Technical Field

The present invention relates to a smart energy management system that combines all energy equipment in the energy infrastructure and enables them to be intelligentized with artificial intelligence.

State of the Art

With the development of technology and the increase in data, the existing structure is insufficient due to security, speed, reporting, analysis and other reasons. In today's energy management systems, it is not possible to continuously monitor all alarm and analog data of all energy devices and to respond instantly in case of crisis, and it is insufficient in terms of security in today's conditions. This situation negatively affects energy efficiency and constitutes an obstacle in effective resource management. For example, there are approximately 4600 generators across Turkey. In the event of a natural disaster such as earthquake, flood or any other natural disaster or any other problem in a province, the existing structure in the province where this disaster occurs can be scanned from a single channel. However, this process takes a long time and it takes about 3 hours to access data such as how many devices are operational and how many alarms are present in the province where the disaster occurred. This causes a serious loss of time when it is desired to respond from the very moment of the occurence of the incident.

However, it is necessary to replace End of Life (EoL) / End of Support (EoS) programs with a more advanced central single application. For example, it is not possible to see whether the Scada system has an alarm in the existing structure in any region. Scada systems only have a closed circuit and there is an alarm cycle inside. Considering that there are 36 Scada systems across Turkey, it is obvious that it is difficult to access data and the system may be inadequate.

Considering all these devices, the interruptions and alarms generated are quite high and create a lot of data. All this data is kept on different servers and cannot be consolidated. This problem causes tardiness and therefore loss of time. In addition, the current structure is insufficient for today in terms of security.

Today, with LDAP Integration, there is a need for authorization-based access and intervention, as well as structures where data exchanges are carried out in an encrypted manner using smart devices, information is prevented from being interpreted by others, and all operations are recorded with log records. In the patent application document numbered TR2022/001863, which is in the state of the art, an energy management system is described. In the relevant application, there is no mention of a smart energy management structure that combines all energy equipment in the energy infrastructure and enables these equipment to be smartened with artificial intelligence.

As a result, the inadequacy of the solutions to meet the needs described above has made it necessary to develop in the relevant technical field.

Brief Description of Invention

The present invention relates to a smart energy management system that combines all energy equipment in the energy infrastructure and enables them to be intelligentized with artificial intelligence.

The object of this invention is to optimize operations, direct investments to the right desicions and increase the productivity of employees to increase operational efficiency and quality in business processes.

In order to fulfill all the above-mentioned and detailed objectives, the invention has an application that supports the Internet of Things and enables the addition of new devices. This application is a user-friendly application where access to devices is provided much faster, data in the data warehouses created from the information received from the devices can be securely retrieved, effectively presented and reported to the end user with artificial intelligence supported analysis. In addition to the above, the application enables rapid field-based electricity consumption analysis, instant detection of faults that have impact on consumption, control of air conditioner set values, control of the operating redundancy of devices, load trends and similar analyzes, and continuous detection of the potential for energy efficiency.

The smart energy management system provides alarm, fault and maintenance data of the equipment, analysis to be made, device replacement processes and improvements in failure and spare parts usage. The system can also detect chronic failures and compare devices by calculating Pue in different provinces according to compensation penalties, invoice checks and load characteristics, thereby comparing a consumption difference between two similar devices, if any.

Thanks to the smart energy management system, all devices that can access the Internet are included in the cloud network and artificial intelligence enables these devices to communicate with each other.

With the smart energy management system, a world-class infrastructure is achieved with uninterrupted communication, where the infrastructure is smartened and managed at a high level, sustainability and continuity are ensured. With the commissioning of the system, significant energy savings are achieved.

Artificial intelligence integration makes the application developed in the smart energy management system valuable. The application performs a continuous interpretation with machine learning with the instant data collected and enables this meaningful data to support both autonomous and manual processes with decision support mechanisms.

The structural and characteristic features and all advantages of the invention will be more clearly understood by means of the figure given below and the detailed description provided by making references to this figure, and therefore, the evaluation should be made by considering this figure and detailed description.

Figure to Help Understand the Invention

Figure 1 is a schematic illustration of the inventive system.

Description of Part References

1 . Smart energy management system

2. AMRS (Automatic Meter Reading System)

3. Generator/Gas Engine

4. DC System

5. Air Conditioner/FCB

6. UPS

7. Connection terminal

8. Server

A. User

Detailed Description of the Invention

In this detailed description, the preferred embodiments of the inventive smart energy management system (1) are described only for a better understanding of the subject matter.

The present invention relates to a smart energy management system (1) that combines all energy equipment in the energy infrastructure and enables this equipment to be intelligentized with artificial intelligence.

The inventive smart energy management system (1) as shown schematically in Figure 1 comprises:

AMRS (2), which is used in energy consumption, malfunction, data storage and billing processes of energy-using devices and uses MODBUS, TCP/IP, MQTT, IEC 62056-21 communication protocols, ❖ generator/gas engine (3) that provides electrical energy management and uses MODBUS, TCP/IP, MQTT communication protocols,

❖ DC system (4) providing direct current and using SNMP, MQTT communication protocols,

❖ air conditioner/FCB (5) that adjusts the ambient temperature and uses SNMP, MQTT communication protocols,

❖ UPS (6) that provides backup electrical energy and uses SNMP, MQTT communication protocols,

❖ connection terminal (7), such as a computer, mobile phone, etc., which enables users (A) to connect to the smart energy management system (1 ); and

❖ server (8) with an application (C) running on the cloud system, using MODBUS, TCP/IP, SNMP, MQTT, IEC 62056-21 communication protocols, which: o supports the Internet of Things, enabling the addition of new devices to the smart energy management system (1), o securely retrieves data from AMRS (2), generator/gas engine (3), DC system (4), air conditioning/FCB (5), UPS (6) devices by providing quick access, o performs artificial intelligence (machine learning) supported analysis on the data received from AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices and performs a continuous interpretation, o supports both autonomous and manual processes with decision support mechanisms with analysized data as a result of analysis, o controls the setpoints of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices, controls their operational redundancy, analyzes load trends, o performs field-based electricity consumption analysis for AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices and instantaneous detection of faults affecting consumption, o performs continuous detection of the potential for energy efficiency of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6), o performs the analyses for the alarm, failure and maintenance data of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices, change processes and improvements in failure and spare parts usage, o detects chronic malfunctions of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices, o performs calculation of compensation penalties of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices, invoice checks and Pue (measurement of energy efficiency) calculation in different provinces according to load characteristics, o calculates the energy consumption difference between two similar devices by comparing AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices according to Pue calculation, o enables all AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices that can access the Internet to be included in the cloud network and communicate with each other through artificial intelligence; and o enables the results of the operations and analyses to be efficiently presented and reported to the end user (A) via connection terminal (7).

In the inventive smart energy management system (1 ), the user (A) connects to the application on the server (8) via the connection terminal (7), using his/her name and login credentials. After connecting to the application, the user (A) can see the AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices on the homepage/interface on the connection terminal (7) depending on their level of authorization. In this application, not every user (A) can see every page and also the actions taken by the user (A) are recorded by the server (8) in the form of log records.

The user (A) who establishes a connection via the application interface of the server (8) using the connection terminal (7) lists the number of devices with IP, number of connected/unconnected devices, number of devices with reactive penalty, number of devices with reactive penalty, number of devices with power outage, alarms and total daily energy consumption for AMRS (2), generator/gas engine (3), DC system (4), and air conditioner/FCB (5), UPS (6) devices by province/district/region.

AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices are combined in a single application on the server (8). Thanks to the user (A) friendly interface provided by the server (8), fast access to information, ensuring information security in this access (B), and effective resource management with the help of artificial intelligence are ensured. In addition, the relevant interface provides energy efficiency with reporting outputs such as fault alarm detection, prevention of consumption increases due to faults, device life calculation with fault cycle, year and similar data, load analysis, capacity analysis, investment analysis, outage estimation from fault analysis, chronic fault detection, Pue calculation and comparison according to load characteristics, and electricity bill.

With microservices running on servers (8) using cloud technology, the data of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices in the field are read in real time, the results of such readings can be monitored on the web page provided by the server (8) and these data are periodically recorded in the database on the server (8). The server (8) enables retrospective graphing and reporting. Server (8) can automatically turn off and on microservices that read AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices. Server (8) communicates with AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) and connection terminal (7) in an encrypted manner via SSL/TLS certificates, thus ensuring data security. The server (8) is able to identify important parameters by means of machine learning and deep learning methods on the data warehouses created after the data is recorded. Using key parameters, energy consumption anomalies and the impact of new inputs in the smart energy management system (1) on consumption are detected. Due to failures or interruptions in the smart energy management system (1), the lifetime of AMRS (2), generator/gas engine (3), DC system (4), air conditioner/FCB (5), UPS (6) devices is determined, spare material and stock can be tracked. By tracking the lifetime of AMRS (2), generator/gas engine (3), DC system (4), air conditioning/FCB (5), UPS (6), the quality of the service provided is monitored and new investment planning is ensured.

SCADA systems offer the opportunity to quickly access and manage the data of multiple devices in a center. In the current structure, such access and management are used. In the inventive smart energy management system (1), it is possible to access and manage the data of multiple devices in thousands of centers and locations from a single point. Thus, the work done by thousands of Scada systems can be done from a single point. In addition, the smart energy management system (1) can integrate and work with different brands and models.

While a minority of the AMRS (2), generator/gas engine (3), DC system (4), A/C/FCB (5), UPS (6) devices can be integrated into the cloud structure, the remaining devices need to be smartened.

In the smart energy management system (1), for example, when an earthquake occurs in a province, all generators/gas engines (3) are scanned within 1 minute at tO thanks to the emergency button. In the relevant province, data on how many generators/gas engines (3) are running, how many generators/gas engines (3) have low fuel levels and similar data can be accessed instantly and thus intervened immediately. With the new structure, all alarm and analog data of all generators/gas engines (3) in the smart energy management system (1 ) are continuously monitored, all scans are performed within 1 minute in the province focused on emergency situations, and the required detailed report is presented to the user (A) within 1 minute. In normal situations, all generators/gas engines (3) are periodically scanned every 5 minutes. Thus, operations that take hours, especially in disaster scenarios, are carried out in a very short time.

In another example there is a lot of data in the DC system (4), and they are located in different clouds. With the new structure, it is aimed to collect this big data in a single cloud. Big data will be analyzed and visualized through artificial intelligence and operations will be managed.

For another example, a failure of the A/C/FCB (5) in a province may be given. In the existing structure, if this fault is not big enough to prevent the A/C/FCB (5) from working and turn the A/C/FCB (5) off, the A/C/FCB (5) will work, but it will cause the motor and gas circuit of the A/C/FCB (5) to work more, thus consuming more electricity. In the current structure, this problem can be detected in 3-month periods from maintenance to maintenance with manual intervention. This situation causes the monthly invoice from the breakdown cost to increase up to 3 times and causes very high invoices to be paid.

In the current structure, faults that are detected in 2-3 months with manpower can be detected in 1-2 days with the new smart energy management system (1 ) supported by artificial intelligence. In this way, both savings are achieved, and the number of man/days is reduced. Thus, effective resource management is ensured.