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Analyzing television discourse during 2021 through a statistical sample of records extracted from TV networks, the configuration that, in the pandemic, adjusted the dialectical mediation between television communication and cognitive capital available for resilience to Climate Change is revealed. This study originates from reports that in collaboration with ECODES and funding from the Ministry for the Ecological Transition and the Demographic Challenge, carried out by the Media Communication Observatory on Climate Change at its headquarters of the MDCS Research Group of the UCM. The analysis revealed how the causes, impacts, mitigation, and adaptation projects to the effects of climate change were communicated, and the identity of those who speak and/or are referred to. The discursive hegemony of mediators (journalists) and politicians is confirmed, to the detriment of scientists, and improved communication for resilience to climate change is promoted. ; Analizado el discurso televisivo durante 2021 a través de una muestra representativa de registros extraídos de cadenas de TV, se revela la configuración que, en la pandemia, ajustó la mediación dialéctica entre comunicación televisiva y capital cognitivo disponible para la resiliencia ante el Cambio Climático. Este estudio se origina en informes que en colaboración con ECODES y financiación del Ministerio para la Transición Ecológica y el Reto Demográfico, realiza el Observatorio de la Comunicación Mediática del Cambio Climático en su sede del Grupo de Investigación MDCS, de la UCM. El análisis desveló cómo se comunicaron las causas, los impactos, los proyectos de mitigación y adaptación ante los efectos del cambio climático, y la identidad de quienes toman la palabra y/o son aludidos. Se confirma la hegemonía discursiva de mediadores (periodistas) y políticos, en detrimento de los científicos, y se promueve mejorar la comunicación para la resiliencia ante el cambio climático.

Analyzing television discourse during 2021 through a statistical sample of records extracted from TV networks, the configuration that, in the pandemic, adjusted the dialectical mediation between television communication and cognitive capital available for resilience to Climate Change is revealed. This study originates from reports that in collaboration with ECODES and funding from the Ministry for the Ecological Transition and the Demographic Challenge, carried out by the Media Communication Observatory on Climate Change at its headquarters of the MDCS Research Group of the UCM. The analysis revealed how the causes, impacts, mitigation, and adaptation projects to the effects of climate change were communicated, and the identity of those who speak and/or are referred to. The discursive hegemony of mediators (journalists) and politicians is confirmed, to the detriment of scientists, and improved communication for resilience to climate change is promoted. ; Analizado el discurso televisivo durante 2021 a través de una muestra representativa de registros extraídos de cadenas de TV, se revela la configuración que, en la pandemia, ajustó la mediación dialéctica entre comunicación televisiva y capital cognitivo disponible para la resiliencia ante el Cambio Climático. Este estudio se origina en informes que en colaboración con ECODES y financiación del Ministerio para la Transición Ecológica y el Reto Demográfico, realiza el Observatorio de la Comunicación Mediática del Cambio Climático en su sede del Grupo de Investigación MDCS, de la UCM. El análisis desveló cómo se comunicaron las causas, los impactos, los proyectos de mitigación y adaptación ante los efectos del cambio climático, y la identidad de quienes toman la palabra y/o son aludidos. Se confirma la hegemonía discursiva de mediadores (periodistas) y políticos, en detrimento de los científicos, y se promueve mejorar la comunicación para la resiliencia ante el cambio climático.

Abstract This paper aims to present a feasibility study of the innovative plant for methanol synthesis from carbon dioxide-sequestered by fossil fuel power plant and hydrogen, which is produced by water electrolyzer employing the over-production on the electrical grid. The thermo-economic analysis is performed in the framework of the MefCO2 H2020 EU project and it is referred to the German economic scenario, properly taking into account the real market costs and cost functions for different components of the plant. Three different plant capacities for methanol production (4000 10,000 and 50,000 ton/year) have been investigated, assuming an average cost for electrical energy to feed electrolysers and analyzing the influence of the most significant parameters (oxygen selling option, methanol selling price and electrolysers’ capital cost) on the profitability of the plant. The analysis has been performed in W-ECoMP, software for the thermo-economic analysis and plant optimization developed by the University of Genoa.

Abstract This paper aims to present a feasibility study of the innovative plant for methanol synthesis from carbon dioxide-sequestered by fossil fuel power plant and hydrogen, which is produced by water electrolyzer employing the over-production on the electrical grid. The thermo-economic analysis is performed in the framework of the MefCO2 H2020 EU project and it is referred to the German economic scenario, properly taking into account the real market costs and cost functions for different components of the plant. Three different plant capacities for methanol production (4000 10,000 and 50,000 ton/year) have been investigated, assuming an average cost for electrical energy to feed electrolysers and analyzing the influence of the most significant parameters (oxygen selling option, methanol selling price and electrolysers’ capital cost) on the profitability of the plant. The analysis has been performed in W-ECoMP, software for the thermo-economic analysis and plant optimization developed by the University of Genoa.

Abstract The price effect of the rising share of renewable electricity, which is called ‘merit-order-effect’, leads to noticeable changes in the German power industry and debates about the electricity market design. This paper estimates the merit-order-effect induced by variable renewable energy in the German-Austrian electricity sector with a multivariate regression model. The research focus lies on the impact of the estimated effects on the marketability of variable renewable electricity generation. The results show a systematic decline of the average market revenues for wind and photovoltaic plants in the period from January 2011 to December 2013. Current market data shows a continuation of this trend into 2016. According to the German long term goals for the use of renewables, wind and solar power will play a crucial role in the future electricity generation mix. If investments in these technologies will be profitable without any regulatory remuneration mechanisms in addition to the market revenues, depends on the further cost degression and the development of the merit-order-effect.

Abstract The price effect of the rising share of renewable electricity, which is called ‘merit-order-effect’, leads to noticeable changes in the German power industry and debates about the electricity market design. This paper estimates the merit-order-effect induced by variable renewable energy in the German-Austrian electricity sector with a multivariate regression model. The research focus lies on the impact of the estimated effects on the marketability of variable renewable electricity generation. The results show a systematic decline of the average market revenues for wind and photovoltaic plants in the period from January 2011 to December 2013. Current market data shows a continuation of this trend into 2016. According to the German long term goals for the use of renewables, wind and solar power will play a crucial role in the future electricity generation mix. If investments in these technologies will be profitable without any regulatory remuneration mechanisms in addition to the market revenues, depends on the further cost degression and the development of the merit-order-effect.

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.

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.

Abstract Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model. The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.