GridBeyond: Unlocking the Power of Full Energy Optimisation

Manufacturers are constantly facing challenges including how to keep production steady while managing unpredictable and costly energy bills.

Companies are being encouraged to maximise savings and take control of energy costs to solidify production.

GridBeyond’s whitepaper, Unlocking the Power of Energy, explores how businesses can separate energy procurement from production planning, resulting in essential opportunities and reduced costs.

Demand response for energy optimisation

According to GridBeyond, most industrial operators are already familiar with demand response (DR).

DR is said to allow companies to adjust energy usage inline with peak price events, allowing for excessive costs to be avoided.

With today's advanced AI integration, DR has the opportunity to become more powerful with the use of intelligent production schedule optimisation.

With advanced systems, energy prices can remain favourable and reduced.

The company states that wholesale electric prices are volatile and when in an energy-intensive industry, these fluctuations can result in unpredictable and vast operating costs.

By setting a 'strike price' (the maximum cost per unit of energy they’re willing to pay) companies can make decisions about when to curtail load to avoid paying high market prices.

“GridBeyond is embedding AI to accelerate the energy transition,” says Michael Ryan, Chairman, GridBeyond.

“GridBeyond is a leader in monetising and optimising energy flexibility both behind and in front of the meter for industrial and commercial customers as well as renewable players and asset owners.

“GridBeyond as a proven AI driven market-leading distributed energy resource management platform to support the massive transformation and decentralisation of global energy markets.”

Instead of treating energy as a fixed background cost, businesses can actively align their production with market signals, enabling businesses to: 

• Run production during lower prices taking advantage of forecasted dips in energy costs
• Build stock in advance and proactively create inventory before predicted high-price period
• Curtail at peak times by scaling back or pause production during price surges but leveraging stock to maintain throughput, using pre-built inventory to keep customer commitments on track while avoiding costly energy.

Data and digital twins

According to GridBeyond, businesses are increasingly turning to data-driven technologies to optimise energy use, improve operational efficiency and unlock new sources of flexibility. 

By combining market forecasts, machine learning and digital twin technology, GridBeyond enables operators to understand how assets such as kilns, mills and storage systems can respond to changing energy conditions. 

Seven-day forecasts provide insight into future price fluctuations, while digital twins allow businesses to simulate different scenarios and identify the most effective strategies without disrupting live operations. 

Through real-time integration with plant infrastructure, AI-powered optimisation can automatically adjust production processes based on market signals, helping reduce costs, support demand response and improve energy management. 

As performance data continuously feeds back into the system, these models become more accurate over time, creating a framework for ongoing optimisation and long-term operational value.

Scaling smarter performance

Scaling energy optimisation across multiple sites can unlock greater value by enabling businesses to co-ordinate production, energy consumption and flexibility across their entire operational footprint, states GridBeyond.

Rather than managing facilities independently, multi-site energy-aware scheduling allows companies to shift production towards locations with lower energy costs, respond to regional grid conditions and co-ordinate demand response participation across their portfolio. 

By benchmarking sites based on energy intensity, businesses can identify which facilities are best positioned to increase output or provide flexibility during periods of market volatility. 

Combined with AI-driven optimisation, this approach creates a more intelligent way to balance production targets with energy efficiency, helping reduce costs, improve resilience and maximise the value of existing assets. 

By moving from reactive energy purchasing to proactive energy management, businesses can transform energy from a cost challenge into a strategic advantage.

Read the whitepaper here.