Expansion decisions are often made on gut feeling rather than data. As a result, synergies between energy carriers and technologies are overlooked – and significant savings potential remains untapped.
Minimize capex
The Decision Hub enables optimal sizing and the right timing of investments through simultaneous optimization of all components. This way you avoid oversizing and never miss synergies.
Minimize long-term opex
Use market volatility to your advantage and build out flexibility deliberately. The multi-year view accounts for future price developments and unlocks revenue potential through flexible operating modes.
Reduce emissions cost-efficiently
Integrate your CO2 targets as a constraint and find the cheapest path to climate neutrality. Pareto analyses show you the trade-off between cost and emissions.
The building blocks of the Decision Hub
The Decision Hub systematically analyses the entire solution space and progressively narrows it down to the optimal investment decision.
Request a demoThe Decision Hub optimizes simultaneously across all energy carriers: electricity, gas, heat, cooling and steam. In doing so it identifies cross-carrier synergies such as waste heat recovery between different energy carriers.
The Decision Hub optimizes investment timing over a horizon of 10 to 20 years. It accounts for asset life cycles and market developments and identifies when which technology should be built.
The Decision Hub sizes plants automatically by size and capacity. It compares different technology options such as heat pump, e-boiler or gas boiler and performs a trade-off analysis between capex and opex.
The Decision Hub integrates spot, day-ahead and intraday markets into the optimization. It accounts for PPAs, futures and balancing energy and uses flexibility marketing as an additional revenue source.
The Decision Hub offers multi-site capability for portfolio optimization. It aggregates sites for cross-cutting strategies and uses temporal compression for efficient long-term calculations.
The Decision Hub fully models grid connections and internal networks. It accounts for capacity limits and bottlenecks and represents self-supply as well as direct lines.
The Decision Hub calculates scenarios for grid capacity expansions including the cost per MW. It integrates CO2 budgets as an optimization constraint and represents Scope 1 and 2 emissions for ESG compliance.
Frequently asked questions
Answers to the most important questions about strategic investment planning with the Decision Hub.
More questions?The Decision Hub analyses the entire solution space with all possible combinations of technologies, timings and sizes. Through mathematical optimization this is systematically narrowed down to the cost-optimal solution – like a funnel that narrows from top to bottom.
Yes, the same algorithm optimizes both investment decisions (capex) and operational performance (opex). The optimal plant design already accounts for future operating costs and thus unlocks the full savings potential.
The Decision Hub is responsible for strategic long-term planning (years) and investment decisions: what should be built? The Operation Hub handles operational short-term planning (hours/days) and schedule optimization: how should it be operated? Both use the same energy model (Digital Twin).
RIZM uses base data for capex and opex that can be overridden customer-specifically. You can model costs as fixed euro values, euros per MW or euros per MWh. Annuitization is done over selectable periods and interest rates.
Yes, you can set CO2 budgets as a constraint. The algorithm then finds the cost-optimal path within your CO2 budget. Pareto fronts show you the trade-off between cost and emissions so you can make well-founded decisions.
The horizon typically spans 10 to 20 years and accounts for asset life cycles as well as replacement investments. The Decision Hub also models dynamic market price developments and regulatory changes to enable robust investment decisions.
We recommend first developing a cost-optimal scenario. You then run sensitivity analyses for prices, CO2 costs and investment limits. This lets you compare different roadmaps with different assumptions.
Yes, via the infrastructure expansion parameter, costs per MW for grid expansion are taken into account. The algorithm automatically decides whether grid expansion is economical or whether other solutions such as local generation or storage are cheaper.
RIZM provides base cost data that you can review and adjust. For special cases an iterative approach for inverse calculations is also possible, where missing parameters are back-calculated from known results.
Depending on complexity, an optimization takes a few minutes to several hours. Clustering methods significantly reduce computation time for large systems. Results are provided as interactive visualization and CSV export.
