Showing papers in "Applied Energy in 2018"

TL;DR: In this paper, the authors present the concept of a blockchain-based microgrid energy market without the need for central intermediaries, where consumers and prosumers can trade self-produced energy in a peer-to-peer fashion.

TL;DR: Test results in a LV grid-connected Microgrid show that P2P energy trading is able to improve the local balance of energy generation and consumption and the increased diversity of generation and load profiles of peers is ability to further facilitate the balance.

TL;DR: A comparative and critical analysis on decision making strategies and their solution methods for microgrid energy management systems are presented and various uncertainty quantification methods are summarized.

TL;DR: A recurrent neural network model to make medium-to-long term predictions of electricity consumption profiles in commercial and residential buildings at one-hour resolution and uses the deep NN to perform imputation on an electricity consumption dataset containing segments of missing values is presented.

TL;DR: A novel modeling framework for forecasting electricity prices is proposed and it is shown how the proposed deep learning models outperform the state-of-the-art methods and obtain results that are statistically significant.

TL;DR: In this paper, a state-of-the-art review on phase change materials (PCMs) and their applications for heating, cooling and electricity generation according to their working temperature ranges from (−20°C to +200°C).

TL;DR: In this article, a RL-based real-time power management strategy for hybrid energy storage system (HESS) in a plug-in hybrid electric vehicle (PHEV) is presented.

TL;DR: In this paper, the greenhouse gas impact of battery electric vehicles (BEVs) would be worse than that of conventional vehicles if electricity generation and the energy used for battery production are not sufficiently decarbonized.

TL;DR: In this paper, the authors provide an account on the research efforts put forth in solidified natural gas (SNG) technology, which has remarkable potential to store multi-fold volumes of natural gas in compact hydrate crystals offering the safest and the most environmental friendly mode of NG storage.

TL;DR: The proposed two-stage aggregated control method was applied to residential community Microgrids with photovoltaic (PV) battery systems and it was revealed that P2P energy sharing is able to reduce the energy cost of the community by 30% compared to the conventional P2G energy trading.

TL;DR: Different energy-harvesting technologies were compared in terms of power output, cost-effectiveness, technology readiness level, advantages and disadvantages, support from government and industry, and future research recommendations of energy harvesting in roadway and bridge were proposed.

TL;DR: In this article, a comprehensive review and critical discussion of state-of-the-art analytical techniques for optimal planning of renewable distributed generation is conducted, and a comparative analysis of analytical techniques is presented to show their suitability for distributed generation planning in terms of various optimization criteria.

TL;DR: In this article, the authors present a literature review of model-based analyses in this field, focusing on residential heating and compare geographical and temporal research scopes and identify state-of-the-art analytical model formulations, particularly considering heat pumps and thermal storage.

TL;DR: Using big data techniques, this study estimates the impacts of bike sharing on energy use and carbon dioxide and nitrogen oxide emissions in Shanghai from a spatiotemporal perspective and finds morning and evening peaks of the environmental benefits are higher than morning peaks.

TL;DR: Simulation results show that this proposed DR algorithm, can promote SP profitability, reduce energy costs for CUs, balance energy supply and demand in the electricity market, and improve the reliability of electric power systems, which can be regarded as a win-win strategy for both SP and CUs.

TL;DR: In this article, a robust sliding-mode control using nonlinear perturbation observers for wind energy conversion systems (WECS), in which a doubly-fed induction generator (DFIG) is employed to achieve an optimal power extraction with an improved fault ride-through (FRT) capability.

TL;DR: A game theoretic approach for a DSM model incorporating storage components is suggested in this paper, illustrating how a decentralized demand side management approach could be implemented in practice to facilitate peer-to-peer transactions following optimized demand profiles.

TL;DR: An exhaustive review of artificial neural networks used in wind energy systems is presented, identifying the methods most employed for different applications and demonstrating that Artificial Neural Networks can be an alternative to conventional methods in many cases.

TL;DR: In this paper, the authors compared the total cost of ownership of conventional, hybrid, plug-in hybrid and battery electric vehicles in three industrialized countries (UK, USA and Texas) for the time period 1997-2015.

TL;DR: In this article, the authors investigate the contribution of batteries located at the customer level versus a central battery shared by the community in a small community in London, United Kingdom, and investigate the combined features of trade and flexibility from storage produce savings of up to 31% for the end-users.

TL;DR: The proposed machine-learning technique, random forest regression, is able to learn the dependency of the battery capacity on the features that are extracted from the charging voltage and capacity measurements, and is promising for online battery capacity estimation.

TL;DR: In this article, an electrostatic vibration energy harvester is proposed and fabricated with both broad bandwidth and high normalized power density (NPD, harvested power/volume/acceleration2).

TL;DR: In this paper, an SP-based degradation model is developed by including Solid Electrolyte Interface (SEI) layer formation, coupled with crack propagation due to the stress generated by the volume expansion of the particles in the active materials.

TL;DR: In this article, an improved real-coded genetic algorithm and an enhanced mixed integer linear programming (MILP) based method have been developed to schedule the unit commitment and economic dispatch of microgrid units.

TL;DR: Simulation results showed that both of the step length control and learning process involvement techniques improve the performance of P2P energy sharing mechanisms with moderate ramping/learning rates and showed that P2p energy sharing has the potential to bring both economic and technical benefits for Great Britain.

TL;DR: The challenging issues and research gaps that remain unresolved are addressed, some recommendations regarding such challenges are stated for further research and the most common energy harvesting systems in vehicle suspensions are compared in terms of advantages and limitations.

TL;DR: Experimental results show that TLABC can achieve superior performance in terms of accuracy and reliability for different PV parameter estimation problems, and the results are compared with well-established TLBO and ABC algorithms.

TL;DR: In this article, a review of water-energy nexus analysis is presented, which provides a depository summary of a wide range of current existing methods and tools for water energy nexus analysis, and discusses these approaches based on their main purposes.

TL;DR: In this paper, the degradation mechanism of a proton exchange membrane fuel cell (PEMFC) under start-stop conditions is discussed. But, the degradation process is not discussed in detail.

TL;DR: A novel ETS model customised for Industry 4.0 integration incorporates blockchain technology to address ETS’s management and fraud issues whilst it utilizes a reputation system in a new approach to improve ETS efficacy.