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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.

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.

Biofuels have been identified as a mid-term GHG emission abatement solution for decarbonising the transport sector. This study examines the techno-economic analysis of biofuel production via biomass fast pyrolysis and subsequent bio-oil upgrading via zeolite cracking. The aim of this study is to compare the techno-economic feasibility of two conceptual catalyst regeneration configurations for the zeolite cracking process: (i) a two-stage regenerator operating sequentially in partial and complete combustion modes (P-2RG) and (ii) a single stage regenerator operating in complete combustion mode coupled with a catalyst cooler (P-1RGC). The designs were implemented in Aspen Plus® based on a hypothetical 72 t/day pine wood fast pyrolysis and zeolite cracking plant and compared in terms of energy efficiency and profitability. The energy efficiencies of P-2RG and P-1RGC were estimated at 54% and 52%, respectively with corresponding minimum fuel selling prices (MFSPs) of £7.48/GGE and £7.20/GGE. Sensitivity analysis revealed that the MFSPs of both designs are mainly sensitive to variations in fuel yield, operating cost and income tax. Furthermore, uncertainty analysis indicated that the likely range of the MFSPs of P-1RGC (£5.81/GGE  £11.63/GGE) at 95% probability was more economically favourable compared with P-2RG, along with a penalty of 2% reduction in energy efficiency. The results provide evidence to support the economic viability of biofuel production via zeolite cracking of pyrolysis-derived bio-oil.

This article makes the central argument that basic democratic values such as justice, autonomy and participation run the risk of being neglected when designing ‘nudges’ (i.e., indirect suggestions to influence individual behaviour) for sustainable behaviour change in the context of food governance, potentially complicating a democratisation of the food system. ‘Nudges’ uphold freedom of choice while simultaneously advocating a non-coercive soft force of paternalism to help people realise their preferences, maximise societal well-being and meet macro-sustainability goals. While the promises of the ‘nudge’ approach are widely echoed, nudging is also being contested because of its possible anti-democratic effects, such as individualisation, depoliticization and the emphasis of the status of citizens as ‘consumer-citizens.’ From a food democracy perspective, these dangers may undermine efforts to organise collective political action and impede alternative visions of a future food system. Empirically, the article examines specifically how behavioural-economic approaches imagine transitions to a more sustainable food system. By using the “COOP Supermarket of the Future” as a case study, the following analysis will illustrate how private actors are increasingly involved in steering consumer choice towards socially desirable actions. The analysis suggests that the design of choice environments may under specific circumstances increase the susceptibility of individuals to the influence of corporate preferences and simultaneously decrease the prospects for democratic legitimation and decision-making. The article therefore critically assesses whether reforming the food system by altering consumers’ choice-sets and the attribution of personal responsibility, may in fact point towards implicit anti-democratic tenets underlying the ‘will to nudge’ citizens.

Interconnectivity and interoperability are very important features in the development of integrated energy management systems for industrial facilities. A simple and common strategy for exchanging energy-related information among the entities in a facility is currently lacking. To this end, the purpose of this study is to present an IoT-based communication framework with a common information model to facilitate the development of a demand response (DR) energy management system for industrial customers. Additionally, we developed and implemented an IoT-based energy-management platform based on a common information model and open communication protocols, which takes advantage of integrated energy supply networks to deploy DR energy management in an industrial facility. The experimental results of this study demonstrate that the proposed platform can not only improve the interconnectivity of the entities in industrial energy management systems but also reduce the energy costs of industrial facilities.

Aiming at the large carbon emissions of facility agricultural heating in severe cold regions in winter, a compound parabolic concentrator based soil heating system was presented. The system integrated with novel trough compound parabolic concentrator and was used for soil heating in facility agriculture. Following the structure of the compound parabolic concentrator, TracePro software was selected to trace the light in the compound parabolic concentrator. The variation trend of the light escape rate of the compound parabolic concentrator with the different incident angles was analyzed. Based on the calculation results, the performance of the solar collector system was investigated, and the impact of circulating air velocity on the photo-thermal performance of the solar collector system was explored. Research results indicate that when the circulating air velocity is 1.4 m/s and the average ambient temperature is about 28.9?, the temperature of the system outlet is up to 90.9?. The average instantaneous heat collection, maximum photo-thermal conversion efficiency, and unit area heat collection of the system are 740.6 W, 27.83%, and 0.8 MJ/m2, respectively. This research can effectively promote the efficient integration of the solar collector system in facility agriculture.