Intelligent park energy management method and system based on artificial intelligence

Abstract

The invention discloses a smart park energy management method and system based on artificial intelligence, and the method comprises the steps: obtaining first information which is used for indicating a current weather condition; acquiring second information, wherein the second information is used for indicating historical weather conditions; generating a meteorological model according to the first information and the second information; acquiring third information, wherein the third information is used for indicating the visitor flow rate in the current time period; obtaining fourth information, wherein the fourth information is used for indicating the visitor flow rate in the historical time period; acquiring fifth information, wherein the fifth information is used for indicating the energy consumption in the current time period; acquiring sixth information, wherein the sixth information is used for indicating energy consumption in a historical time period; and performing information integration on the information by adopting artificial intelligence, and issuing a current optimal smart park energy management method instruction. Therefore, an artificial intelligence technology can be utilized, a comprehensive park energy consumption data acquisition system is established, manual intervention is reduced, the park energy efficiency management level is improved, the operation and maintenance cost is reduced, and energy conservation and emission reduction are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of smart park energy management, and specifically, to a smart park energy management method and system based on artificial intelligence. Background Art

[0002] With the development of social economy and the improvement of people's living standards, the requirements for the environment are getting higher and higher. As a part of the city, the park is one of the main places for residents to live. Therefore, how to achieve green, low-carbon and sustainable development has become the key direction of park development.

[0003] At present, in order to achieve the goal of energy saving and consumption reduction, parks generally adopt manual control to save energy by controlling the operating status of equipment in the park through human experience. However, this manual control method has the following problems:

[0004] (1) It requires a large amount of human and material resources;

[0005] (2) Due to the uneven level of personnel, it is impossible to achieve refined management, resulting in energy waste;

[0006] (3) It is difficult to detect and solve energy consumption abnormalities and other problems in a timely manner, resulting in low energy efficiency. Summary of the invention

[0007] The purpose of the present invention is to provide an artificial intelligence-based smart park energy management method and system to solve the problems raised in the above-mentioned background technology.

[0008] In order to solve the above technical problems, the present invention provides a technical solution: a smart park energy management method based on artificial intelligence, comprising the following steps:

[0009] 1) Acquiring first information, wherein the first information is used to indicate current weather conditions;

[0010] 2) obtaining second information, wherein the second information is used to indicate historical weather conditions; and generating a meteorological model based on the first information and the second information;

[0011] 3) obtaining third information, wherein the third information is used to indicate the flow of people in the current time period;

[0012] 4) obtaining fourth information, wherein the fourth information is used to indicate the flow of people in a historical time period;

[0013] 5) obtaining fifth information, wherein the fifth information is used to indicate energy consumption in a current time period;

[0014] 6) obtaining sixth information, wherein the sixth information is used to indicate energy consumption in a historical time period;

[0015] 7) Use artificial intelligence to integrate the first information, the second information, the third information, the fourth information, the fifth information, and the sixth information, and issue instructions for the current optimal smart park energy management method.

[0016] Optionally, before generating a meteorological model according to the first information and the second information, the method further includes: when both the first information and the second information meet preset conditions, performing an operation of generating a meteorological model according to the first information and the second information.

[0017] Optionally, before generating a crowd flow model according to the third information and the fourth information, the method further includes: when both the third information and the fourth information meet a preset condition, performing an operation of generating a crowd flow model according to the third information and the fourth information.

[0018] Optionally, before generating the energy consumption model according to the fifth information and the sixth information, the method further includes: when both the fifth information and the sixth information meet preset conditions, performing the operation of generating the energy consumption model according to the fifth information and the sixth information.

[0019] Optionally, the meteorological model in step 2) is used to predict weather conditions for a period of time in the future; the first information includes current temperature value, current humidity value, current wind speed, and current air pressure; the second information includes historical temperature value, historical humidity value, historical wind speed, and historical air pressure.

[0020] Optionally, in the step 4), a crowd flow model is generated according to the third information and the fourth information, wherein the crowd flow model is used to predict the flow of people in a future period of time.

[0021] Optionally, the fifth information and the sixth information in step 6) generate an energy consumption model, wherein the energy consumption model is used to predict energy consumption in a future period of time.

[0022] In the second aspect, the present invention also provides an artificial intelligence-based smart park energy management system, including a current weather condition acquisition module for acquiring first information, a current pedestrian flow acquisition module for acquiring third information, a current energy consumption acquisition module for acquiring fifth information, an information storage module for acquiring second information, fourth information and sixth information and storing the first information, third information and fifth information, and also including an artificial intelligence analysis module for integrating the first information, second information, third information, fourth information, fifth information and sixth information, and issuing instructions for the current optimal smart park energy management method.

[0023] Optionally, the artificial intelligence analysis module is Tongyi Qianwen.

[0024] Optionally, the information storage module is a memory, in which program instructions are stored; when the program instructions are executed, the artificial intelligence-based smart park energy management system executes the method described above.

[0025] The advantages of the present invention are: the energy management method and system of a smart park based on artificial intelligence provided by the present invention obtains the first information, wherein the first information is used to indicate the current weather conditions; obtains the second information, wherein the second information is used to indicate the historical weather conditions; generates a meteorological model according to the first information and the second information; obtains the third information, wherein the third information is used to indicate the flow of people in the current time period; obtains the fourth information, wherein the fourth information is used to indicate the flow of people in the historical time period; obtains the fifth information, wherein the fifth information is used to indicate the energy consumption in the current time period; obtains the sixth information, wherein the sixth information is used to indicate the energy consumption in the historical time period; uses artificial intelligence to integrate the first information, the second information, the third information, the fourth information, the fifth information, and the sixth information, and issues the current optimal energy management method instruction for the smart park. In this way, artificial intelligence technology can be used to establish a comprehensive park energy consumption data collection system, realize automatic collection and analysis of energy consumption data, reduce manual intervention, improve the energy efficiency management level of the park, reduce operation and maintenance costs, and save energy and reduce emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flowchart of the energy management method of smart park based on artificial intelligence.

[0027] Figure 2 This is a structural diagram of the smart park energy management system based on artificial intelligence. DETAILED DESCRIPTION

[0028] For purposes of the following detailed description, it is to be understood that the invention may assume various alternative variations and step sequences, except where expressly specified to the contrary.

[0029] Example

[0030] A smart park energy management method based on artificial intelligence includes the following steps:

[0031] S1. Acquire first information, wherein the first information is used to indicate current weather conditions;

[0032] Specifically, the first information includes but is not limited to the current temperature value, the current humidity value, the current wind speed, and the current air pressure.

[0033] S2. Acquire second information, wherein the second information is used to indicate historical weather conditions; and generate a meteorological model according to the first information and the second information;

[0034] Specifically, the second information includes but is not limited to historical temperature values, historical humidity values, historical wind speeds, and historical air pressure.

[0035] Also, meteorological models are used to predict weather conditions for a period of time in the future.

[0036] S3, obtaining third information, wherein the third information is used to indicate the flow of people in the current time period;

[0037] S4. Acquire fourth information, wherein the fourth information is used to indicate the flow of people in a historical time period;

[0038] S5. Acquire fifth information, wherein the fifth information is used to indicate energy consumption in a current time period;

[0039] S6. Acquire sixth information, wherein the sixth information is used to indicate energy consumption in a historical time period;

[0040] S7. Use artificial intelligence to integrate the first information, the second information, the third information, the fourth information, the fifth information, and the sixth information, and issue instructions for the current optimal smart park energy management method.

[0041] Specifically, the embodiment of the present application discloses a smart park energy management method based on artificial intelligence, by obtaining first information, wherein the first information is used to indicate the current weather conditions; obtaining second information, wherein the second information is used to indicate the historical weather conditions; generating a meteorological model according to the first information and the second information; obtaining third information, wherein the third information is used to indicate the flow of people in the current time period; obtaining fourth information, wherein the fourth information is used to indicate the flow of people in the historical time period; obtaining fifth information, wherein the fifth information is used to indicate the energy consumption in the current time period; obtaining sixth information, wherein the sixth information is used to indicate the energy consumption in the historical time period; using artificial intelligence to integrate the first information, the second information, the third information, the fourth information, the fifth information, and the sixth information, and issuing the current optimal smart park energy management method instructions. In this way, artificial intelligence technology can be used to establish a comprehensive park energy consumption data collection system, realize automatic collection and analysis of energy consumption data, reduce manual intervention, improve the park energy efficiency management level, and reduce operation and maintenance costs.

[0042] Optionally, before generating a meteorological model based on the first information and the second information, it also includes: when the first information meets a preset condition, or when the second information meets a preset condition, executing the operation of generating a meteorological model based on the first information and the second information.

[0043] Optionally, before generating a crowd flow model according to the third information and the fourth information, it also includes: when the third information meets a preset condition, or when the fourth information meets a preset condition, executing the operation of generating a crowd flow model according to the third information and the fourth information.

[0044] Optionally, before generating the energy consumption model according to the fifth information and the sixth information, it also includes: when the fifth information meets a preset condition, or when the sixth information meets a preset condition, executing the operation of generating the energy consumption model according to the fifth information and the sixth information.

[0045] Optionally, the meteorological model in step 2) is used to predict weather conditions for a period of time in the future; the first information includes current temperature value, current humidity value, current wind speed, and current air pressure; the second information includes historical temperature value, historical humidity value, historical wind speed, and historical air pressure.

[0046] Optionally, in the step 4), a crowd flow model is generated according to the third information and the fourth information, wherein the crowd flow model is used to predict the flow of people in a future period of time.

[0047] Optionally, the fifth information and the sixth information in step 6) generate an energy consumption model, wherein the energy consumption model is used to predict energy consumption in a future period of time.

[0048] The embodiment of the present application discloses an artificial intelligence-based smart park energy management system, including a current weather condition acquisition module for acquiring first information, a current traffic acquisition module for acquiring third information, a current energy consumption acquisition module for acquiring fifth information, an information storage module for acquiring second information, fourth information and sixth information and storing the first information, third information and fifth information, and also includes an artificial intelligence analysis module for integrating the first information, second information, third information, fourth information, fifth information and sixth information, and issuing instructions for the current optimal smart park energy management method. In this way, artificial intelligence technology can be used to establish a comprehensive park energy consumption data collection system, realize automatic collection and analysis of energy consumption data, reduce manual intervention, improve the park energy efficiency management level, and reduce operation and maintenance costs.

[0049] Optionally, the artificial intelligence analysis module is Tongyi Qianwen.

[0050] Optionally, the information storage module is a memory, in which program instructions are stored; when the program instructions are executed, the artificial intelligence-based smart park energy management system executes the method described above.

[0051] The application of the present invention in energy saving and emission reduction is as follows:

[0052] Smart Park Energy Management Method Based on Artificial Intelligence:

[0053] Data collection and monitoring: Various sensors installed in the park collect energy consumption data in real time, including electricity, water, gas, etc.

[0054] Using the Internet of Things technology, the collected data is transmitted to the energy management system for real-time monitoring and analysis.

[0055] Energy data analysis and forecasting: Use artificial intelligence algorithms to analyze collected energy data and explore patterns and trends in energy consumption.

[0056] An energy consumption prediction model is established through machine learning algorithms to predict future energy demand and provide a basis for energy management decisions.

[0057] Energy optimization and scheduling: Based on energy data analysis and prediction results, intelligent optimization algorithms are used to optimize the scheduling of energy equipment within the park.

[0058] For example, reasonably arrange the start and stop time of equipment and adjust the operating parameters of equipment to achieve efficient use of energy.

[0059] Intelligent control and energy-saving strategies: Use artificial intelligence technology to achieve intelligent control of energy equipment in the park, such as smart lighting, smart air conditioning, etc. Formulate energy-saving strategies, such as time-of-use electricity price strategy and demand response strategy, to encourage users to use energy when energy prices are low and reduce energy demand during peak hours.

[0060] Reduce energy consumption: Through real-time monitoring and analysis of energy consumption data, energy waste can be discovered in a timely manner and corresponding energy-saving measures can be taken.

[0061] Optimize the operating parameters and scheduling strategies of energy equipment, improve energy utilization efficiency and reduce energy consumption.

[0062] Reduce carbon emissions: Smart campus energy management systems can reduce energy consumption and indirectly reduce carbon emissions by optimizing the operation of energy equipment.

[0063] Improve energy management efficiency: The smart park energy management system based on artificial intelligence can realize automated energy management, reduce manual intervention, and improve energy management efficiency. The system can monitor energy consumption in real time, identify problems in time and deal with them, and improve the timeliness and accuracy of energy management.

[0064] In smart park energy management, the specific indicators for measuring weather conditions such as temperature, humidity, wind speed, and air pressure are as follows:

[0065] 1. Temperature value

[0066] Measurement indicators: Usually measured in degrees Celsius (℃).

[0067] Impact on energy management:

[0068] Impact on heating and cooling demand: When the temperature is low, the park's heating system needs to consume more energy to maintain the indoor temperature; when the temperature is high, the energy consumption of the cooling system increases. By monitoring the temperature value in real time, the operating parameters of the heating and cooling equipment can be adjusted according to the actual situation to achieve efficient use of energy.

[0069] Impact on equipment operating efficiency: Some equipment operates more efficiently within a certain temperature range. For example, electronic equipment works more stably at a suitable temperature and consumes less energy. Too high or too low a temperature may cause equipment failure, increase maintenance costs and energy consumption.

[0070] 2. Humidity value

[0071] Measurement indicators: expressed as percentage relative humidity (%RH).

[0072] Impact on energy management:

[0073] Impact on air conditioning system energy consumption: In a high humidity environment, the air conditioning system needs to consume more energy for dehumidification in order to reduce indoor humidity. Maintaining an appropriate humidity value can reduce the load on the air conditioning system and reduce energy consumption.

[0074] Impact on building structure and equipment life: Excessive humidity may cause corrosion of building structure, rust of equipment and other problems, increasing maintenance costs. At the same time, low humidity environment may cause static electricity problems and damage electronic equipment.

[0075] 3. Wind speed

[0076] Measurement indicators: in meters per second (m / s).

[0077] Impact on energy management:

[0078] Influence on natural ventilation effect: Reasonable use of wind speed can reduce indoor temperature through natural ventilation, reduce the use time of air conditioning system, and thus save energy. In smart parks, the operation status of ventilation equipment can be automatically adjusted according to changes in wind speed and direction to achieve the best natural ventilation effect.

[0079] Influencing wind power generation potential: If wind power generation equipment is installed in the park, the wind speed directly determines the output power of wind power generation. By monitoring wind speed, the operation of the wind power generation system can be optimized and energy output can be increased.

[0080] 4. Air pressure

[0081] Measurement indicator: hectopascal (hPa) as the unit.

[0082] Impact on energy management: Impact on the combustion efficiency of gas equipment: Changes in gas pressure will affect the combustion efficiency of gas equipment. Under different gas pressure conditions, the air intake and combustion parameters of the gas equipment need to be adjusted to ensure efficient operation of the equipment and reduce energy waste.

[0083] Impact on building ventilation: Air pressure difference can drive natural ventilation, but too large or too small air pressure difference may affect the ventilation effect. By monitoring air pressure changes, the design of the building's ventilation system can be optimized, ventilation efficiency can be improved, and energy consumption can be reduced.

[0084] To sum up, in the energy management of smart parks, accurate monitoring of weather conditions such as temperature, humidity, wind speed, and air pressure can provide an important basis for the formulation and optimization of energy management strategies, and achieve efficient use and sustainable development of park energy.

[0085] Meteorological model overview: The meteorological model is designed to provide accurate meteorological data forecasting and analysis for energy management in smart parks to optimize energy production, distribution and use. The model comprehensively considers meteorological factors such as temperature, humidity, wind speed, air pressure, and energy demand and supply in the park, and achieves efficient energy utilization and cost savings through data analysis and algorithm optimization.

[0086] In order to solve the problems of energy consumption anomaly and other problems that are difficult to find and solve in time, the data collection and processing of the meteorological model are as follows:

[0087] Install meteorological sensors: Install temperature, humidity, wind speed, air pressure and other meteorological sensors at different locations in the park to collect meteorological data in real time.

[0088] Access external meteorological data sources: obtain weather forecast data released by local meteorological departments, including temperature, humidity, wind speed, air pressure and other information, as well as weather trend forecasts for the next period of time.

[0089] Data cleaning: Clean and filter the collected meteorological data to remove outliers and noise to ensure the accuracy and reliability of the data.

[0090] Data analysis: Use data analysis techniques to conduct statistical analysis and trend forecasting of meteorological data, and extract useful information and features. For example, analyze the relationship between factors such as temperature, humidity, wind speed and energy demand, and establish mathematical models and forecasting algorithms.

[0091] Energy demand forecasting: Based on meteorological data and historical energy consumption data, an energy demand forecasting model is established. The model takes into account the impact of factors such as temperature, humidity, and wind speed on energy demand, and predicts the energy demand of the park in the future. Through energy demand forecasting, park managers can arrange energy production and supply plans in advance, optimize energy distribution and use, and avoid energy shortages and waste.

[0092] Energy production optimization: For renewable energy power generation systems in the park (such as solar photovoltaic power generation, wind power generation, etc.), meteorological models can provide real-time meteorological data and forecast information to optimize energy production efficiency. For example, the output power of solar photovoltaic power generation can be predicted based on light intensity and temperature, and the output power of wind power generation can be predicted based on wind speed, so as to adjust the operating parameters of power generation equipment and improve energy output.

[0093] Energy allocation and dispatch: Formulate energy allocation and dispatch strategies based on meteorological data and energy demand forecasts. Under different meteorological conditions, allocate energy reasonably and give priority to meeting the energy needs of key equipment and important areas. For example, in hot weather, give priority to ensuring the energy supply of air-conditioning systems; when the wind is strong, increase the output power of wind power generation to reduce dependence on traditional energy.

[0094] Implementation of energy-saving measures: Implement corresponding energy-saving measures based on the analysis results of the meteorological model. For example, natural ventilation can be used instead of air conditioning systems under suitable temperature and humidity conditions to reduce energy consumption; when there is sufficient sunlight, solar lighting systems can be used to reduce electricity consumption.

[0095] Model evaluation and optimization: Regularly evaluate and verify the meteorological model, and compare the difference between the model prediction results and the actual energy consumption. Evaluation indicators include prediction accuracy, energy saving rate, etc. According to the evaluation results, adjust and optimize the model to improve the accuracy and reliability of the model. With the development of the park and the changes in meteorological conditions, continuously collect new data and continuously optimize and improve the meteorological model. Introduce new algorithms and technologies to improve the prediction ability and adaptability of the model.

[0096] Unless otherwise specifically stated, terms such as processing, computing, calculating, determining, etc. may refer to one or more processing or computing, calculating, determining operations, and these operations may be implemented in software, hardware, firmware, or any combination thereof. The computer-readable medium used to practice some embodiments of the present application may be a non-transitory computer-readable medium. A non-transitory computer-readable medium may be any available medium that can be accessed by a computer. By way of example and not limitation, such a computer-readable medium may include

[0097] RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer. As used herein, magnetic disks and optical disks include compact disks (CDs), laser disks, optical disks, digital versatile disks (DVDs), floppy disks, and Blu-ray disks, where magnetic disks usually reproduce data magnetically, while optical disks use lasers to reproduce data optically. A combination of the above components can also be a computer-readable medium.

[0098] It should be noted that, although multiple instances of the device or module for action execution are mentioned in the above detailed description, it is not meant that all the instances must be used, as long as one of them is used, it will be beneficial to improve the effect. In addition, in the above, various operations are described with reference to several different positions. It should be noted that these positions are only for convenience, because each individual position may be unnecessary. That is, if appropriate, elements from different positions can be combined with each other to produce some embodiments.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0100] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. The energy management method of a smart park based on artificial intelligence is characterized by: The following steps are involved: 1) Acquiring first information, wherein the first information is current weather conditions; 2) obtaining second information, wherein the second information is historical weather conditions; generating a meteorological model according to the first information and the second information; 3) obtaining third information, wherein the third information is the flow of people in the current time period; 4) obtaining fourth information, wherein the fourth information is the flow of people in a historical time period; 5) obtaining fifth information, wherein the fifth information is energy consumption in the current time period; 6) obtaining sixth information, wherein the sixth information is energy consumption in a historical time period; 7) An artificial intelligence analysis module is used to integrate the first information, the second information, the third information, the fourth information, the fifth information, and the sixth information, and an instruction on the currently optimal smart park energy management method is issued.

2. The method for smart park energy management based on artificial intelligence according to claim 1 is characterized in that: Before generating a meteorological model according to the first information and the second information, the method further includes: when both the first information and the second information meet preset conditions, performing an operation of generating a meteorological model according to the first information and the second information.

3. The method for smart park energy management based on artificial intelligence according to claim 2 is characterized in that: Before generating a crowd flow model according to the third information and the fourth information, the method further includes: when the third information and the fourth information both meet a preset condition, performing an operation of generating a crowd flow model according to the third information and the fourth information.

4. The method for smart park energy management based on artificial intelligence according to claim 3 is characterized in that: Before generating the energy consumption model according to the fifth information and the sixth information, the method further includes: when both the fifth information and the sixth information meet preset conditions, performing an operation of generating the energy consumption model according to the fifth information and the sixth information.

5. The method for smart park energy management based on artificial intelligence according to claim 4 is characterized in that: The meteorological model in step 2) is used to predict weather conditions for a period of time in the future; the first information includes the current temperature value, the current humidity value, the current wind speed, and the current air pressure; the second information includes the historical temperature value, the historical humidity value, the historical wind speed, and the historical air pressure.

6. The method for smart park energy management based on artificial intelligence according to claim 5 is characterized in that: In the step 4), a crowd flow model is generated according to the third information and the fourth information, wherein the crowd flow model is used to predict the crowd flow in a future period of time.

7. The method for smart park energy management based on artificial intelligence according to claim 6 is characterized in that: The fifth information and the sixth information in step 6) generate an energy consumption model, wherein the energy consumption model is used to predict energy consumption in a future period of time.

8. The smart park energy management system based on artificial intelligence is characterized by: It includes a current weather condition acquisition module for acquiring the first information, a current pedestrian flow acquisition module for acquiring the third information, a current energy consumption acquisition module for acquiring the fifth information, an information storage module for acquiring the second information, the fourth information and the sixth information and storing the first information, the third information and the fifth information, and also includes an artificial intelligence analysis module for integrating and analyzing the first information, the second information, the third information, the fourth information, the fifth information and the sixth information, and issuing instructions for the currently optimal smart park energy management method.

9. The smart park energy management system based on artificial intelligence according to claim 8 is characterized in that: The artificial intelligence analysis module is Tongyi Qianwen.

10. The smart park energy management system based on artificial intelligence according to claim 9 is characterized in that: The information storage module is a memory, in which program instructions are stored; when the program instructions are executed, the artificial intelligence-based smart park energy management system executes the method described in any one of claims 1-7.

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