By Sundar Ram, Oracle, vice president – technology sales consulting, Asia Pacific
One of the best-kept secrets in the technology industry is the pace of innovation and the resultant transformation of utilities businesses.
Smart meters and smart grid technologies are changing the way utilities serve their customers in Australia.
Simultaneously, a continuously evolving regulatory environment and a strong push toward renewable energy sources and conservation has brought forth a period of change and transition for the utilities industry. This transformation is simultaneously resulting in the generation of tremendous volumes of data. In fact, the biggest opportunities as well as risks for utilities lie in the oncoming torrent of new data, along with the events resulting from efforts to modernise utility networks.
Change doesn’t come easy for an industry that operated for a hundred plus years with systems that have been stable and worked well for the most part. However, traditional systems that have served utilities well over the years were not built to handle the frequency and volume of data that will emerge from smart meters, grid devices and other network controls and sensors. As a result, utility businesses are cautiously restructuring their current IT infrastructure, systems and tools to accommodate emerging needs such as customer prepay, demand response, self-service analytics, near-real-time operational control and distributed generation.
Advanced distribution management
One of the significant trends in utilities in recent years is the Advanced Distribution Management System (ADMS), which takes a more proactive approach to the management of distribution networks based on a common network model with real-time field sensor measurement and more advanced control options. If a network operations team implements advanced distribution management, they can reduce network outages, limit exposure during outages and generally improve reliability.
ADMS also enables greater number of Distributed Energy Resource (DER) connections and better network access. Further, it minimises, defers or completely avoids network reinforcements. Finally, it makes the network observable, controllable, automated and integrated.
Improve customer experience
Utilities are learning that Big Data can help them achieve and maintain the levels of satisfaction desired by customers and by regulators. For instance, by integrating advanced metering, grid devices and network management systems, utilities are able to address more pro-actively outages and other system conditions that exist within their territories. This allows them to be much more proactive in the provision of network condition information to customers and other stakeholders. Leveraging Big Data and other analytical tools, assists utilities in quickly addressing basic customer concerns by providing interactive maps and other visualisation context via the web and mobile platforms. Implied in the scenario is the need to integrate key customer processes and interaction points to operational applications for combined analysis and action.
Today, many of these core processes lack end-to-end integration, visibility and control, leading to high rates of exceptions, poor efficiencies and negative impact on the customer experience. Leveraging a common data model on top of these processes and systems to track and trace key transactions provide the necessary visibility, insight and action to catch
and remediate issues before they
Big Data solutions provide the technology foundation and framework to enable the analysis of meter and event data consumption, from a broad array of sources, both stored and streaming. Utilities are able to perform continuous analytics against this data to look for anomalies, patterns and trends that might indicate an opportunity for them to make actionable decisions on both supply and demand.
Integration into outage and distribution management applications allows for further development of business capabilities such as distribution, load management switching etc. Protocols can be established to move customers to alternate feeders during times of over capacity. Analytical information also allows utilities to look at granular use and consumption patterns for neighbourhoods, districts, or cities to facilitate better supply planning and load forecasting in these service territories. A utility’s use of Big Data has the potential to fundamentally change the way they can address network capacity needs.
Many organisations have geo-spatial data available from their equipment, diagrams and vehicles. This data can be used to deliver real-time analytics to pin-point the need for a maintenance person, when a network is down, overloaded or reaching capacity. This consists of any and all geo-spatial data; assets, maintenance crews, electrical network equipment and other resources.
Utilities are gradually moving away from “one size fits all” services. For example, at the customer premise level, utilities are able to analyse usage patterns at the meter level and provide this usage information back to consumers with the intent of developing market driven and customised pricing offers that reflect individual consumption characteristics.
In mature markets, the use of Big Data solutions can also help utilities determine competitor strengths and weakness, enabling them to exploit competitive strongholds and target marketing programs towards specific customers or segments of customers.
Renewable and distributed energy generation planning
Traditional power generation investments involve large amounts of property to build a large plant on, but newer renewable sources like wind and solar energy can be located closer to demand sources. Big Data solutions can look at all of factors of a city, from standard utility ones like load profiles and capacity to more unstructured ones from city demographics.
Traditional utility data, demographic information and new sensor data can therefore be combined to provide the optimal investment scenarios necessary to meet growing renewable energy portfolio requirements. This can then be used to make smarter investment decisions.
Imagine a scenario where data on wealth distribution in office spaces, commuter congestion and electric vehicle population history together with current load profiles and capacity is combined to predict which buildings will have the highest growth in electric vehicles over the next two decades. This data can feed portfolio planning decisions like deciding where to invest in solar panels – to help source cheaper and cleaner local energy to charge those vehicles instead of transporting it in from a remote fossil plant at high cost.
These scenarios hold a fresh wave of promise in meaningfully addressing at least a portion of Australia’s energy issues. An optimised power generation and distribution system that draws upon Big Data analytics can complement new additions to power generation to meet the power deficit in the country. These advancements will continue to drive utility IT an Operations Technology (OT) convergence and the need for more comprehensive utility Enterprise Information Management (EIM) strategies. Above all, it is an opportunity to transform our utilities that we cannot afford to miss.