Incremental capacity analysis (ICA) has proven to be an effective tool for determining the state of health (SOH) of Li-ion cells under laboratory conditions. This paper deals with an outstanding challenge of applying ICA in practice: the evaluation of battery series connections. The study uses experimental aging and characterization data of lithium iron phosphate (LFP) cells down to 53% SOH. The evaluability of battery series connections using ICA is confirmed by analytical and experimental considerations for cells of the same SOH. For cells of different SOH, a method for identifying non-uniform aging states on the modules’ IC curve is presented. The findings enable the classification of battery modules with series and parallel connections based on partial terminal data.

An energy management system (EMS) for a household energy system is proposed in this paper, which is composed of a photovoltaic (PV) generator , a home energy storage (HES), an electric vehicle (EV), an electrical household load and a grid connection, with 24 h operation horizon. The EMS objective is to reduce the electricity cost of the household by using a linear optimization algorithm. Two different EV schedules are utilized for simulations. One mainly describes rides to work and the other describes rides in a domestic context, such as rides to a supermarket. A forecast algorithm for the electrical load of the household, based on k-means clustering and an artificial neural network, is evaluated and integrated into the EMS to realistically represent the household’s load profile. It is shown that the developed forecast algorithm performs better than two of the benchmarks. Another finding is that the more storage is available at PV-production intervals, the higher the effect of forecast uncertainties and the lower the electricity cost of the household, disregarding the investment cost.

In the light of energy transition, existing systems have shown to be often characterised by fundamental challenges that could potentially threaten its functioning, particularly when exposed to extreme forms of stress. To overcome this, we argue that an inter- and transdisciplinary approach—aimed to integrate relevant stakeholder perspectives and acknowledge different spatial–temporal scales—can provide indications in relation to the development of resilience. In this context, the included contributions have highlighted that resilience remains a topic surrounded by promises and confusion, but also illustrate that improved conceptualisation and operationalisation of associated processes and structures can be realised. Through clustering these contributions—according to understanding, envisioning, analysing, and managing resilience of energy systems—a structured overview is provided. Based on obtained insights, various recommendations are given how resilience in energy systems can be realised. Also, some indications are given how policy advice could be improved by means of resilience monitoring.

One challenge in future digitally interconnected distribution power grids is that the digitalisation introduces the possibility of malfunctions, such as ICT network failures, which might lead to grid instabilities. Additionally, the rising complexity of the systems makes it harder to predict and respond to potential disruptions. Possible solutions for enhancing resilience in digitalized distribution grids are integrated fallback behaviours, local measurements and machine learning based operations implemented at single energy systems (assets) in the grid. In an example from the project IKTfree it was evaluated, how effective fallback behaviours in single assets can ensure stable grid operation in an event of ICT network failures. The analysed fallback behaviours range from keeping the latest power value to changing it to a pre-defined set point up to change the power level in accordance to the measured value at the connection point. The results show that these approaches can help to keep the voltage at house connection points and loadings of lines and transformer stations within operating limits. In conclusion, these results demonstrate the potential for fallback behaviours to enhance resilience in digitalized distribution power grids, even in situations where ICT control is lost.