An energy intelligent management system for hospitals

Abstract

The present invention relates to the technical field of energy management, and particularly to an intelligent energy management system for hospitals, including: an information acquisition module for acquiring hospital equipment data and the number of patients in each department during the monitoring period, and also for acquiring historical electricity consumption data of the hospital; a time period analysis module for analyzing the electricity consumption stability of the hospital and analyzing the energy transmission state; a department level analysis module for classifying the electricity consumption levels of departments; an electric energy monitoring module for analyzing the electricity consumption status of each department and analyzing the abnormal electricity consumption status of the hospital; an adjustment and optimization module for adjusting the analysis process of the electricity consumption status of each department; and an electric energy scheduling and management module for generating an electric energy management plan for the next monitoring period. The present invention effectively improves the efficiency of hospital energy management.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and particularly to an intelligent energy management system for hospitals. Background Art

[0002] With the development of society and the progress of medical facilities, hospitals, as important public institutions, have seen an increasing annual energy consumption. An effective energy management system can not only improve energy use efficiency but also reduce operating costs, and is also of positive significance for environmental protection. Most of the energy management systems on the market currently focus on a single type of energy or lack intelligent management means, and there are many deficiencies for places like hospitals with diverse energy demands.

[0003] Chinese Patent Publication No. CN111817296A discloses a method and system for power energy scheduling in a microgrid. Among them, the method includes: obtaining the historical power distribution information and power distribution plan of microgrid devices; based on the historical power distribution information and power distribution plan, and taking a preset time period as a cycle, optimizing a preset decision model function through a rolling optimization algorithm for model predictive control; solving the optimized preset decision model function; and scheduling the power distribution plan of microgrid devices according to the solution result. Through the above technical solution, it can be achieved that: constructing corresponding models according to the operating characteristics of different microgrid devices in the microgrid, introducing a rolling optimization algorithm for optimizing the design of model predictive control strategies, designing a utility function including the usage preferences of microgrid devices and the safe operating conditions of the devices, and realizing the goals of reducing the peak load in the microgrid, stabilizing power demand, ensuring the safe operation of the power grid, and saving power generation costs through power trading, scheduling, and collaborative management among users; thus, it can be seen that this invention does not analyze the power energy scheduling of the microgrid under different application scenarios, cannot achieve precise scheduling of electric energy, and has the problem of low efficiency in hospital energy management. Summary of the Invention

[0004] Therefore, the present invention provides an intelligent energy management system for hospitals to overcome the problem of low efficiency in hospital energy management in the prior art.

[0005] To achieve the above object, the present invention provides an intelligent energy management system for hospitals, including:

[0006] An information acquisition module for acquiring the device data, patient numbers, and environmental data of each department during a monitoring period, and also for acquiring the historical electricity consumption data of the hospital and the department levels;

[0007] A time period analysis module for analyzing the electricity consumption stability of the hospital based on historical power grid data, and analyzing the energy transmission state according to the analysis result of the hospital's electricity consumption stability;

[0008] The department level analysis module is used to divide the electricity consumption levels of departments according to the historical electricity consumption data of the hospital and the department levels.

[0009] The electric energy monitoring module is used to analyze the power consumption status of each department according to the medical equipment data, basic equipment data and department electricity consumption levels within the monitoring period, and analyze the abnormal power consumption status of the hospital according to the analysis results of the power consumption status of each department within the monitoring period.

[0010] The adjustment and optimization module is used to adjust the analysis process of the hospital's power consumption status according to the number of patients and environmental data within the monitoring period.

[0011] The power dispatching management module is used to generate a power management plan for the next monitoring period according to the analysis results of the abnormal power consumption status of the hospital and the energy transmission status within the monitoring period, and output the power management plan to the user.

[0012] Furthermore, the time period analysis module is provided with a time period analysis unit, and the time period analysis unit divides the monitoring period into each monitoring time period according to a preset duration t.

[0013] The time period analysis unit analyzes the power consumption stability of the hospital within each monitoring time period according to the historical power grid data, where:

[0014] When β(j) < B, the time period analysis unit determines that the power consumption stability of the hospital within this monitoring time period is normal.

[0015] When β(j) ≥ B, the time period analysis unit determines that the power consumption stability of the hospital within this monitoring time period is abnormal.

[0016] Among them, β(j) is the hospital power consumption stability index of the jth monitoring time period, and it is set that β(j) = |p(j) - H(j)| / H(j), p(j) is the power grid load of the jth monitoring time period, H(j) is the historical average power grid load of the jth monitoring time period, and B is the preset stability index.

[0017] The time period analysis module is also provided with a transmission analysis unit, and the transmission analysis unit analyzes the energy transmission status according to the analysis results of the hospital power consumption stability, where:

[0018] When the power consumption stability of the hospital within the time period is normal, the transmission analysis unit determines the energy transmission status of this time period as grid transmission.

[0019] When the power consumption stability of the hospital within the time period is abnormal, the transmission analysis unit determines the energy transmission status of this time period as combined transmission.

[0020] Further, the department level analysis module is provided with a single historical analysis unit, and the single historical analysis unit analyzes the historical power consumption status of each department according to the hospital's historical power consumption data;

[0021] The single historical analysis unit divides the historical power consumption status of each department according to the historical power consumption power w(i) of each department, where:

[0022] When w(i) < P, the single historical analysis unit determines that the historical power consumption status of this department is a low power consumption status;

[0023] When w(i) ≥ P, the single historical analysis unit determines that the historical power consumption status of this department is a high power consumption status;

[0024] The department level analysis module is also provided with an emergency status analysis unit, and the emergency status analysis unit analyzes the emergency status of each department according to the department level of each department in the hospital, where:

[0025] When the department level is a non-emergency disease department, the emergency status analysis unit sets the emergency status of this department to a non-emergency status;

[0026] When the department level is an emergency disease department, the emergency status analysis unit sets the emergency status of this department to an emergency status.

[0027] Further, the department level analysis module is also provided with a level analysis unit, and the level analysis unit analyzes the power consumption level of each department according to the analysis results of the historical power consumption status and the emergency status of each department, where:

[0028] When the historical power consumption status of the department is a low power consumption status, if the emergency status of the department is a non-emergency status, the level analysis unit sets the power consumption level of this department to level four; if the emergency status of the department is an emergency status, the level analysis unit sets the power consumption level of this department to level two;

[0029] When the historical power consumption status of the department is a high power consumption status, if the emergency status of the department is a non-emergency status, the level analysis unit sets the power consumption level of this department to level three; if the emergency status of the department is an emergency status, the level analysis unit sets the power consumption level of this department to level one.

[0030] Further, the power monitoring module is provided with a power statistics unit, and the power statistics unit analyzes the power consumption of each department during the monitoring period according to the medical equipment data and basic equipment data of each department during the monitoring period;

[0031] The electric energy statistics unit calculates the electricity consumption e(i) of each department according to the basic equipment data and medical equipment data of each department within the monitoring period. The calculation formula for the electricity consumption e(i) of the department is as follows:

[0032] e(i) = μ(i) × W + t(i) × p(i);

[0033] μ(i) = k(i) / K;

[0034] Where, μ is the sharing coefficient of the i-th department, W is the total electricity consumption of the hospital's basic electricity circuit, k(i) is the air-conditioning electricity consumption of the i-th department within the monitoring period, K is the total electricity consumption of the hospital's air-conditioning machine room, t(i) is the usage duration of the medical equipment in the i-th department, and p(i) is the total average working power of the medical equipment in the i-th department.

[0035] Further, the department anomaly analysis unit is used to analyze the electricity consumption status of each department according to the electricity consumption analysis results of each department, where:

[0036] When the electricity consumption level of the department is level one, if e(i) ≥ H1, the department anomaly analysis unit determines that the electricity consumption of the department is abnormal; if e(i) < H1, the department anomaly analysis unit determines that the electricity consumption of the department is normal;

[0037] When the electricity consumption level of the department is level two, if e(i) ≥ H2, the department anomaly analysis unit determines that the electricity consumption of the department is abnormal; if e(i) < H2, the department anomaly analysis unit determines that the electricity consumption of the department is normal;

[0038] When the electricity consumption level of the department is level three, if e(i) ≥ H3, the department anomaly analysis unit determines that the electricity consumption of the department is abnormal; if e(i) < H3, the department anomaly analysis unit determines that the electricity consumption of the department is normal;

[0039] When the electricity consumption level of the department is level four, if e(i) ≥ H4, the department anomaly analysis unit determines that the electricity consumption of the department is abnormal; if e(i) < H4, the department anomaly analysis unit determines that the electricity consumption of the department is normal;

[0040] Where, H1 is the first preset power consumption, H2 is the second preset power consumption, H3 is the third preset power consumption, and H4 is the fourth preset power consumption.

[0041] Further, the power monitoring module is also provided with a hospital anomaly analysis unit, and the hospital anomaly analysis unit is used to analyze the abnormal state of the hospital's electricity consumption according to the analysis results of the electricity consumption status of each department within the monitoring period;

[0042] The hospital anomaly analysis unit counts the number n1 of departments with abnormal power consumption, and analyzes the abnormal state of the hospital's power consumption according to the statistical results, where:

[0043] When v < M, the hospital anomaly analysis unit determines that the hospital's power consumption is normal;

[0044] When v ≥ M, the hospital anomaly analysis unit determines that the hospital's power consumption is abnormal;

[0045] Where M is the preset abnormal ratio, v is the abnormal department ratio of the hospital, and it is set that v = n1 / N.

[0046] Further, the adjustment and optimization module is provided with an adjustment unit, and the adjustment unit is used to adjust the analysis process of the abnormal state of the hospital's power consumption according to the number of patients NS within the monitoring period, where:

[0047] When NS < NK, the adjustment unit determines that the number of patients in the hospital within the monitoring period is normal and does not perform adjustment;

[0048] When NS ≥ NK, the adjustment unit determines that the number of patients in the hospital within the monitoring period is abnormal, and adjusts the preset abnormal ratio M to M', and it is set that M' = M × {1 - arctan[(NS - NK) / NK]};

[0049] Where NK is the preset number of patients that the hospital can accommodate.

[0050] Further, the adjustment and optimization module is also provided with an optimization unit. The optimization unit optimizes the adjustment process of the abnormal state of the hospital's power consumption according to the environmental data within the monitoring period, where:

[0051] When U1 ≤ u < U2, the optimization unit determines that the temperature within the monitoring period is normal and does not perform optimization;

[0052] When u ≥ U2 or u < U1, the optimization unit determines that the temperature within the monitoring period is abnormal. If u ≥ U2, the optimization unit optimizes the preset number of patients NK that the hospital can accommodate to NK'; if u < U1, the optimization unit optimizes the preset number of patients NK that the hospital can accommodate to NK'';

[0053] Where u is the average temperature of the city where the hospital is located within the monitoring period, U1 is the first preset temperature, U2 is the second preset temperature, and U1 < U2.

[0054] Further, the power scheduling management module generates a power management plan for the next monitoring period according to the analysis results of the abnormal state of power consumption and the analysis results of the abnormal state of energy within the monitoring period, where:

[0055] When the power consumption of the hospital is normal, if the energy transmission state during the period is grid transmission, the power scheduling management module does not change the power scheduling process of the hospital's electrical energy in the next monitoring period; if the energy transmission state is combined transmission, the power scheduling management module prioritizes each department of the hospital according to the electricity consumption priority γ(i) of each department, obtains a sorting queue, and uses the sorting queue as the power management plan for the next monitoring period.

[0056] When the power consumption of the hospital is abnormal and the energy transmission state is grid transmission, the power scheduling management module takes "starting the hospital's standby electrical energy" as the power management plan for the next monitoring period.

[0057] When the power consumption of the hospital is abnormal and the energy transmission state is combined transmission, the power scheduling management module prioritizes each department of the hospital according to the electricity consumption priority γ(i) of each department, obtains a sorting queue, and uses the sorting queue as the power management plan for the next monitoring period.

[0058] Among them, it is set that γ(i) = exp{lg[g(i)] + n(i)}, where g(i) is the electricity consumption level of the department numbered i, and n(i) is the number of patients in the i-th department during the monitoring period.

[0059] The power scheduling management module outputs the power management plan to the user.

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows: through the information acquisition module to acquire the information required in this embodiment, the integrity and accuracy of information acquisition are improved; through the time period analysis module to analyze the power consumption stability of the hospital and analyze the energy transmission state, the accuracy of energy transmission state analysis is improved; through the department level analysis module to divide the electricity consumption levels of departments, the accuracy of electricity consumption level division of each department is improved; through the power monitoring module to analyze the power consumption status of each department and analyze the abnormal power consumption status of the hospital, the accuracy of hospital power consumption monitoring is improved; through the adjustment and optimization module to adjust the analysis process of the hospital's power consumption status, the accuracy of hospital power consumption monitoring is improved; through the power scheduling management module to generate the power management plan for the next monitoring period according to the analysis results of the abnormal power consumption status and energy transmission state of the hospital's electrical energy during the monitoring period, and output the power management plan to the user, the efficiency of hospital energy management is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic structural diagram of the energy intelligent management system for the hospital in this embodiment.

[0062] Figure 2 It is a schematic structural diagram of the time period analysis module in this embodiment.

[0063] Figure 3 This is the structural schematic diagram of the department level analysis module of this embodiment.

[0064] Figure 4 This is the structural schematic diagram of the electric energy monitoring module of this embodiment.

[0065] Figure 5 This is the structural schematic diagram of the adjustment and optimization module of this embodiment. Detailed implementation manners

[0066] In order to make the objectives and advantages of the present invention more clear and understandable, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0067] The preferred implementation manners of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of the present invention and do not limit the protection scope of the present invention.

[0068] It should be noted that in the description of the present invention, unless otherwise clearly defined and limited, the terms "installed", "connected", and "coupled" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0069] Please refer to Figure 1 as shown, which is the structural schematic diagram of the energy intelligent management system for a hospital in this embodiment, including

[0070] An information acquisition module is used to acquire the equipment data, patient numbers, and environmental data of each department during the monitoring period, and is also used to acquire the historical electricity consumption data of the hospital and the department levels; the department levels include non-emergency disease departments and emergency disease departments; the non-emergency disease department is the department level for treating non-emergency type diseases, and the emergency disease department is the department level for treating emergency type diseases; in this embodiment, no specific limitations are imposed on the types of diseases included in the non-emergency type diseases, and those skilled in the art can freely set them as long as the requirements of the non-emergency type diseases are met. For example, the non-emergency type diseases can include chronic diseases, minor injuries, etc.; at the same time, in this embodiment, no specific limitations are imposed on the types of diseases included in the emergency type diseases, and those skilled in the art can freely set them as long as the requirements of the emergency type diseases are met. For example, the emergency type diseases can include cardiovascular diseases, respiratory diseases, etc.; the equipment data includes the medical equipment data and basic equipment data of each department; the medical equipment data includes the usage duration of medical equipment in each department and the total average working power of the medical equipment in each department; the basic equipment data includes the total consumed electric energy of the hospital's basic electricity consumption circuits, the air-conditioning electricity consumption of each department, and the power grid load; the equipment data can be acquired through equipment monitoring software; the historical electricity consumption data of the hospital includes historical power grid data and the historical electricity consumption power of each department; the historical power grid data includes the historical average power grid load; the environmental data includes the average temperature of the city where the hospital is located. In this embodiment, no specific limitations are imposed on the acquisition method of the environmental data, and those skilled in the art can freely set it as long as the acquisition requirements of the environmental data are met. For example, the environmental data can be acquired by setting sensors; in this embodiment, no specific limitations are imposed on the acquisition method of the historical electricity consumption data of the hospital, and those skilled in the art can freely set it as long as the acquisition requirements of the historical electricity consumption data of the hospital are met. For example, the historical electricity consumption data of the hospital can be acquired through the hospital's statistical database; in this embodiment, no specific limitations are imposed on the acquisition quantity of the historical electricity consumption data of the hospital, and those skilled in the art can freely set it as long as the acquisition quantity requirements of the historical electricity consumption data of the hospital are met. For example, the average electricity consumption data of the same quarter in multiple historical years can be acquired and used as the historical electricity consumption data of the hospital; the data structure of the average electricity consumption data is the same as that of a set of data in the historical electricity consumption data of the hospital; in this embodiment, no specific limitations are imposed on the value of the monitoring period, and those skilled in the art can freely set it as long as the value requirements of the monitoring period are met. In this embodiment, the value of the monitoring period is set to 1 day, and it can also be set to 2 days, etc.;

[0071] A time period analysis module is used to analyze the electricity consumption stability of the hospital based on the historical power grid data, and analyze the energy transmission state according to the analysis result of the hospital's electricity consumption stability. The time period analysis module is connected to the information acquisition module;

[0072] The department level analysis module is used to classify the electricity consumption levels of departments according to the historical electricity consumption data of the hospital and the department levels. The department level analysis module is connected to the information acquisition module;

[0073] The electric energy monitoring module is used to analyze the power consumption status of each department according to the medical equipment data, basic equipment data and department electricity consumption levels within the monitoring period, and analyze the abnormal power consumption status of the hospital according to the analysis results of the power consumption status of each department within the monitoring period. The electric energy monitoring module is connected to the department level analysis module;

[0074] The adjustment and optimization module is used to adjust the analysis process of the hospital's power consumption status according to the number of patients and environmental data within the monitoring period. The adjustment and optimization module is connected to the electric energy monitoring module;

[0075] The power scheduling management module is used to generate a power management plan for the next monitoring period according to the analysis results of the abnormal power consumption status of the hospital and the analysis results of the energy transmission status within the monitoring period, and output the power management plan to the user. The power scheduling management module is connected to the adjustment and optimization module and the time period analysis module.

[0076] Specifically, the energy intelligent management system for hospitals described in this embodiment is applied to the intelligent management of the hospital's standby power energy; the standby power energy of the hospital described in this embodiment is the self-generated electric energy of the hospital when the power supplied by the power grid is unstable; the power consumption management method of the hospital described in this embodiment is a method of unified management of power consumption by the hospital without separate metering for each department.

[0077] Please refer to Figure 2 as shown, which is the structural schematic diagram of the time period analysis module of this embodiment, including

[0078] The time period analysis unit is used to analyze the power consumption stability of the hospital during each monitoring time period according to the historical power grid data;

[0079] The transmission analysis unit is used to analyze the energy transmission status according to the analysis results of the hospital's power consumption stability. The transmission analysis unit is connected to the time period analysis unit.

[0080] Specifically, the time period analysis module is provided with a time period analysis unit, and the time period analysis unit divides the monitoring period into each monitoring time period according to the preset duration t;

[0081] Define the monitoring time period as [t1, t2... tj... tJ], where t1 is the first monitoring time period within the monitoring period, t2 is the second monitoring time period within the monitoring period, tj is the jth monitoring time period within the monitoring period, tJ is the Jth monitoring time period within the monitoring period, J is the number of monitoring time periods, and it is set that J = t / T, where T is the duration of the monitoring period;

[0082] The time period analysis unit analyzes the electricity consumption stability of the hospital during each monitoring time period according to historical power grid data, where:

[0083] When β(j) < B, the time period analysis unit determines that the electricity consumption stability of the hospital during this monitoring time period is normal;

[0084] When β(j) ≥ B, the time period analysis unit determines that the electricity consumption stability of the hospital during this monitoring time period is abnormal;

[0085] Among them, β(j) is the hospital electricity consumption stability index of the j-th monitoring time period, and it is set that β(j) = |p(j) - H(j)| / H(j), where p(j) is the power grid load of the j-th monitoring time period, H(j) is the historical average power grid load of the j-th monitoring time period, and B is the preset stability index.

[0086] Specifically, the time period analysis unit analyzes the electricity consumption stability of the hospital during each monitoring time period according to historical power grid data, improving the accuracy of the analysis of the electricity consumption stability of the hospital during each monitoring time period, thereby improving the accuracy of the analysis of the energy transmission state, thus improving the accuracy of the electricity energy scheduling of the hospital, and finally improving the efficiency of the energy management of the hospital; it can be understood that in this embodiment, no specific limitation is imposed on the value of the preset stability index B, and those skilled in the art can freely set it as long as it meets the value requirements of the preset stability index B. For example, the preset stability index B can be set to 0.2; those skilled in the art do not make specific limitations on the value of the preset duration t, as long as it meets the value requirements of the preset duration t. For example, the preset duration t can be set to 1 hour.

[0087] Specifically, the time period analysis module is further provided with a transmission analysis unit, and the transmission analysis unit analyzes the energy transmission state according to the analysis result of the hospital electricity consumption stability, where:

[0088] When the electricity consumption stability of the hospital during the time period is normal, the transmission analysis unit determines the energy transmission state of this time period as grid transmission;

[0089] When the electricity consumption stability of the hospital during the time period is abnormal, the transmission analysis unit determines the energy transmission state of this time period as combined transmission.

[0090] Specifically, the combined transmission in this embodiment is to transmit electric energy to the hospital through the power grid and the in-hospital power generation equipment, and the combined transmission is a backup energy solution for the hospital energy management system when the power grid cannot meet the electricity demand of the hospital during some time periods.

[0091] Specifically, the transportation analysis unit analyzes the energy transportation status according to the analysis result of the hospital's electricity consumption stability, which improves the accuracy of the analysis of the energy transportation status, thereby improving the accuracy of the hospital's electricity dispatching, and ultimately improving the efficiency of the hospital's energy management.

[0092] Please refer to Figure 3 as shown, which is a schematic structural diagram of the department level analysis module of this embodiment, including

[0093] a single historical analysis unit for analyzing the historical electricity consumption status of each department according to the hospital's historical electricity consumption data

[0094] an emergency status analysis unit for analyzing the emergency status of each department according to the department level of each department in the hospital. The emergency status analysis unit is connected to the single historical analysis unit;

[0095] a level analysis unit for analyzing the electricity consumption level of each department according to the analysis results of the historical electricity consumption status and the emergency status of each department. The level analysis unit is connected to the emergency status analysis unit.

[0096] Specifically, the department level analysis module is provided with a single historical analysis unit, and the single historical analysis unit analyzes the historical electricity consumption status of each department according to the hospital's historical electricity consumption data;

[0097] The single historical analysis unit divides the historical electricity consumption status of each department according to the historical electricity consumption power w(i) of each department, where:

[0098] When w(i) < P, the single historical analysis unit determines that the historical electricity consumption status of this department is a low power consumption status;

[0099] When w(i) ≥ P, the single historical analysis unit determines that the historical electricity consumption status of this department is a high power consumption status;

[0100] Among them, P is the preset electricity consumption power of the department, w(i) represents the historical electricity consumption power of the i-th department, i is the department number, and it is set that i = 1, 2... N, and N is the number of departments in the hospital.

[0101] Specifically, the single historical analysis unit analyzes the historical power consumption status of each department based on the hospital's historical power consumption data, improving the accuracy of the analysis of the historical power consumption status of each department. Furthermore, it improves the accuracy of the analysis of the power consumption level of each department, thereby enhancing the accuracy of the analysis of the hospital's power consumption status. Moreover, it improves the accuracy of the hospital's power scheduling and ultimately enhances the efficiency of the hospital's energy management. It can be understood that in this embodiment, no specific limitation is imposed on the value of the preset power consumption P of each department. Those skilled in the art can freely set it as long as it meets the value requirements of the preset power consumption P of each department. For example, the preset power consumption P of each department can be set as the median of the historical power consumption of each department in the hospital.

[0102] Specifically, the department level analysis module is also provided with an emergency status analysis unit. The emergency status analysis unit analyzes the emergency status of each department according to the department level of each department in the hospital, where:

[0103] When the department level is a non-emergency disease department, the emergency status analysis unit sets the emergency status of this department as a non-emergency status;

[0104] When the department level is an emergency disease department, the emergency status analysis unit sets the emergency status of this department as an emergency status.

[0105] Specifically, the emergency status analysis unit analyzes the emergency status of each department according to the department level of each department in the hospital, improving the accuracy of the analysis of the emergency status of each department. Furthermore, it improves the accuracy of the analysis of the power consumption level of each department, thereby enhancing the accuracy of the analysis of the hospital's power consumption status. Moreover, it improves the accuracy of the hospital's power scheduling and ultimately enhances the efficiency of the hospital's energy management.

[0106] Specifically, the department level analysis module is also provided with a level analysis unit. The level analysis unit analyzes the power consumption level of each department according to the analysis results of the historical power consumption status and the emergency status of each department, where:

[0107] When the historical power consumption status of the department is a low power consumption status, if the emergency status of the department is a non-emergency status, the level analysis unit sets the power consumption level of this department as level four; if the emergency status of the department is an emergency status, the level analysis unit sets the power consumption level of this department as level two;

[0108] When the historical power consumption status of the department is a high power consumption status, if the emergency status of the department is a non-emergency status, the level analysis unit sets the power consumption level of this department as level three; if the emergency status of the department is an emergency status, the level analysis unit sets the power consumption level of this department as level one.

[0109] Specifically, the fourth-level power consumption level described in this embodiment indicates the power consumption level of the department for treating non-emergency diseases and with low power consumption; the third-level power consumption level indicates the power consumption level of the department for treating non-emergency diseases and with high power consumption; the second-level power consumption level indicates the power consumption level of the department for treating emergency diseases and with low power consumption; the first-level power consumption level indicates the power consumption level of the department for treating emergency diseases and with high power consumption.

[0110] Please refer to Figure 4 as shown, which is a schematic structural diagram of the electric energy monitoring module of this embodiment, including,

[0111] An electric energy statistics unit for analyzing the power consumption of each department within the monitoring period according to the medical equipment data and basic equipment data of each department within the monitoring period;

[0112] A department abnormal analysis unit for analyzing the power consumption status of each department according to the analysis result of the power consumption of each department within the monitoring period. The department abnormal analysis unit is connected to the electric energy statistics unit;

[0113] A hospital abnormal analysis unit for analyzing the abnormal power consumption status of the hospital according to the analysis result of the power consumption status of each department within the monitoring period. The hospital abnormal analysis unit is connected to the department abnormal analysis unit.

[0114] Specifically, the electric energy monitoring module is provided with an electric energy statistics unit, and the electric energy statistics unit analyzes the power consumption of each department within the monitoring period according to the medical equipment data and basic equipment data of each department within the monitoring period;

[0115] The electric energy statistics unit calculates the power consumption e(i) of the department according to the basic equipment data and medical equipment data of each department within the monitoring period. The calculation formula for the power consumption e(i) of the department is as follows:

[0116] e(i) = μ(i) × W + t(i) × p(i);

[0117] μ(i) = k(i) / K;

[0118] Where, μ is the sharing coefficient of the i-th department, W is the total power consumption of the hospital's basic power supply circuit, k(i) is the air-conditioning power consumption of the i-th department within the monitoring period, K is the total power consumption of the hospital's air-conditioning machine room, t(i) is the usage duration of the medical equipment in the i-th department, and p(i) is the total average working power of the medical equipment in the i-th department.

[0119] Specifically, the electric energy statistics unit calculates the electricity consumption of each department according to the basic equipment data and medical equipment data of each department within the monitoring period, improving the accuracy of calculating the electricity consumption of each department in a unified management hospital. Furthermore, it improves the accuracy of analyzing the electricity consumption status of each department, thereby improving the accuracy of analyzing the overall electricity consumption status of the hospital, and ultimately improving the efficiency of hospital energy management.

[0120] Specifically, the department anomaly analysis unit is used to analyze the electricity consumption status of each department based on the analysis results of the electricity consumption of each department, where:

[0121] When the electricity consumption level of a department is level one, if e(i) ≥ H1, the department anomaly analysis unit determines that the electricity consumption of this department is abnormal; if e(i) < H1, the department anomaly analysis unit determines that the electricity consumption of this department is normal;

[0122] When the electricity consumption level of a department is level two, if e(i) ≥ H2, the department anomaly analysis unit determines that the electricity consumption of this department is abnormal; if e(i) < H2, the department anomaly analysis unit determines that the electricity consumption of this department is normal;

[0123] When the electricity consumption level of a department is level three, if e(i) ≥ H3, the department anomaly analysis unit determines that the electricity consumption of this department is abnormal; if e(i) < H3, the department anomaly analysis unit determines that the electricity consumption of this department is normal;

[0124] When the electricity consumption level of a department is level four, if e(i) ≥ H4, the department anomaly analysis unit determines that the electricity consumption of this department is abnormal; if e(i) < H4, the department anomaly analysis unit determines that the electricity consumption of this department is normal;

[0125] Among them, H1 is the first preset power consumption, H2 is the second preset power consumption, H3 is the third preset power consumption, and H4 is the fourth preset power consumption.

[0126] Specifically, the department anomaly analysis unit analyzes the power consumption status of each department according to the analysis results of the power consumption of each department, improving the accuracy of the analysis of the power consumption status of each department, thereby improving the accuracy of the analysis of the overall power consumption status of the hospital, and ultimately improving the efficiency of hospital energy management; it can be understood that in this embodiment, no specific limitations are imposed on the values of the first preset power consumption H1, the second preset power consumption H2, the third preset power consumption H3, and the fourth preset power consumption H4. Those skilled in the art can freely set them as long as they meet the value requirements of the first preset power consumption H1, the second preset power consumption H2, the third preset power consumption H3, and the fourth preset power consumption H4. For example, the first preset power consumption H1 can be set to the power consumption of the sample department × 120%, the second preset power consumption H2 can be set to the power consumption of the sample department × 100%, the third preset power consumption H3 can be set to the power consumption of the sample department × 80%, and the fourth preset power consumption H4 can be set to the power consumption of the sample department × 50%; the power consumption of the sample department is the power consumption of the department under the same equipment state.

[0127] Specifically, the power monitoring module is also provided with a hospital anomaly analysis unit, which is used to analyze the abnormal power consumption status of the hospital according to the analysis results of the power consumption status of each department within the monitoring period.

[0128] The hospital anomaly analysis unit counts the number n1 of departments with abnormal power consumption and analyzes the abnormal power consumption status of the hospital according to the statistical results, where:

[0129] When v < M, the hospital anomaly analysis unit determines that the hospital's power consumption is normal;

[0130] When v ≥ M, the hospital anomaly analysis unit determines that the hospital's power consumption is abnormal;

[0131] Among them, M is the preset abnormal ratio, v is the abnormal department ratio of the hospital, and it is set that v = n1 / N.

[0132] Specifically, the hospital anomaly analysis unit analyzes the abnormal power consumption status of the hospital according to the analysis results of the power consumption status of each department within the monitoring period, improving the accuracy of the analysis of the power consumption status of the hospital, thereby improving the accuracy of the power dispatching of the hospital, and ultimately improving the efficiency of hospital energy management; it can be understood that in this embodiment, no specific limitations are imposed on the value of the preset abnormal ratio M. Those skilled in the art can freely set it as long as it meets the value requirements of the preset abnormal ratio M. For example, the preset abnormal ratio M can be set to 10%.

[0133] Please refer to Figure 5 as shown, which is the structural schematic diagram of the adjustment and optimization module of this embodiment, including

[0134] An adjustment unit for adjusting the analysis process of the abnormal state of the hospital's power consumption according to the number of patients in each department during the monitoring period;

[0135] An optimization unit for optimizing the adjustment process of the power consumption state according to the environmental data during the monitoring period. The optimization unit is connected to the adjustment unit.

[0136] Specifically, the adjustment and optimization module is provided with an adjustment unit, and the adjustment unit is used to adjust the analysis process of the abnormal state of the hospital's power consumption according to the number of patients NS during the monitoring period, where:

[0137] When NS < NK, the adjustment unit determines that the number of patients in the hospital during the monitoring period is normal and does not make adjustments;

[0138] When NS ≥ NK, the adjustment unit determines that the number of patients in the hospital during the monitoring period is abnormal and adjusts the preset abnormal ratio M to M', where M' = M × {1 - arctan[(NS - NK) / NK]};

[0139] Among them, NK is the preset number of patients that the hospital can accommodate.

[0140] Specifically, the adjustment unit adjusts the analysis process of the abnormal state of the hospital's power consumption according to the number of patients during the monitoring period, improving the accuracy of the analysis of the hospital's power consumption state, and then improving the accuracy of the hospital's power scheduling, thereby improving the efficiency of the hospital's energy management; it can be understood that in this embodiment, no specific limitation is made on the value of the preset number of patients NK that the hospital can accommodate, and those skilled in the art can freely set it as long as it meets the value requirements of the preset number of patients NK that the hospital can accommodate. For example, the preset number of patients NK that the hospital can accommodate can be set to 70% of the maximum number of patients that the hospital can accommodate, and the maximum number of patients that the hospital can accommodate can be obtained through user interaction input.

[0141] Specifically, the adjustment and optimization module is further provided with an optimization unit, and the optimization unit optimizes the adjustment process of the abnormal state of the hospital's power consumption according to the environmental data during the monitoring period, where:

[0142] When U1 ≤ u < U2, the optimization unit determines that the temperature during the monitoring period is normal and does not perform optimization;

[0143] When u≥U2 or u<U1, the optimization unit determines that the temperature is abnormal within the monitoring period. If u≥U2, the optimization unit optimizes the preset number of patients NK that the hospital can accommodate to NK’, where NK’ = NK × {1 + sin[(u - U2) / U2]}; if u<U1, the optimization unit optimizes the preset number of patients NK that the hospital can accommodate to NK”, where NK” = NK / exp[(U1 - u) / U1].

[0144] Where u is the average temperature of the city where the hospital is located within the monitoring period, U1 is the first preset temperature, U2 is the second preset temperature, and U1<U2.

[0145] Specifically, the optimization unit optimizes the adjustment process of the power consumption status according to the environmental data within the monitoring period, improving the accuracy of the analysis of the hospital's power consumption status, thereby improving the accuracy of the power scheduling for the hospital, and thus improving the efficiency of the hospital's energy management. It can be understood that in this embodiment, no specific limitations are imposed on the values of the first preset temperature U1 and the second preset temperature U2, and those skilled in the art can freely set them as long as they meet the value requirements of the first preset temperature U1 and the second preset temperature U2. For example, the first preset temperature U1 can be set to 3°C and the second preset temperature U2 can be set to 24°C.

[0146] Specifically, the power scheduling management module generates a power management plan for the next monitoring period according to the analysis results of the abnormal power consumption status and the abnormal energy status within the monitoring period, where:

[0147] When the hospital's power consumption is normal, if the energy delivery status during the period is grid delivery, the power scheduling management module does not change the power scheduling process of the hospital's electrical energy for the next monitoring period; if the energy delivery status is combined delivery, the power scheduling management module prioritizes each department of the hospital according to the electricity consumption priority γ(i) of each department to obtain a sorting queue, and takes the sorting queue as the power management plan for the next monitoring period.

[0148] When the hospital's power consumption is abnormal and the energy delivery status is grid delivery, the power scheduling management module takes "activate the hospital's standby power energy" as the power management plan for the next monitoring period.

[0149] When the hospital's power consumption is abnormal and the energy delivery status is combined delivery, the power scheduling management module prioritizes each department of the hospital according to the electricity consumption priority γ(i) of each department to obtain a sorting queue, and takes the sorting queue as the power management plan for the next monitoring period.

[0150] Among them, it is set that γ(i) = exp{l g[g(i)] + n(i)}, where g(i) is the electricity consumption level of the department numbered i, and n(i) is the number of patients in the i-th department during the monitoring period;

[0151] The power energy scheduling management module outputs the power energy management plan to the user.

[0152] It can be understood that in this embodiment, "g(i) is the electricity consumption level of the department numbered i" means that when the electricity consumption level is level one, g(i) = 1; when the electricity consumption level is level two, g(i) = 2; when the electricity consumption level is level three, g(i) = 3; when the electricity consumption level is level four, g(i) = 4.

[0153] Specifically, the power energy scheduling management module analyzes the power energy management plan for the next monitoring period, improves the accuracy of the hospital's power energy scheduling, and thus improves the efficiency of the hospital's energy management.

[0154] So far, the technical solution of the present invention has been described in combination with the preferred embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An intelligent energy management system for a hospital, characterized in that: include: The information acquisition module is used to obtain the equipment data, patient numbers and environmental data of each department during the monitoring period, and is also used to obtain the hospital's historical electricity consumption data and department level; The time period analysis module is used to analyze the stability of hospital power consumption based on historical power grid data, and to analyze the energy transmission status based on the results of the hospital power consumption stability analysis; Department level analysis module, used to classify department electricity usage levels based on the hospital's historical electricity usage data and department levels; The power monitoring module is used to analyze the power consumption status of each department according to the medical equipment data, basic equipment data and department power consumption level within the monitoring period, and analyze the abnormal power consumption status of the hospital according to the power consumption status analysis results of each department within the monitoring period; Adjustment and optimization module, used to adjust the analysis process of hospital power consumption status according to the number of patients and environmental data during the monitoring period; The power dispatch management module is used to generate the power management plan for the next monitoring period according to the analysis results of the abnormal state of power consumption and energy transmission state of the hospital within the monitoring period, and output the power management plan to the user; β(j) is the hospital electricity stability index in the jth monitoring period, and β(j) = |p(j)-H(j)| / H(j), p(j) is the grid load in the jth monitoring period, and H(j) is the historical average grid load in the jth monitoring period; The time period analysis module is further provided with a transmission analysis unit, which analyzes the energy transmission status according to the hospital power stability analysis result, wherein: When the hospital's electricity consumption is stable during the time period, the transmission analysis unit sets the energy transmission state of the time period to grid transmission; When the hospital's electricity consumption stability is abnormal during a period, the transmission analysis unit sets the energy transmission state of the period to joint transmission; the joint transmission is a backup energy solution of the hospital energy management system when the power grid cannot meet the hospital's electricity demand during some periods; The electric energy dispatch management module generates an electric energy management plan for the next monitoring period according to the analysis results of abnormal state of electric energy consumption and abnormal state of energy in the monitoring period, wherein: When the hospital's power consumption is normal, if the energy transmission state in the time period is grid transmission, the power dispatching management module does not change the scheduling process of the hospital's power energy in the next monitoring cycle; if the energy transmission state is joint transmission, the power dispatching management module prioritizes each department of the hospital according to the power consumption priority γ(i) of each department, obtains a sorting queue, and uses the sorting queue as the power management plan for the next monitoring cycle; When the hospital's power consumption is abnormal and the energy transmission state is grid transmission, the power dispatch management module will "start the hospital's backup power energy" as the power management plan for the next monitoring cycle; When the hospital's power consumption is abnormal and the energy transmission state is joint transmission, the power dispatch management module prioritizes each department of the hospital according to the power consumption priority γ(i) of each department, obtains a sorting queue, and uses the sorting queue as the power management plan for the next monitoring cycle; Among them, set γ(i) = exp{lg[g(i)] + n(i)}, g(i) is the electricity level of the department numbered i, and n(i) is the number of patients in the i-th department during the monitoring period; The electric energy dispatching management module outputs the electric energy management plan to the user.

2. The energy intelligent management system for hospitals according to claim 1 is characterized in that: The time period analysis module is provided with a time period analysis unit, and the time period analysis unit divides the monitoring cycle into various monitoring time periods according to a preset time length t; The time period analysis unit analyzes the hospital power consumption stability in each monitoring period based on historical power grid data, wherein: When β(j)<B, the time period analysis unit determines that the hospital power consumption stability is normal during the monitoring period; When β(j)≥B, the time period analysis unit determines that the hospital power stability during the monitoring period is abnormal; Among them, B is the preset stability index.

3. The energy intelligent management system for hospitals according to claim 2 is characterized in that: The department level analysis module is provided with a single historical analysis unit, which analyzes the historical power consumption status of each department based on the hospital's historical power consumption data; The single historical analysis unit divides the historical power consumption status of each department according to the historical power consumption w(i) of each department, wherein: When w(i)<P, the single history analysis unit determines that the historical power consumption state of the department is a low power consumption state; When w(i)≥P, the single history analysis unit determines that the historical power consumption state of the department is a high power consumption state; Among them, P is the power consumption of the preset department; The department level analysis module is further provided with an emergency status analysis unit, which analyzes the emergency status of each department according to the department level of each department of the hospital, wherein: When the department level is a non-emergency disease department, the emergency status analysis unit sets the emergency status of the department to a non-emergency status; When the department level is an emergency disease department, the emergency state analysis unit sets the emergency state of the department as an emergency state.

4. The energy intelligent management system for hospitals according to claim 3 is characterized in that: The department level analysis module is further provided with a level analysis unit, which analyzes the power usage level of each department according to the historical power usage status analysis results and emergency status analysis results of each department, wherein: When the historical power consumption state of the department is a low power consumption state, if the emergency state of the department is a non-emergency state, the level analysis unit sets the power consumption level of the department to level four; if the emergency state of the department is an emergency state, the level analysis unit sets the power consumption level of the department to level two; When the historical power consumption status of a department is a high power consumption status, if the emergency status of the department is a non-emergency status, the level analysis unit sets the power consumption level of the department to level three; if the emergency status of the department is an emergency status, the level analysis unit sets the power consumption level of the department to level one.

5. The energy intelligent management system for hospitals according to claim 4 is characterized in that: The power monitoring module is provided with a power statistics unit, which analyzes the power consumption of each department during the monitoring period according to the medical equipment data and basic equipment data of each department during the monitoring period; The electric energy statistics unit calculates the department's electricity consumption e(i) according to the basic equipment data and medical equipment data of each department during the monitoring period. The calculation formula of e(i) is as follows: e(i)=μ(i)×W+t(i)×p(i); μ(i)=k(i) / K; Among them, μ(i) is the allocation coefficient of the i-th department, W is the total power consumption of the hospital's basic power circuit, k(i) is the air-conditioning power consumption of the i-th department during the monitoring period, K is the total power consumption of the hospital's air-conditioning room, t(i) is the usage time of the medical equipment in the i-th department, and p(i) is the total average working power of the medical equipment in the i-th department.

6. The energy intelligent management system for hospitals according to claim 5 is characterized in that: The power monitoring module is also provided with a department abnormality analysis unit, which is used to analyze the power consumption status of each department according to the power consumption analysis results of each department, wherein: When the power consumption level of the department is level 1, if e(i)≥H1, the department abnormality analysis unit determines that the power consumption of the department is abnormal; if e(i)<H1, the department abnormality analysis unit determines that the power consumption of the department is normal; When the power consumption level of the department is level 2, if e(i)≥H2, the department abnormality analysis unit determines that the power consumption of the department is abnormal; if e(i)<H2, the department abnormality analysis unit determines that the power consumption of the department is normal; When the power consumption level of the department is level 3, if e(i)≥H3, the department abnormality analysis unit determines that the power consumption of the department is abnormal; if e(i)<H3, the department abnormality analysis unit determines that the power consumption of the department is normal; When the power consumption level of the department is level 4, if e(i)≥H4, the department abnormality analysis unit determines that the power consumption of the department is abnormal; if e(i)<H4, the department abnormality analysis unit determines that the power consumption of the department is normal; Among them, H1 is the first preset power consumption, H2 is the second preset power consumption, H3 is the third preset power consumption, and H4 is the fourth preset power consumption.

7. The energy intelligent management system for hospitals according to claim 6 is characterized in that: The power monitoring module is also provided with a hospital abnormality analysis unit, which is used to analyze the abnormal state of hospital power consumption according to the power consumption state analysis results of each department within the monitoring period; The hospital abnormality analysis unit counts the number of departments with abnormal power consumption n1, and analyzes the abnormal power consumption state of the hospital according to the statistical results, wherein: When v<M, the hospital abnormality analysis unit determines that the hospital power consumption is normal; When v≥M, the hospital abnormality analysis unit determines that the hospital power consumption is abnormal; Among them, M is the preset abnormal ratio, v is the abnormal department ratio of the hospital, and v=n1 / N is set, where N is the number of departments in the hospital.

8. The energy intelligent management system for hospitals according to claim 7, characterized in that: The adjustment and optimization module is provided with an adjustment unit, which is used to adjust the analysis process of abnormal state of power consumption of the hospital according to the number of patients NS in the monitoring period, wherein: When NS<NK, the adjustment unit determines that the number of patients in the hospital during the monitoring period is normal and does not make any adjustments; When NS≥NK, the adjustment unit determines that the number of patients in the hospital during the monitoring period is abnormal, and adjusts the preset abnormal ratio M to M', setting M'=M×{1-arctan[(NS-NK) / NK]}; Among them, NK is the preset number of patients that the hospital can accommodate.

9. The energy intelligent management system for hospitals according to claim 8, characterized in that: The adjustment and optimization module is further provided with an optimization unit, which optimizes the adjustment process of the abnormal state of hospital power consumption according to the environmental data within the monitoring period, wherein: When U1≤u<U2, the optimization unit determines that the temperature within the monitoring period is normal and does not perform optimization; When u≥U2 or u<U1, the optimization unit determines that the temperature is abnormal during the monitoring period. If u≥U2, the optimization unit optimizes the preset hospital carrying patient number NK to NK'; if u<U1, the optimization unit optimizes the preset hospital carrying patient number NK to NK". Wherein, u is the average temperature of the city where the hospital is located during the monitoring period, U1 is the first preset temperature, U2 is the second preset temperature, and U1<U2.

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