"At a time when the Indian utilities are likely to transform into network services providers, derivation of accurate, consistent and complete data holds the key to obtaining actionable insights," a team from Cyient utilities business told POWER TODAY during an interaction in New Delhi. Established in 1991, Cyient with its domain knowledge and technical expertise leverages the power of digital technology and advanced analytics capabilities in helping clients solve complex business problems, as their design-build-maintain partner.
Given the accelerated rate of changes happening in the utility space globally, the Indian utilities are expected to evolve into providers of network services. This has led service providers like Cyient to interconnect diverse systems used in the utility industry for generation of effective data, thus creating the right ecosystem.
"Our teams are focused on developing a framework that can take inconsistent and incomplete information or data from multiple unconnected systems and deliver a strong takeaway," says Venkata Satyadeep Mane, Programme Manager, India Sales (Utilities). For instance, in a single asset like a transformer, the Geographic Information System (GIS) may have an attribute that is different from that of the Asset Information Management System (AIMS). Cyient's intelligent Asset Information Management Solution (iAIMS) enables utilities to assess, improve, associate and maintain enterprise asset data for efficient asset management and performance.
Also, if utilities are to employ data from these systems in a definitive manner, it is important that the data fed in be viable, secure and accurate. "One of our flagship solutions, intelligent Data Management Solution (iDMS), helps clean, validate, establish and govern data quality. As a result, by enhancing the quality of input into the end system, we help utilities accurately predict and share correct information with the control or dispatch centre," informs Mane.
Copious amount of data is expected to be generated from the growth in the generation of renewable energy and from the federal government's plans to electrify at least 30 per cent of all vehicles on the country's roads by 2030. Avers Sunil Kumar Kotagiri, Lead Consultant, "We believe that this is the right time for us to create robust solutions and that is where iDMS comes in. The solution helps utilities validate data across systems." Going forward, utilities will leverage high-quality data for both accurate decision-making and advanced analytics.
Innovating in times of disruption
Amit Kishore Mathur, India Sales (Utilities), provides an interesting insight. "With Indian utilities becoming increasingly mature, we see three actionable areas: one, on smart metering, two, on renewable energy and three, on improving their overall operational efficiency."
In fact for smart metering, Cyient has developed an innovative solution to convert a standard metre into a smart metre by retrofitting it. It is an end-to-end product made completely in-house, which is aligned with Cyient's Make in India programme. "The product connects the modem to the Distributor Transformer Ratiometers (DTR) to get information on power consumption, voltage, etc., and sends it through IoT to the cloud for analysis and predictions," elaborates Mane.
In January this year, Cyient implemented 50 metres at the famed Medaram Jatara festival for the Telangana State Northern Power Distribution Company (TSNPDCL) to ensure uninterrupted power during the four days of festivities. SMS alerts based on threshold average were enabled to be automatically sent out to field technicians in case of any disruption.
"The interesting thing here is that we made regular legacy metres smart by adding a retrofit module. Power consumers simply had to buy our module that works on the Device Language Message Specification (DLMS) protocol compliant with most metres," asserts Mane. The solution comes at almost one-eighth of the price of a smart metre.
The need for keeping data relevant
But how can utilities ensure that the data collated stay relevant to which Kotagiri explains, "No data is useless or irrelevant; one just needs to determine its importance. Cyient solutions help utilities assess and understand the importance of each data element and the right source to pick it up from. We also try to leverage the existing data to the maximum." If a utility gets a lot of data from smart metres or other Supervisory Control and Data Acquisition (SCADA) devices, Cyient can take those data to validate the static information in the GIS or other management systems. "From the market side of the business, we assess the customers' mindset. Since Indian utilities are catching up with the developed world, consistency of data has become important," adds Mane. He mentions the major gaps in interconnectivity within the industry. Data flow between the GIS and Advanced Distribution Management Systems (ADMSs) is a prime example. Cyient has successfully addressed such issues for its clients.
Similarly, integration of heterogeneous systems includes Outage Management Systems (OMSs), Advanced Metering Infrastructure (AMI), Field Force Automation (FFA) and IT systems like SAP and CRM. Mathur says, "Some of the regulatory processes followed by the utilities for the procurement of such solutions need to be amended so that they can evaluate, choose and obtain the right solutions in bridging specific gaps. Eventually, given the speed at which Indian utilities are evolving, they are likely to move towards becoming network service providers rather than just being power distribution companies." However, since such a transition will only add to their data inconsistency challenges, Cyient offers advanced solutions such as iDMS to Indian utilities.
Declares Mane, "We are simultaneously trying to reduce the false positives with the iDMS and iAIMS. Data collected from various systems on assets are transformed into information on which you derive insights and take actionable steps."
Incorporating machine learning into systems
The iDMS solution comes with the machine learning aspect built into it. For instance, it can validate the phase that is critical from the operational point of view for load balancing in a network to compare it against historical data. "By using machine learning over a period and assessing all available historical data, we help improve the validation process. Instead of having to send a person to physically validate a component, utilities can now validate it within the system," states Kotagiri.
He goes on to explain how machine learning is also leveraged in the connectivity of the transformer to the metre. "In the eventuality of an outage, if utilities do not have the right connectivity, they will end up going to a different transformer than the one which is affected, leading to delays and an impact on the revenue. However, machine learning algorithms promptly help validate data received from smart metres and the GIS to precisely show any gaps."
Cyient's solution is based on a proprietary framework called the Framework for Intelligent Operations (FIOPS). This essentially comprises pre-operational and operational segments. At the pre-operational stage, both iDMS and iAIMS have inbuilt machine learning to ensure that the right data gets ingested into the system. On the operational side, a Disaster Operations Management System (DOMS) helps utilities prepare for disasters, both proactively and reactively.
The system helps in making predictions by evaluating weather, social media and historical asset behaviour data. “After aggregating multiple sources, we try to layer data on a map and help utilities identify potential areas that pose a higher threat to the assets in case of natural disasters,” emphasises Mane. This would enable utilities to proactively plan for a field team to help restore power supply at the earliest.
According to the Cyient trio, several private utilities in India have shown immense enthusiasm for these solutions and systems. Among other things, the unexpected August floods in Kerala once again highlights the need for the Indian utilities to plan well ahead of contingencies to mitigate the sufferings of consumers.
- Manish Pant
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