vision & thinking


Our vision is to significantly reduce European energy costs in the coming years through intelligent expansion. Our state of the art planning tool gives you the means to model complex renewable energy behaviour accurately and hereby enables you to build more profitable and at the same time more sustainable systems

We work together as a multidisciplinary and international team to reach this goal.


solutions & services

How we save the world using thermodynamics

We offer a complete solution containing four products withtin one platform.

Our platform includes a unique planning tool that reliably plans energy systems of all degrees of complexity. In addition, we integrate, check and provide all data relevant to the respective optimization as required. The platform visualizes optimization results intuitively, interactively and fully customizable. Different company units and even different companies work simultaneously and jointly on optimizations and evaluate their energy systems.

We constantly develop our energy systems optimization. We cooperate with the RWTH Aachen, Stanford University, and University of California to make the latest scientific findings usable.


competitive advantage

Look further than others: into the future



independent from device and timezone



adapted to energy planners’ work processes



using extensive computing capacities, latest algorithms and automatic parallelization



focused on the critical information and answers



decision making through the comparison of multiple, detailed scenarios



integrate your own expertise

Kerith Laptop


Infrastructure planning

AI optimization & data aggregation

Our energy system tool develops cost-optimized, reliable and sustainable energy systems. For the valid optimization of highly complex energy systems, the planning tool takes into account high-resolution temporal and spatial data and integrates them using modern aggregation methods. In this way, the temporal fluctuation of energy availability and energy demand over several years, different generation, storage, sector coupling and transmission technologies are combined in the optimization. Furthermore, the optimization takes into account the change from the existing to the future energy system. For intelligent and valid investment decisions.



Integration & quality

Our data preparation enables a time-saving and error-resistant integration of own and external data.


Software as a Service

Cloud & Collaboration

Our scalability and on-demand delivery of computing power from the cloud exceeds the capabilities of local computing capacity.



Intuitive & Interactive

Input data and results of the optimization can be analyzed and understood more deeply through our intuitive and interactive visualizations. Furthermore, our visualization allows collaboration and cooperative presentation of results.


Challenges & Trends

Which energy megatrends need to be considered

We have identified five megatrends that are disruptively changing the energy sector and that are often missed by conventional energy system planning:


Nondispatchable energies & storage systems

In the last 9 years, the share of photovoltaics and wind in Germany’s gross electricity generation has increased by 400%. In practice, however, conventional static methods (e.g. merit order) are often used, but they do not adequately design expansion capacities, locations and times for either nondispatchable generations or storage systems.


Decentralized power generation & micro power plants

The number of decentralised power generators in Germany already exceeds 1.5 million solar, 27,000 wind and 9,000 biogas power plants. Nevertheless, the usual single-node representation of the energy system does not provide high geographical resolution. No high geographical representation lacks representation of decentralisation and network bottlenecks.


Storage systems & seasonal coupling

In private households we are observing a massive expansion of 182,000 photovoltaic home storage units in 2019 alone. Here too, the use of conventional methods leads to avoidable misjudgements and investments.


Sector coupling & Power2X

Interconnecting the electricity, heat and transport sectors is a core EU strategy for the cost-effective decarbonisation of the energy system. Nevertheless, conventional energy system planning often looks exclusively at the electrical energy system and thus misses the potentials of sector coupling.


Change in technology & emission prices

While we have seen a 90% reduction in photovoltaic prices over the last nine years, the CO2 price has risen by 500% in the last three years alone. However, it is common practice to look at individual investment years and thus fail to take long-term effects of future technology and emission prices into account.

Our progressive optimization focuses on these megatrends.


Research & Knowledge

Why our energy system planning is superior

Emission reduction targets and falling prices for renewable generation and storage technologies are leading to structural changes in energy systems. This increases their dependence on weather conditions. The planning of future energy systems is supported by mathematical simulation and optimization models, which are, however, limited by available storage and the time required for solution. This leads to a balancing act between modelling of temporal complexity, spatial complexity and mapping of physical properties and ends in compromises.


To enable more detailed physical and spatial representation, it is common practice to reduce the temporal complexity of models by aggregation. For this aggregation, representative periods are usually modelled instead of the complete time series. We have shown that the aggregated representation of wind time series to representative days reduces the reliability of the energy system, leads to considerable distortions and underestimates the total costs. This phenomenon is particularly relevant for simulations and planning of energy systems with low emission limits. We find that the required capital costs are underestimated by more than 35% and the emissions using three weeks on representative days are more than twice as high as the planned emission limit.


Neither an increase in the number of representative periods, nor any other representation of the clusters, nor any different attribute weighting can solve the three problems mentioned. We recommend not to use time series aggregation to representative days to design energy systems with low emissions, especially if wind resources are important. Planning should consider cross-sectoral different technologies, high resolution weather, consumer and grid data in time and space.


The solutions offered by the market so far are no longer up to date because they use less adaptable and outdated algorithms, depend on expensive local computing power and require time-consuming data preparation.



Contact us!

We are looking forward to explain our value for your business in a personal conversation!