The power sector is witnessing an uptick in data generation and aggregation owing to the rapid growth of digital systems equipped with internet of things (IoT) and data analytics capacities in the electricity grid. These systems help in facilitating the timely diagnosis and rectification of issues as well as advanced prediction of demand and supply dynamics, thus enhancing grid stability. To manage this data, power utilities need to systematically transition from the existing supervisory control and data acquisition (SCADA) system based on a distributed architecture to a cloud-based architecture that is capable of processing data and generating useful insights.
A traditional SCADA or a distributed SCADA system operates on a locally hosted server with on-the-ground staff available to provide and operate the communications infrastructure. This system entails significant expenditure on staff and local technologies for data logging as well as maintenance. In addition, these systems are vulnerable and, therefore, the companies have to ensure data security through upkeep and maintenance. Moreover, it gathers data on broad parameters and takes a reasonably long time to process it.
Although distributed SCADA is effective in managing day-to-day operations of power utilities, it has a limited ability to carry out predictive analysis of future demand patterns and maintenance issues as these systems cannot archive data on a long-term basis nor process large volumes of data to gain insights based on recursive patterns.
Distributed SCADA systems such as traditional SCADA systems require components made by the same manufacturer, as they are incompatible with products made by different manufacturers. Therefore, these systems have high switching costs as well as high repair and maintenance costs. Similarly, these traditional systems are only usable in power plants of a certain capacity and require staff with a high level of technical knowledge for supervision and maintenance.
In cloud-based SCADA systems, data is logged on to a large array of remote internet servers rented from a cloud hosting service, making it easy to scale, upgrade, monitor and deploy these systems at a low cost. These systems do not require local data centres, thus saving expenses on their maintenance and security.
With the growing installation of IoT-based digital components across the grid, there will be more parameters that will be monitored in real time, making data acquisition immensely granular and specific. This will lead to an exponential growth in the demand for data storage and data processing capacities, thus spurring the transition to cloud-based SCADA systems, as they are operationally superior to extant distributed SCADA systems at handling, analysing and storing a vast quantum of data at a lower expense.
Unlike traditional SCADA systems, cloud-based SCADA systems are interoperable with standard protocols such as message queuing telemetry transport enabling communication between different platforms irrespective of their vendors. Further, SCADA systems hosted on the cloud can be deployed by small microgrids as well as thermal power plants with 1,200 MW of capacity as they are priced as per the data storage utilised. These systems delegate technical competency and maintenance to the cloud hosting companies unlike traditional systems. Utilities need not maintain in-house technical staff to repair them in case of breakdowns.
Renewable technology and cloud-based SCADA
Cloud-based SCADA is ideal for renewable energy projects based on solar and wind energy because these assets require constant and regular monitoring and calibration in accordance with the changing weather conditions. Further, decentralised renewable assets such as rooftop solar have limited capacity and thus cannot employ sufficient on-ground manpower to manage it. In addition, renewable energy assets are relatively new and therefore they can leapfrog directly to cloud-based SCADA instead of having to invest in traditional SCADA equipment and then its replacement with cloud-based SCADA.
Renewable energy assets also have irregular yields with a lot of volatility in generation due to various factors such as angle of sunlight, weather and wind patterns. Cloud-based SCADA, equipped with higher processing capacities, can also harness past data and predict future generation yields using machine learning (ML) and artificial intelligence (AI). It will also be able to offer suggestions to maximise the plant load factor and efficiency of assets.
It is expected that this technology will be useful for consumers who are producing electricity (prosumers). It will empower them to effectively predict over the short term the electricity to be generated by their renewable assets and also estimate their indigenous requirements. This will help them to independently determine the electricity that they can sell during peak time and the electricity they will have to purchase in off-peak periods.
The way forward
Most of the installed capacity functions on traditional SCADA systems and therefore it is expected that the existing generation companies will opt for a steady and phased transition to cloud-based SCADA architecture. Initially, utilities are likely to switch over to remote terminal units (RTUs) so that plant operations can be seamlessly monitored, supervised and controlled over several devices such as phones and computers. This will be possible through advanced human-machine interaction (HMI) technologies.
Gradually, utilities are expected to integrate IoT devices in existing field devices and the data gathered by these devices will be instantly transmitted to SCADA. This will help in real-time monitoring of fault passage indicators in the system, and ensure immediate replacement and repair of faulty components in the system. It will also help in automating the parameters that have to be actively monitored and controlled by the utility personnel. Utilities can later install IoT devices in other plant-related operations, thus expanding the scope of cloud-based SCADA to auxiliary functions such as energy storage and plant maintenance. Microgrids and decentralised renewable assets are also likely to integrate the SCADA architecture in their operations in addition to using it for storage of excess electricity generated during peak periods.
Net, net, utilities, owners of distributed electricity assets and prosumers are likely to completely transition their SCADA infrastructure to a cloud-based architecture, which will provide data analytics and predict the demand and supply dynamics through data-intensive ML and AI processes. The cloud-based SCADA system will also provide advanced information on component failures and help plant owners to accordingly engage in preventive maintenance of components in their systems. n
With inputs from a presentation by Amitava Chakraborty, Manager, Distribution Automation, CESC, at a recent Power Line conference