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Abstract A holistic statistical modelling procedure for the analysis of energy balance (EB) studies is proposed in this review. We show that a switch from EB-based analysis to heat production (HP)-based analysis has some advantages. The use of augmented EB data with a fasting HP estimate is proposed to correct slope bias due to non-linearity. This is facilitated by joint or parallel analysis of HP and EB data. Increasing levels of metabolizable energy intake (MEI) will lead to an increased HP attributed to greater energy cost of digestion and other metabolic processes following an exponential-like trajectory. This will correspondingly introduce a diminishing-returns-like non-linearity in the EB versus MEI relationship because HP and EB complement each other. This makes the assumption of linearity somewhat erroneous unless the MEI range is very close to the maintenance level. By using non-linear regression models (e.g. diminishing returns curves), we do not need to impose the assumption of linearity of the relationship EB versus MEI. In this study, we show how estimates of FHP, derived from the analysis of HP data (scaled by metabolic weight), can be included in EB data analysis allowing for the estimation of unbiased curvature-based slope parameters.

The rise in gas prices, accelerated by the war in Ukraine, has exposed the volatility of the energy market and Europe’s need to achieve independence from external supplies from politically sensitive areas. Reaching such independence, while simultaneously complying with climate agreements, will inevitably require a substantial expansion of subsurface energy and byproducts storage options. JMM is funded by the DeepNL research programme (project DEEP.NL.2019.003) which is financed by the Dutch Research Council. JA is funded by the Spanish Ministry of Science and Innovation through the Juan de la Cierva fellowship (IJC 2018-036074-I), funded by MCIN/AEI/10.13039/501100011033. NH is funded by the UK Engineering and Physical Sciences Research Council funded research project “HyStorPor” (grant number EP/S027815/1). Peer reviewed

In this paper, five projected tunnel FET (TFET) technologies are evaluated and compared with MOSFET and FinFET transistors for high-performance low-power objectives. The scope of this benchmarking exercise is broader than that of previous studies in that it seeks solutions to different identified limitations. The power and the energy of the technologies are evaluated and compared assuming given operating frequency targets. The results clearly show how the power/energy advantages of TFET devices are heavily dependent on required operating frequency, switching activity, and logic depth, suggesting that architectural aspects should be taken into account in benchmarking experiments. Two of the TFET technologies analyzed prove to be very promising for different operating frequency ranges and, therefore, for different application areas. Peer reviewed

The aim of this paper is to identify the factors that drive support levels for wind on-shore electricity in the Member States of the European Union (EU) with the help of econometric techniques. The econometric analysis is based on cross-section linear regressions with ordinary least squares. Four alternative specifications of the model have been estimated. The estimates comply with the basic hypotheses of the lineal model, i.e., absence of multicollinearity, accurate functional form, homokedasticity and normality in the distribution of errors. Thus, the estimations are unbiased, efficient and consistent. The results show that countries with higher wind energy generation costs have higher support levels. The higher support levels in countries with higher carbon intensities suggest that wind energy deployment is regarded as effective to mitigate carbon emissions. The type of support scheme also influences support levels, with feed-in tariffs leading to lower levels of support than other instruments. In addition, a general good investment climate in the country makes higher support levels less necessary, stressing the importance of lowering risks in order to reduce support levels and, thus, financial transfers from consumers to producers. Thus, providing stable regulatory frameworks should be a priority of policy-makers. The rest of variables (renewable energy resource potentials, administrative barriers, energy import dependency, interest rates, share of wind energy in total electricity generation as a proxy of lobbying pressures and electricity demand) are not statistically significant in most specifications and some of them do not have the expected sign. Cristina Peñasco gratefully acknowledges support from the Ministry of Science and Innovation and CSIC through the JAE (Junta para la Ampliación de Estudios) predoc program. Peer Reviewed

The size of bidders has been the focus of some research in the empirical literature in renewable electricity auctions, mostly related to the (negative) impact of auctions and auction design elements on the participation and award of small bidders. The main result of this literature is that small actors are discouraged from participating and being awarded in the auction and that this is a detrimental outcome of auctions. However, the impact of small bidders on the efficiency of the auction has not received a comparable degree of attention. The aim of this paper is to contribute to this literature with an analysis of the efficiency effects of bidders with different sizes in renewable electricity auctions. Our results show that a greater diversity of bidders’ sizes increases the probability that the auction will not be efficient. In other words, promoting small actors with respect to large ones comes at a cost in terms of a lower allocative efficiency i.e., that the lowest-cost bidders will not be awarded. Although some governments have a goal of promoting the participation of small actors in auctions, our findings suggest that the reason for promoting actor diversity is not in the allocative efficiency of the auction, but must lie elsewhere i.e., a greater competition, mitigation of the risk of collusion, social acceptability or decentralization of renewable energy production. Peer reviewed

A novel configuration of the Ca-Cu looping process based on dynamically operated packed-bed reactors is proposed to convert blast furnace gas (BFG) into H2/N2 and highly concentrated CO2, accompanied by a large amount of high-temperature heat. Preliminary energy and mass balances of the process reveal that around 30% of the BFG can be upgraded via calcium assisted water gas shift (WGS) if only BFG is used as reducing gas in the reduction/calcination stage. A higher amount of H2/N2 can be produced by using other steel mill off gases, such as coke oven gas (COG) or basic oxygen furnace gas (BOFG), or natural gas in the regeneration of the CO2 sorbent. This decarbonized fuel gas could be used for onsite power generation or to obtain sponge iron by a Direct Reduced Iron (DRI) process, increasing the overall capacity of the steel plant. Energy efficiencies higher than 75% have been calculated, reaching maximum values around 88% in case of using natural as fuel gas for the sorbent regeneration stage. Low values for the specific energy consumption of around 1.5 MJLHV/kgCO2 and CO2 capture efficiencies higher than 95% support the further development of the proposed Ca-Cu looping process. The authors acknowledge the financial support from the EPSRC BREINSTORM project, EP/S030654/1. Peer reviewed