Utilize AI to reduce energy costs amidst market volatility

The Energy Optimizer, a cloud-based AI application, utilizes mathematical optimization and machine-learning electricity price forecasts to significantly cut energy costs in industrial processes with varying power input, while concurrently reducing the carbon footprint.

Savings can be up to 15%.

Why act now?

In today's energy landscape, where electricity spot prices are scaling to unprecedented heights and becoming increasingly volatile, the need to reduce energy costs has become a top priority for any industrial manufacturer with substantial power consumption.

  • The strategic shift extends beyond improving operational efficiency; it also involves optimizing production planning to benefit from the fluctuations in electricity spot prices.
  • This approach not only directly translates into cost savings on spot-market electricity purchases, but also presents an opportunity to trade surplus power from fixed-price contracts.
  • Moreover, it serves as a driver for grid stability, curtailing peak-hour demand surges and contributing to a reduction in CO2 emissions by reducing peak load, when fossil fuels are the largest contributor in the energy mix.

Energy optimization for the process industry

Industrial processes are conducive to energy optimization when they run on electricity purchased from the public grid, load can be modulated without disrupting the process itself, and the power input is a dominant cost factor.

Example processes that can benefit from the Energy Optimizer include:

  • Water electrolysis for the production of hydrogen (e.g., as an input for green ammonia)
  • The chlor-alkali process for the production of chlorine and caustic soda
  • Aluminum electrolysis (with potlines retrofitted with heat exchangers to ensure thermal stability)
  • Silicon smelting
  • Electric arc steelmaking
  • Paper and pulp production

Leverage load modulation:

  • Our solution is easily configurable and takes into account intricate operational constraints and site configurations, offering you a timely and practical pathway to cost efficiency in a volatile energy landscape.

Calculate your energy cost savings

Energy Savings Calculator
Annual production capacity (tons):Material:AluminiumChlorineCountry:GermanyNorwayFranceItalyTurkeyGreeceCalculate Savings

Total Cost of Production in a Year:

0 Euro
Average Savings Potential:

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Calculations are based on 2022 (aluminium) / 2023 (chloralkali) spot prices. Savings may vary depending on factors such as industry, digital maturity, electricity contracts, and site constraints.

Manifold benefits from optimized energy consumption

Reduced costs

Find the optimal power profile to adapt to future electricity prices, either producing the target amount of product at the lowest possible cost or making a variable amount of product to maximize profits.

Increased revenue

Take into account sell-back clauses in fixed-price contracts, allowing increased revenue by selling back power to the market when spot prices are high.

Reduced carbon footprint

Using an optimized load profile means consuming less power when demand and prices are high, leading to lower CO2 emissions as fossil fuels are the dominant part of the energy mix at peak demand.

Improved electricity grid stability

Lower energy consumption at peak demand has the societal benefit of contributing to grid stability.

Advantages for the process industry

Savings potential

The application can be used for any industrial process where there is an opportunity to modulate the electrical power load.

Potential savings depend on electricity prices and the plant's modulation capacity, influenced by factors like production volume and the degree of automation in plant controls.

In the chlor-alkali industry, for instance, savings of up to 15% can be realized for highly automated sites not running at full capacity situated in volatile energy markets.

Minimize energy costs with the Energy Optimizer

Learn more about using the Energy Optimizer for the chlor-alkali process at a leading global chemical manufacturer.

Download case study