Asset and Fleet Optimization: Key to Success for Power Generators

It's a tough task: accelerate the energy transition without pushing risk out of bounds.

Intelligent fleet and power asset optimization are essential for power generators to meet the demands of the future.

Power generation companies are at the center of mounting demands from governments, the private sector, and consumers to transition from reliance on fossil fuels towards a decarbonized world. Utilities and power generators are rapidly seeking greater levels of decarbonization and energy flexibility by investing in solar, wind, storage, hybrid and decentralized energy systems. The diversity of fleet assets is growing, too – renewables, storage and hybrids are creating a dramatic shift in status quo.

Yet, even as the cost of renewable energy comes down, utilities and independent power producers (IPPs) are under intensifying economic pressure to improve their balance sheet, increase revenue, and drive cost-out. They’re being charged with managing operations to maintain reliability and improve profitability, while responding to dynamic, variable, and uncertain market conditions through the transition.

Power generators face multiple interrelated challenges as they strive for the ambitious goal of net-zero carbon emissions including responding to shifting market forces, labor forces, and next- generation technology.

Leaders in the energy sector are exploring how digital technology can create intelligent and autonomous fleet operations to optimize daily generation, manage risk, improve margins and operate from anywhere.

Integrate control room, commercial ops, commitment and dispatch optimization, with a focus on:

Intelligent fleet operations start at the asset level, with a focus on advanced analytics for predicting week-ahead, day-ahead capacity and its cost. This seemingly straightforward task is complicated by weather forecast inaccuracies and new generation availability dynamics, so traditional methods for forecasting capacities and operating costs are insufficient.

In place of static curves and cost profiles, advanced AI/ML analytics are integrated with asset operational and availability data. This power generation asset management software more effectively predict capacity, its cost and uncertainty, and efficiently alert all users – from the site- level to central operations – to changes in predictions and uncertainty in real time. Similarly, market predictions down to the site level prevent inefficient resource allocation and ensure an optimal commitment at the fleet level.

Commitment optimization must manage the risk associated with both increasing capacity and market uncertainty to position the asset, site, and fleet most economically and reliably. As solar and wind generators transition from being price-takers in real-time markets to committing in day-ahead markets – where opportunity is greater, but risk is higher – commitment optimization is even more paramount.

Once we move from commitment optimization to real-time dispatch optimization, we must be able to adjust fleet-to-asset operations quickly based on available capacity and market dynamics. To enable greater flexibility during the energy transition, investments in dispatchable generation are needed.

For example, during times of high demand or uncertainty due to variable energy resources such as wind and solar, gas-powered plants must manage the need for reserve capacity or emergency response on the system with a focus on minimizing maintenance and reducing energy imbalance costs. On the other hand, gas plants competing in an open or wholesale energy market need to capture revenue when energy prices are high, while avoiding penalties from missed targets and minimizing the impact of any operational changes on outage intervals.

In both scenarios, power generation asset optimization software that safely and reliably extends capacity and optimizes energy production at times of highest demand can result in significant returns for the generator. And, by securely connecting IT to OT, edge-to-cloud and cloud-to-edge, the system can increasingly operate on its own, in real time, with supervisory oversight from a centralized team of cross-functional experts to maximize profitability in a deregulated market or minimize cost to meet demand in a regulated market.

As utilities and power generators strive toward net-zero carbon emissions, they can drive business growth by expanding intelligent and autonomous operations. Through centralized operations, specialized analytics to handle market and operational uncertainty, and software and user experiences that offer greater data availability, transparency, integration, and security, make faster decisions that balance risk with the great opportunity presented by the energy transition.