Water and electricity mobile intelligent management system

Abstract

The invention discloses a water and electricity mobile intelligent management system, and relates to the technical field of water and electricity management. The system comprises the following components: a refined region division and function association module, an omnibearing environment data acquisition and integration module, a dynamic load monitoring and intelligent allocation strategy module, an environment adaptive hydroelectric equipment intelligent regulation and control module and a mobile terminal visual intelligent management platform. According to the invention, through the refined region division and function association module, a large-scale place is accurately divided into a plurality of sub-regions, and the operation characteristics and mutual relations of various kinds of hydroelectric equipment are defined in detail, so that the system can carry out personalized management according to the functional attributes and the power and water utilization modes of different regions, and meanwhile, the system is more intelligent. Environmental information and time data are collected and integrated in real time, the hydropower load condition of each sub-region is monitored, an intelligent allocation algorithm is started according to multiple factors to allocate hydropower resources when the load changes, and high efficiency and stability of the allocation process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of video surveillance, and particularly to a mobile intelligent management system for water and electricity. Background Art

[0002] In modern society, the management of water and electricity in large venues such as shopping malls, factories, multi-storey buildings, etc. has become a crucial task. These venues have large water and electricity consumption, and there is an urgent need for efficient utilization and reasonable allocation of resources. With the progress of technology, intelligent and automated management systems have gradually come into view, providing new solutions for water and electricity management. Especially driven by technologies such as the Internet of Things, big data, and artificial intelligence, the intelligent level of water and electricity management systems has been continuously improved, enabling more refined resource management and allocation.

[0003] Traditional water and electricity management methods mainly rely on manual inspections and fixed control systems. Manual inspections are difficult to achieve real-time monitoring and dynamic allocation of water and electricity resources, resulting in low management efficiency and inability to respond promptly to changes in water and electricity demands in each area. Secondly, fixed control systems lack flexibility and cannot perform personalized management according to the functional attributes and environmental factors of each area, leading to waste of water and electricity resources and unstable supply. In addition, traditional management methods also lack in-depth analysis of historical data and intelligent decision-making support, and cannot provide scientific and reasonable management suggestions for managers, restricting the improvement of water and electricity management levels.

[0004] In view of the above problems, it is necessary to optimize the existing mobile intelligent management system for water and electricity. Through refined area division and functional association, personalized management of water and electricity resources in different areas can be achieved, and based on comprehensive environmental data collection and integration and environment-adaptive intelligent control technology for water and electricity equipment, real-time monitoring, dynamic allocation, and intelligent control of water and electricity resources can be realized. Therefore, it is of great significance to develop a mobile intelligent management system for water and electricity that can comprehensively achieve the above characteristics. Summary of the Invention

[0005] The objective of the present invention is to make up for the deficiencies of the prior art and provide a mobile intelligent management system for water and electricity. It can divide large venues into multiple sub-areas through refined area division and function correlation modules, and construct exclusive water and electricity management modules according to the functional attributes and water and electricity usage patterns of each area. At the same time, the system also integrates multiple functional modules such as an all-round environmental data collection and integration module, a dynamic load monitoring and intelligent allocation strategy module, an environment-adaptive water and electricity equipment intelligent control module, and a mobile terminal visual intelligent management platform. Through collaborative work, it realizes the real-time monitoring, intelligent allocation, and efficient utilization of water and electricity resources. And through the application of big data processing and artificial intelligence algorithms, the system can accurately predict future water and electricity demand trends, put forward optimization suggestions, and help managers conduct refined operation and maintenance management and in-depth energy consumption analysis.

[0006] To solve the above technical problems, the present invention provides the following technical solution: A mobile intelligent management system for water and electricity, which includes the following components: a refined area division and function correlation module, an all-round environmental data collection and integration module, a dynamic load monitoring and intelligent allocation strategy module, an environment-adaptive water and electricity equipment intelligent control module, and a mobile terminal visual intelligent management platform;

[0007] The refined area division and function correlation module accurately divides the overall space into multiple sub-areas according to the functional attributes and water and electricity usage patterns of each area in the large venue, and constructs an exclusive water and electricity management mode for each sub-area, defining the operating characteristics and mutual relationships of various water and electricity equipment;

[0008] The all-round environmental data collection and integration module establishes a deep connection with weather stations, various types of environmental sensors, and intelligent time management systems, collects and integrates comprehensive environmental information and accurate time data in real time, and through big data processing technology, cleans, classifies, and analyzes the data, extracts key factors that have a significant impact on water and electricity management, and provides a data basis for subsequent intelligent decision-making;

[0009] The dynamic load monitoring and intelligent allocation strategy module uses intelligent electricity meters, water meters, and data collection terminals to continuously monitor the water and electricity loads of each sub-area in real time, obtains real-time load values, change rates, and historical load curves, and through a resource reserve assessment algorithm, calculates the remaining and allocable amounts of water and electricity resources in each area according to the water and electricity equipment capacity, historical usage data, and current load conditions of each sub-area. When the load of a certain sub-area exceeds the preset threshold, through the intelligent allocation algorithm, comprehensively considering the functional priorities of each area, the current load status, environmental factors, and water and electricity resource reserve conditions, it preferentially allocates backup water and electricity resources from relatively idle sub-areas with redundant resources. And during the allocation process, considering factors such as the resistance loss of the power transmission line, the pressure drop of the water pipe network, and the starting impact current of the equipment, it ensures the efficiency and stability of the allocation process through an optimized control strategy;

[0010] The intelligent regulation module of the environment - adaptive water and electricity equipment formulates personalized operation parameter adjustment strategies for water and electricity equipment in each sub - region according to the real - time collected environmental data and time information. At the same time, according to the seasonal change law and circadian rhythm, it plans in advance the operation plans of water and electricity equipment in each region, converts the generated regulation strategies into equipment control instructions, and sends them to the water and electricity equipment controllers in each sub - region through the communication interface;

[0011] The mobile - terminal visual intelligent management platform develops mobile - terminal applications for management personnel, provides a visual management interface. Management personnel can view the detailed water and electricity usage in each partition at any time and place through mobile phones or tablets, and it has a function of recording resource allocation. At the same time, based on big - data analysis and artificial intelligence algorithms, it provides optimization suggestions for management personnel.

[0012] Further, in the all - around environmental data collection and integration module, the multi - type sensors include temperature sensors, humidity sensors, light - intensity sensors, air - quality sensors, ultraviolet - index sensors, and noise sensors.

[0013] Furthermore, the all - around environmental data collection and integration module cleans, classifies, and analyzes the data through big - data processing technology, extracts key factors that have a significant impact on water and electricity management. The formula of its extraction algorithm is: where K ij represents the j - th key - factor index related to water and electricity management in the i - th region, T is the time - series length of data collection, ω t is the weight factor of time t, S is the number of environmental or other basic data variables directly related to this key factor, λ s is the influence weight coefficient of the s - th basic data variable, X ijs (t) is the value of the s - th basic data variable corresponding to the j - th key factor in the i - th region at time t, and R is the number of environmental or other adjustment factors related to this key factor.

[0014] Furthermore, the dynamic load monitoring and intelligent allocation strategy module calculates the remaining amount and allocable amount of water and electricity resources in each region through the resource reserve evaluation algorithm, according to the capacity of water and electricity equipment, historical usage data, and current load conditions in each sub - region. For the calculation of electric power resources, its formula is: where is the capacity of the power equipment in region k, is the power load of region k at the current moment t, is the allocable proportion coefficient of electric power resources. For the calculation of water resources, its formula is where is the water storage facility capacity of region k, is the water flow rate of region k at the current moment t, and Δt is the calculation time interval, is the coefficient of the adjustable proportion of water resources.

[0015] Furthermore, in the dynamic load monitoring and intelligent allocation strategy module, when the load of a certain sub-region exceeds the preset threshold, the intelligent allocation algorithm comprehensively considers the function priorities of each region, the current load status, environmental factors, and the reserve situation of hydropower resources, and preferentially allocates standby hydropower resources from relatively idle sub-regions with redundant resources. The formula of its intelligent allocation algorithm is: Among them, E ij represents the comprehensive evaluation value of allocating resources from region i to region j. The larger this value is, the more suitable it is for region i to allocate resources to region j as the allocation source region. C i is the function priority coefficient of region i, L i is the current load of region i, M i is the maximum load capacity of region i, λ is the weight coefficient of the influence of power transmission line loss, ΔU ij is the estimated voltage drop ratio due to line resistance when allocating power from region i to region j, μ is the weight coefficient of the influence of water pipe network pressure drop, which depends on the pipe network design and the tolerance of pressure drop, ΔP ij is the estimated pressure drop ratio in the water pipe network when allocating water from region i to region j, v is the weight coefficient of the influence of the starting inrush current of equipment, I sij is the relative value of the starting inrush current when allocating resources from region i to region j involving equipment startup, and n is the total number of regions where resources can be allocated.

[0016] Furthermore, the dynamic load monitoring and intelligent allocation strategy module considers factors such as power transmission line resistance loss, water pipe network pressure drop, and equipment startup inrush current. Among them, ΔU ij is the estimated voltage drop ratio due to line resistance when allocating power from region i to region j, and its calculation formula is Among them, R ij is the power transmission line resistance from region i to region j, I ij is the estimated allocated current, and its calculation formula is P ij is the estimated allocated power, U ij is the average voltage between region i and region j, and ΔP ij is the estimated pressure drop ratio in the water pipe network when allocating water from region i to region j, and its calculation formula is Among them, ρ is the density of water, f ij is the friction coefficient of the water pipe from region i to region j, L ij is the length of the water pipe, Q ijis the estimated water flow rate for allocation, D ij is the inner diameter of the water pipe.

[0017] Furthermore, the intelligent regulation module of the environment-adaptive water and electricity equipment formulates personalized operation parameter adjustment strategies for water and electricity equipment in each sub-region according to the real-time collected environmental data and time information. For air-conditioning equipment, according to the indoor-outdoor temperature difference, season and personnel activity conditions, by determining the cooling or heating power demand, it generates adjustment strategies for the air-conditioning temperature setting value, wind speed mode and start-stop time. For lighting equipment, according to the light intensity, it determines the lighting brightness adjustment plan and the on-off time strategy of the lamps. For ventilation equipment, according to the air quality and personnel density, it determines the regulation strategy for the ventilation volume and operation time.

[0018] Furthermore, when converting the regulation strategy into a control instruction, the intelligent regulation module of the environment-adaptive water and electricity equipment establishes a control instruction library for different equipment and adds a check code and an execution feedback mechanism. In the communication interface adaptation and transmission unit, encryption technology is used to ensure the security of the control instruction transmission and monitor the communication status in real time, and the regulation strategy and control instruction are optimized and adjusted according to the equipment execution result and the relevant information is recorded.

[0019] Furthermore, the mobile terminal visualization intelligent management platform can provide optimization suggestions for managers based on big data analysis and artificial intelligence algorithms, and its algorithm formula is: where C ij is the cost after the layout adjustment between region i and region j, c m is the m-th cost factor, x ijm is the corresponding cost factor weight or quantity, B ij is the benefit after the layout adjustment between region i and region j, b n is the n-th benefit factor, y ijn is the corresponding benefit factor weight or quantity, F ij is the comprehensive evaluation function for the layout adjustment between region i and region j, ω1 and ω2 are the weight coefficients of cost and benefit. By continuously optimizing the regional layout combination, make F ij the smallest, so as to obtain a better regional function layout adjustment plan. By evaluating the characteristics of water and electricity demand in each region under different functional layouts, the supply of water and electricity resources can be more accurately matched with the actual demand.

[0020] Compared with the prior art, this mobile intelligent management system for water and electricity has the following beneficial effects:

[0021] 1. The present invention divides large-scale venues precisely into multiple sub-regions through refined regional division and functional association modules, and defines in detail the operating characteristics and interrelationships of various types of water and electricity equipment, enabling the system to perform personalized management according to the functional attributes and electricity and water usage patterns of different regions. At the same time, it collects and integrates environmental information and time data in real time, monitors the water and electricity loads of each sub-region, and activates an intelligent allocation algorithm based on multiple factors to allocate water and electricity resources when the load changes, ensuring the efficiency and stability of the allocation process.

[0022] 2. The present invention, through an environment-adaptive intelligent control module for water and electricity equipment, formulates personalized operation parameter adjustment strategies for water and electricity equipment in each sub-region according to real-time collected environmental data and time information. It can not only flexibly adjust the operation parameters of water and electricity equipment according to environmental changes to achieve dynamic matching of water and electricity resources and environmental requirements, but also plan in advance the operation plans of water and electricity equipment according to the seasonal change rules and circadian rhythms, thus achieving the effects of intelligent energy conservation and consumption reduction and creating a comfortable environment.

[0023] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0025] Figure 1 It is a flow operation diagram of a mobile intelligent management system for water and electricity;

[0026] Figure 2 It is a flow chart of a mobile intelligent management system for water and electricity. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention objective, the following will, in combination with the accompanying drawings and preferred embodiments, describe in detail the specific embodiments, structures, features, and effects of the present invention as follows.

[0028] Embodiment 1

[0029] A large comprehensive shopping mall covers a vast area and has numerous stores, dining areas, entertainment facilities, and office management areas.

[0030] The shopping mall is divided into multiple sub - regions such as a clothing retail area, a dining area, a cinema entertainment area, a supermarket area, an office management area, etc. A water and electricity management module is constructed for each area. For example, in the dining area, the operating characteristics of equipment such as stoves, ovens, refrigerated cabinets, ice machines, etc. are clarified, as well as the flow rate and water temperature requirements of kitchen water - using equipment; in the entertainment area, the parameters and inter - relationships of equipment such as stage lights, sound systems, air - conditioning ventilation, etc. are determined.

[0031] Temperature sensors, humidity sensors, light intensity sensors, air quality sensors, and noise sensors are installed in various areas inside the shopping mall. At the same time, it is connected to the local weather station to obtain external weather information, and the business hours, holidays and other time information are determined through an intelligent time management system. Key factors that have a significant impact on water and electricity management are analyzed using big data processing technology. The formula for its extraction algorithm is: Among them, K ij represents the j - th key factor index related to water and electricity management in the i - th area. T is the length of the time series of data collection. ω t is the weight factor of time t. S is the number of environmental or other basic data variables directly related to this key factor. λ s is the influence weight coefficient of the s - th basic data variable. X ijs (t) is the value of the s - th basic data variable corresponding to the j - th key factor in the i - th area at time t. R is the number of environmental or other adjustment factors related to this key factor. For example, during high - temperature periods in summer, the air - conditioning energy consumption in the shopping mall is positively correlated with the outdoor temperature, and the change in the density of people inside the shopping mall will affect the air - conditioning load; the light intensity directly affects key factors such as the lighting brightness requirements in public areas.

[0032] Intelligent electricity meters and water meters are installed in each sub - region to monitor the water and electricity load in real - time. For example, during peak shopping hours on weekends or holidays, the water and electricity demands in the dining area and the entertainment area increase sharply. Through an intelligent allocation algorithm, the formula for its intelligent allocation algorithm is: Among them, E ij represents the comprehensive evaluation value of allocating resources from area i to area j. The larger this value, the more suitable it is for area i to allocate resources to area j as the source area. C i is the functional priority coefficient of area i. L i is the current load of area i. M i is the maximum load capacity of area i. λ is the influence weight coefficient of power transmission line losses. ΔU ij is the estimated proportion of voltage drop generated due to line resistance when allocating power from area i to area j. μ is the influence weight coefficient of water pipe network pressure drop, which depends on the pipe network design and the tolerance of pressure drop. ΔP ijis the estimated proportion of pressure drop in the water pipe network when water is allocated from area i to area j, v is the weight coefficient of the impact current of equipment startup, and I sij is the relative value of the impact current when the equipment involved in resource allocation from area i to area j starts up. n is the total number of areas where resources can be allocated. Considering the functional priorities of each area (for example, the priority of the fire protection facility area is the highest to ensure safe power use, and the priorities of the dining area and entertainment area are relatively high during peak business hours), the current load status, environmental factors (such as adjusting the load weight of the air-conditioning area at high temperatures), and the reserve situation of water and electricity resources, it is found that the water and electricity resources in the office management area are relatively idle and redundant during non-business hours. Therefore, some standby water and electricity resources are allocated to the dining area and entertainment area. During the allocation process, appropriate voltage compensation is calculated based on the resistance loss of the power transmission line, and the pressure drop of the water pipe network is considered to ensure the stable water pressure in the kitchen of the dining area, while avoiding the impact of the equipment startup impact current on the overall power system of the shopping mall.

[0033] According to the real-time collected environmental data and time information, when the sun is strong and the temperature is high in summer, the intelligent control system of the shopping mall automatically increases the air-conditioning cooling power in public areas and stores, and at the same time uses intelligent curtains to block the direct sunlight area and moderately reduces the lighting brightness in non-critical indoor areas (such as warehouses and logistics passages). The water and electricity supply is accurately increased according to the estimated cooling load. When the air quality is poor, the air purification equipment in the entertainment area is automatically turned on and different purification modes are automatically switched according to the pollution degree. At the same time, the air volume and operation time of the ventilation system are optimized to achieve the best balance between the efficient use of water and electricity resources and environmental comfort. In addition, according to the seasonal change law and circadian rhythm, the system automatically reduces the operation load of water and electricity equipment in public areas during non-business hours, such as turning off some elevators late at night and reducing the number of public area lights, to achieve intelligent energy conservation and consumption reduction and create a comfortable environment.

[0034] The shopping mall management personnel can log in to the mobile terminal application through a mobile phone or tablet computer, and can view the detailed water and electricity usage of each area at any time, including real-time usage data, historical usage curve analysis, cost detail statistics, etc.; intuitively present the comparison between the current load status and the historical load peak, the prediction of the load change trend and the load warning information; detailed records of the time, source area, target area, allocation volume and allocation reasons of each water and electricity resource allocation. The intelligent decision-making assistance function integrated in the platform, based on big data analysis and artificial intelligence algorithms, predicts the future water and electricity demand trend according to environmental changes, and proposes a regional function layout adjustment plan. Its algorithm formula is: Among them, C ij is the cost after the layout adjustment between area i and area j, c m is the mth cost factor, x ijm is the corresponding cost factor weight or quantity, B ijis the benefit after the layout adjustment between region i and region j, b n is the nth benefit factor, y ijn is the corresponding benefit factor weight or quantity, F ij is the comprehensive evaluation function for the layout adjustment between region i and region j. ω1 and ω2 are the weight coefficients of cost and benefit. By continuously optimizing the regional layout combination, make F ij minimal, so as to obtain a better regional function layout adjustment plan. By evaluating the characteristics of hydropower demand in each region under different functional layouts, the supply of hydropower resources can be more accurately matched with the actual demand. For example, it is recommended to layout some seasonal commodity sales areas adjacent to areas with lower air-conditioning energy consumption to reduce the overall air-conditioning energy consumption. Recommendations for the maintenance plan and upgrade suggestions of hydropower equipment are provided, such as reminding the filter replacement time of air-conditioning equipment in a certain area or suggesting replacing some high-energy-consuming lighting equipment with energy-saving lamps, which greatly facilitates the management personnel to carry out refined operation and maintenance management and in-depth energy consumption analysis, and improves the intelligent level and management efficiency of the mall's hydropower management.

[0035] Embodiment 2

[0036] A large manufacturing factory includes different functional areas such as production workshops, raw material storage areas, finished product storage areas, office areas, and employee living areas.

[0037] After the factory is divided into regions, the hydropower management module in the production workshop details the electricity consumption characteristics of various production equipment (such as CNC machine tools, stamping machines, welding equipment, etc.), as well as the demand for cooling water and cleaning water during the production process. The storage area clarifies the operating parameters and mutual relationships of lighting, ventilation, and dehumidification equipment to ensure a stable storage environment for goods. The office area focuses on the energy consumption management and environmental comfort control of equipment such as computers, printers, lighting fixtures, and air conditioners; the employee living area conducts hydropower management planning for dormitory appliances, cafeteria equipment, public bathrooms, etc.

[0038] Deploy environmental sensors in each region of the factory to collect data such as temperature, humidity, light intensity, and air quality, and connect with a weather station and an intelligent time management system to obtain more comprehensive information. Through big data analysis, it is concluded that in the production workshop, some precision production equipment has extremely high requirements for environmental temperature and humidity. Excessive temperature fluctuations or high humidity will affect product quality and equipment life, and the energy consumption of production equipment is closely related to the production task volume and environmental temperature; in the storage area, when the humidity is high during the rainy season, the operation of the dehumidification equipment is closely related to the humidity data and other key factor models.

[0039] Intelligent electricity meters and water meters are installed in each sub-region to monitor the load in real time for 24 hours. For example, during the peak production season, the water and electricity demand in the production workshop increases significantly. The intelligent allocation algorithm makes allocations based on the regional function priorities (the production workshop has the highest priority to ensure the smooth progress of production tasks), the current load status, environmental factors (such as the increased load weight of the air conditioners in the production workshop during high temperatures), and the water and electricity resource reserves. If it is found that there is relatively redundant water and electricity resources in the raw material storage area during the period of low raw material turnover, and the water and electricity consumption in the staff living area is relatively low during non-rest periods, then part of the water and electricity resources are allocated from these two areas to the production workshop. When allocating, factors such as the resistance loss of the power transmission line, the pressure drop of the water pipe network, and the starting inrush current of the equipment are fully considered. Through optimizing the control strategy, the efficiency and stability of the allocation process are ensured, effectively avoiding problems such as local overload tripping, insufficient water pressure, or excessive voltage fluctuations, and ensuring the continuity and reliability of the water and electricity supply for the entire factory.

[0040] According to the real-time environmental data and time information, in the hot summer, the production workshop automatically increases the air-conditioning cooling power to maintain a stable operating environment temperature for the equipment. At the same time, it dynamically adjusts the operating power of the production equipment according to the production task volume to optimize water and electricity consumption. In the storage area, during the rainy season with high humidity, the dehumidifier is started in a timely manner and the operating power is intelligently adjusted according to the humidity change to reasonably allocate power resources. In the office area, according to the indoor-outdoor temperature difference and the personnel activity situation, the air-conditioning temperature setting value and the wind speed mode are dynamically adjusted. At the same time, the sleep and wake-up times of office equipment such as computers are optimized to reduce standby power consumption. In the staff living area, the power supply of the lighting and electrical equipment in the dormitory area is automatically regulated according to the personnel's work and rest time. For example, when there is no one in the dormitory during the day, the power supply of some unnecessary electrical appliances is turned off. The public bathroom intelligently adjusts the hot water supply volume according to the use time period to achieve the balance between the efficient utilization of water and electricity resources and environmental comfort. In addition, the system plans in advance the operation plans of the water and electricity equipment in each area according to the seasonal change rules and the circadian rhythm. For example, in winter, the heating equipment in the production workshop is preheated in advance, and in summer, the air-conditioning system in the office area is precooled. During non-production or low-traffic periods, the operating load of the water and electricity equipment in the public area is automatically reduced to achieve intelligent energy conservation and consumption reduction and create a comfortable environment.

[0041] Factory managers can, through the mobile terminal visual intelligent management platform, view the detailed water and electricity usage of each area at any time and place, including the real-time electricity consumption power and water consumption of different equipment in each production workshop, the water and electricity consumption of lighting and environmental control equipment in the storage area, the details of water and electricity usage in the office area and living area, etc. Through the load curve display, they can intuitively understand the current load status, compare it with the historical load peak, predict the load change trend, and obtain load warning information. The platform details and records information such as the time, source area, target area, allocation volume, and allocation reason of each water and electricity resource allocation. The intelligent decision-making assistance function integrated in the platform, based on big data analysis and artificial intelligence algorithms, predicts the future water and electricity demand trend, such as estimating the growth rate of water and electricity demand in each production workshop in the next few months according to the production order plan; proposes a regional function layout adjustment plan, such as suggesting concentrating production processes with similar environmental requirements for more precise regulation of water and electricity resources, recommends maintenance and upgrade suggestions for water and electricity equipment, such as reminding that the motor of a certain production equipment needs regular maintenance or suggesting upgrading the old lighting system to an intelligent energy-saving lighting system, etc., which facilitates managers to carry out refined operation and maintenance management and in-depth energy consumption analysis, improves the intelligent level and management efficiency of factory water and electricity management, and ensures the stability and high efficiency of factory production operations.

[0042] The above are only the preferred embodiments of the present invention, and do not impose any form of limitation on the present invention. Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the disclosed technical content within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A hydropower mobility intelligent management system, characterized in that: The system includes the following components: refined regional division and function association module, all-round environmental data collection and integration module, dynamic load monitoring and intelligent allocation strategy module, environmental adaptive hydropower equipment intelligent control module and mobile terminal visual intelligent management platform; The refined area division and function association module divides the overall space into multiple sub-areas based on the functional attributes and electricity and water usage patterns of each area in a large venue, and builds a dedicated water and electricity management model for each sub-area, defining the operating characteristics and relationships of various types of water and electricity equipment; The all-round environmental data collection and integration module establishes deep connections with weather stations, multiple types of environmental sensors and intelligent time management systems, collects and integrates comprehensive environmental information and precise time data in real time, cleans, classifies and analyzes the data through big data processing technology, extracts key factors that have a significant impact on water and power management, and provides a data basis for subsequent intelligent decision-making; The dynamic load monitoring and intelligent allocation strategy module uses smart electricity meters, water meters and data acquisition terminals to implement uninterrupted real-time monitoring of the hydropower load in each sub-region, obtain the real-time value of the load, the rate of change and the historical load curve, and calculate the remaining amount and the amount of hydropower resources that can be allocated in each region according to the hydropower equipment capacity, historical usage data and current load conditions of each sub-region through the resource reserve evaluation algorithm. When the load of a sub-region exceeds the preset threshold, the intelligent allocation algorithm comprehensively considers the functional priority, current load status, environmental factors and hydropower resource reserves of each region, and preferentially allocates hydropower resources from relatively idle and redundant sub-regions. In the allocation process, the resistance loss of the power transmission line, the pressure drop of the water pipe network and the impact current of the equipment startup are considered, and the efficiency and stability of the allocation process are guaranteed by optimizing the control strategy; The environment-adaptive hydropower equipment intelligent control module formulates personalized operation parameter adjustment strategies for hydropower equipment in each sub-area based on real-time collected environmental data and time information, and plans the operation plan of hydropower equipment in each area in advance based on seasonal changes and circadian rhythms, converts the generated control strategy into equipment control instructions, and sends them to the hydropower equipment controllers in each sub-area through the communication interface; The mobile terminal visual intelligent management platform develops a mobile terminal application for managers, providing a visual management interface. Managers can view the detailed water and electricity usage of each partition anytime and anywhere through mobile phones or tablets, and it has a resource allocation record function. At the same time, it can provide optimization suggestions for managers based on big data analysis and artificial intelligence algorithms.

2. The intelligent management system for hydropower mobility according to claim 1 is characterized in that: In the all-round environmental data collection and integration module, the multiple types of sensors include temperature sensors, humidity sensors, light intensity sensors, air quality sensors, ultraviolet index sensors and noise sensors.

3. The intelligent management system for hydropower mobility according to claim 1 is characterized in that: The all-round environmental data collection and integration module cleans, classifies and analyzes the data through big data processing technology to extract key factors that have a significant impact on hydropower management. The formula of its extraction algorithm is: Among them, K ij represents the jth key factor index related to hydropower management in the i-th region, T is the time series length of data collection, ω t is the weight factor at time t, S is the number of environmental or other basic data variables directly related to the key factor, and λ s is the influence weight coefficient of the sth basic data variable, X ijs (t) is the value of the sth basic data variable corresponding to the jth key factor in the ith region at time t, and R is the number of environmental or other regulatory factors related to the key factor.

4. The intelligent management system for hydropower mobility according to claim 1 is characterized in that: The dynamic load monitoring and intelligent allocation strategy module calculates the remaining amount and the amount of water and electricity resources that can be allocated in each area through the resource reserve evaluation algorithm according to the hydropower equipment capacity, historical usage data and current load conditions of each sub-area. For the calculation of power resources, the formula is: in, is the capacity of power equipment in region k, is the power load of region k at the current time t, is the proportion coefficient of power resources that can be allocated. For water resources calculation, the formula is: in, is the water storage capacity of region k, is the water flow in area k at the current time t, Δt is the calculation time interval, It is the coefficient of water resource allocation ratio.

5. The intelligent management system for hydropower mobility according to claim 1 is characterized in that: In the dynamic load monitoring and intelligent allocation strategy module, when the load of a sub-region exceeds the preset threshold, the intelligent allocation algorithm comprehensively considers the functional priority of each region, the current load status, environmental factors and the water and electricity resource reserves, and preferentially allocates water and electricity resources from relatively idle sub-regions with redundant resources. The formula of the intelligent allocation algorithm is: Among them, E ij represents the comprehensive evaluation value of allocating resources from region i to region j. The larger the value, the more suitable it is for region i to allocate resources to region j as the allocation source region. i is the function priority coefficient of region i, L i is the current load of region i, M i is the maximum load capacity of region i, λ is the weight coefficient of power transmission line loss, ΔU ij is the estimated proportion of voltage drop due to line resistance when allocating power from area i to area j, μ is the weight coefficient of water pipe network pressure drop, which depends on the pipe network design and tolerance to pressure drop, ΔP ij is the estimated ratio of pressure drop in the water network when distributing water from area i to area j, v is the weight coefficient of the impact of the equipment startup impact current, I sij is the relative value of the inrush current when allocating resources from area i to area j involves equipment startup, and n is the total number of areas where resources can be allocated.

6. The intelligent management system for hydropower mobility according to claim 5, characterized in that: The dynamic load monitoring and intelligent deployment strategy module takes into account the resistance loss of the power transmission line, the pressure drop of the water pipe network and the equipment startup impact current factors, where ΔU ij is the estimated proportion of voltage drop due to line resistance when power is allocated from area i to area j. The calculation formula is Among them, R ij is the power transmission line resistance from region i to region j, I ij is the estimated dispatch current, calculated as P ij is the estimated allocated power, U ij is the average voltage between regions i and j, and ΔP ij is the estimated ratio of pressure drop in the water network when water is transferred from area i to area j. The calculation formula is: Where ρ is the density of water, f ij is the friction coefficient of the water pipe from area i to area j, L ij is the length of the water pipe, Q ij is the estimated water flow rate, D ij Is the inner diameter of the water pipe.

7. The intelligent management system for hydropower mobility according to claim 1, characterized in that: The environmentally adaptive hydropower equipment intelligent control module formulates personalized operating parameter adjustment strategies for hydropower equipment in each sub-area based on real-time collected environmental data and time information. For air-conditioning equipment, it generates air-conditioning temperature set points, wind speed modes, and start-stop time adjustment strategies by determining cooling or heating power requirements based on indoor and outdoor temperature differences, seasons, and personnel activities. For lighting equipment, it determines lighting brightness adjustment plans and lamp switching time strategies based on light intensity. For ventilation equipment, it determines ventilation volume and operating time control strategies based on air quality and personnel density.

8. The intelligent management system for hydropower mobility according to claim 1 is characterized in that: The environmentally adaptive hydropower equipment intelligent control module establishes a control instruction library for different devices and adds verification codes and execution feedback mechanisms when converting control strategies into control instructions. Encryption technology is used in the communication interface adaptation and transmission unit to ensure the security of control instruction transmission and monitor the communication status in real time. The control strategies and control instructions are optimized and adjusted according to the equipment execution results and relevant information is recorded.

9. The intelligent management system for hydropower mobility according to claim 1, characterized in that: The mobile terminal visualization intelligent management platform can provide optimization suggestions for managers based on big data analysis and artificial intelligence algorithms. The algorithm formula is: Among them, C ij is the cost of the layout adjustment between region i and region j, c m is the mth cost factor, x ijm is the corresponding cost factor weight or quantity, B ij is the benefit after the layout adjustment between region i and region j, b n is the nth benefit factor, y ijn is the corresponding benefit factor weight or quantity, F ij is the comprehensive evaluation function of the layout adjustment between region i and region j, ω1 and ω2 are the weight coefficients of cost and benefit, and by continuously optimizing the regional layout combination, F ij Minimize, thus obtaining a better regional functional layout adjustment plan. By evaluating the characteristics of hydropower demand in each region under different functional layouts, the supply of hydropower resources can be more accurately matched with actual demand.

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