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Energy price volatility has become a structural feature of modern electricity markets rather than a temporary disruption. For energy-intensive manufacturers and large commercial operators, fluctuating wholesale prices are reshaping how energy costs are managed, making reactive approaches increasingly inadequate.
In its Unlocking the power of energy | FlexPilot white paper, GridBeyond said the transition toward variable renewable generation and more dynamic pricing conditions is driving greater price uncertainty. While market mechanics are complex, the operational impact is simple: prices can change significantly within hours, affecting cost per unit, throughput economics and budgeting certainty.
According to GridBeyond, managing energy risk is now as much an operational and planning challenge as it is a procurement one.
From reactive response to predictive planning
Demand response programs have traditionally helped businesses manage extreme price events by setting a “strike price” – the maximum price per unit of energy an operator is willing to pay before reducing consumption.
GridBeyond noted that while this approach can help avoid peak costs, it may also disrupt production schedules or affect delivery commitments if not carefully managed.
The company said the next stage of energy management is predictive energy intelligence, which combines real-time operational data with forward price forecasting to anticipate risk rather than respond after prices rise.
Linking price signals to operational reality
GridBeyond said industrial forecasting can be complex because production systems must balance energy costs with technical performance, commercial obligations and quality requirements.
Processes involving equipment such as kilns, mills and bulk storage cannot be adjusted arbitrarily, as sudden changes may affect thermal stability, equipment wear, production consistency and customer supply schedules.
To help address these constraints, GridBeyond’s FlexPilot platform combines energy market signals with operational data specific to each site using advanced modelling techniques and virtual simulation tools.
The platform enables operators to explore different operational strategies before making adjustments in live environments. Through scenario testing, businesses can evaluate the consequences of modifying production schedules, managing energy-intensive stages of processing, or shifting certain activities to align with periods of more favourable pricing.
GridBeyond said the approach supports more strategic energy use by helping companies determine when production can be safely adjusted while still meeting output commitments.
Potential applications include scheduling energy-heavy operations during forecast low-price windows, building inventory in advance of anticipated price increases, or moderating selected processes during price spikes while maintaining overall production continuity.
Automation and continuous optimisation
As price volatility becomes more frequent, GridBeyond said manual scheduling alone is increasingly unable to respond to rapid market changes. Predictive modelling and automation are designed to help businesses limit exposure to extreme price spikes while keeping operations stable. Through integration with plant control systems, predictive platforms can automatically adjust flexible assets as market conditions evolve.
GridBeyond emphasised that energy optimisation is not a one-time exercise. Continuous feedback loops allow forecasting models to learn from real-world performance, refine operational strategies and identify additional flexibility opportunities over time.
For multi-site operators, portfolio-level coordination can unlock further value. Production can be shifted to lower-cost facilities where practical, demand response participation can be synchronised across regions, and overall energy intensity across operations can be improved.
According to GridBeyond, the outcome is more predictable operating costs, improved returns from demand response participation and stronger resilience in production planning despite ongoing market volatility.
Predictive intelligence as a strategic capability
GridBeyond said predictive intelligence and automation are increasingly moving from optional tools to core operational capabilities as energy markets evolve.
Executive teams are now looking beyond short-term procurement strategies toward integrated approaches that connect price forecasting, operational data and automated control systems.
The company said the central challenge for energy-intensive businesses is no longer whether volatility will occur, but how effectively it can be anticipated and managed.
Energy and industry leaders can register for the upcoming webinar, “Turning energy consumption into measurable value with digital intelligence,” to learn how predictive energy intelligence can be applied in real-world industrial settings.
The session will explore how forecasting, modelling and automation can help businesses manage energy cost risks more proactively.
This article contains information provided by GridBeyond and is intended for general use only. It does not take into account your personal, professional, or business circumstances. Please seek professional advice and review the product’s terms and conditions before making any decisions based on this information.
