Showing papers in "Applied Energy in 2019"

TL;DR: In this article, the shape stability of phase change materials is investigated in thermal management and energy storage systems, and the critical issues in different shape-stabilization strategies and the possible rectifications are discussed.

TL;DR: In this article, a comprehensive overview of the methods reported to enhance each step involved in anaerobic digestion is provided, and the strategies for improving enzyme activity are summarized, as well as the key points for future studies are proposed.

TL;DR: In this paper, a review of the use of reinforcement learning for demand response applications in the smart grid is presented, and the authors identify a need to further explore reinforcement learning to coordinate multi-agent systems that can participate in demand response programs under demand-dependent electricity prices.

TL;DR: In this article, the current state of the art in passive radiative cooling technology is reviewed and updated, and the advanced materials and structures of various radiators, which are popular topics in radiative heating, are presented.

TL;DR: In this article, the authors model seven scenarios for the European power system in 2050 based on 100% renewable energy sources, assuming different levels of future demand and technology availability, and compare them with a scenario which includes low-carbon non-renewable technologies.

TL;DR: Among all of the investigated deep learning techniques, the gated 24-h CNN model, performed in a direct multi-step manner, proves itself to have the best performance, improving the forecasting accuracy by 22.6% compared to that of the seasonal ARIMAX.

TL;DR: The strategies utilized by microgrids for enhancing their resilience during major outage events are analyzed, which include proactive scheduling, outage management, feasible islanding, and advanced operation strategies for reducing the impact of major disruptions.

TL;DR: In this article, the authors investigated the thermal runaway mechanism of Li(NixCoyMnz)O2 cathode and carbon-based anode and found that the major heat source during thermal runaway was the redox reaction between the cathodes and anodes at high temperature.

TL;DR: The results showed that when the input sequence is increased, the accuracy of the model is improved, and the prediction effect of the hybrid model is the best, followed by that of convolutional neural network.

TL;DR: In this paper, a comprehensive and critical review of the enhanced oil recovery (EOR) processes in the post steam injection era in both experimental and field cases is presented, where the recovery mechanisms and field performance of thermal EOR processes by reservoir lithology (sandstone and carbonate formations) and offshore versus onshore oilfields.

TL;DR: In this article, a microgrid system that consists of photovoltaic, wind turbine generator, electric storage system and diesel generator is implemented to test their commercial prospects in rural communities that have no access to electricity due to economic and technical constraints.

TL;DR: In this paper, the authors reviewed the research on membranes in vanadium redox flow battery (VRFB) system, including the properties, development of traditional commercial membranes as well as recently developed membranes.

TL;DR: Comparative and statistical results demonstrate that PGJAYA has a superior performance as it always obtains the most accurate parameters with strong robustness among all compared algorithms.

TL;DR: A deep learning based framework to forecast electricity demand by taking care of long-term historical dependencies is proposed and applied to the electricity consumption data of Union Territory Chandigarh, India.

TL;DR: In this article, the authors investigated trends in seawater reverse osmosis (SWRO) application using more than 70 datasets on large-scale SWRO plants, and analyzed the increasing number of large-size SW RO plants, the SEC reduction by isobaric energy recovery devices (ERDs), and the use of different SWRO configurations to meet the energy and quality requirements.

TL;DR: A probabilistic load forecasting method for individual consumers is proposed to handle the variability and uncertainty of future load profiles, using a deep neural network, long short-term memory (LSTM), to model both the long-term and short- term dependencies within the load profiles.

TL;DR: Wang et al. as discussed by the authors proposed a novel and efficient sunlight-driven phase change materials (PCMs) based on polyethylene glycol (PEG) supported by Ag nanoparticle-functionalized graphene nanosheets (Ag-GNS).

TL;DR: Simulation results show that this proposed incentive-based demand response algorithm induces demand side participation, promotes service provider and customers profitabilities, and improves system reliability by balancing energy resources, which can be regarded as a win-win strategy for both service providers and customers.

TL;DR: In this paper, the key roles of mechanical modulations for energy harvesting are emphasized, and the methods and principles of mechanical modulation and their applications to energy harvesting systems are reviewed and classified into three categories: excitation type conversions, frequency up-conversions, force/motion amplifications.

TL;DR: In this article, the authors present a state-of-the-art review of existing research on the study of grid resilience, which focuses on the point of view of power system engineering with respect to extreme weather events.

TL;DR: This paper proposes how a motivational psychology framework can be used effectively to design peer-to-peer energy trading to increase user participation, and how the outcomes of the scheme satisfy all the motivational psychology models shows its potential to attract users to participate in energy trading.

TL;DR: A stochastic model predictive controller (MPC) based on Pontryagin’s Minimum Principle (PMP), which differs from widely used dynamic programming (DP)-based predictive methods is proposed, demonstrating the promising performance and computational efficiency of the proposed methodology.

TL;DR: It is ascertained that a proposed hybrid model based on a convolution network framework can accurately predict GSR and enable energy availability to be regularly monitored over multi-step horizons when coupled with a low latency Long Short-Term Memory network.

TL;DR: This review looks at the current developments in the smart energy sector, focussing on techniques in the main application areas along with relevant implemented examples, while highlighting some of the key challenges currently faced and outlining future pathways for the sector.

TL;DR: In this article, a thermal management module with a sandwich structure consisting of a battery, phase change material, and heat pipe is assembled, and a lumped thermal model is built to consider the coupling of battery heat generation.

TL;DR: A comprehensive review of decomposition-based wind forecasting methods in order to explore their effectiveness, and discusses decomposition methods in the context of alternative forecasting algorithms, and explores the challenges of each method.

TL;DR: This paper proposes a comprehensive and critical state of the art review on power supply configurations and energy management systems to find out gaps and to provide insights and recommendations for future research.

TL;DR: In this paper, a new energy regulation issue is considered based on the operational principles of EI, and a model-free deep reinforcement learning algorithm is applied to obtain the desired control scheme.

TL;DR: In this paper, a novel form-stable and thermally induced flexible composite PCM inspired by shape memory polymers was successfully prepared, where paraffin (PA) with large latent heat was employed as PCM, olefin block copolymer (OBC) performed as the supporting material and expanded graphite (EG) was the additives for thermal conductivity enhancement.

TL;DR: In this article, the authors explore the implementation of thermal energy storage in district heating and cooling systems, highlighting their potential in combination with district heating, taking into account the research maturity of each type technology.