CN116962469A - Wisdom garden electric energy monitoring management system - Google Patents
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Abstract
The invention discloses an intelligent park electric energy monitoring and management system, which relates to the technical field of electric power and comprises a monitoring sensor group, a management center, a correlation evaluation module, a transmission management module and an electric energy analysis module; the association evaluation module is used for collecting the operation records of each energy utilization device to evaluate the association degree; when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in the terminal database; the transmission management module is used for carrying out monitoring grade analysis on the data packet cached in the terminal database and assisting in determining the transmission path of the data packet according to the monitoring grade; network congestion is effectively avoided, and communication efficiency is improved; after the management center receives the data packet, the power consumption time sequence parameters in the data packet are acquired by the power analysis module to perform early warning analysis so as to remind a manager to overhaul and maintain the power consumption equipment, find out the reason of electrical abnormality, improve the power quality and improve the power utilization rate.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to an electric energy monitoring and management system for an intelligent park.
Background
The construction of the smart park is an important component of the smart city and is also an advanced stage of the development of the smart city. The intelligent park takes the Internet as a carrier, and the industrial mode of Internet and industry is fused, so that a solution for providing full-industry-chain supporting service for the park can help the park to establish a unified organization management coordination framework in the aspect of informatization; the smart park is high in electricity consumption, various in user side equipment categories, and often has high power or electrical equipment with extremely high requirements on power supply stability, so that the requirements of the smart park on electricity reliability are extremely high.
The existing electricity safety monitoring device is poor in monitoring stability, single in monitoring range, for example, only single in monitoring electricity consumption or temperature information, and the monitoring information is often displayed on the device body, so that the reading is inconvenient; to improve the power quality of the intelligent park, firstly, the power quality of the intelligent park is accurately detected and analyzed, the power quality level of the intelligent park is measured, and the reasons for various power quality problems are analyzed and judged, so that a basis is provided for improving the power quality; based on the defects, the invention provides an intelligent park electric energy monitoring and management system.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides an intelligent park electric energy monitoring and management system.
To achieve the above objective, an embodiment according to a first aspect of the present invention provides an intelligent park electric energy monitoring and management system, including a monitoring sensor group, a management center, an association evaluation module, a transmission management module, a data transmission module and an electric energy analysis module;
the intelligent park is provided with a plurality of energy utilization devices, and each energy utilization device is connected with a corresponding monitoring sensor group; the monitoring sensor group is used for transmitting the running state of each energy utilization device to the management center for real-time display for user inquiry; the running state comprises starting and closing;
the association evaluation module is used for collecting operation records of all the energy utilization devices to evaluate association degree GL, and time stamping the association degree GL of each energy utilization device and storing the time stamping to the cloud platform;
when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in a terminal database; the energy consumption time sequence parameters comprise unit electricity consumption, running power, noise decibel value and real-time temperature of the equipment at the same moment;
the transmission management module is used for carrying out feature extraction on the data packet cached in the terminal database so as to analyze the monitoring grade Jd of the data packet and determining the transmission path of the data packet in an auxiliary way according to the monitoring grade Jd; if Jd is larger than a preset monitoring threshold value, determining the transmission path of the data packet as a primary transfer path; otherwise, determining the transmission path of the data packet as a multi-stage transfer path;
wherein the first-stage transit path is expressed as: the data packet is directly sent to the management center through a base station; the multi-stage transit path is represented as: the data packet is sequentially transferred to a management center through a plurality of base stations;
after the management center receives the data packet, the power analysis module is utilized to acquire power utilization time sequence parameters in the data packet for early warning analysis, and the overload index Cs of the power utilization equipment is calculated;
if the overload index Cs is greater than a preset overload threshold value; judging that the load of the energy utilization equipment is abnormal, and generating an early warning instruction to a management center; and the management center drives the control alarm module to give an alarm after receiving the early warning instruction and controls the energy utilization equipment to enter a standby mode so as to remind a manager of overhauling and maintaining the energy utilization equipment.
Further, the specific analysis steps of the transmission management module are as follows:
extracting characteristic values of the data packet, wherein the characteristic values comprise data types, data amounts, data transmission distances and data transmission bandwidths;
the data quantity, the data transmission distance and the data transmission bandwidth are marked as WLi, WDi and WKi in sequence; acquiring the data type of the data packet, and marking the corresponding type value as Wxi; calculating to obtain a characteristic coefficient WTi of the data packet by using a formula wti=wli×a1+ WDi ×a2+wxi×a3+ WKi ×a4, wherein a1, a2, a3 and a4 are all preset coefficient factors;
acquiring energy utilization equipment corresponding to the data packet, and automatically calling the association degree GL of the energy utilization equipment from the cloud platform; counting the early warning times of the energy utilization equipment to be Z1 in a preset time period; the operation period of the statistical energy consumption equipment is N1; the monitoring level Jd of the data packet is calculated by using a formula jd=wti×b1+gl×b2+n1×b3+z1×b4, wherein b1, b2, b3, b4 are all preset coefficient factors.
Further, the specific evaluation process of the association evaluation module is as follows:
collecting operation records of each energy utilization device in a preset time period; for a certain energy using device, taking the starting time of one operation record of the energy using device as the center, and marking other energy using devices with starting time difference within a preset value as associated devices; counting the number of associated devices to be L1; if L1 is greater than a preset quantity threshold, marking the start as associated start;
counting the number of times of associated starting of the energy utilization equipment to be Zb; performing time difference calculation on adjacent two associated starting moments of the energy using equipment to obtain an associated interval duration LTi; the associated starting time is the starting time of the energy utilization equipment during associated starting;
comparing the associated interval duration LTi with a preset interval duration; counting the times of the correlation interval duration LTi smaller than the preset interval duration as the proportion Lb; when the LTi is smaller than the preset interval duration, obtaining a difference value between the LTi and the preset interval duration and summing the difference value to obtain a total difference value CZ; the relevance GL of the energy consuming device is calculated by using the formula gl=μ×zb× (lb×g3+cz×g4), wherein g3, g4 are preset coefficient factors, μ is a preset equalization coefficient.
Further, the data transmission module is used for selecting a plurality of base stations to form transmission paths according to preset rules, and sending corresponding data packets to the management center according to the transmission paths; the method specifically comprises the following steps:
when the transmission path is a multi-stage transit path, acquiring a monitoring grade Jd of the data packet, and determining the number of corresponding transit base stations in an auxiliary manner according to the monitoring grade Jd, wherein the method specifically comprises the following steps:
a comparison table of the monitoring level range and the quantity threshold value of the transit base stations is prestored in a terminal database;
determining the quantity threshold value of the transit base stations corresponding to the monitoring level Jd as D2 according to the comparison table; d2 transit base stations are selected to be sequentially connected to form a transmission path.
Further, the specific analysis steps of the electric energy analysis module are as follows:
acquiring energy utilization time sequence parameters of energy utilization equipment, and marking unit power consumption, running power, noise decibel values and real-time temperature in the energy utilization time sequence parameters as W1, W2, W3 and W4 in sequence;
calculating a load value FZ of the energy utilization device by using a formula FZ=W1×d1+W2×d2+W3×d3+W4×d4, wherein d1, d2, d3 and d4 are all preset coefficient factors;
establishing a graph of the change of the load value FZ with time; when the curve graph is in the ascending stage, deriving the curve graph to obtain a load migration value curve graph, and marking the load migration value of the energy utilization equipment as FQi; comparing the load migration value FQi with a preset migration threshold, if FQi is greater than or equal to the preset migration threshold, intercepting and marking a corresponding curve segment in a corresponding curve graph, and recording the curve segment as an overload curve segment;
counting the number of the overload curve segments as C1 in a preset time period; integrating all the overload curve segments with respect to time to obtain an overload reference area M1; and calculating the overload index Cs of the energy utilization device by using a formula Cs=C1×d5+M1×d6, wherein d5 and d6 are preset coefficient factors.
Further, the device parameters include the model and the size of the device, and the device parameters are input into the monitoring sensor group by a user.
Compared with the prior art, the invention has the beneficial effects that:
1. the association evaluation module is used for collecting the operation records of each energy utilization device to evaluate the association degree GL; when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in a terminal database; the transmission management module is used for carrying out feature extraction on the data packet cached in the terminal database so as to analyze the monitoring grade Jd of the data packet and determining the transmission path of the data packet in an auxiliary way according to the monitoring grade Jd; if Jd is larger than a preset monitoring threshold value, determining the transmission path of the data packet as a primary transfer path; wherein the first-stage transit path is expressed as: the data packet is directly sent to the management center through a base station; otherwise, determining the transmission path of the data packet as a multi-stage transfer path; the multi-stage transit path is represented as: the data packets are sequentially transferred to the management center through a plurality of base stations, so that network congestion is effectively avoided, and communication efficiency is improved; the data transmission is more hierarchical;
2. after receiving the data packet, the management center acquires the energy utilization time sequence parameters in the data packet by utilizing the electric energy analysis module to perform early warning analysis, and calculates the load value FZ of the energy utilization equipment; establishing a graph of the change of the load value FZ with time; when the curve graph is in the ascending stage, deriving the curve graph to obtain a load migration value curve graph, and calculating according to the space-time change condition of the load migration value FQi to obtain the overload index Cs of the energy utilization equipment; if the overload index Cs is greater than a preset overload threshold value; judging that the load of the energy utilization equipment is abnormal, and generating an early warning instruction to a management center; to remind the manager to repair and maintain the energy-using equipment; the reason of electrical abnormality is found out, so that the electric energy quality is improved, and the electric energy utilization rate is improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of a system for intelligent campus power monitoring and management according to the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the system for monitoring and managing electric energy in the intelligent park comprises a monitoring sensor group, a management center, an association evaluation module, a cloud platform, a transmission management module, a data transmission module, an electric energy analysis module and an alarm module;
the intelligent park is provided with a plurality of energy utilization devices, each energy utilization device is connected with a corresponding monitoring sensor group, and the monitoring sensor groups are connected with the management center in a distributed mode through the nodes of the Internet of things; the monitoring sensor group is used for transmitting the running state of each energy utilization device to the management center for real-time display for inquiry of users; the running state comprises starting and closing;
the association evaluation module is used for collecting the operation records of each energy utilization device to evaluate the association degree GL, and the specific evaluation process is as follows:
collecting operation records of each energy utilization device in a preset time period; the operation record comprises a starting time and a closing time;
for a certain energy utilization device, marking other energy utilization devices with starting time difference within a preset value as associated devices by taking starting time of one operation record of the energy utilization device as a center; the starting time difference is the interval between the starting moments of the two energy utilization devices; counting the number of associated devices to be L1; if L1 is greater than a preset quantity threshold, marking the start as associated start;
counting the number of times of associated starting of the energy utilization equipment as Zb; performing time difference calculation on adjacent two associated starting moments of the energy utilization equipment to obtain an associated interval duration LTi; the associated starting time is the starting time of the energy utilization equipment during the associated starting;
comparing the associated interval duration LTi with a preset interval duration; counting the times of the correlation interval duration LTi smaller than the preset interval duration as the proportion Lb; when the LTi is smaller than the preset interval duration, obtaining a difference value between the LTi and the preset interval duration and summing the difference value to obtain a total difference value CZ;
calculating the association degree GL of the energy utilization equipment by using a formula GL=mu×Zb× (Lb×g3+CZ×g4), wherein g3 and g4 are preset coefficient factors, and mu is a preset equalization coefficient; the association evaluation module is used for marking time stamps on association degrees GL of all the energy utilization devices and storing the time stamps to the cloud platform;
when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in the terminal database; the equipment parameters comprise the model, the size and the like of equipment, and the equipment parameters are input into a monitoring sensor group by a user; the energy consumption time sequence parameters comprise unit electricity consumption, running power, noise decibel value and real-time temperature of the equipment at the same moment;
the transmission management module is connected with the terminal database, and is used for extracting characteristics of the data packet cached in the terminal database so as to analyze the monitoring level Jd of the data packet and determining the transmission path of the data packet in an auxiliary manner according to the monitoring level Jd; the specific analysis steps are as follows:
extracting characteristic values of the data packet, wherein the characteristic values comprise data types, data amounts, data transmission distances and data transmission bandwidths; the data quantity, the data transmission distance and the data transmission bandwidth are marked as WLi, WDi and WKi in sequence; acquiring the data type of the data packet, and marking the corresponding type value as Wxi;
calculating to obtain a characteristic coefficient WTi of the data packet by using a formula WTi=WLi×a1+ WDi ×a2+Wxi×a3+ WKi ×a4, wherein a1, a2, a3 and a4 are all preset coefficient factors;
acquiring energy utilization equipment corresponding to the data packet, and automatically calling the association degree GL of the energy utilization equipment from the cloud platform; the operation period of the statistical energy consumption equipment is N1;
counting the early warning times of the energy utilization equipment to be Z1 in a preset time period; calculating a monitoring grade Jd of the data packet by using a formula jd=wti×b1+gl×b2+n1×b3+z1×b4, wherein b1, b2, b3 and b4 are all preset coefficient factors;
comparing the monitoring grade Jd with a preset monitoring threshold value; if Jd is larger than a preset monitoring threshold value, determining the transmission path of the data packet as a primary transit path; wherein the first-stage transit path is expressed as: the data packet is directly sent to the management center through a base station;
otherwise, determining the transmission path of the data packet as a multi-stage transit path; the multi-stage transit path is represented as: the data packets are sequentially transferred to the management center through a plurality of base stations, so that network congestion is effectively avoided, and communication efficiency is improved; the data transmission is more hierarchical;
the data transmission module is used for selecting a plurality of base stations to form transmission paths according to preset rules, and sending the data packets cached in the terminal database to the management center according to the transmission paths; the method specifically comprises the following steps:
when the transmission path is a multi-stage transit path, acquiring a monitoring grade Jd of the data packet, and determining the number of corresponding transit base stations in an auxiliary manner according to the monitoring grade Jd, wherein the method specifically comprises the following steps:
a comparison table of the monitoring level range and the quantity threshold value of the transit base stations is prestored in a terminal database;
determining the quantity threshold value of the transit base stations corresponding to the monitoring level Jd as D2 according to the comparison table; selecting D2 transit base stations to be sequentially connected to form a transmission path; the smaller the monitoring level Jd is, the larger the threshold value of the quantity of the transit base stations is;
after receiving the data packet, the management center acquires the energy use time sequence parameters in the data packet by utilizing the electric energy analysis module to perform early warning analysis, wherein the specific analysis steps are as follows:
acquiring energy utilization time sequence parameters of energy utilization equipment, and marking unit power consumption, running power, noise decibel values and real-time temperature in the energy utilization time sequence parameters as W1, W2, W3 and W4 in sequence;
calculating a load value FZ of the energy utilization device by using a formula FZ=W1×d1+W2×d2+W3×d3+W4×d4, wherein d1, d2, d3 and d4 are all preset coefficient factors;
establishing a graph of the change of the load value FZ with time; when the curve graph is in the ascending stage, deriving the curve graph to obtain a load migration value curve graph, and marking the load migration value of the energy utilization equipment as FQi;
comparing the load migration value FQi with a preset migration threshold, if FQi is greater than or equal to the preset migration threshold, intercepting and marking a corresponding curve segment in a corresponding curve graph, and recording the curve segment as an overload curve segment;
counting the number of the overload curve segments as C1 in a preset time period; integrating all the overload curve segments with respect to time to obtain an overload reference area M1; calculating an overload index Cs of the energy utilization device by using a formula Cs=C1×d5+M1×d6, wherein d5 and d6 are preset coefficient factors;
comparing the overload index Cs with a preset overload threshold; if the overload index Cs is greater than a preset overload threshold value; judging that the load of the energy utilization equipment is abnormal, and generating an early warning instruction to a management center;
the management center drives the control alarm module to give an alarm after receiving the early warning instruction and controls the energy utilization equipment to enter a standby mode so as to remind a manager of overhauling and maintaining the energy utilization equipment; the reason of electrical abnormality is found out, so that the electric energy quality is improved, and the electric energy utilization rate is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the intelligent park electric energy monitoring and managing system is characterized in that a monitoring sensor group is used for transmitting the running state of each energy utilization device to a management center for real-time display for user inquiry during operation; the association evaluation module is used for collecting operation records of each energy utilization device to evaluate association degree GL; when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in the terminal database; the transmission management module is used for extracting characteristics of the data packet cached in the terminal database, analyzing the monitoring grade Jd of the data packet and determining the transmission path of the data packet in an auxiliary manner according to the monitoring grade Jd; if Jd is larger than a preset monitoring threshold value, determining the transmission path of the data packet as a primary transit path; wherein the first-stage transit path is expressed as: the data packet is directly sent to the management center through a base station; otherwise, determining the transmission path of the data packet as a multi-stage transit path; the multi-stage transit path is represented as: the data packets are sequentially transferred to the management center through a plurality of base stations, so that network congestion is effectively avoided, and communication efficiency is improved; the data transmission is more hierarchical;
after receiving the data packet, the management center acquires the energy utilization time sequence parameters in the data packet by utilizing the electric energy analysis module to perform early warning analysis, and calculates a load value FZ of the energy utilization equipment; establishing a graph of the change of the load value FZ with time; when the curve graph is in the ascending stage, deriving the curve graph to obtain a load migration value curve graph, and calculating according to the space-time change condition of the load migration value FQi to obtain the overload index Cs of the energy utilization equipment; if the overload index Cs is greater than a preset overload threshold value; judging that the load of the energy utilization equipment is abnormal, and generating an early warning instruction to a management center; to remind the manager to repair and maintain the energy-using equipment; the reason of electrical abnormality is found out, so that the electric energy quality is improved, and the electric energy utilization rate is improved.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. The intelligent park electric energy monitoring and managing system is characterized by comprising a monitoring sensor group, a management center, an association evaluation module, a transmission management module, a data transmission module and an electric energy analysis module;
the intelligent park is provided with a plurality of energy utilization devices, and each energy utilization device is connected with a corresponding monitoring sensor group; the monitoring sensor group is used for transmitting the running state of each energy utilization device to the management center for real-time display for user inquiry; the running state comprises starting and closing;
the association evaluation module is used for collecting operation records of all the energy utilization devices to evaluate association degree GL, and time stamping the association degree GL of each energy utilization device and storing the time stamping to the cloud platform;
when the energy utilization device is started, the monitoring sensor group is used for collecting device parameters and energy utilization time sequence parameters of the energy utilization device and packaging the device parameters and the energy utilization time sequence parameters into a data packet to be cached in a terminal database; the energy consumption time sequence parameters comprise unit electricity consumption, running power, noise decibel value and real-time temperature of the equipment at the same moment;
the transmission management module is used for carrying out feature extraction on the data packet cached in the terminal database so as to analyze the monitoring grade Jd of the data packet and determining the transmission path of the data packet in an auxiliary way according to the monitoring grade Jd; if Jd is larger than a preset monitoring threshold value, determining the transmission path of the data packet as a primary transfer path; otherwise, determining the transmission path of the data packet as a multi-stage transfer path;
wherein the first-stage transit path is expressed as: the data packet is directly sent to the management center through a base station; the multi-stage transit path is represented as: the data packet is sequentially transferred to a management center through a plurality of base stations;
after the management center receives the data packet, the power analysis module is utilized to acquire power utilization time sequence parameters in the data packet for early warning analysis, and the overload index Cs of the power utilization equipment is calculated;
if the overload index Cs is greater than a preset overload threshold value; judging that the load of the energy utilization equipment is abnormal, and generating an early warning instruction to a management center; and the management center drives the control alarm module to give an alarm after receiving the early warning instruction and controls the energy utilization equipment to enter a standby mode so as to remind a manager of overhauling and maintaining the energy utilization equipment.
2. The system for monitoring and managing electric energy in an intelligent campus according to claim 1, wherein the specific analysis steps of the transmission management module are as follows:
extracting characteristic values of the data packet, wherein the characteristic values comprise data types, data amounts, data transmission distances and data transmission bandwidths; the data quantity, the data transmission distance and the data transmission bandwidth are marked as WLi, WDi and WKi in sequence; acquiring the data type of the data packet, and marking the corresponding type value as Wxi; calculating to obtain a characteristic coefficient WTi of the data packet by using a formula wti=wli×a1+ WDi ×a2+wxi×a3+ WKi ×a4, wherein a1, a2, a3 and a4 are all preset coefficient factors;
acquiring energy utilization equipment corresponding to the data packet, and automatically calling the association degree GL of the energy utilization equipment from the cloud platform; counting the early warning times of the energy utilization equipment to be Z1 in a preset time period; counting the operation years of the energy utilization equipment to be N1; the monitoring level Jd of the data packet is calculated by using a formula jd=wti×b1+gl×b2+n1×b3+z1×b4, wherein b1, b2, b3, b4 are all preset coefficient factors.
3. The system of claim 2, wherein the specific evaluation process of the association evaluation module is as follows:
collecting operation records of each energy utilization device in a preset time period; for a certain energy using device, taking the starting time of one operation record of the energy using device as the center, and marking other energy using devices with starting time difference within a preset value as associated devices; counting the number of associated devices to be L1; if L1 is greater than a preset quantity threshold, marking the start as associated start;
counting the number of times of associated starting of the energy utilization equipment to be Zb; performing time difference calculation on adjacent two associated starting moments of the energy using equipment to obtain an associated interval duration LTi; the associated starting time is the starting time of the energy utilization equipment during associated starting;
comparing the associated interval duration LTi with a preset interval duration; counting the times of the correlation interval duration LTi smaller than the preset interval duration as the proportion Lb; when the LTi is smaller than the preset interval duration, obtaining a difference value between the LTi and the preset interval duration and summing the difference value to obtain a total difference value CZ; the relevance GL of the energy consuming device is calculated by using the formula gl=μ×zb× (lb×g3+cz×g4), wherein g3, g4 are preset coefficient factors, μ is a preset equalization coefficient.
4. The system for monitoring and managing electric energy of intelligent park according to claim 2, wherein the data transmission module is used for selecting a plurality of base stations to form transmission paths according to preset rules, and sending corresponding data packets to the management center according to the transmission paths; the method specifically comprises the following steps:
when the transmission path is a multi-stage transit path, acquiring a monitoring grade Jd of the data packet, and determining the number of corresponding transit base stations in an auxiliary manner according to the monitoring grade Jd, wherein the method specifically comprises the following steps:
a comparison table of the monitoring level range and the quantity threshold value of the transit base stations is prestored in a terminal database;
determining the quantity threshold value of the transit base stations corresponding to the monitoring level Jd as D2 according to the comparison table; d2 transit base stations are selected to be sequentially connected to form a transmission path.
5. The system for monitoring and managing electric energy in an intelligent campus according to claim 1, wherein the specific analysis steps of the electric energy analysis module are as follows:
acquiring energy utilization time sequence parameters of energy utilization equipment, and marking unit power consumption, running power, noise decibel values and real-time temperature in the energy utilization time sequence parameters as W1, W2, W3 and W4 in sequence; calculating a load value FZ of the energy utilization device by using a formula FZ=W1×d1+W2×d2+W3×d3+W4×d4, wherein d1, d2, d3 and d4 are all preset coefficient factors;
establishing a graph of the change of the load value FZ with time; when the curve graph is in the ascending stage, deriving the curve graph to obtain a load migration value curve graph, and marking the load migration value of the energy utilization equipment as FQi;
comparing the load migration value FQi with a preset migration threshold, if FQi is greater than or equal to the preset migration threshold, intercepting and marking a corresponding curve segment in a corresponding curve graph, and recording the curve segment as an overload curve segment;
counting the number of the overload curve segments as C1 in a preset time period; integrating all the overload curve segments with respect to time to obtain an overload reference area M1; and calculating the overload index Cs of the energy utilization device by using a formula Cs=C1×d5+M1×d6, wherein d5 and d6 are preset coefficient factors.
6. The smart campus power monitoring and management system of claim 1 wherein the device parameters include model number, size of the device, and user input into the monitoring sensor group.
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| CN202310941337.1A CN116962469A (en) | 2023-07-28 | 2023-07-28 | Wisdom garden electric energy monitoring management system |
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| CN202310941337.1A CN116962469A (en) | 2023-07-28 | 2023-07-28 | Wisdom garden electric energy monitoring management system |
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| CN117172510A (en) * | 2023-11-02 | 2023-12-05 | 广州崇实自动控制科技有限公司 | Intelligent park operation and maintenance system |
| CN117172510B (en) * | 2023-11-02 | 2024-01-09 | 广州崇实自动控制科技有限公司 | Intelligent park operation and maintenance system |
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