Showing papers in "Energy Procedia in 2018"

TL;DR: In this paper, the authors present a review of power-to-gas (PtG) research and demonstration projects in Europe, identifying and assessing relevant projects regarding their field of application, applied processes and technologies for electrolysis, type of methanation, capacity, location and year of commissioning.

TL;DR: In this article, the authors analyzed fossil fuel energy consumption in European countries as well as its relationship with other variables such as energy dependence and share of renewable energy in gross final energy consumption.

TL;DR: In this paper, the authors investigated the characteristics of the virtual battery and its characteristics for PV power plant deployment and showed that the flexibility of operation of reservoir-based power plants and their current connection to grids facilitates a virtual battery consisting of supplying the electricity demand with solar energy during peak irradiation hours, while balancing grids with hydropower during low/no irradiation times and providing a zero impact area for PV-powered deployment.

TL;DR: In this paper, the authors analyzed energy storage technologies from an energy security perspective and concluded that all storage technologies show a positive relationship with energy security and all increase energy security, albeit at different levels.

TL;DR: The technical issues associated with the transition of the 4th generation district heating: supplying low temperature to buildings, integrating various heat sources and thermal storages, and developing smart DH systems are reviewed.

TL;DR: The limits and potentials of MILP methods for the optimization problem of polygeneration energy systems are reviewed and discussed.

TL;DR: In this paper, the authors investigated the use of machine learning algorithms to predict the aggregated heating load of the community in a solar district heating system with 52 homes and found that decision trees can significantly improve the accuracy of predicted heating loads by incorporating the effect of additional influencing factors (e.g., time of the day, day of the week, solar radiation).

TL;DR: In this article, a review of various biodegradable industrial by-products as substrates for production of SCP are categorized and compared, as well as a comparison of their performance.

TL;DR: In this paper, two power and energy management strategies for a hybrid residential PV-wind system with battery energy storage were evaluated, and the stress to which the battery was subjected, while providing the two management strategies, was also quantified.

TL;DR: In this paper, the Sleipner and Snohvit CCS projects had captured and stored 22 Mt of CO2 in saline aquifers offshore Norway, with approximately one tenth of this volume dissolved in the brine phase.

TL;DR: Deep learning based on the deep neural network structure is applied to predict a future short-term speed with the collected dataset including the historical vehicle speed and its corresponding acceleration, steering information, location and driving date and the results show the prediction effect is the best and the proposed prediction method has good generalization ability.

TL;DR: Wang et al. as discussed by the authors presented the method of support vector machines (SVM) to forecast building energy consumption in China, using weather data such as yearly mean outdoor dry-bulb temperature, relative humidity and global solar radiation and economic factors such as the ratio of urbanization, gross domestic product, household consumption level and total area of structure.

TL;DR: The first phase of the CarbFix project ran for over a decade and consisted of the training of students, creating the scientific basis for the fixation of carbon dioxide in the subsurface through the in-situ carbonation of basalts, and the demonstration of this technology by fixing approximately 200 tons of injected CO2 as carbonate minerals during 2012 and 2013 as mentioned in this paper.

TL;DR: A hybrid MCDM model based on FAHP and FTOPSIS is proposed to evaluate and prioritize five low-emission energy technologies development in Poland and shows that renewable energy technologies should be utilized instead of nuclear energy.

TL;DR: In this paper, a hybrid parametric workflow of Ladybug Tools is applied to validate their generic outdoor thermal comfort, calculated in Physiological Equivalent Temperature (PET), against measured meteorological data using HOBO-U30 weather station, and ENVI-met simulations for a case study in Cairo, Egypt.

TL;DR: In this article, a Gaussian process metamodel is developed to predict the ship fuel consumption for different scenarios, which not only considers the effects of operational conditions such as speed and trim, but also takes into account the impacts of wind and wave effects.

TL;DR: In this article, the authors discuss the work that has been done on the side of electrodes and electrolytes for use in high temperature Li-ion batteries, which is a problem for a number of applications that require high energy rechargeable batteries that operate at a high temperature (>100 °C).

TL;DR: Results show that the proposed extraction scheme based on 3D-CNNs achieves to derive intrinsic features for prediction of wind power generation from NWP data.

TL;DR: This work forecasts the generated power of photovoltaic (PV) power station using the general regression and back propagation neural network prediction method and finds out that the BP neural prediction method have better prediction results than GR method on PV power generation.

TL;DR: This paper evaluated the quality of existing PHREEQC databases (phreeqc.dat, llnl.dat and core10.dat) through the analysis of mineral saturation states for various carbonates, sulfur-containing minerals, silicates and hydroxides.

TL;DR: In this article, the authors presented methodology and assumptions underlying the DTReM-LV model, which is a System Dynamics based computer simulation model for CO2 emission mitigation analysis in the road transport sector in Latvia.

TL;DR: In this article, the authors provide a review summary of current thermal energy storage systems, including design concepts, application criteria, specific cost comparisons of various storage systems and a summary of applicable modelling and design tools currently available.

TL;DR: In this paper, an indicator-based framework for assessing the long-term environmental sustainability of higher education institutions (HEi) is proposed. But the authors focus on the evaluation of the sustainability of HEI.

TL;DR: The CarbFix gas injection method was developed to mitigate the gas emissions associated with geothermal utilization at Hellisheidi power plant as mentioned in this paper, and the first industrial scale injection took place in 2014.

TL;DR: In this paper, the world's first direct air capture (DAC) installation that is combined with mineral storage of CO2 is presented, where the CO2 removal solution may be expanded and applied globally.

TL;DR: This work demonstrates the performance gain obtained with shingling interconnection technology in terms of module output power and efficiency and describes the technological challenges for each step in theShingling assembly process flow.

TL;DR: This work proposes the novel approach which considers the constraint of ramp rate limit (RRL) to solve the ELD problem and build up the time varying dynamic economic load dispatch based on Levenberg Marquardt algorithm.

TL;DR: The AEKF method with innovation-based adaptive estimator has the strongest suppression of noise with less than 2% SOC estimation error.

TL;DR: In this paper, the embodied carbon and energy of an industrial building construction with 6733 m² of built area, following a LCA methodology, on a gate-to-gate approach, were evaluated.

TL;DR: Based on the online volunteered geographic information and some publicly available official data sources, the authors intends to provide a standardized framework for estimating the indirect building carbon emissions within the boundaries of various types of Local Climate Zones (LCZs), to better forecast the LCZ carbon emission patterns and assist district wide energy management.