Intelligent cooling and heating big data system

Abstract

The invention provides an intelligent cooling and heating big data system which solves the common problems existing in the processes of development, production, digital transformation and the like of existing heat pump application related enterprises that scientific and reasonable planning and simple equipment and system construction are lacked; the maintenance cost is high, the system stability is poor, the system fault loss is huge, and the salary of maintenance personnel is increased year by year. The system can be widely applied to the energy management field; the system specifically comprises a comprehensive management platform used for collecting and processing various data; the meteorological module is used for adopting the current-day meteorological data and analyzing the current-day meteorological data to adjust heat source output energy; the geographical environment analysis module is used for analyzing local climate and geographical position to adjust heat source output; the dynamic temperature control module is used for collecting temperature data of a heat source input end, a heat source output end and a user terminal and adjusting the heat source temperature in real time according to user requirements; the heat source comprises a photovoltaic heat source, an air source heat pump and a water and ground source heat pump.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy management, and in particular relates to an intelligent heating and cooling big data system. Background Art

[0002] Energy management system is a management system that measures energy consumption. With the development of energy management technology and the continuous improvement of energy management systems, users are no longer satisfied with simple measurement of energy consumption, but incorporate every link of the entire energy flow process into the energy management system. In recent years, geographic information technology or geographic information system has been used to establish a geographic information map data model for the environment in which the energy management system is located, and various energy flow pipelines, energy-consuming equipment, control valves, metering equipment, communication equipment, etc. in the energy management system have been geographically informatized, which has greatly improved the maintainability of the energy management system.

[0003] The common problems faced by most heat pump application-related enterprises in the process of development, production, and digital transformation are: 1. Lack of scientific and reasonable planning. The central heating system is a system engineering composed of multiple factors. The equipment and system are simple to build, the design is unprofessional, the heat is uneven, and the quality is difficult to guarantee. 2. The maintenance cost is high, the system stability is poor, the system failure losses are huge, and the maintenance personnel's salary increases year by year. 3. The operation and management cost is high, the system energy consumption is large, and energy leakage is difficult to detect. 4. Lack of automation and intelligent system supporting services. Summary of the invention

[0004] The purpose of the present invention is to solve the deficiencies of the above-mentioned technologies and provide a smart heating and cooling big data system.

[0005] To this end, the present invention provides a smart heating and cooling big data system, including an integrated management platform for collecting and processing various types of data; also including a meteorological module for adopting the meteorological data of the day and analyzing the meteorological data of the day to adjust the output energy of the heat source; a geographical environment analysis module for analyzing the local climate and geographical location to adjust the output of the heat source; a dynamic temperature control module for collecting temperature data of the heat source input end, output end and user terminal, and adjusting the heat source temperature in real time according to user needs; the heat source includes a photovoltaic heat source, an air source heat pump and a water source heat pump, which are controlled by the integrated management platform to adjust the output mode of each heat source.

[0006] Furthermore, the photovoltaic heat source uses PVT photovoltaic panels to achieve heat storage and energy storage.

[0007] Furthermore, it also includes a load prediction module, which is used to predict whether the total energy storage of the system itself will be exceeded in the future time period based on the heat source consumption; if exceeded, the city power is connected in time to supplement the power consumption.

[0008] Furthermore, it includes a multi-energy complementary control system, which is used to call on other heat sources to operate together when the heat source serving as the main energy supply cannot meet the user's demand on the day when providing energy alone; a peak-valley electricity operation module is used to reduce the consumption of heat source electricity and use energy storage units to supply electricity during peak and valley periods of electricity use, while ensuring that user demand can be met.

[0009] Furthermore, it also includes a leakage detection module for detecting the integrity of the water channels of each module; a fault warning module for real-time monitoring of the operating status of each module, and issuing a warning alarm in advance if the operating status tends to fail.

[0010] Furthermore, it also includes a user building balance module, which is used to schedule the flow distribution of the main pipeline and the branch pipeline to ensure the water supply balance of each building; the room temperature collection module is used to collect the room temperature in the user's room as a heat source output judgment parameter. If the outdoor temperature is lower, heat is output in time.

[0011] Furthermore, it also includes a fault reporting terminal, which is installed in the user's house. After the user finds a equipment fault, the user sends a warranty signal through the fault warranty terminal. The integrated management platform receives the warranty signal and reminds the staff to come to the house for inspection and maintenance; a remote locking module, the user can understand the current room temperature, water temperature and other parameters in the house through the app, and control the opening and closing of the indoor heating equipment through the app.

[0012] Furthermore, it also includes a financial management system for displaying the operating consumption data of each heat source in real time and calculating the total accumulated expenditure based on the corresponding unit price.

[0013] The present invention provides a smart heating and cooling big data system, which has the following beneficial effects:

[0014] The present invention combines energy consumption, geographical environment, precise meteorology, building load characteristics, user behavior habits and other system operation-related factors through a big data platform, utilizes the computing and AI capabilities of a smart energy platform, integrates building environment and thermal energy professional algorithms for comprehensive analysis, and forms an intelligent dynamic operation plan. According to weather, temperature, flow, heat, pressure, pipe network heat loss, building load characteristics, energy usage habits and other factors, the optimal system operation and balance plan and control strategy are formed in real time. Then, through precise control through the network and intelligent control system, dynamic and refined adjustment of the entire system of "source, network, load, storage and use" is achieved, ultimately achieving balance across the entire network, maintaining the most efficient operation of the energy station in the long term, and realizing "heating on demand" at the energy station, achieving efficient energy conservation and emission reduction. DETAILED DESCRIPTION

[0015] The present invention is further described below in conjunction with specific examples to help understand the content of the present invention. The methods used in the present invention are all conventional methods unless otherwise specified; the raw materials and devices used are all conventional commercially available products unless otherwise specified.

[0016] The present invention provides a smart heating and cooling big data system, including an integrated management platform for collecting and processing various types of data; a meteorological module for using the meteorological data of the day and analyzing the meteorological data of the day to adjust the output energy of the heat source; a geographical environment analysis module for analyzing the local climate and geographical location to adjust the output of the heat source; a dynamic temperature control module for collecting temperature data of the heat source input end, output end and user terminal, and adjusting the temperature of the heat source in real time according to user needs; the heat source includes a photovoltaic heat source, an air source heat pump and a water source heat pump, which are controlled by the integrated management platform to adjust the output mode of each heat source. The photovoltaic heat source uses PVT photovoltaic panels to achieve heat storage and energy storage.

[0017] By setting up a meteorological instrument to collect meteorological data such as the temperature and light intensity of the day, the power generation and heat output that the photovoltaic heat source can generate on the day are calculated. If the heat output on the day is higher than the user's daily demand, it will be stored in other heat sources; if the heat output on the day is lower than the user's daily demand, it will be supplemented by other heat sources.

[0018] Analyze the local geographical environment, calculate the amount of heat required to raise a certain mass of water to the required temperature through data such as altitude, atmospheric pressure, climate, average sunshine time, etc., and adjust the supply relationship of multiple heat sources in time according to the meteorological data of the day to ensure the overall needs of users.

[0019] It also includes a load prediction module, which is used to predict whether the total energy storage of the system will exceed the total energy storage of the system in the future based on the heat source consumption; if it exceeds, it will be connected to the mains in time to supplement the power consumption. The solar energy is converted into heat energy and electrical energy through PVT photovoltaic panels, and the heat energy is directly consumed by users; the electrical energy is directly stored for backup. If excess heat energy is generated, it can be stored in other forms.

[0020] It includes a multi-energy complementary control system, which is used to call on other heat sources to operate together when the heat source serving as the main energy source cannot meet the user's demand on the day when providing energy alone; the peak-valley electricity operation module is used to reduce the consumption of heat source electricity and use energy storage units to supply electricity during peak and valley periods of municipal electricity use while ensuring that user demand can be met.

[0021] The platform comprehensively monitors various operating data of the heating system, integrates geographical environment, accurate weather, behavioral needs, load characteristics and other big data, and accurately controls the whole system to operate well and efficiently in real time. It uses big data technology with a large number of professional algorithms and models to form a comprehensive dynamic optimization operation strategy for the heating system. It realizes digital monitoring of the whole system, refined management services, and intelligent system operation. After actual verification in many places, it can achieve energy saving of more than 20% in the heating system, reduce labor costs by more than 50%, reduce system failure rate by 50%, improve management efficiency by 80%, and save energy consumption costs of no less than 6 yuan per square meter per heating season.

[0022] In view of the complex status of the local pipeline network, the system data collection and control nodes are scientifically set up to monitor the operating data of the entire energy system, including various heat source units, water pumps, pipelines, and terminals, in real time. Combined with energy consumption, geographical environment, precise meteorology, building load characteristics, user behavior habits and other system operation-related factors, the computing and AI capabilities of the smart energy platform are used to integrate the building environment and thermal energy professional algorithms for comprehensive analysis to form an intelligent dynamic operation plan. According to factors such as weather, temperature, flow, heat, pressure, pipeline heat loss, building load characteristics, and people's energy habits, the system's optimal operation and balance plan and control strategy are formed in real time. Then, through the network and on-site intelligent control system, precise control is achieved to realize dynamic and refined adjustment of the entire system of source, network, load, storage, and use, and finally achieve the balance of the entire network, maintain the most efficient operation of the energy station in the long term, realize the "heating on demand" of the energy station, and achieve efficient energy conservation and emission reduction.

[0023] It also includes a leakage detection module for detecting the integrity of the water channels of each module; a fault warning module for real-time monitoring of the operating status of each module and issuing a warning alarm in advance if the operating status tends to fail.

[0024] It also includes a user building balance module, which is used to dispatch the flow distribution of the main pipeline and the branch pipeline to ensure the water supply balance of each building; the room temperature collection module is used to collect the room temperature of the user's room as a heat source output judgment parameter. If the outdoor temperature is lower, heat is output in time.

[0025] It also includes a fault reporting terminal, which is installed in the user's house. After the user finds a equipment fault, the user sends a warranty signal through the fault warranty terminal. The integrated management platform receives the warranty signal and reminds the staff to come to the house for inspection and maintenance; a remote locking module, the user can understand the current room temperature, water temperature and other parameters in the house through the app, and control the opening and closing of the indoor heating equipment through the app.

[0026] It also includes a financial management system for displaying the operating consumption data of each heat source in real time and calculating the total accumulated expenditure based on the corresponding unit price.

[0027] However, what is described above is only a specific embodiment of the present invention and should not be used to limit the scope of implementation of the present invention. Therefore, the replacement of equivalent components, or equivalent changes and modifications made according to the scope of protection of the present invention should still fall within the scope covered by the claims of the present invention.

Claims

1. A smart heating and cooling big data system, characterized by: It includes an integrated management platform for collecting and processing various types of data; it also includes a meteorological module for using and analyzing the meteorological data of the day to adjust the output energy of the heat source; Geographic environment analysis module, used to analyze local climate and geographical location to adjust heat source output; The dynamic temperature control module is used to collect temperature data from the heat source input, output and user terminal, and adjust the heat source temperature in real time according to user needs; the heat sources include photovoltaic heat sources, air source heat pumps and water source heat pumps, which are controlled through an integrated management platform to adjust the output mode of each heat source.

2. According to claim 1, the intelligent heating and cooling big data system is characterized by: Photovoltaic heat sources use PVT photovoltaic panels to achieve heat and energy storage.

3. The intelligent heating and cooling big data system according to claim 2 is characterized by: It also includes a load prediction module, which is used to predict whether the system's own energy storage capacity will be exceeded in the future based on the heat source consumption; if exceeded, it will be connected to the city power in time to supplement the power consumption.

4. The intelligent heating and cooling big data system according to claim 2 is characterized by: It includes a multi-energy complementary control system, which is used to call on other heat sources to operate together when the heat source serving as the main energy source cannot meet the user's demand on the day when providing energy alone; the peak-valley electricity operation module is used to reduce the consumption of heat source electricity and use energy storage units to supply electricity during peak and valley periods of municipal electricity use while ensuring that user demand can be met.

5. The intelligent heating and cooling big data system according to claim 3 is characterized by: It also includes a leakage detection module for detecting the integrity of the water channels of each module; a fault warning module for real-time monitoring of the operating status of each module and issuing a warning alarm in advance if the operating status tends to fail.

6. The intelligent heating and cooling big data system according to claim 3 is characterized by: It also includes a user building balance module, which is used to dispatch the flow distribution of the main pipeline and the branch pipeline to ensure the water supply balance of each building; the room temperature collection module is used to collect the room temperature of the user's room as a heat source output judgment parameter. If the outdoor temperature is lower, heat is output in time.

7. The intelligent heating and cooling big data system according to claim 6, characterized in that: It also includes a fault reporting terminal, which is installed in the user's house. After the user finds a equipment fault, the user sends a warranty signal through the fault warranty terminal. The integrated management platform receives the warranty signal and reminds the staff to come to the house for inspection and maintenance; a remote locking module, the user can understand the current room temperature, water temperature and other parameters in the house through the app, and control the opening and closing of the indoor heating equipment through the app.

8. The intelligent heating and cooling big data system according to claim 6 is characterized by: It also includes a financial management system for displaying the operating consumption data of each heat source in real time and calculating the total accumulated expenditure based on the corresponding unit price.