Data produced by power distribution networks is critical, but so is perfecting data quality and governance. This article looks at utility data acquisition, processing, management and utilisation to enhance operations and customer services through real-time monitoring of grid assets and response to events occurring within the entire network.
The electric utility industry is undergoing a major transformation driven by new sources of energy generation, consumer demand for faster and more affordable services, cybersecurity, and big data.
Gathering data to harvest insights and forecast more accurately offers a significant potential to optimise the way utilities operate.
Data acquisition, networks and communication
Emerging modern grids require accurate data and as-operated network information to function optimally. Given these business imperatives, utilities must overcome current constraints and limitations to enable essential operations data quality.
Good quality data enables the utility to understand network and asset behaviour, operating conditions, and their impact on customer service. Electric networks change routinely, and operations reflect a dynamic condition. Therefore, quality data must be regularly assessed based on its context of use. The utility network must enable accurate measurements of network behaviour to ensure accurate observations and the ability to optimise measures in response to current and accurate data.
The ability to ensure correct inputs from system and operations data enables the utility to substantially improve the quality and cost efficiency of its operations.
To begin with, many utilities agree that they are still missing key information about their assets. This is because the underlying infrastructure for utility networks used today was deployed decades ago when recording data was not critical to business. To make up for this limitation, operators can leverage newly gathered records that come from smart meters and other sources.
Extracting real value from utility data, however, requires the development of a data-driven operation and a data ecosystem that can underpin processes, systems, and people; and create an as-operated paradigm as opposed to an as-designed model.
Utilities generate substantial volumes of data, and while the Internet of Things (IoT) proliferates across networks, thanks to smart devices, it creates multiple new data points that can put pressure on infrastructure.
BI Intelligence estimates that the global installed base of smart meters will increase from 450 million in 2015 to 930 million in 2020. On top of this, distributed energy resources (DER) and legacy IT systems bring fresh challenges to utilities having to manage and interpret greater volumes of information. For example, thousands of mini-generation plants can sit all over the network, bringing in new data points every minute. A system is therefore required to gather and maintain multiple sources of data.
This is where the need for smart, fast and resilient communication networks is vital, because without effective and secure data telemetry smart grid operations are non-existent.
Richelle Elberg, a principal research analyst with Navigant Research, said: “Many electric utilities today are at a critical juncture in terms of determining their long-term connectivity needs and networking technology choices.
“The number of ways in which a utility may leverage connectivity across its territory is exploding as traditional smart grid applications like AMI and DA/SA become the norm, and as emerging applications – ranging from new IT systems and analytics, solar integration, electric vehicle charging networks, and smart city applications – all present opportunities for utilities to benefit from this increasingly networked environment.
Hence utilities are increasing their focus and investments in cellular, RF mesh, point-to-multipoint, microwave point-to-point, private 4G, Wi-Fi, satellite services, leased lines, TDM/ethernet/ broadband, power line carrier (PLC), fibre, and low power wide area (LPWA).
Control and communications at the DER level will enable the development of markets for aggregated clean resources and services, service-oriented business models, and integrated grid management strategies.
Demand for visibility at the DER level is expected to supersede most regulatory or cost considerations. Navigant Research predicts Asia Pacific is expected to lead the global market for utility communications in terms of overall revenue. North America and Europe also present attractive markets, with particularly high growth expected across the smart inverter and EV charging markets.
Grid data management
However, data management and usage remain the most important factor as far as optimising the operations grid systems is concerned.
Energy network operators believe that a principal challenge they face lies in ascertaining a single source of dependable information from the data gathered. Most of these records remain siloed in multiple files and IT systems and therefore need to be unified.
To consolidate this data, it must be segregated from the setups where it gets stored. This is also necessary because the fast pace of development in the power sector implies that the lifespan of discrete IT systems may get shorter over time. Data should be able to move seamlessly between traditional and modern systems.
The modern grid enables the utility to react quickly and effectively in a complex and demanding environment. To enable this intelligence, it is imperative to harmonise data with actual operating conditions. Creating this harmony between data and as-is or as-switched conditions requires an Intelligent Data Management Solution to align utility process and system data.
Finding the right model and system to align this data is the first step to obtaining high quality, actionable data and improving modern grid service quality.
Geographic information systems (GISs) have made it critical to use data for networks. And these are not just digitalised maps that can offer information to third parties. GISs have today been transformed into data centres that can be customised in several ways based on the purpose for which they are needed. They can also be used to prioritise power projects and bundle different projects together for more cost-effective work.
Furthermore, the outlook of network operators to data sharing must shift from a “need to know” basis to a presumption of disclosure. In particular, there should be more data-sharing between gas and electricity networks.
While the value of data for network operators is understandable, it is also essential to collect data in the right ways. If things move in the right direction from the earliest stage, problems that emerge later can be prevented. There have been cases where network operators amassed volumes of data that were never actually utilised – such attempts only result in wastage of time and resources. Therefore, data must always be gathered for a specific purpose and not just for the sake of record-keeping.
On the other hand, some operators feel that if they get too selective in the data gathering process, it can throttle innovation because there are several upcoming uses of data.
By also consulting their stakeholders, operators can accommodate the data needs of others instead of just acting to meet their own objectives.
Mastering a data governance model
Electric utilities are large organizations with many discrete sub-organisations, with each managing various programmes, processes, and systems. Typically, these organisations work separately, in silos, often duplicating and not sharing data. As a result, harmonising data systems and processes with increasing volumes of data aggravates problems associated with a lack of data governance. Today’s mandate is, therefore, a need to engage a governance model ensuring process, system, and data alignment to meet modern grid demands.
Data governance enables the utility to aggregate data across multiple processes and systems, and requires blending accountability, agreed service levels and measurement.
Adopting a strong governance model will improve the approach to the data lifecycle.
As departments are getting reshuffled to facilitate more collaboration between asset managers and data organizers, data-driven transformation for networks needs to be intensified with the judicious deployment of data validation tools. SEI
About the author
Sunil Kotagiri is deputy general manager, U&G BU, Cyient. Kotagiri has 20+ years of experience across various functions – consultancy, programme management and business development in the areas of IT and operational technologies of utilities domain. He currently leads the Grid Solutions portfolio at Cyient. He has a strong knowledge of business processes and a deep understanding of how different systems can be utilised effectively for resolving various business challenges.