Energy-saving control system based on heat management of energy storage room

Abstract

The invention relates to the technical field of energy-saving control, and discloses an energy-saving control system based on heat management of an energy storage room, which comprises an energy storage room data acquisition module, a multi-source data processing module, a coefficient generation module, an intelligent analysis module and an energy-saving control module, according to the invention, through double-track acquisition of equipment operation states and environmental parameters, a three-dimensional energy consumption database is established, and cross validation and complementary analysis of equipment-environment data are realized; an energy consumption coefficient algorithm is created, an equipment energy consumption coefficient and an environment energy consumption coefficient generate a comprehensive energy consumption index, and a five-level threshold early warning mechanism is adopted to realize upgrading from passive response to active control; a three-dimensional visual billboard is built in, energy consumption grade distribution and an energy consumption abnormity thermodynamic diagram are presented in real time, and historical data backtracking and energy efficiency report one-key generation are supported; a complete control chain of'monitoring-analysis-decision-execution-feedback 'is formed, automatic triggering of hierarchical regulation and control strategies is supported, and quick response is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving control, more particularly to an energy-saving control system based on energy storage room thermal management. BACKGROUND

[0002] With the global energy storage installed capacity expected to reach 741 GWh by 2030, the energy-saving control system can achieve the "double carbon" target requirement through energy scheduling, and reduce operation and maintenance costs.

[0003] The traditional energy-saving control system uses a combination of temperature sensors and relays. When the detected ambient temperature exceeds the set threshold, the ventilation or refrigeration equipment is started, and when the threshold is lower, the heating device is activated. The energy consumption control is mostly fixed power output, and the system responds to real-time temperature changes. The equipment control and environmental monitoring are independent of each other, but have the disadvantages of single dimension, static threshold, control lag and management confusion, specifically:

[0004] The traditional system only monitors basic equipment parameters, lacks multi-source data such as environmental temperature and humidity, and thermal radiation intensity, resulting in a single dimension of energy consumption evaluation data.

[0005] Using fixed threshold to trigger equipment adjustment cannot dynamically respond to load changes, and this mode will cause the adjustment system to frequently start and stop.

[0006] The typical one-way monitoring-execution process lacks energy efficiency feedback links, and the delay time from data exceeding the standard to system response is long, during which environmental fluctuations directly affect the service life of the equipment.

[0007] Dependence on paper records, key parameters such as equipment energy consumption influencing parameters and environmental energy consumption influencing parameters cannot be presented and traced in real time.

[0008] Therefore, a method of full-dimensional data fusion, dynamic intelligent decision-making, closed-loop energy-saving control, and transparent management interface is needed to solve the above problems. SUMMARY

[0009] In order to overcome the above-mentioned defects of the prior art, the present application provides an energy-saving control system based on energy storage room thermal management to solve the problems existing in the background art.

[0010] To achieve the above-mentioned purpose, the present application provides the following technical solution: an energy-saving control system based on energy storage room thermal management, comprising:

[0011] An energy storage room data acquisition module for acquiring energy storage room thermal management equipment operating state related data and energy storage room environment related data;

[0012] A multi-source data processing module for cleaning and processing the collected data, calculating equipment energy consumption related indicators and environmental energy consumption related indicators;

[0013] Coefficient generation module: used to generate equipment energy consumption coefficients based on equipment status energy consumption related indicators, and to generate environmental energy consumption coefficients based on environmental energy consumption related indicators;

[0014] Intelligent analysis module: used to generate a comprehensive energy consumption index from the equipment energy consumption coefficient and the environmental energy consumption coefficient, and to set thresholds for classification;

[0015] Energy-saving control module: Used to take corresponding measures for energy-saving control based on the index classification results, and to visualize the energy consumption of equipment and the environment.

[0016] Intelligent energy management is achieved through the collaborative work of multiple modules. First, the data acquisition module monitors the equipment operating status and environmental parameters in real time. After data processing, the equipment energy consumption coefficient and environmental energy consumption coefficient are generated. Then, through intelligent analysis, a comprehensive energy consumption index is formed and classified. Finally, the energy-saving control module executes the classified control strategy and realizes energy consumption visualization, forming a closed-loop energy control system of "monitoring-analysis-decision-execution".

[0017] The technical effects and advantages of this invention are as follows:

[0018] 1. This invention establishes a three-dimensional energy consumption database by collecting data on both equipment operating status and environmental parameters, thereby enabling cross-validation and complementary analysis of "equipment-environment" data.

[0019] 2. This invention creates an energy consumption coefficient algorithm to generate a comprehensive energy consumption index from the energy consumption coefficient of the equipment and the energy consumption coefficient of the environment. It adopts a five-level threshold early warning mechanism to realize the upgrade from passive response to active control.

[0020] 3. This invention forms a complete control chain of "monitoring-analysis-decision-execution-feedback", supports automatic triggering of hierarchical control strategies, and achieves rapid response.

[0021] 4. This invention has a built-in 3D visualization dashboard that presents the distribution of energy consumption levels and heat maps of energy consumption anomalies in real time, and supports historical data backtracking and one-click generation of energy efficiency reports. Attached Figure Description

[0022] Figure 1 This is a structural block diagram of the present invention.

[0023] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The automatic unloading device for rotary kiln with self-cooling function involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Reference Figure 1 The present invention provides an energy-saving control system based on thermal management of energy storage rooms, including an energy storage room data acquisition module, a multi-source data processing module, a coefficient generation module, an intelligent analysis module, and an energy-saving control module.

[0026] Reference Figure 2 The specific implementation steps of the present invention include the following steps:

[0027] S1. Real-time data collection of operating status of thermal management equipment and environmental data of energy storage room through energy storage room data acquisition module;

[0028] It should be noted that the energy storage room data acquisition module collects the operating parameters of the energy storage room's thermal management control equipment in real time by deploying a sensor array, including start-up and shutdown status, load, and fault conditions; environmental parameters include the temperature, humidity, pressure, and light intensity of the energy storage room.

[0029] S2. The collected data is cleaned and processed by the multi-source data processing module to calculate equipment energy consumption-related indicators and environmental energy consumption-related indicators.

[0030] The multi-source data processing module analyzes and evaluates data distribution and anomaly characteristics, identifies outliers that deviate from the normal range according to the ±3σ principle, deletes outliers caused by errors, and retains extreme but reasonable values ​​to ensure data consistency and reliability. It is then integrated into the cleaning process and works with other processes to handle missing and duplicate values ​​to obtain the final data that enters the calculation process.

[0031] It should be noted that the energy consumption-related indicators of the equipment include start-stop state coefficient, working mode coefficient, and fault state coefficient.

[0032] The start / stop state coefficient is specifically as follows:

[0033] ;

[0034] Where Z is the start-stop state coefficient, which quantifies the continuity of the equipment's operating state. The coefficient range is [0,1]. The closer it is to 1, the higher the energy consumption of the equipment, indicating that it is continuously operating at high load.

[0035] Zt represents the real-time status of the device at the current moment. A shutdown status of 0 indicates no energy consumption, while a running status of 1 indicates the baseline energy consumption. λ represents the weight of the current status, which ranges from 0.7 to 0.8 since the current status plays a dominant role.

[0036] Zt-1 is the start-stop state coefficient of the previous moment. The historical operating state is introduced to avoid the coefficient jump caused by instantaneous start-stop. If it is necessary to suppress instantaneous fluctuations, the weight of the historical state 1-λ is higher, and the value of λ is in the range of 0.2-0.3.

[0037] The specific working mode coefficient is as follows:

[0038] ;

[0039] Where M is the working mode coefficient, which quantifies the energy efficiency of the device in its current state. The coefficient range is [c, 1]. The larger M is, the worse the energy efficiency.

[0040] It should be explained that c is a basic constant, representing the minimum energy consumption baseline of the device in standby mode. Even in a zero-load state, the system needs to maintain basic functions, and its value ranges from 0.1 to 0.2.

[0041] P represents the actual power, which is the effective power consumed by the equipment in real time; Pe represents the rated power, which is the design power of the equipment when it is running at full load; the ratio represents the load rate. When P is 0, it means that the equipment is idling. When P = Pe, it means that the equipment is running at full load.

[0042] k is the energy efficiency coefficient, which represents the nonlinear relationship between load rate and energy efficiency. k > 1 and its value ranges from 1.5 to 1.6. When the load is low, the coefficient decays slowly, reflecting the loss of inefficient operation. When the load is high, the coefficient increases rapidly, reflecting the deterioration of overload efficiency.

[0043] The fault state coefficient is specifically as follows:

[0044] ;

[0045] Where G is the fault state coefficient, which represents the severity of equipment failure and quantifies the negative impact of failure on energy consumption. The coefficient range is [0,1], and the larger G is, the more severe the failure.

[0046] It should be explained that Ai is the fault severity parameter, with a value between 0 and 1. The larger the value, the more severe the fault. Ti represents the fault repair time, reflecting the complexity of the corresponding fault repair. n is the number of faults, and the superposition effect amplifies the abnormal energy consumption. The minimum value function indicates that the maximum value is 1.

[0047] It should be noted that the environmental energy consumption related indicators include temperature and humidity coefficients, air pressure coefficients, and light intensity coefficients.

[0048] The temperature and humidity coefficients are specifically:

[0049] ;

[0050] Where W is the temperature and humidity coefficient, Ws is the real-time temperature and humidity deviation, and Wmax is the historical maximum temperature and humidity deviation threshold. The real-time temperature and humidity deviation is normalized, and the minimum value function prevents extreme environments from causing extreme values, so that the coefficient range is [0,1].

[0051] It should be noted that Ws is the real-time temperature and humidity deviation calculation method, specifically as follows:

[0052] ;

[0053] Ws represents the real-time temperature and humidity deviation. By quantifying the degree to which temperature and humidity deviate from the ideal range, it reflects the additional energy consumption required for the equipment to maintain a standard environment. The larger Ws is, the greater the degree to which the ambient temperature and humidity deviate from the standard, and the greater the energy consumption of the equipment.

[0054] It should be explained that T is the real-time temperature, reflecting the current ambient temperature, which affects the equipment's heat dissipation efficiency and energy consumption; Tz is the optimal operating temperature of the equipment, which is the ideal temperature value when the equipment has the highest energy efficiency. Deviations, whether too high or too low, will increase the energy consumption of temperature control.

[0055] μ1 represents the intensity of the effect of temperature deviation on energy consumption, with a value ranging from 0.02 to 0.03.

[0056] S represents the real-time humidity, reflecting the current ambient humidity, which affects the equipment's heat dissipation efficiency and energy consumption; Sz represents the optimal humidity, which is the ideal humidity when the equipment is most efficient.

[0057] μ2 represents the intensity of the effect of humidity deviation on energy consumption. Humidity has a weaker effect on energy consumption than temperature, and its value ranges from 0.01 to 0.02.

[0058] The pressure coefficient is specifically:

[0059] ;

[0060] Where Q is the air pressure coefficient, which quantifies the impact of air pressure deviation on equipment energy consumption. The larger the coefficient, the greater the energy consumption caused by air pressure abnormality. The value range is [0,1].

[0061] It should be explained that Qs is the real-time air pressure, that is, the current measured air pressure in the environment; Qb is the standard air pressure, which is the optimal air pressure standard for equipment operation. Deviating from this value increases energy consumption; the energy consumption sensitivity when deviating from the standard is enhanced by squaring; the impact is weak when the deviation is small, and aggravated when the deviation is large; γ is an adjustment factor that controls the magnitude of the deviation and avoids abnormal coefficient range, with a value range between 0.5 and 0.6.

[0062] It should be noted that when Qs < Qb, a correction term is added to specifically compensate for the increase in energy consumption caused by the loss of equipment intake pressure and the decrease in heat dissipation efficiency due to low air pressure. The value of the correction term is between 0.1 and 0.2, and they are directly added together.

[0063] The light intensity coefficient is specifically:

[0064] ;

[0065] Where D is the illuminance coefficient, which quantifies how ambient light affects the thermal radiation of the energy storage room and indirectly affects the load of the equipment during operation. The formula normalizes the real-time illuminance coefficient to a value range of [0,1]. The maximum value function makes D 0 when Ds≤Db, indicating that the illuminance has no effect and no additional energy consumption is required. When D>0, the stronger the illuminance, the greater the load on the equipment and the higher the energy consumption.

[0066] It should be explained that Ds is the real-time light intensity, i.e. the current ambient light intensity; Db is the standard light intensity for thermal management, and not exceeding this value indicates no thermal radiation impact; Dmax is the local historical maximum light intensity; η is the heat absorption efficiency coefficient, which is related to the surface material of the energy storage room, and its value ranges from 0.2 to 0.5.

[0067] S3. Generate equipment energy consumption coefficients based on equipment status energy consumption related indicators and environmental energy consumption related indicators through the coefficient generation module;

[0068] It should be specifically noted that the energy consumption coefficient of the aforementioned equipment is as follows:

[0069] ;

[0070] Where B is the equipment energy consumption coefficient, which quantifies the overall energy efficiency of the thermal management equipment in the energy storage room. Its value range is [0,1]. The closer B is to 1, the higher the equipment energy consumption and the lower the energy efficiency, caused by continuous high-load operation, inefficient load conditions, or serious malfunctions. The closer B is to 0, the more it reflects that the equipment is in an energy-efficient state.

[0071] It needs to be explained that the Z-start / stop state coefficient quantifies the impact of equipment operation continuity on energy consumption. It is a fundamental determinant of energy consumption; shutdown represents zero energy consumption, while instantaneous start-stop consumes significant energy and is given the highest weight. The value of ωq ranges from 0.4 to 0.5.

[0072] M is the operating mode coefficient, which is directly related to energy efficiency due to the load rate. The weight ωm ranges from 0.3 to 0.4.

[0073] G is the fault state coefficient. Faults are abnormal states with low frequency of occurrence and the lowest weight is given to avoid interfering with normal energy efficiency assessment. The value of ωg ranges from 0.1 to 0.2.

[0074] It should be specifically noted that the environmental energy consumption coefficient is as follows:

[0075] ;

[0076] H is the environmental energy consumption coefficient, which quantifies the load pressure of the external environment on the thermal management system of the energy storage room. Its value range is [0,1]. The larger the value, the greater the additional energy consumption caused by environmental conditions.

[0077] It should be explained that W is the temperature and humidity coefficient, which directly affects the heat dissipation efficiency and material properties of the equipment and is a fundamental variable for energy consumption control. It is directly related to the core thermodynamic performance of the equipment and has a high degree of persistence in affecting energy consumption, so it is given the highest weight. The weight ωw ranges from 0.5 to 0.6.

[0078] Q is the air pressure coefficient. Changes in air pressure affect air density and heat exchange efficiency, thus affecting the stability of equipment operation. Due to large regional differences, flexible adjustments are needed. It is stable in the long term and has few sudden impacts. The value of ωq is between 0.2 and 0.4. The weight of the impact on energy consumption in plateau areas needs to be increased.

[0079] D is the illuminance coefficient. Illuminance indirectly increases energy consumption through thermal radiation; it only affects the exterior of buildings and indirectly affects equipment. The value of ωd ranges from 0.1 to 0.2.

[0080] S4. The intelligent analysis module generates a comprehensive energy consumption index from the equipment energy consumption coefficient and the environmental energy consumption coefficient, and sets thresholds for classification.

[0081] It should be specifically noted that the comprehensive energy consumption index is as follows:

[0082] ;

[0083] E represents the comprehensive energy consumption index, which maps the equipment operating status and environmental impact factors into a dimensionless value, directly reflecting the overall energy efficiency level of the energy storage room's thermal management system.

[0084] It should be explained that B is the equipment energy consumption coefficient, which reflects the equipment's own energy efficiency, including start-up and shutdown losses, load rate, and operating efficiency, and directly affects the basic energy consumption level. Since the equipment status has a more direct and dominant impact on energy consumption, it is given a higher weight, with the weight α ranging from 0.6 to 0.8.

[0085] H is the environmental energy consumption coefficient, which quantifies the external environmental load. It indirectly increases equipment energy consumption through temperature, humidity, pressure, and light intensity. The environment affects the equipment through indirect load and serves as an auxiliary factor. The weight β ranges from 0.2 to 0.4.

[0086] It should be noted that the weights of both are adaptively adjusted according to the season. During the high temperatures of summer, the environmental weight reaches its highest level, while during the low temperatures of winter, the equipment weight reaches its highest level.

[0087] It should be specifically noted that setting thresholds and classifying the comprehensive energy efficiency index involves the following steps:

[0088] When E≤a, the system is at level 1 energy efficiency and is in its optimal operating state.

[0089] When a < E ≤ b, it is a level 2 energy efficiency, which meets the energy-saving requirements;

[0090] When b < E ≤ c, it is a level 3 energy efficiency, which meets the basic usage standards;

[0091] When c < E ≤ d, it is a level 4 energy efficiency, exceeding the energy consumption limit;

[0092] When E > d, it is a Level 5 energy efficiency, which is a serious deviation from the standard.

[0093] The value of a ranges from 0.2 to 0.3, the value of b ranges from 0.4 to 0.5, the value of c ranges from 0.6 to 0.7, and the value of d ranges from 0.8 to 0.9.

[0094] S5. The energy-saving control module takes corresponding measures to control energy consumption based on the index classification results and visualizes the energy consumption of equipment and the environment.

[0095] It should be noted that when the comprehensive energy efficiency index is Level 1, the existing operating status should be maintained without additional intervention. The optimal operating parameters should be recorded as a reference benchmark, and the visualization interface should display a green indicator.

[0096] When the comprehensive energy efficiency index is level 2, the adaptive algorithm is activated to automatically adjust the operating parameters, and an energy efficiency diagnostic report is submitted every quarter. The visualization interface displays a blue warning and optimization suggestions.

[0097] When the comprehensive energy efficiency index is level three, energy-saving renovations will be mandatory and must be completed within a specified period.

[0098] Install equipment to monitor abnormal wear and tear, automatically generate maintenance work orders, and reduce downtime due to malfunctions; establish optimization models to simulate load optimization methods; utilize and transform waste energy, add heat storage tanks to the waste heat recovery system, store energy at night for use in daytime processes, and improve heat recovery rate; display yellow warnings and energy efficiency comparison curves on a visual interface.

[0099] When the comprehensive energy efficiency index is level four, production capacity is restricted to operate at reduced load, and equipment is updated simultaneously, with key monitoring; a dynamic rotation mode for high-energy-consuming units is adopted, with alternating operation to ensure continuous production capacity; low-carbon power sources are activated to replace grid power supply; and a visual interface displays orange warnings and the percentage of units exceeding energy consumption standards.

[0100] When the comprehensive energy efficiency index is level five, production is suspended for rectification, and equipment that does not meet the energy efficiency standards is forcibly replaced. Production can only resume after passing the energy efficiency test; the visual interface displays a flashing red alarm.

[0101] It should be specifically noted that the visualization of equipment and environmental energy consumption is as follows:

[0102] The data dashboard uses a pie chart to dynamically display the real-time energy efficiency index and different colors corresponding to different levels;

[0103] The line chart compares historical energy efficiency trends, and users can selectively switch between daily, weekly, monthly, and yearly comparisons.

[0104] The heat map shows the distribution of high energy consumption.

[0105] The location of abnormal equipment is marked on the equipment status chart. Clicking on it will display the specific energy consumption coefficient.

[0106] The early warning management system establishes threshold-triggered alarms and generates energy efficiency diagnostic reports containing improvement measures, which are then sent to relevant personnel.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that the various embodiments of this application can be implemented by means of software or software combined with necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware functions; based on this understanding, the technical solution of this application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to cause a computer device, such as including but not limited to a personal computer, server, or network device, to execute all or part of the steps of the method described in any embodiment of this application.

[0108] The foregoing describes exemplary embodiments of this application. It should be understood that the above exemplary embodiments are not restrictive but illustrative, and the scope of protection of this application is not limited thereto. It should be understood that those skilled in the art can make modifications and variations to the embodiments of this application without departing from the spirit and scope of this application, and such modifications and variations should be within the scope of protection of this application.

Claims

1. An energy-saving control system based on thermal management of an energy storage room, characterized in that, Specifically, it includes: Energy storage room data acquisition module: used to collect data related to the operating status of thermal management equipment in the energy storage room and data related to the energy storage room environment; Multi-source data processing module: used to clean and process the collected data, and calculate equipment energy consumption related indicators and environmental energy consumption related indicators; Coefficient generation module: used to generate equipment energy consumption coefficients based on equipment status energy consumption related indicators, and to generate environmental energy consumption coefficients based on environmental energy consumption related indicators; Intelligent analysis module: used to generate a comprehensive energy consumption index from the equipment energy consumption coefficient and the environmental energy consumption coefficient, and to set thresholds for classification; Energy-saving control module: Used to take corresponding measures for energy-saving control based on the index classification results, and to visualize the energy consumption of equipment and the environment.

2. The energy-saving control system based on thermal management of an energy storage room according to claim 1, characterized in that: The equipment energy consumption related indicators include start-stop state coefficient, working mode coefficient, and fault state coefficient; the environmental energy consumption related indicators include temperature and humidity coefficient, air pressure coefficient, and light intensity coefficient.

3. The energy-saving control system based on thermal management of an energy storage room according to claim 2, characterized in that: The start / stop state coefficient is specifically as follows: ； Where Z is the start-stop state coefficient, which quantifies the continuity of the equipment's operating state. The coefficient range is [0,1]. The closer it is to 1, the higher the energy consumption of the equipment. Zt is the real-time state of the equipment at the current moment, λ is the weight of the current state, Zt-1 is the start-stop state at the previous moment, and 1-λ is the weight of the historical state. The specific working mode coefficient is as follows: ； Where M is the working mode coefficient, which quantifies the energy efficiency of the device in the current state. The coefficient range is [c, 1]. The larger M is, the worse the energy efficiency. c is the basic constant, P is the actual power, Pe is the rated power, and k is the energy efficiency coefficient, where k > 1. The fault state coefficient is specifically as follows: ； Where G is the fault state coefficient, which represents the severity of equipment faults and quantifies the negative impact of faults on energy consumption. The coefficient range is [0,1], and the larger G is, the more severe the fault is. Ai is the fault severity parameter, Ti represents the fault repair time, and n is the number of faults.

4. The energy-saving control system based on thermal management of an energy storage room according to claim 2, characterized in that: The temperature and humidity coefficients are specifically: ； Where W is the temperature and humidity coefficient, Ws is the real-time temperature and humidity deviation, Wmax is the historical maximum temperature and humidity deviation threshold, and Ws is the real-time temperature and humidity deviation calculated as follows: ； Where Ws is the real-time temperature and humidity deviation, which quantifies the degree to which the temperature and humidity deviate from the ideal range, reflecting the additional energy consumption required for the equipment to maintain the standard environment. The larger Ws is, the greater the degree to which the ambient temperature and humidity deviate from the standard, and the greater the energy consumption of the equipment. T is the real-time temperature, Tz is the optimal equipment operating temperature, μ1 is the influence intensity of temperature deviation on energy consumption, S is the real-time humidity, Sz is the optimal humidity, and μ2 is the influence intensity of humidity deviation on energy consumption. The pressure coefficient is specifically: ； Where Q is the air pressure coefficient, which quantifies the impact of air pressure deviation on equipment energy consumption. The larger the coefficient, the greater the energy consumption caused by air pressure abnormality. The value range is [0,1]. Qs is the real-time air pressure, Qb is the standard air pressure, and γ is the adjustment factor. The light intensity coefficient is specifically: ； Where D is the illuminance coefficient, and the formula normalizes the real-time illuminance coefficient to a value range of [0,1]; the maximum value function makes D 0 when Ds≤Db, indicating that the illuminance has no effect and no additional energy consumption is required; when D>0, the stronger the illuminance, the greater the load on the equipment operation and the higher the energy consumption; Ds is the real-time illuminance, Db is the thermal management standard illuminance, and Dmax is the local historical maximum illuminance. η is the heat absorption efficiency coefficient.

5. The energy-saving control system based on thermal management of an energy storage room according to claim 1, characterized in that: The specific energy consumption coefficient of the equipment is: ； Where B is the equipment energy consumption coefficient, the closer B is to 1, the higher the equipment energy consumption and the lower the energy efficiency, and the closer B is to 0, the more the equipment is in an energy-saving and efficient state; Z is the start-stop state coefficient, M is the working mode coefficient, G is the fault state coefficient, and ω is the weight. The environmental energy consumption coefficient is specifically: ； Where H is the environmental energy consumption coefficient, the larger the value, the greater the additional energy consumption caused by environmental conditions; W is the temperature and humidity coefficient, Q is the air pressure coefficient, D is the light intensity coefficient, and ω is the weight.

6. The energy-saving control system based on thermal management of an energy storage room according to claim 1, characterized in that: The comprehensive energy consumption index is specifically: ； Where E is the comprehensive energy consumption index, which directly reflects the overall energy efficiency level of the thermal management system of the energy storage room; B is the equipment energy consumption coefficient, which is the dominant factor with a weight of α; and H is the environmental energy consumption coefficient, which is the auxiliary factor with a weight of β. The specific steps for setting a threshold and classifying the comprehensive energy efficiency index are as follows: When E≤a, it is level one; When a < E ≤ b, it is level two; When b < E ≤ c, it is level three; When c < E ≤ d, it is level four; When E > d, it is level five.

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