Smart Grid: Integration of Artificial Intelligence, Machine learning, crypto anchoring & Energy Open Source protocolling.

Smart Grid: Integration of Artificial Intelligence, Machine learning, crypto anchoring & Energy Open Source protocolling.
The integration of Artificial Intelligence, Machine learning, crypto anchoring, open source protocolling and other beyond state-of-the-art techniques will be essential in keeping the grid under control and facilitate new (green) energy opportunities.

New philosophy
The European distribution grids connect 260 million customers and transport 2700 TWh of electricity annually over 10 million km of power lines and over 4.5 million substations managing the transformation between high, medium and low voltage levels.

The transition towards a more sustainable energy production and a further electrification comes with major investments in the distribution grid. The bi-directional and variable energy flows and the increasing electricity demand however urges for a dramatic increase in  closer monitoring, control and analysis of the energy flows in general.

The wide-scale adoption of distributed generation, electric vehicles, solar panels and heat pumps have brought with them a host of challenges and opportunities to the distribution system operators but also to other stakeholders. The increased load, and the now bi-directional energy flow, have made the well-behaved and easily predictable MV/LV distribution system a thing of the past. As a result of the changing operations to an active management of loads, generation, and both localized and over-all power flows, the historically simple, distribution sub-station monitoring is no longer sufficient. With nowadays managed power flows, a control fault causing a neighborhood to connect all their electric vehicles at once, or disconnect all PV generation at once, severe, zone-crossing, upwards-propagating, cascading effects on the distribution system can occur.

Knowing the true system state, having the ability to isolate problem areas, adapt the system operation, and diagnose and anticipate the problem remotely becomes a basic necessity, not just on the larger sub-stations, but also on the smaller distribution cabins, once of secondary importance.  Instead of designing for the peak load, the nature of many of the new loads allows an automated shifting in time. It is now sought to no longer passively undergo the demand, but actively manage the demand and spread it out in time.

It will be crucial to integrate much more data from much more stakeholders, such as Electric Vehicle Infrastructures, Solar Parks, Heath Coupling … not only taking in account mere DSO SCADA monitoring (and control).  This means existing power distribution infrastructure can be used more effectively and less expensive and intervening wiring upgrades are needed.

All the above demands a paradigm change in the way of monitoring and controlling the different energy (electricity) flows in the near future:

  • Evolution of a static (grid) monitoring of energy flows towards a flexible one.
  • Migrate from a ‘No overview of state of grid’ – ‘Fit and forget approach’ – to an  increase of network state observability – ‘Forecast and remediate’
  • Deviate from ‘fixed rule-of-thumbs’ and none or little operations based on actual observations towards organizing a multi-objective Demand Response control based on grid observations across the Cloud/Edge ecosystem in a scalable manner

This changes the philosophy of grid operation & electricity production and trading on a fundamental level. The integration of Artificial Intelligence, Machine learning, crypto anchoring, open source protocolling and other beyond state-of-the-art techniques will be essential in keeping the grid under control and facilitate new (green) energy opportunities. Using crypto ancoring for labeling energy flows with undeniable identification will stimulate and promote the trading of (green) energy and boost ways of decentralized production and it will be crucial in the continuous struggle against hacking and mass calculation (Quantum Computing). Machine learning techniques, implemented in back office and EDGE platforms will tune the data streams from EDGE to central system, and will improve the efficiency of the used algorithms. A back Office that has the ability to for instance detect 'hot spots' in the grid, based on input of the grid itself and decentralized producers or customers will be a powerful tool to anticipate possible problems even on the Low Voltage level (MV/LV substations 10-36 kV to 230 V) and RMU's (Ring Main Units)

The Bausch Datacom portfolio

The M4 System:
The M4 System is a communication RTU/Gateway for monitoring and controlling equipment in electrical energy distribution systems. It acts as an interface for sub-modules that offer electrical measurements, power quality monitoring, directional fault detection, fault recording etc. Reduced digital and analog I/O’s for system automation are integrated (DinBox version). The M4 System is a micro RTU tailored for all-in solutions, offering mobile communication (LTE Cat. 1 GPRS …), security (TLS, VPN IPsec), protocolling (IEC 60870-5-104 MODBUS RTU, MODBUS TCP, MQTT), routing, I/O extensions. It offers DINrail or industrial housing and comes optionally with a management DMSW (Data Management Software).

Main Features:

  • IEC 60870-5-104 Slave (6 Masters possible)
  • Modbus RTU + Modbus TCP
  • TLS or VPN IPsec  (Optional)
  • MQTT
  • LTE Cat.1 & GPRS module
  • Integrated I/O (DinBox RTU M4)

Product Codes:

  • InduBox RTU M4: IB_RTU_M4
  • DinBox RTU M4: DB_RTU_M4
  • DinBox RTU  IoT M4: DB_RTU_IoT_M4 (Q4 2021)

The Q7 System:
The Q7 System is the big brother of the M4 platform. It is not only deployable in MV/LV (10KV to 230V) substations but also in MV substations for RMU and switching controlling. Due to the container software approach new applications can be integrated such as Crypto Anchoring, Machine learning etc. The Q7 System is a full RTU tailored for core RTU functions, offering mobile communication (LTE Cat. 1 GPRS …), security (TLS, VPN IPsec), protocolling (IEC 61850 IEC 60870-5-104 MODBUS RTU, MODBUS TCP, MQTT), routing, I/O and Power Quality Fault Passage extensions. It offers DINrail housing and comes optionally with a management DMSW (Data Management Software).

Main Features:

  • IEC 61850 non-Goose
  • IEC 60870-5-104 Slave (6 Masters possible)
  • Modbus RTU + Modbus TCP
  • TLS or VPN IPsec  (optional)
  • MQTT
  • LTE Cat.1 & GPRS module
  • Remote I/O (Optional)
  • New applications on demand by Container technology
  • Crypto ancoring (2022)
  • Machine Learning, AI algorithms (2023)
  • Open Source Energy protocolling (2023)

Product Codes:

  • DinBox RTU Q7: DB_RTU_Q7 (Q4 2021)
  • DinBox I/O: DinBox_IO (Q4 2021)
  • DinBox FPI PQ: DB_FPI_PQ (Q1 2022)

The DMSW System:
The DMSW Back Office Tool (Data Management Software) is a modular management system designed to be integrated into existing management systems. It offers mass firmware upload, remote config, automatic commissioning, health check and many other features. Through container techniques customer related functionality can be easily integrated. Configuration and management is done using a file-based management concept.  Firmwares, containers, and configurations of the RTU’s in the field are created using File Upload and Plugin Mechanisms and uploaded to the DMSW. In addition to the management system, the DMSW system has monitoring functionalities that can be monitored via the open source application Grafana.

Main Features:

  • Telegraf Agent Server for collecting and reporting
  • Grafana
  • InfluxDB (Time-Series Database for Metrics)
  • Node-Red
  • Container Technology (Docker)
  • Supports all ‘M4’ and ‘Q7’ and third party products

Product Code:

  • Data Management Software: DMSW_V1.0 (Q4 2021)

More information on article or products:
Rik Verheyen - Business Development Mgr. - 003216461288 - rik.verheyen@bausch.be

 

 

date_range Published on 17-06-2021 10:39
person Rik
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