In the face of rising energy costs in industry, what can be done to bolster competitiveness?

Optimising energy costs

What can industrial enterprises do to optimise their energy costs in order to remain competitive – also in regard to the the international markets? The electricity price plays a crucial role in the industrial energy mix. According to Statista, electricity prices have risen continuously. Despite the exceptions in the Renewable Energy Sources Act (RESA), such as the special compensation scheme, industrial enterprises in Germany pay the highest prices in a European comparison. And many companies expect electricity prices to continue to rise due to the phase-out of coal.

The continuous operational optimisation approach is one way to optimise energy costs in the company and to actively manage one’s own energy system holistically.

Save up to 20% on energy costs

Projects (see also Seven2one projects) have demonstrated that optimisation can enable companies to save up to 20% in energy costs. A calculation example: In its various work processes, a production company consumes 7 GWh of electricity per year. Continuous optimisation could allow the production company to save energy costs of up to 224,000 euros annually.

The following applies: the more complex the energy system, the more potential there is for optimisation. Energy storage options, variable prices and flexible consumers are some of the factors that can increase the complexity of an energy system. With each variable, the number of input parameters, the volume of data to be processed and the dependencies increase. And it is precisely in the interdependencies that you find the potential for optimisation that needs to be explored in a complex energy system.

What is continuous operational optimisation?

Until now, companies have used operational optimisation to operate their power plants in such a way that they cover their energy needs at the lowest possible cost. This means that the aim was to determine an optimal schedule based on minimal operating costs, taking into account framework conditions such as startup and shutdown ramps, scheduled maintenance windows and so on.

Continuous operational optimisation also increases the potential for optimisation during operation. Consumers, generators and energy storage systems are included in the optimisation and their flexibility potential is taken into consideration. If the conditions change, such as due to a change in heating or cooling demand or plant failure, a new optimal schedule is calculated for the current conditions. This means that continuous operational optimisation is an optimisation of the entire energy system – across generators, energy storage units and consumers as well as all sectors and sources of energy.

Dovetailing energy generation, consumption and storage – optimising energy costs

In concrete terms, this means continuous operational optimisation dovetails with energy generation, consumption and energy storage in industrial energy management – from data capture to optimisation and schedule preparation to plant and system control. Current information from meters and component sensors is recorded underground and combined with additional information such as weather data and prices. The software then determines optimal schedules for the current framework conditions, while continuous operational optimisation incorporates the volatility of the framework conditions and provides the necessary specifications for the use of all components of the energy system. (See also the blog post entitled Conventional versus forecast-based energy management)

In addition to optimising energy costs, other goals can also be implemented.

With continuous operational optimisation, industrial enterprises can also manage their energy system according to other goals. These goals can include reducing CO2 emissions or ensuring that the supply of energy remains reliable. The companies have all the information they need for purposes such as responding in the event of unavailability and adapting the system to new conditions on an ad-hoc basis.

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