• Energy Research
• 2021-2025close
• 7. Clean energy close
• 13. Climate action close
• 11. Sustainability close
• 1. No poverty close
• DE close

Lithium-ion batteries exhibit a dynamic voltage behaviour depending nonlinearly on current and state of charge. The modelling of lithium-ion batteries is therefore complicated and model parametrisation is often time demanding. Grey-box models combine physical and data-driven modelling to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling. Differential equations given by physical laws and NODEs can be combined in a single modelling framework. Here we demonstrate the use of NODEs for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis and represents the physical part of the model. The voltage drop over the resistor–capacitor circuit, including its dependency on current and state of charge, is implemented as a NODE. After training, the grey-box model shows good agreement with experimental full-cycle data and pulse tests on a lithium iron phosphate cell. We test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.

AbstractLightning is the main precursor of natural wildfires and Long-Continuing-Current (LCC) lightning flashes are proposed to be the main igniters of lightning-ignited wildfires (LIW). Previous studies predict a change of the global occurrence rate and spatial pattern of total lightning. Nevertheless, the sensitivity of lightning-ignited wildfire occurrence to climate change is uncertain. Here, we investigate space-based measurements of LCC lightning associated with lightning ignitions and present LCC lightning projections under the Representative Concentration Pathway RCP6.0 for the 2090s by applying a recent LCC lightning parameterization based on the updraft strength in thunderstorms. We find a 41% global increase of the LCC lightning flash rate. Increases are largest in South America, the western coast of North America, Central America, Australia, Southern and Eastern Asia, and Europe, while only regional variations are found in northern polar forests, where fire risk can affect permafrost soil carbon release. These results show that lightning schemes including LCC lightning are needed to project the occurrence of lightning-ignited wildfires under climate change.

Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).

The failure to fully internalize externalities from production and consumption, including on future generations, is supposed to be at the core of the perceived failure to ensure (ecological) sustainability within the realm of antitrust enforcement. While some argue that sustainability should constitute a goal in itself that must be balanced against economic efficiency in antitrust analysis, we instead want to explore whether and how sustainability can be incorporated into a consumer welfare approach. We make a key distinction between what we term an individualistic and a collective consumer welfare analysis. Within an individualistic consumer welfare analysis, consumers’ willingness-to-pay is measured ceteris paribus, holding other consumers’ choices fixed. In a collective consumer welfare analysis, consumers may express their willingness-to-pay also for the choices of others and, thereby, also for the reduction of externalities on themselves. Borrowing from environmental and resource economics, we also discuss more indirect ways of incorporating such externalities. And we critically assess the possibility of ‘laundering’ consumers’ sustainability preferences in the light of supposed biases and cognitive limitations. Finally, we relate our analysis to the Draft Horizontal Guidelines of the European Commission, published in March 2022. antitrust, consumer welfare, conjoint analysis, contingent valuation, Draft EU Horizontal Guidelines, environmental economics, externalities, laundering preferences, sustainability, willingness-to-pay

AbstractSmart Grids are electrical grids that require a decentralised way of controlling electric power conditioning and thereby control the production and distribution of energy. Yet, the integration of Distributed Renewable Energy Sources (DRESs) in the Smart Grid introduces new challenges with regards to electrical grid balancing and storing of electrical energy, as well as additional monetary costs. Furthermore, the future smart grid also has to take over the provision of Ancillary Services (ASs). In this paper, a distributed ICT infrastructure to solve such challenges, specifically related to ASs in future Smart Grids, is described. The proposed infrastructure is developed on the basis of the Smart Grid Architecture Model (SGAM) framework, which is defined by the European Commission in Smart Grid Mandate M/490. A testbed that provides a flexible, secure, and low-cost version of this architecture, illustrating the separation of systems and responsibilities, and supporting both emulated DRESs and real hardware has been developed. The resulting system supports the integration of a variety of DRESs with a secure two-way communication channel between the monitoring and controlling components. It assists in the analysis of various inter-operabilities and in the verification of eventual system designs. To validate the system design, the mapping of the proposed architecture to the testbed is presented. Further work will help improve the architecture in two directions; first, by investigating specific-purpose use cases, instantiated using this more generic framework; and second, by investigating the effects a realistic number and variety of connected devices within different grid configurations has on the testbed infrastructure.