Energising the Utility Data Paradigm

Energising the Utility Data Paradigm


As electric utilities continue to evolve into increasingly data-driven organisations, GIS is fast emerging as the backbone for data management platforms.

A transformation is underway at electric utilities. The very foundations of electricity distribution that have supported our way of life for decades — the systems, processes, assets, information — all are poised for a major overhaul.

A variety of catalysts have instigated this transformation. Green technology such as renewable energy and electric vehicles are placing new dynamics and demands on the distribution network. Increasingly advanced monitors and devices continue to redefine the electric distribution system, producing more detailed network information faster than ever before. Progressive technology schemes are now able to self-analyse conditions and automatically reconfigure power flow, quickly and safely minimising the extent of outages. Consumers of today expect more control and real-time information about their energy use, on the device of their choice. Yet, as climate change threatens our world with more intense weather patterns, our ageing energy infrastructure stands at ever greater risk.


Old hand-drawn-electric-distribution-map
Old hand-drawn electric distribution map, and the same neighbourhood in Electric Distribution GIS

At the core of this transformation lies data; and they are all over the place. But while the concept of GIS as a backbone for complete data management and data sharing platform has been talked about for some time now, it is yet to take off fully. For instance, in complex urban areas where infrastructure is underground, paper maps from decades ago are often still preferred over digital records. And most surprisingly, a power company is usually unaware of a residential power outage until customers call in to report it!

Information — lifeblood of an electric utility
Every project proposed, every asset installed, every crew member dispatched — all begin with data from the systems. When decisions are made using incomplete or incorrect information, there is always a chance of missing out on a more optimal or cost-effective alternative.

Modern electric utility information architecture is a complex landscape of software solutions and databases. Due to the geographic distribution of electrical system assets, GIS is often the primary repository for asset information. This also makes GIS the natural source for maps in system operations, as well as the model for electrical connectivity. Other core enterprise systems are integrated with the GIS to manage various business functions: a Customer Information System (CIS) manages billing and account information; the Work Management System (WMS) handles work order scheduling and progression of construction jobs; and Outage Management System (OMS) models the flow of electricity by interpreting the GIS electrical connectivity (network) model. Combined with real-time customer calls from CIS, the OMS is able to infer the location and extent of power outages.

Understandably, it can be difficult for engineers and analysts to navigate this complex landscape of systems. However, a strong data governance programme can mitigate these challenges. A comprehensive data governance programme for an electric utility is comprised of six components.

A single authoritative source: Every piece of data must have a single and identified source among all systems. It is common, particularly in large organisations, to have similar or duplicate data stored in different locations, different formats, and managed separately by different people. Even something as fundamental to an electric utility as pole locations can be difficult to have clarity on because of disparate data sets. Ideally, a change in the pole asset base would be recorded in all systems in the same way, but organisational, business process, and communications issues can prevent a systematic update from happening. A data governance programme should identify where the record will be maintained and ensure that authoritative source is used to populate and maintain the other data repositories.

Standardisation: Multiple systems are a necessary reality in most utilities today. In order to support authoritative sourcing of data, an organisation needs to have data standards in place. Standards allow systems to easily share data and enables users to efficiently collect, integrate, and aggregate information from otherwise disparate systems. If adopting a standard requires modification to a system data model or to an application, then it may be prohibitively expensive or disruptive to the business. A case can be made, however, to address some of the more fundamental data elements. An electric utility, for instance, may implement a systematic circuit naming convention, as circuit-based reporting is common across many functions in the business.

Data quality: Poor business processes, inadequate training, lack of awareness, and systems or tools that are difficult to use are all major contributors to data quality degradation. GIS can present a special type of issue since the spatial component, the topological dependencies, and electrical connectivity models can be difficult for someone to understand. Data presented in a mapped view on a computer screen may look visually fine, yet have hidden problems. A strong data governance programme should measure the quality of data, identify causes of problems, and prioritise those problems that need to be addressed first.

Interoperability: Data infrastructure must promote communication, exchange, and re-use of information across diverse system platforms. Interoperability is supported by the implementation of data standards, but standards are not absolutely necessary. As described previously, it is not always possible for a system to adopt standards. Establishing communication between systems that do not subscribe to the same standard requires more complex solutions, and can be more vulnerable to system-specific changes. Since a standard is not in play, nuances of more custom system interfaces can be overlooked. Interoperability across systems, however, means data can be more readily available to a larger audience in a consistent way.

Availability: Data must be readily discoverable and available. Tools for accessing information from mobile devices and the Internet are evolving rapidly. Data consumers are all empowered to access and use much more information than has ever been available. The challenge for the utility is ensuring the information is accurate and that it conveys the truth. Objectives of a data governance programme should include consistency, transparency, reproducibility, and meaningfulness in data that is presented to any audience.

Accountability: Tracking mechanisms must monitor any modification of data in authoritative source systems. Data stewards and data owners must be part of a successful data governance programme. They provide overview, develop an understanding of how the organisation can continually improve data, and drive best practices.

Implementation of a comprehensive data governance programme is never a simple task. Support from company leadership is mandatory, as data governance requires participation at all levels, and impacts just about any business processes that manages or consumes information. Data governance often requires that long-standing practices receive an overhaul. Modifications will need to be coded into systems and ETL processes. Due to the significant changes required to adopt a full data governance framework, many organisations get by with only partial or limited components. The resulting challenges of redundant, unavailable, or incorrect information are considered acceptable inconveniences. However, as electric utilities continue to evolve into increasingly data-driven organisations, the penalty for ignoring data governance will soon outweigh the difficulties of embracing it.

To sum it up
GIS was once regarded by many in the electric industry as just a simple mapping tool; old paper construction sketches and drawings had been manually digitised, and GIS was the programme to explore and print maps. Some then began to leverage GIS as the source for asset records. More innovative utilities eventually adopted GIS as a design tool, digitising work plans and issuing maps to the field for construction. Through the years, GIS has continued this trend of broader use, weaving its way into the fabric of enterprise architecture and business processes. With the adoption of open standards and Web 2.0 in the past decade, however, the role of utility GIS is now evolving into something different, something more. Based in the universal language of geography, GIS has the adaptability and flexibility to become a means of integration. Web-GIS is emerging as this common platform, empowering our analysts, engineers, managers, and executives with the information they need to make better, faster decisions.