hot energy according to granularity of a certain time;
analysis of various energy consumption change trend: displaying various energy consumption change trends in a chart mode;
analysis of various energy consumption homoratio and ring ratio: the same-ratio ring ratio analysis of various energy consumption according to year, month and day;
analysis of energy consumption ratio of various energy consumption systems: calculating and analyzing the energy consumption duty ratio of various energy consumption systems;
energy consumption analysis of each production workshop: calculating water, electricity, fuel gas and cold and heat energy consumption analysis and duty ratio of each workshop;
user energy carbon emission change analysis: and calculating the carbon emission of the user through the energy consumption data and analyzing the change trend of the carbon emission.
Further, the energy comprehensive service platform based on the internet of things, the analysis of the split energy consumption includes:
and (3) energy consumption analysis of a power distribution system: carrying out special statistical analysis on the electric energy quality, the electricity consumption parameter, the electricity consumption and the electricity saving quantity;
and (3) energy consumption analysis of the air compression system: carrying out special statistical analysis on the electricity consumption of the air compression system and the air compressor;
and (3) energy consumption analysis of a cold and hot system: carrying out special statistical analysis on the cold and hot consumption and the electricity consumption of the cooling and heating system;
and (3) energy consumption analysis of the lighting system: performing special energy consumption analysis on the electricity consumption of the lighting system;
and (3) energy consumption analysis of a boiler system: performing special analysis on the electricity consumption of the boiler;
elevator system energy consumption analysis: carrying out special statistical analysis on the electricity consumption of the elevator system;
and (3) analyzing a photovoltaic energy storage system: and carrying out special statistical analysis on the generated energy of the photovoltaic power and the energy storage system.
A computer device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is characterized in that the processor is used for any one of the energy comprehensive service platforms based on the internet of things when the processor executes the computer program.
A computer readable storage medium having stored thereon a computer program for any of the internet of things based energy comprehensive service platforms when executed by a processor.
The invention has the beneficial effects that:
the data acquisition and analysis capability is strong: the platform can collect a large amount of building energy consumption data through the equipment layer, and carry out deep analysis on the data through the business layer, including comprehensive energy consumption statistics, energy consumption change trend, system energy consumption analysis and the like, so that the building energy consumption condition is known more carefully.
And (3) a comprehensive building thermal energy analysis model: the platform adopts a comprehensive building energy consumption analysis model, and can more accurately describe heat distribution and heat transmission conditions in the building by combining historical energy consumption data, design data, environmental data and an electrical layout scheme, so that accurate monitoring and management of building energy utilization are realized.
Automated improvement advice: according to the analysis of the building thermal energy data by the analysis model, the platform can automatically judge which parts need improvement and give corresponding improvement suggestions, so that intelligent assistance of building energy management is realized.
Efficient energy management: through the analysis of the changed heat conduction coefficient and temperature distribution, the platform can help users find out the heat conduction path inside the building and perform effective energy distribution and management so as to improve the energy utilization efficiency and reduce the energy waste.
Drawings
Fig. 1 is a schematic structural diagram of an energy comprehensive service platform based on the internet of things of the invention;
fig. 2 is a schematic structural diagram of a computer device according to the present invention.
Detailed Description
In order to more clearly and completely describe the technical scheme of the invention, the invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, the present invention provides an energy comprehensive service platform based on the internet of things;
in one embodiment, an energy comprehensive service platform based on the internet of things comprises: the system comprises an application layer, a service layer, a data layer, a network layer and an equipment layer, wherein the equipment layer collects data and stores the data in the data layer through the network layer, the service layer analyzes the data in the data layer and unifies data standards and interface protocols to upload the data to the application layer, and the service layer realizes the analysis of public building energy consumption, the analysis of industrial energy consumption and the analysis of classified energy consumption;
the process of analyzing the energy consumption of the public building comprises comprehensive and subentry statistical analysis, each energy consumption change trend analysis, each system energy consumption analysis and unit area energy consumption analysis of various energy consumption of the public building in a specific past time period;
analyzing the public building by adopting a building energy consumption analysis model, wherein the building energy consumption analysis model comprises the following components:
collecting historical energy consumption data of a building, wherein the historical energy consumption data comprises various energy consumption data of electricity, water, fuel gas and cold and hot energy sources, and the energy consumption data comprises daily, monthly or yearly energy consumption;
collecting design data, environmental data and electrical layout schemes of a building;
according to the design data, the environment data and the building structure, the exterior wall materials, the window types, the outdoor temperature, the humidity, the solar radiation and the equipment power information in the electrical layout scheme of the building, a thermal energy model of the building is obtained by using a preset thermodynamic mathematical model to perform thermal energy calculation and modeling treatment, and the thermal energy model is used for describing the heat distribution, the heat transmission and the interaction with the external environment inside the building.
The building energy consumption analysis model further comprises:
dividing the building into a plurality of subsystems, calculating energy consumption levels of different parts in the building by considering heat transmission and temperature variation difference in each subsystem, setting a building as X and n parts respectivelyThe thermal energy model in the building is:
；
wherein the method comprises the steps ofIs energy consumption and outputs energy, < >>Is the total energy in the air, +.>Is heat conduction energy, +.>Other energy;
according to the principle of heat conduction:
；
is the unit energy consumption of the building, < >>Is the heat inside the building, < >>Is the average temperature in the building, +.>Is the average temperature outside the building, and a is the sum of the interior spaces of the building.
Taking the interior of a building as a unified whole, uniformly distributing the temperature of each area in the interior of the building, and comprehensively calculating and counting the energy consumption range of the public building energy consumption information;
the calculation formulas of the heat quantity are as follows:
；
；
where W is the ventilation, cpp is the air heat capacity, ft is the reduction coefficient, B is the exterior wall area, B is the heat difference per unit area, G is the solar radiation, fi is the solar gain coefficient of the glass, and S is the area of the glass.
Because the thermal conductivity coefficients of different parts in the building are different at different time and temperature, aiming at finding out the part needing improvement, for example, in a building, the thermal conductivity coefficient difference of the landing window in different time periods can be reflected in the presence or absence of direct sunlight, when the direct sunlight is generated in summer, the internal energy consumption such as the internal energy consumption of a refrigerating air conditioner can be enhanced, the internal energy consumption can be reduced in winter, and the building part of the landing window is improved in different time periods according to the time and temperature of the building part, so that the aim of saving energy is fulfilled, and the improvement measures are as follows: when the heat is unevenly heated in a building, the part with high heat bearing capacity can transfer heat to the part with low heat bearing capacity, and in the process of constructing a heat energy model, the heat transfer between adjacent parts can cause inaccuracy of the heat energy model, so that the calculated amount with high heat transfer coefficient originally is reduced, and the calculated amount with low heat transfer coefficient is increased;
the method comprises the steps that a preset node analysis network is adopted to analyze thermal energy data of each part of a building in temperature and time respectively in two-dimensional coordinates, and the thermal energy data identified in the two-dimensional coordinates are gradient ascending or gradient descending;
judging whether the thermal energy data of one part of the building rises or falls along with the gradient of the adjacent part;
if yes, calculating the influence weight of heat conduction between adjacent parts, and reconstructing a two-dimensional coordinate to calibrate the heat conductivity coefficient of the part;
and judging whether the part needs to be improved according to whether the heat conductivity coefficient meets the preset requirement.
When being heated unevenly in the building, the part that bears the heat quantity can be conducted the heat to the part that bears the heat quantity lowly, and the prior function of the interaction intensity of two is:
；
wherein the method comprises the steps ofRepresenting a part of a building, < >>Representation and->Is->Representing the interaction strength of the two;
the interaction intensity is related to the heat quantity:
；
p is the difference in heat quantity between the two,and->Respectively indicate->And->K is the derivative of heat with respect to time or temperature, nt and mt each represent +.>And->The gradient of the gradient rise or gradient fall in the coordinates.
In one embodiment, the industrial energy consumption analysis comprises:
comprehensive and itemized statistical analysis of various energy consumption: calculating statistics of comprehensive and fractional consumption of electricity, water, fuel gas and cold and hot energy according to granularity of a certain time;
analysis of various energy consumption change trend: displaying various energy consumption change trends in a chart mode;
analysis of various energy consumption homoratio and ring ratio: the same-ratio ring ratio analysis of various energy consumption according to year, month and day;
analysis of energy consumption ratio of various energy consumption systems: calculating and analyzing the energy consumption duty ratio of various energy consumption systems;
energy consumption analysis of each production workshop: calculating water, electricity, fuel gas and cold and heat energy consumption analysis and duty ratio of each workshop;
user energy carbon emission change analysis: and calculating the carbon emission of the user through the energy consumption data and analyzing the change trend of the carbon emission.
The industrial energy consumption analysis further comprises monitoring of the electrical load:
the method comprises the steps of collecting operation data of equipment by using an Internet of things technology, and displaying load, current, voltage, line voltage and power factor data in real time; and inquiring historical data according to the specified date and time period, and simultaneously comparing a plurality of time periods to calculate the power saving rate.
The monitoring of the electrical load further comprises electrical energy analysis:
analyzing three-phase current and voltage unbalance, harmonic distortion rate and power factor data of a user by combining the data, and alarming abnormal data; and simultaneously, the load condition of the transformer is monitored on line.
In this example, the industrial energy consumption was analyzed as shown in the following table:
the power distribution system is also realized:
overview of power saving benefits: comprehensively displaying the outline of accessed industrial enterprises, the quantity of the accessed enterprises, the power consumption condition overview (load trend and power consumption trend) of the enterprises, and the total power saving quantity;
and (3) monitoring an electric load: the method comprises the steps of collecting operation data of equipment by using an Internet of things technology, and displaying load, current, voltage, line voltage and power factor data in real time; the method comprises the steps of supporting to inquire historical data according to specified date and time periods, and simultaneously comparing a plurality of time periods to calculate the power saving rate; the load condition of the transformer can be monitored on line to prevent overload operation;
and (3) monitoring the electric energy quality: analyzing data such as three-phase current, voltage unbalance, harmonic distortion rate, power factor and the like of a user by combining the data, and alarming abnormal data; the peak, flat and valley electricity consumption conditions are monitored in real time, so that an enterprise can conveniently analyze the electricity consumption proportion to formulate an electricity saving scheme;
telegram table: generating a statistical report according to the actual electricity consumption data of the user, and supporting export; monitoring a digital ammeter on site, and providing a remote meter reading function;
and the electricity is safe: accessing sensors such as temperature, humidity, smoke feeling, cameras and the like, and receiving and displaying the environmental information of a power distribution room of an industrial enterprise in real time;
electricity-saving benefit: and carrying out statistics and calculation of electricity consumption and electricity saving quantity in a specified time period according to the checked electricity saving rate, carrying out analysis of the same ratio, the ring ratio, the trend and the like, supporting report generation and export.
In one embodiment, the analyzing the fractional energy consumption includes:
and (3) energy consumption analysis of a power distribution system: carrying out special statistical analysis on the electric energy quality, the electricity consumption parameter, the electricity consumption and the electricity saving quantity;
and (3) energy consumption analysis of the air compression system: carrying out special statistical analysis on the electricity consumption of the air compression system and the air compressor;
and (3) energy consumption analysis of a cold and hot system: carrying out special statistical analysis on the cold and hot consumption and the electricity consumption of the cooling and heating system;
and (3) energy consumption analysis of the lighting system: performing special energy consumption analysis on the electricity consumption of the lighting system;
and (3) energy consumption analysis of a boiler system: performing special analysis on the electricity consumption of the boiler;
elevator system energy consumption analysis: carrying out special statistical analysis on the electricity consumption of the elevator system;
and (3) analyzing a photovoltaic energy storage system: and carrying out special statistical analysis on the generated energy of the photovoltaic power and the energy storage system.
The air compression system energy consumption analysis comprises the following steps:
the system has self-learning capability, continuously optimizes the operation mode, detects the exhaust pressure temperature and the operation condition of the air compressor in real time, can manually control the air compressor, alarms the abnormal operation of the air compressor, records, stores and inquires the operation condition of the air compressor, and generates a daily report, a month report and an annual report;
the air compression system energy consumption analysis further comprises the following steps:
in a configuration mode, real-time operation parameters of each component part in the air compression system are displayed in a refinement mode, the pressure and the temperature of cooling water are monitored in real time, abnormal alarm of the cooling water is adjusted by adjusting the operation of the water pump according to the consumption of the cooling water, the water consumption condition is recorded, stored and inquired, a report is generated, and the cost of the cooling water in any time is calculated.
In one embodiment, analysis of the itemized energy consumption is illustrated: such as analysis of the cooling and heating system:
cold and hot overview: summarizing and analyzing the energy consumption of the cooling/heating system of the whole factory, and displaying the energy consumption trend and the carbon emission data according to the utilization conditions of each cooling/heating energy station in the areas and the classifications of charts and reports;
and (3) state monitoring: and displaying the positions of the cold supply/heat energy source stations according to the map, and clicking the positions of the cold supply/heat energy source stations on the map to enter the specific operation and maintenance monitoring of the station. And displaying the information such as the safe operation days of the cold supply/heat energy source station, the basic information of the energy source station, the operation electric quantity of the same day, the accumulated operation electric quantity, the operation efficiency and the like.
Clicking the station can enter the energy station interface to monitor the running state of the cooling/heating system (air conditioning system), the real-time environment state, the real-time safety state, the real-time alarm and the grading notification. And displaying relevant main monitoring information of the cooling/heating system. Comprises the following information:
monitoring the state of a refrigerating/heating host machine, the temperature and the pressure of water supply and return in real time;
monitoring the running state and inlet and outlet pressures of the water pump in real time;
monitoring the running state of a fan of the cooling tower in real time;
the real-time pushing equipment runs an alarm and the parameters are abnormal.
Through the monitoring function, the system has the monitoring and control on the running states, start-stop control, temperature setting, mode selection, parameter setting and the like of all control equipment, all air cabinet controllers and all air disk temperature controllers of the water system. Taking a chiller as an example, the monitoring content includes, but is not limited to, the following:
(1) The start and stop of a cooling fan of the cooling tower;
(2) Opening of a butterfly valve of the cooling water inlet tower;
(3) Cooling water inlet and return water temperature;
(4) Starting and stopping a cooling water pump;
(5) Starting and stopping a chilled water unit;
(6) The opening degree of a cooling water outlet butterfly valve of the water chilling unit;
(7) Starting and stopping a chilled water circulation pump;
(8) The temperature, pressure and flow of the chilled water supply and return water;
(9) Opening degree of the chilled water bypass valve, and the like.
And (3) energy-saving management: the system can calculate the end load use condition of the air conditioner, and after analysis and calculation, control instructions are issued to the water system controller to load or unload the water chilling unit, and the chilled water flow and the cooling water flow are regulated so as to balance the supplied flow and the energy demand;
and (3) control management: and carrying out partition management, namely dividing the terminal equipment of the air conditioner into areas according to the use characteristics, and adjusting the set temperature or the running state of the partial areas under the condition that the use comfort of the air conditioner is not affected.
According to the characteristics of air conditioner use in each area, the temperature controller is reserved to be started or shut down, so that the energy consumption can be saved, and the management can be convenient;
centralized management includes, but is not limited to, control of refrigerators, heat pumps, hot water units, fans, water pumps, cooling towers, heat exchangers, tanks, valves, and the like. Parameters such as the cooling capacity, heat, water quantity, air quantity, temperature, humidity, pressure and the like of the system are effectively controlled and regulated;
for example: the DDC control device near each unit in each production workshop of the factory is connected with the corresponding central management machine through a field bus, so that the start/stop state of each unit, the temperature, the humidity and the state value of each valve of the air supply can be displayed, the start/stop control signal of any unit is sent out, the set value of the air supply parameter is modified, and an alarm signal is sent out when any new fan unit works abnormally.
And (3) safety management: when the equipment fails, once the failure information is fed back to the computer, the monitoring software should give an alarm immediately and form a record, remind a user of removing the failure, and provide a basis for analyzing the problem in the future.
When the hot water is recovered to normally supply heat, the fan should be started, the fresh air valve is opened, and the normal operation of the unit is recovered.
The system should support the expansion of subsequent safety protection function, and provides targeted safety protection function for different refrigeration systems, taking screw type refrigeration compressor as an example, the safety control system should have the following control functions:
(1) Controlling the inlet and outlet temperature of refrigerant water of the evaporator;
(2) Controlling the temperature of cooling water entering and exiting the condenser;
(3) Controlling the evaporation temperature of an evaporator;
(4) Condensing temperature control of a condenser;
(5) Compressor discharge temperature control;
(6) Controlling the oil pressure difference;
(7) High pressure control;
(8) Low pressure control;
(9) And controlling the flow of the coolant.
Referring to fig. 2, in an embodiment of the present invention, there is further provided a computer device, which may be a server, and an internal structure thereof may be as shown in fig. 2. The computer device includes a processor, a memory, a display screen, an input device, a network interface, and a database connected by a system bus. Wherein the computer is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is for use with the platform when executed by a processor.
The platform comprises: the system comprises an application layer, a service layer, a data layer, a network layer and an equipment layer, wherein the equipment layer collects data and stores the data in the data layer through the network layer, the service layer analyzes the data in the data layer and unifies data standards and interface protocols to upload the data to the application layer, and the service layer realizes the analysis of public building energy consumption, the analysis of industrial energy consumption and the analysis of classified energy consumption;
the process of analyzing the energy consumption of the public building comprises comprehensive and subentry statistical analysis, each energy consumption change trend analysis, each system energy consumption analysis and unit area energy consumption analysis of various energy consumption of the public building in a specific past time period;
analyzing the public building by adopting a building energy consumption analysis model, wherein the building energy consumption analysis model comprises the following components:
collecting historical energy consumption data of a building, wherein the historical energy consumption data comprises various energy consumption data of electricity, water, fuel gas and cold and hot energy sources, and the energy consumption data comprises daily, monthly or yearly energy consumption;
collecting design data, environmental data and electrical layout schemes of a building;
according to the design data, the environment data and the building structure, the exterior wall materials, the window types, the outdoor temperature, the humidity, the solar radiation and the equipment power information in the electrical layout scheme of the building, a thermal energy model of the building is obtained by using a preset thermodynamic mathematical model to perform thermal energy calculation and modeling treatment, and the thermal energy model is used for describing the heat distribution, the heat transmission and the interaction with the external environment inside the building.
It will be appreciated by those skilled in the art that the architecture shown in fig. 2 is merely a block diagram of a portion of the architecture in connection with the present inventive arrangements and is not intended to limit the computer devices to which the present inventive arrangements are applicable.
An embodiment of the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above method. It is understood that the computer readable storage medium in this embodiment may be a volatile readable storage medium or a nonvolatile readable storage medium.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided by the present invention and used in embodiments may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method 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, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method 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, and all equivalent structures or equivalent processes using the descriptions and drawings of the present invention or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (9)
1. An energy comprehensive service platform based on the internet of things, which is characterized by comprising: the system comprises an application layer, a service layer, a data layer, a network layer and an equipment layer, wherein the equipment layer collects data and stores the data in the data layer through the network layer, the service layer analyzes the data in the data layer and unifies data standards and interface protocols to upload the data to the application layer, and the service layer realizes the analysis of public building energy consumption, the analysis of industrial energy consumption and the analysis of classified energy consumption;
the process of analyzing the energy consumption of the public building comprises comprehensive and subentry statistical analysis, each energy consumption change trend analysis, each system energy consumption analysis and unit area energy consumption analysis of various energy consumption of the public building in a specific past time period;
analyzing the public building by adopting a building energy consumption analysis model, wherein the building energy consumption analysis model comprises the following components:
collecting historical energy consumption data of a building, wherein the historical energy consumption data comprises various energy consumption data of electricity, water, fuel gas and cold and hot energy sources, and the energy consumption data comprises daily, monthly or yearly energy consumption;
collecting design data, environmental data and electrical layout schemes of a building;
according to the design data, the environment data and the building structure, the exterior wall materials, the window types, the outdoor temperature, the humidity, the solar radiation and the equipment power information in the electrical layout scheme of the building, a thermal energy model of the building is obtained by using a preset thermodynamic mathematical model to perform thermal energy calculation and modeling treatment, and the thermal energy model is used for describing the heat distribution, the heat transmission and the interaction with the external environment inside the building.
2. The energy comprehensive service platform based on the internet of things according to claim 1, wherein the building energy consumption analysis model further comprises:
dividing the building into a plurality of subsystems, calculating energy consumption levels of different parts in the building by considering heat transmission and temperature variation difference in each subsystem, setting a building as X and n parts respectivelyThe thermal energy model in the building is:
；
wherein the method comprises the steps ofIs energy consumption and outputs energy, < >>Is the total energy in the air, +.>Is heat conduction energy, +.>Other energy;
according to the principle of heat conduction:
；
is the unit energy consumption of the building, < >>Is the heat inside the building, < >>Is the average temperature in the building, +.>Is the average temperature outside the building, and a is the sum of the interior spaces of the building.
3. The energy comprehensive service platform based on the Internet of things according to claim 2, wherein the interior of a building is taken as a unified whole, the temperature distribution of each area in the interior of the building is uniform, and the energy consumption range of the public building energy consumption information is comprehensively calculated and counted;
the calculation formulas of the heat quantity are as follows:
；
；
where W is the ventilation, cpp is the air heat capacity, ft is the reduction coefficient, B is the exterior wall area, B is the heat difference per unit area, G is the solar radiation, fi is the solar gain coefficient of the glass, and S is the area of the glass.
4. The energy comprehensive service platform based on the internet of things according to claim 3, wherein, because of different thermal conductivity coefficients at different times and temperatures of different parts in a building, aiming at finding out the parts needing improvement:
the method comprises the steps that a preset node analysis network is adopted to analyze thermal energy data of each part of a building in temperature and time respectively in two-dimensional coordinates, and the thermal energy data identified in the two-dimensional coordinates are gradient ascending or gradient descending;
judging whether the thermal energy data of one part of the building rises or falls along with the gradient of the adjacent part;
if yes, calculating the influence weight of heat conduction between adjacent parts, and reconstructing a two-dimensional coordinate to calibrate the heat conductivity coefficient of the part;
and judging whether the part needs to be improved according to whether the heat conductivity coefficient meets the preset requirement.
5. The energy comprehensive service platform based on the internet of things according to claim 4, wherein when the building is heated unevenly, the part with high bearing heat can transfer heat to the part with low bearing heat, and the prior function of the interaction strength of the two is:
；
wherein the method comprises the steps ofRepresenting a part of a building, < >>Representation and->Is->Representing the interaction strength of the two;
the interaction intensity is related to the heat quantity:
；
p is the difference in heat quantity between the two,and->Respectively indicate->And->K is the derivative of heat with respect to time or temperature, nt and mt each represent +.>And->The gradient of the gradient rise or gradient fall in the coordinates.
6. The energy comprehensive service platform based on the internet of things according to claim 1, wherein the industrial energy consumption analysis comprises:
comprehensive and itemized statistical analysis of various energy consumption: calculating statistics of comprehensive and fractional consumption of electricity, water, fuel gas and cold and hot energy according to granularity of a certain time;
analysis of various energy consumption change trend: displaying various energy consumption change trends in a chart mode;
analysis of various energy consumption homoratio and ring ratio: the same-ratio ring ratio analysis of various energy consumption according to year, month and day;
analysis of energy consumption ratio of various energy consumption systems: calculating and analyzing the energy consumption duty ratio of various energy consumption systems;
energy consumption analysis of each production workshop: calculating water, electricity, fuel gas and cold and heat energy consumption analysis and duty ratio of each workshop;
user energy carbon emission change analysis: and calculating the carbon emission of the user through the energy consumption data and analyzing the change trend of the carbon emission.
7. The energy comprehensive service platform based on the internet of things according to claim 1, wherein the analyzing the fractional energy consumption comprises:
and (3) energy consumption analysis of a power distribution system: carrying out special statistical analysis on the electric energy quality, the electricity consumption parameter, the electricity consumption and the electricity saving quantity;
and (3) energy consumption analysis of the air compression system: carrying out special statistical analysis on the electricity consumption of the air compression system and the air compressor;
and (3) energy consumption analysis of a cold and hot system: carrying out special statistical analysis on the cold and hot consumption and the electricity consumption of the cooling and heating system;
and (3) energy consumption analysis of the lighting system: performing special energy consumption analysis on the electricity consumption of the lighting system;
and (3) energy consumption analysis of a boiler system: performing special analysis on the electricity consumption of the boiler;
elevator system energy consumption analysis: carrying out special statistical analysis on the electricity consumption of the elevator system;
and (3) analyzing a photovoltaic energy storage system: and carrying out special statistical analysis on the generated energy of the photovoltaic power and the energy storage system.
8. A computer device comprising a memory and a processor, the memory having stored therein a computer program, characterized in that the processor, when executing the computer program, is adapted to the internet of things based energy comprehensive service platform according to any one of claims 1 to 7.
9. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, is for the internet of things-based energy comprehensive service platform according to any one of claims 1 to 7.
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