The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energy availability and the marginal costs of the VPP components. The size of the VPP components is positively correlated to the components’ share of the energy generated. It was also found that projecting or implementing VPPs in Germany at current market prices (EPEX/EEX prices) is not yet economically feasible for a small share of market products. However, the secured power can be marketed on the SPOT and in the futures market with higher and more stable prices compared with the status quo.

This paper describes an automatic sampling system for anaerobic reactors that allows taking representative samples following the guidelines of Gy’s (1998) theory of sampling. Due to the high heterogeneity degree in a digester the sampling errors are larger than the analysis error, making representative sampling a prerequisite for successful process control. In our system, samples are automatically processed, generating a higher density of data and avoiding human error by sample manipulation. The combination of a representative sampling system with a commercial automate titration unit generates a robust online monitoring system for biogas plants. The system was successfully implemented in an operating biogas plant to control a feeding-on-demand biogas system.

Energy sharing among small- and medium-sized enterprises (SMEs) may improve local use of distributed renewable generation and flexibility, but its effects on distribution grids remain uncertain under participant-oriented rather than grid-optimized dispatch. This study assesses the grid impacts and economic implications of participant-oriented energy sharing for a 2024 reference scenario and a highly electrified 2045 stress-test scenario. The analysis uses measured load profiles from SMEs in sectors covering a 30-day period from 15 October to 15 November. The results therefore represent an autumn-specific comparison rather than annual estimates. For both scenarios, grid operation without energy sharing is compared with participant-oriented energy sharing, and the resulting time series are evaluated in a separate load-flow simulation. Grid impacts are assessed using asset utilization, power flows, and aging-related operating costs. In 2024, energy sharing caused no significant adverse grid effects and reduced aging-related operating costs by 5.6%. In the 2045 stress-test scenario, these costs increase by 11.7%. Nevertheless, based on an energy sharing potential of 22.76 GWh, participating companies retain an economic benefit even if additional grid costs are allocated to them. The results indicate that participant-oriented energy sharing can be economically attractive, while its grid effects depend on future electrification and system conditions.

Zusammenfassung: Der stetige Wandel von einer auf fossilen Rohstoffen basierenden Energieversorgung hin zu einer Versorgung auf Basis erneuerbarer Energien dient u. a. dem Ziel der Reduzierung des Kohlenstoffdioxidausstoßes. Dieser Wandel führt neben der Einsparung von Kohlenstoffdioxid zu einem Handlungsbedarf im Stromnetz, da durch die Substitution von steuerbaren durch dargebotsabhängige Erzeuger der Ausgleich zwischen Last und Erzeugung nicht mehr wie bisher durchgeführt werden kann. Ein möglicher Ansatz zur Lösung dieses Problems, ist zusätzlich zum Netzausbau die Ausgestaltung eines Smart Grids, welches durch Steuersysteme anhand verschiedener Netz‑, Umwelt- sowie ökonomischer Parameter erreicht werden kann. Dieser Artikel untersucht verschiedene zentrale und dezentrale Konzepte für die Datenhaltung in Smart Grid-Steuersystemen sowie die Datenverarbeitung, wobei hier die Aspekte der lokalen und der cloudbasierten Verarbeitung betrachtet werden. Betrachtungsgegenstand bei der Datenhaltung sind relationale Datenbanken, Blockchain und NoSQL-Datenbanken. Nach einem Vergleich der verschiedenen Konzepte anhand der Parameter Datensicherheit, Konsistenz, Skalierbarkeit, Kosten, Latenz, Verfügbarkeit und Komplexität sowie einer Abstimmung mit den Anforderungen eines zuvor definierten Use-Case wird eine Beurteilung darüber abgegeben, welches Konzept am besten den Anforderungen entspricht. Der Beitrag schließt mit einem Ausblick und einer Handlungsempfehlung. Eine ausführliche Analyse für die Datenverarbeitung wird in einem zukünftigen Paper veröffentlicht.

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