Energy and Utilities
Streamlining energy: Key automatable processes in the utility sector
Today, our physical world is steadily merging with a digital one. Industries are adopting futuristic technological solutions that are giving rise to digitised industrial production (also called a cyber physical system). And automation has emerged as a game-changer, offering opportunities to optimise operations, enhance reliability, and reduce costs.
From grid management to customer service, automation offers myriad opportunities in the energy and utility sector. Grid automation addresses the core segments of the energy and utility industry, including infrastructure, distribution, generation, and transmission. Some of the technologies used are artificial intelligence and control system sensors. It seamlessly integrates DERs while minimising damage and outages to deliver a resilient network protected from natural disasters as well as cyber-attacks. By embracing automation technologies, utilities can navigate the complexities of the modern energy landscape more effectively while delivering sustainable and reliable power to consumers.
Let's explore some of the key areas where automation is transforming the energy and utility industry.
Key automatable energy and utility business processes
- Customer engagement
- Detection of thefts
- Energy trading
- Energy Storage
- Grid management and efficiency
- AI optimises energy grids by managing energy flows between various sources, including homes, businesses, storage batteries, and renewables. This reduces waste and boosts consumer engagement with energy consumption.
- Robots aid energy installations and grid maintenance, monitoring energy generation and consumption. They automate tasks such as pipeline repair and turbine maintenance, enhancing efficiency and cutting costs.
- Blockchain technology enhances grid management by facilitating secure communication among distributed energy resources, like solar panels and smart meters. This transparency optimises grid performance and minimises outage risks.
- Microgrid
- Improve inertia for increased stability
- Maintain voltage and frequency
- Forecast and self-configure
- Monitor local data
- Manage complex energy structures
- Grid Security
Energy companies are incorporating machine learning (ML) and artificial intelligence (AI) into customer engagement strategies. These technologies apply data analytics to understand customer habits and then offer tailored advice on energy conservation, ultimately enhancing customer satisfaction and promoting sustainability.
A leading non-profit published a report that highlighted energy thefts costing consumers £1.4 billion yearly. ML and AI flag these anomalies, which assist companies in arresting these leaks, thereby saving costs, promoting less energy loss, and protecting their assets.
The bulk sale and purchase of energy products, which includes electricity, petroleum products, steam and natural gas, is the wholesale energy market. It is different from a traditional financial market because wholesale energy cannot be stored, which means that supply-demand should be in a constant state of balance. Through smart contracts known as power purchase agreements, blockchain technology offers a decentralised system to automate energy transactions via a highly secure platform. This platform is transparent, efficient, and shows real-time energy prices.
Smart energy storage systems are emerging as integral components in enhancing energy grid management efficiency and facilitating optimised energy distribution. They also enable the creation of virtual power plants, ensuring energy delivery as needed and reducing the need for new power plant construction.
While renewables like wind and solar gain popularity, their intermittent nature poses challenges for grid management. AI and machine learning predict renewable energy availability, enabling effective grid management.
As the name suggests, this is a smaller version of the actual power grid, and it operates independently of the traditional energy grid. The microgrid control system constitutes the microgrid central controller (MGCC) and the field control units (FCUs). Automation in microgrids helps:
AI and machine learning enhance energy grid security by proactively preventing cyberattacks. Data analytics detect patterns indicative of potential attacks, while AI responds swiftly to mitigate threats once identified.
How can Infosys BPM help?
Infosys BPM advances the digital energy transformation through its comprehensive suite of energy and utility business process services. These offerings include master data management, flex-staffing, supplier enablement, and engineering documentation tailored to meet the specific needs of the energy and utilities sectors.
