From cost exposure to cost control: Using energy flexibility to protect margins

Sponsored content by GridBeyond

Electricity price volatility is reshaping the cost base of Australian manufacturing, challenging long-held assumptions that energy can be treated as a stable operational input.

According to GridBeyond’s white paper, Unlocking the power of energy | FlexPilot, wholesale electricity prices can swing dramatically within hours, with direct implications for operating margins in energy-intensive industries. 

The paper argues that separating energy procurement from production planning is leaving “valuable opportunities to reduce costs without compromising output” untapped.

For many manufacturers, demand response has been the primary tool for managing exposure. By setting a “strike price” – the maximum price they are willing to pay per unit of energy – operators can curtail load during peak price events.

However, the white paper notes that demand response in its basic form is reactive. It responds after price signals emerge and can place pressure on operations if production schedules are not designed to accommodate curtailment.

“Demand response is just the beginning,” the paper states, outlining a transition from isolated peak avoidance to full energy optimisation integrated into day-to-day planning.

Integrating forecasting and production planning

GridBeyond’s FlexPilot concept, as described in the white paper, combines forward market forecasting, advanced machine learning algorithms, and digital twin technology to align production schedules with anticipated energy price conditions.

With forecasts extending up to seven days ahead, operators gain visibility of potential price rises and dips before they occur. This enables manufacturers to:

• Run production during forecast lower-price periods
• Build inventory in advance of predicted high-price windows
• Scale back or pause energy-intensive processes during peak events while maintaining throughput using accumulated stock

Rather than treating energy as a background cost, the white paper positions it as a controllable operational variable that can be optimised alongside output targets.

Digital twins and predictive analytics in practice

At the core of the FlexPilot framework is the use of digital twin technology to replicate industrial operations in a virtual environment. These digital models allow companies to analyse how production systems would respond to different energy price and demand conditions without affecting ongoing plant activity.

GridBeyond said the system enables users to examine operational adjustments such as altering the timing of energy-intensive processes, redistributing workloads across production lines, or aligning output sequencing with market signals. By projecting both technical and commercial outcomes, businesses can evaluate the feasibility of operational changes before deployment.

Beyond stand-alone simulation, the platform is designed for continuous operational support. With real-time connectivity to plant systems, AI-enabled optimisation can automatically recommend or implement production adjustments in response to fluctuating energy prices, while maintaining process quality, equipment performance and operational reliability.

Scenario-based margin protection

The white paper provides a practical illustration of how energy-aware scheduling can protect margins.

If a seven-day forecast signals elevated wholesale prices later in the week, a manufacturer could increase output during lower-cost days, proactively build stock, and reduce load during peak-price periods. Customer commitments are maintained using pre-built inventory, while exposure to high market prices is reduced.

In this way, production remains stable and delivery performance is preserved, but average energy cost per unit declines.

GridBeyond describes this shift as moving from “reacting to costs” to “co-optimising production, energy, and flexibility in a single intelligent system.”

Automation and risk reduction

The paper also highlights the operational risks associated with manual, last-minute adjustments in volatile markets. By embedding forecasting and optimisation directly into plant systems, businesses can reduce reliance on manual intervention and improve decision consistency.

According to GridBeyond, the benefits include lower and more predictable operating costs, improved returns from existing demand response participation, and more resilient production planning in the face of market volatility.

Ultimately, the white paper argues that manufacturers equipped with the right data, forecasting capability, and optimisation tools can transform energy “from a cost risk into a competitive advantage.”

Businesses seeking deeper insight into how predictive energy intelligence and the FlexPilot framework can help manage price swings and market volatility are invited to register for GridBeyond’s upcoming webinar, “Turning energy consumption into measurable value with digital intelligence.”

The session will provide practical insight into how integrating energy-aware scheduling into operational planning can support stronger margin control in a volatile energy market.