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Productivity improvements have major impact on economy and competitiveness in European manufacturing industry. Industrial maintenance contributes largely to this competitiveness through reliability and availability of production equipment. Especially in continuous production industries (energy, chemical, food, cement or paper sectors) the ratio "maintenance costs/added value product" is even higher than 25 %. Defect components or process failures can stop the whole production, therefore predictive maintenance is a critical issue. In this context, the SUPREME project will provide new tools to dynamically adapt the maintenance and operation strategies to the current condition of the critical components of production equipment. It also proposes to develop an integrated approach to optimize the production process and its energy consumption.

Self-consumption of the energy generated by photovoltaics (PV) is playing an increasingly important role in the power grid. "Prosumer" systems consume part of the produced energy directly to meet the local demand, which reduces the feed-in into as well as the demand from the grid. In order to analyse the effects of PV self-consumption in the power grid, we introduce a stochastic bottom-up model of PV power generation and local consumption in the control area of the German transmission system operator TransnetBW. We set up a realistic portfolio of more than 100,000 PV/prosumer systems to generate representative time series of PV generation and consumption as a basis to derive self-consumption and feed-in. This model allows for the investigation of the time-dependent behaviour in detail for the full portfolio whereas measurements are presently only available as aggregated feed-in time series over a nonrepresentative subset of systems. We analyse the variation of self-consumption with PV generation and consumption at the portfolio level and its seasonal, weekly and diurnal cycles. Furthermore, we study a scenario of 100% prosumers as a limiting case for a situation without subsidized feed-in tariffs and local energy storage.

The need for regular, accurate measurements of the spectrally resolved, solar, extreme ultraviolet (EUV) flux is becoming increasingly recognized. Such date are required for fundamental research in astronomy, e.g., in solar physics and in studies of planetary atmospheres and the local interstellar medium, for basic research into physical models of the terrestrial thermosphere, and for operational use in civilian and military space programs where atmospheric drag on spacecraft is a concern. Some in-orbit measurements of the solar irradiance and solar spectral ultraviolet irradiance have been made, planned for, and will continue. For example, SUSIM, the Solar Ultraviolet Spectral Irradiance Monitor on Spacelab I and II and on UARS, is an instrument that measures the solar ultraviolet flux. However, there remains a significant gap in the energy range covered by solar spectral irradiance measurements: the solar EUV flux, the very-variable and principal source of energy for the upper atmosp here, must be measured regularly and accurately in order to understand and interpret correctyl solar variabilit

In recent years, few transportation modes have gained so much attention so quickly as shared e-scooters. Debates focus on usage patterns over shift effects to environmental impacts. Previous research has mainly been conducted in Asia and North America and in metropolitan areas. Potential interdependencies have been analysed mostly towards public transport (PT). Surprisingly, investigations concerning the usage of shared e-scooters and other shared mobility services have been scarce. However, understanding possible (inter-)dependencies and potentials for inter- and multimodality is crucial for policymakers and transport planners to design efficient and sustainable transportation systems. This is why we draw on an original data set of 118,047 shared e-scooter trips in Karlsruhe, a non-metropolitan city in southwest Germany and add information about carsharing and PT. Apart from station information for both modes, we add departure information for tramways, and weather data. Shared e-scooter data is retrieved via the local providers from November 2020 to April 2021, information about the stations of carsharing and PT is added via OpenStreetMap, and tramway service data is retrieved via the local authority. We find an average trip distance of 1.40 km and substantially less usage on Sundays. The potential of combining shared e-scooters is higher for PT than for carsharing. Shared e-scooter trips show longer distances in times of lower or none PT service. Negative binomial regression models with fixed effects for the PT or carsharing stations show that the number of tram departures positively affects shared e-scooter usage, particularly at off-peak times. Applying mode shift scenarios and focusing on the usage phase, the energy consumption effect of shared e-scooters is found to be between -5 to +0.5 TWh. However, it requires providers to revisit their operations and policy to rethink regulation to get even close to the multimodal or energy consumption potential.

The initial SUN-to-LIQUID II project press release was published in December 2023.

Over the recent years, several studies have pointed out the impact of manufacturing on the environment. Especially machining offers great potential for the conservation of energy, resources and the reuse of raw materials. This article gives an overview on the approaches that are currently under investigation at the Institute of Production Engineering and Machine Tools with the aim of improving these aspects. The approaches cover regrinding methods for worn tools, recycling of titanium chips and process planning for hybrid process chains. In the first part of the article, a novel process chain for the automatic regrinding of cemented carbide tools is presented. It is shown that production costs can be reduced significantly, as well as the required energy for production of carbide tools. In the second part of the article, approaches for the recycling of titanium chips from machining processes are described. The last part focuses on the resource and energy efficiency of process chains that contain additive and subtractive processes.

Increasing the share of intermittent renewable electricity generation will require additional flexibility in the electricity system. While energy storage can provide such flexibility, studies about the economics of power storage often conclude that there is no business case for large-scale storage applications. In this paper, we present a new approach on how to assess the benefits of energy storage. Key improvements have been made in two areas: Firstly, the agent-based market simulation model PowerACE has been enhanced to make use of optimization methods (MILP) for the unit commitment of the agents, enabling us to quantify the economic benefit of flexibility at supply agent level. Secondly, we have considerably extended the common unit commitment problem (Carrion and Arroyo, IEEE Trans Power Syst 21(3):1371-1378, 2006), so that we can now model the provision of positive and negative balancing power and the dispatch of storage units. We compare the flexibility offered by thermal power plants to that offered by storage units for the four major German electricity generating companies under two different scenarios. The results for 2030 indicate that it would be more profitable to build up to 4,800 MW storage capacity in the German market rather than investing in flexible combined cycle gas turbine plants or hard coal-fired units. The increasingly fluctuating residual load implies that inflexible power plants will be penalized. Using storage units, the power plants of an existing portfolio can be dispatched in a more efficient way, i.e. with less operation in part load and avoiding start-up or shutdown events.

The urgency of climate change mitigation, rising energy prices and geopolitical crises make a quick and efficient energy transition in the building sector imperative. Building owners, housing associations, and local governments need support in the complex task to build sustainable energy systems. Motivated by the calls for more solution-oriented, practice-focused research regarding climate change and guided by design science research principles, we address this need and design, develop, and evaluate the web-based decision support system NESSI. NESSI is an open-access energy system simulator with an intuitive user flow to facilitate multi-energy planning for buildings and neighborhoods. It calculates the technical, environmental, and economic effects of 14 energy-producing, consuming, and storing components of the electric and thermal infrastructure, considers time-dependent effects, and accounts for geographic as well as sectoral circumstances. Its applicability is demonstrated with the case of a single-family home in Hannover, Germany, and evaluated through twelve expert interviews.