Key challenges to data-centric utility business models

Global utilities are speeding up the digital transformation in a bid to utilise data to enhance grid management, improve customer services, adhere to regulation, optimise revenue collection and decarbonise. However, a number of factors hinder utilities from unlocking the full potential of grid data to maximise operations.

A discussion held during the Grid of the Future Summit by industry representatives discussed challenges facing data-centric businesses, and the key considerations for leveraging data today and in the future.

Data handling, security and privacy

Gary Ang, director at Singaporean utility SP Group, said utility companies are struggling with data protection and security because they do not have the complete architecture that enables them to have a clear view of the data that is communicated within networks.

As a result, Ang said: “It is hard to move to data-centric operations.”

He said energy firms will need to invest heavily in technologies that provide clear visibility of the data being communicated amongst grid assets.

He added that the lack of interoperability of data from various applications and assets within utility operations is a major barrier to digital services. To address this, energy firms need to stop operating various applications and divisions in silos from a data management perspective but rather integrate the data from various apps for single processing, said Ang.

Data quality

Ang reiterated that “quality data is very important for decision-making and utilities do not have good data governance and control to be able to improve the quality of their data.”

David Kirkland, Solution & Innovation Director, Oracle Utilities EMEA, added: “Good data quality is a process and to achieve it, utilities and industry need to take advantage of best practices.

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“They should consider data as one of their primary assets.”

Kirkland said energy companies should employ robust methods of data collection and processing and of ditching and discarding data that is deemed poor quality.

“Understanding what data is valuable is very critical as it is easy to gather every bit of data available but difficult to end up with data that will result in positive outcomes,” he said.

Kannan Munisamy, Lead, Business Interface & Partners, TNB, added that “the problem with utilities is that they want to know everything.”

Data management and automation

Munisamy urged utility firms to leverage data filtering within the IT and OT environment to make sure they have the right data format. In addition, he said data categorisation is vital to avoid utilities struggling with a ‘tsunami’ of data with information coming from various sources including call centers, smart meters, and field workers.

“Business objectives must be used to assess the data quality and management. When you have an objective, the data makes sense,” said Munisamy.

And as such data acquisition, management and processing need to be automated and data storage be on the cloud, said Munisamy.

In addition, Munisamy said utilities need to make sure that quality data is readily available for sharing across various divisions.

For data management to be optimal across businesses, the speakers highlighted the role Chief Information Officers play (CIOs) and Chief Data Officers.

Key considerations for leveraging utility data

Munisamy, said data is expanding utility operations from grid operation and asset management to energy and customer management.

For instance, TNB, through its Smart Utility Initiative which was started three years ago, is deploying digital solutions to make data available for asset productivity, distribution and outage management, smart mobility, and smart metering.

Owing to the initiative, TNB will be able to utilise use cases such as distributed energy resources, integrated energy optimisation, and prosumers to accelerate the energy transition, according to Munisamy.

Ang, added that SP Group plans to make use of data and digitalisation for decarbonisation purposes.

He said SP Group plans to achieve peak emissions by 2030 and data will help the company to achieve the goal.

”By 2030, we plan to have 160,000 electric vehicle chargers which we will use data to optimise as well as to expand our portfolio of renewable energy,” said Ang, “We will need visibility of DERs to optimise the bi-directional flow of energy and we will use data to forecast energy demand and ensure load balancing to avoid outages.”

However, the three speakers agreed that for utilities to deliver the energy transition using data, they need to gain consumer trust regarding data security, privacy, and usage.

Gaining consumer trust will open doors to open data sharing, however, to achieve this energy companies will first have to show consumers the value of them sharing their data.”

“Consumers will share more data when they know they will get something out of it,” reiterated Ang.

Find out more about the Data Science in Future Grid Management session.