Article
Environmental Sciences
Vishal Sharma, Mei-Ling Tsai, Chiu-Wen Chen, Pei-Pei Sun, Parushi Nargotra, Cheng-Di Dong
Summary: In response to global climate change concerns, the society is striving towards the development of renewable and sustainable energies. Machine learning technologies show great potential in managing complex scientific tasks and improving decision-making in energy distribution networks. By applying data-driven probabilistic machine learning algorithms, accurate estimates of biofuel product yields can be obtained, reducing the cost of experimental research. This review provides a comprehensive understanding of the application of different machine learning models in regulating and monitoring biofuel production from waste biomass.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Energy & Fuels
Silvia Rodriguez-Fernandez, Ismael Diaz, Maria Gonzalez-Miquel, Emilio J. Gonzalez, Manuel Rodriguez
Summary: In the framework of the European Green Deal, Spain has set ambitious climate and energy goals for the year 2030. The use of lignocellulosic biorefineries can contribute to these goals, but the production of advanced biofuels is not profitable compared to fossil fuels. To address this issue, the efficient production of a wide range of bioproducts is proposed. A systematic evaluation of the economic potential of various bio-building blocks is presented, and different combinations of feedstock and conversion technologies are considered. Pine and eucalyptus residues, as well as olive tree pruning wastes, are analyzed as available feedstocks in Spain. The results show that bio-based building blocks have good economic and energy performance compared to advanced biofuels and should be considered to improve the profitability of biorefineries. Pine, eucalyptus, and olive residues can satisfy the demand for advanced gasoline, bioethanol, hydrogen, and building blocks in Spain. However, further research is needed for routes other than lactic acid production to reach the break-even point.
BIOMASS CONVERSION AND BIOREFINERY
(2022)
Article
Chemistry, Multidisciplinary
Zhengwen Cao, Yun Xu, Pengbo Lyu, Michael Dierks, Angel Morales-Garcia, Wolfgang Schrader, Petr Nachtigall, Ferdi Schuth
Summary: This study presents a catalytic system that can convert lignin into high-quality hydrocarbons by controlling hydrogen partial pressure, providing flexibility in hydrogen storage/consumption to meet different regional and temporal demands. The product distribution between aromatics and aliphatics can be tuned by controlling hydrogen availability on the catalyst surface, leading to almost complete oxygen removal from lignin biomass.
Review
Agricultural Engineering
Mariano Martin, Manuel Taifouris, Guillermo Galan
Summary: Biomass has the potential to be a sustainable source of chemicals, but the challenges it presents necessitate an integrated approach to design a novel production system. The use of multiscale approaches in biorefinery design and deployment has been limited due to the extensive experimental and modeling work required. A systems perspective provides a systematic framework for analyzing the availability and composition of raw materials, as well as the impact on process design and product portfolio. The use of lignocellulosic materials requires multidisciplinary work and the development of process engineers with technical competencies in biology, biotechnology, process engineering, mathematics, computer science, and social sciences for a sustainable process/chemical industry.
BIORESOURCE TECHNOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Joakim Lofgren, Dmitry Tarasov, Taru Koitto, Patrick Rinke, Mikhail Balakshin, Milica Todorovic
Summary: This study optimized lignin in the AquaSolv omni biorefinery using Bayesian optimization and identified processing conditions that simultaneously optimize lignin yield and β-O-4 linkages.
ACS SUSTAINABLE CHEMISTRY & ENGINEERING
(2022)
Review
Agricultural Engineering
Alvin B. Culaba, Andres Philip Mayol, Jayne Lois G. San Juan, Carlo L. Vinoya, Ronnie S. Concepcion, Argel A. Bandala, Ryan Rhay P. Vicerra, Aristotle T. Ubando, Wei-Hsin Chen, Jo-Shu Chang
Summary: Lignocellulosic biomass is seen as a sustainable feedstock for biorefineries, but challenges like commercialization and cost effectiveness exist. This article emphasizes studies on the sustainability of LCB and the role of computational intelligence methods in improving biorefineries.
BIORESOURCE TECHNOLOGY
(2022)
Article
Agricultural Engineering
Wojciech Jerzak, Marcin Gajek, Aneta Magdziarz
Summary: The purpose of this study was to investigate the effect of adding NH4Cl to oat straw on the evolved gases, kinetic triplet, and thermodynamic parameters during the pyrolysis process at 873 K. The results showed that the addition of NH4Cl promoted carbonization of the chars, formation of C-N bonds, and reduced the production of CH4 and CO2. Furthermore, the addition of NH4Cl increased the mean values of the effective activation energy and thermodynamic parameters.
BIORESOURCE TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Xiaofei Chen, Jinmei Xiao, Jiaqi Yuan, Ziwei Xiao, Wenjie Gang
Summary: This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. Results show that low-density communities in most regions of China can achieve 100% renewable energy systems with a relatively short payback period.
Review
Agricultural Engineering
Sarita Candida Rabelo, Pedro Yoritomo Souza Nakasu, Eupidio Scopel, Michelle Fernandes Araujo, Luiz Henrique Cardoso, Aline Carvalho da Costa
Summary: Biorefineries aim to convert biomass sustainably into chemicals, materials, and bio-energy with minimized effluents. Efficient and sustainable biomass fractionation is crucial for the success of lignocellulosic biorefineries. This review discusses the recent advances of organosolv pretreatment, including the use of biobased solvents, and explores the opportunities of utilizing cellulose, hemicellulose, and lignin to produce biofuels and high-value products. It also presents the challenges and opportunities in the industrial implementation of organosolv processes.
BIORESOURCE TECHNOLOGY
(2023)
Article
Agricultural Engineering
V. Karuppasamy Vikraman, D. Praveen Kumar, G. Boopathi, P. Subramanian
Summary: The pyrolysis kinetics of finger millet straw was studied using a thermogravimetric analyzer under N2 environment, with the average activation energy determined to be around 177.80 kJ mol-1. The empirical modeling of the pyrolysis process showed a high model adequacy of 97.55%, indicating the feasibility of exploiting finger millet straw as a pyrolysis feedstock for deriving biofuels.
BIORESOURCE TECHNOLOGY
(2021)
Article
Green & Sustainable Science & Technology
Zeba Usmani, Minaxi Sharma, Abhishek Kumar Awasthi, Tiit Lukk, Maria G. Tuohy, Liang Gong, Phuong Nguyen-Tri, Alan D. Goddard, Roslyn M. Bill, S. Chandra Nayak, Vijai Kumar
Summary: Lignocellulosic biomass is a valuable and sustainable feedstock, yet commercial success remains low due to factors such as irregular biomass supply chains, inefficient technologies, and high operating costs. Investing in research and development to address these challenges is essential for the advancement of lignocellulosic biorefineries.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Green & Sustainable Science & Technology
Wei Wu, Muhammad Ikhsan Taipabu, Wei-Chen Chang, Karthickeyan Viswanathan, Yi-Lin Xie, Po-Chih Kuo
Summary: A torrefied biomass polygeneration system has been developed to simultaneously produce electricity, hydrogen, and synthetic natural gas. Three different frameworks are proposed to meet the daily energy demands, and the results show that the third framework has lower operating costs and levelized cost of energy compared to the second framework.
Article
Engineering, Industrial
Sobhan Razm, Nadjib Brahimi, Ramzi Hammami, Alexandre Dolgui
Summary: In this study, a production planning problem for a biorefinery is modeled and solved, considering the production and storage of bioenergy and biofuel from different types of biomass. The impact of biomass deterioration on storage decisions is analyzed. The results show that perishability can lead to profit losses, but there is a threshold above which perishability does not have any longer impact on the profit. Storage and transformation of biofuel can increase profit and smooth production. The model provides guidelines on setting a maximum age for biomass to enhance quality and reduce health risks.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Review
Agricultural Engineering
Salvador Sanchez Munoz, Thercia Rocha Balbino, Edith Mier Alba, Fernanda Goncalves Barbosa, Fernando Tonet de Pier, Alexandra Lazuroz Moura de Almeida, Ana Helena Balan Zilla, Felipe Antonio Fernandes Antunes, Ruly Teran Hilares, Nagamani Balagurusamy, Julio Ceaser dos Santos, Silvio Silverio da Sliva
Summary: This review discusses the potential of using surfactants to enhance lignocellulosic biomass processing, including their key role and mechanisms in biorefinery processes. The application of surfactants in pretreatment, enzymatic hydrolysis, and fermentation processes to increase the efficiency of bioproduct production and reduce production costs is explored.
BIORESOURCE TECHNOLOGY
(2022)
Review
Green & Sustainable Science & Technology
F. A. Plazas-Nino, N. R. Ortiz-Pimiento, E. G. Montes-Paez
Summary: Energy planning is crucial for the future sustainability, affordability, and reliability of the energy mix. Energy system optimization models (ESOMs) serve as accurate tools to guide national energy planning decisions. This article provides a systematic literature review on ESOMs, including their characteristics, data requirements, trends in decarbonization scenario analysis, and challenges associated with energy system optimization modeling. The review highlights the importance of decarbonization pathways as the primary objective in energy system optimization modeling, with factors such as renewable energy integration, energy efficiency improvement, sector coupling, and sustainable transport as key drivers.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Amalia Pizarro-Alonso, Hans Ravn, Marie Munster
Article
Economics
Giada Venturini, Kenneth Karlsson, Marie Munster
Article
Energy & Fuels
Ida Graested Jensen, Frauke Wiese, Rasmus Bramstoft, Marie Munster
ENERGY STRATEGY REVIEWS
(2020)
Article
Thermodynamics
Mason Scott Lester, Rasmus Bramstoft, Marie Munster
Article
Energy & Fuels
Rasmus Bramstoft, Amalia Pizarro-Alonso, Ida Graested Jensen, Hans Ravn, Marie Munster
Article
Engineering, Environmental
Sara Shapiro-Bengtsen, Frits Moller Andersen, Marie Munster, Lele Zou
Article
Energy & Fuels
Juan Gea-Bermudez, Ida Graested Jensen, Marie Muenster, Matti Koivisto, Jon Gustav Kirkerud, Yi-kuang Chen, Hans Ravn
Summary: This study examines the role of sector coupling in the energy system of Northern-central Europe towards 2050, showing that sector coupling contributes to achieving the green transition by increasing renewable energy utilization, reducing emissions, and costs.
Article
Energy & Fuels
Philip Swisher, Juan Pablo Murcia Leon, Juan Gea-Bermudez, Matti Koivisto, Helge Aagaard Madsen, Marie Munster
Summary: The study aims to investigate the competitiveness and impact of low wind turbines in the energy system of Northern and Central Europe, finding that investment starts when their price is 45% higher than traditional turbines. It also shows reductions in transmission investment and increased revenue from this technology, suggesting its potential commercial value in the future energy system of Northern and Central Europe, especially in wind-rich areas such as Denmark.
Article
Energy & Fuels
Yi Zheng, Shi You, Henrik W. Bindner, Marie Munster
Summary: In this paper, a comprehensive model for alkaline electrolyser is developed to describe its dynamic behavior, and the optimal dispatch of an electrolyser based on a real-world system is studied using this model. The results show that the model can effectively capture the coupling between thermal-electric dynamics and on-off performance of an electrolyser, and the flexible operation strategy can significantly increase revenues.
Article
Thermodynamics
Yi Zheng, Shi You, Ximei Li, Henrik W. Bindner, Marie Muenster
Summary: This paper introduces a grid-connected Power-to-Methanol system, which is modeled, simulated, and optimized for its daily operation by considering participation in day-ahead electricity markets. The results show that the proposed data-driven method performs well in reducing operational costs.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Energy & Fuels
Yi Zheng, Jiawei Wang, Shi You, Ximei Li, Henrik W. Bindner, Marie Munster
Summary: A decision-making framework based on data-driven robust chance constrained programming (DRCCP) is proposed in this paper, which effectively handles uncertainties, manages risks, and reduces operational costs for wind/hydrogen systems.
Article
Multidisciplinary Sciences
Sebastian Franz, Nicolas Campion, Sara Shapiro-Bengtsen, Rasmus Bramstoft, Dogan Keles, Marie Munster
Summary: The study finds that achieving emission reduction targets in the shipping industry requires high growth rates in green fuel availability, high carbon pricing, and significant fuel demand savings.
Article
Green & Sustainable Science & Technology
Nicolas Campion, Hossein Nami, Philip R. Swisher, Peter Vang Hendriksen, Marie Munster
Summary: This paper develops a fast-solving open-source model for dynamic power-to-X plant techno-economic analysis and investigates the bias in using other state-of-the-art power-to-X cost calculation methods. The model optimizes investments and operation-costs based on techno-economic data, power profiles, and grid prices. The study focuses on ammonia fuel synthesized from electrolytic hydrogen produced by photovoltaics, wind turbines, or the grid. Comparisons are made using different weather profiles and electrolyser technologies. The results show that a semi-islanded set-up is the most cost-effective option, reducing costs by up to 23% compared to off-grid systems.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Chemistry, Multidisciplinary
Sara Shapiro-Bengtsen, Lorie Hamelin, Lars Bregnbaek, Lele Zou, Marie Munster
Summary: This study assesses the large-scale scenarios for utilizing residual biomass and simulates impacts to electricity and heating systems, finding major benefits in all impact categories and identifying nitrogen leaching as posing the largest economic impact.
ENERGY & ENVIRONMENTAL SCIENCE
(2022)
Article
Energy & Fuels
Yi Zheng, Shi You, Henrik W. Bindner, Marie Munster
Summary: This paper proposes a two-stage multi-objective optimization framework to reveal optimal investment plans considering different operational strategies. The results show a trade-off between system investment and operational performance, and different operation objectives affect component capacities during the planning phase.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.