The ReKs project set out to raise the attractiveness of combined heat and power (KWKK) systems by improving the energy efficiency of cold‑generation plants through energy‑optimised control strategies. The central aim was to reduce the primary energy demand and the electrical energy consumption of single and combined absorption chillers by up to 75 % compared with the state of the art. To achieve this, the project developed a hierarchical control architecture that operates on three levels: component, plant (KEA) and system. Component control handles individual pumps, valves and heat exchangers; plant control aggregates the components into a single cold‑generation unit and passes set‑points and minimum run times; system control orchestrates several cold‑generation units in parallel or in series, deciding which units are active based on temperature, power or efficiency criteria. The system‑level strategy was the core research focus and was built on a model‑based multi‑variable control framework that had been refined from the preceding FAkS project.

The technical results are expressed through two key performance indicators: the specific primary energy demand (π̇_K) and the specific electrical energy demand (ŵ_K). The primary energy indicator includes both the electrical and the thermal energy required to drive the cold‑generation process, whereas the electrical indicator counts only the electric power used for refrigeration. The project derived analytical expressions for the instantaneous and integrated values of these indicators. For a thermally driven absorption plant (e.g., a low‑temperature absorption chiller) the instantaneous primary energy demand is calculated as π̇_K = f_th·Q̇₂,K + f_e·L_K / Q̇₀,K, where f_th and f_e are the thermal and electrical fractions, Q̇₂,K the heat input, L_K the total heat losses and Q̇₀,K the nominal cooling capacity. For an electrically driven compressor plant the instantaneous electrical demand is ŵ̇_K = L_K / Q̇₀,K, with the same loss terms. These formulas were implemented in the plant‑level controller and used to evaluate the performance of different operating modes: free cooling (FKB), absorption (AKB), compression (KKB) and mixed operation (MKB). Experimental tests on a laboratory absorption unit confirmed that the model‑based controller could keep the instantaneous primary energy demand below the baseline by 30 % during typical load variations, while the integrated primary energy over a 24‑hour period was reduced by 45 %. In a simulation study of a real‑world heat‑and‑cooling plant (ESTW) the system controller achieved a 60 % reduction in electrical energy consumption during peak periods, and the overall primary energy savings reached 70 % when the plant operated in a mixed mode that combined free cooling with absorption and compression units.

The project also demonstrated the feasibility of a fully automated monitoring and verification system. Sensors on each component fed real‑time data to a central supervisory control and data acquisition (SCADA) platform, which logged the instantaneous π̇_K and ŵ̇_K values. The logged data were used to validate the model predictions and to fine‑tune the control parameters. The demonstration phase included a field test at a commercial building, where the ReKs controller was integrated with the existing HVAC system. The field test confirmed the laboratory results, showing a 25 % reduction in electrical energy use during the summer months and a 15 % reduction in primary energy over the full year.

Collaboration was essential to the project’s success. The research was carried out by a consortium of universities, research institutes and industry partners, coordinated by the project carrier PTJ Jülich. The Federal Ministry of Economics and Climate Protection provided the funding under the programme for energy efficiency in industrial processes. Within the consortium, the universities supplied the theoretical modelling and algorithm development, the research institutes performed the experimental validation, and the industry partners supplied the plant hardware and facilitated the field deployment. The project ran over several years, during which the partners exchanged data, refined the control algorithms and documented the results in a series of technical reports and peer‑reviewed publications. The collaborative effort ensured that the developed control strategies are not only scientifically robust but also ready for industrial implementation.