Article
Thermodynamics
Etienne Cuisinier, Pierre Lemaire, Bernard Penz, Alain Ruby, Cyril Bourasseau
Summary: This paper proposes a new approach to balance long-term and short-term decisions and tests it on an energy production problem. Both approaches show promise and offer different trade-offs between model complexity, computation times, and solution quality.
Article
Biotechnology & Applied Microbiology
Georgios P. Georgiadis, Apostolos P. Elekidis, Michael C. Georgiadis
Summary: This study focuses on the optimal production planning and scheduling problem in beer production facilities. By proposing a novel MILP model, the total production costs are minimized efficiently, leading to improvements in both computational efficiency and solution quality.
FOOD AND BIOPRODUCTS PROCESSING
(2021)
Article
Computer Science, Interdisciplinary Applications
Yunning Yang, Renchu He, Guo Yu, Wei Du, Minglei Yang, Wenli Du
Summary: This paper addresses a crude oil scheduling problem in a marine-access refinery, considering the storage, blending, and processing of complex types of crude and the demands of downstream units. A full-space MINLP model is proposed to optimize the operation of crude unloading and blending, and handle the complex mixtures in the tank. An efficient rolling horizon approach is developed for large model sizes. Case studies show the efficiency of this approach and the influence of new constraints on the final solution.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Engineering, Civil
Ahmed A. Shalaby, Mostafa F. Shaaban, Mohamed Mokhtar, Hatem H. Zeineldin, Ehab F. El-Saadany
Summary: This paper proposes a new approach for optimal operation of an Electric Vehicle (EV) battery-swapping station (BSS) based on Rolling-Horizon optimization (RHO). The proposed model considers serving different types of EVs using a heterogeneous battery stock and utilizes a long short-term memory (LSTM) recurrent neural network for demand prediction. Simulation results show that the proposed dynamic scheduling mechanism increases profit and the number of served EVs compared to day-ahead scheduling.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Thermodynamics
Sepideh Saravani Ghayour, Taghi Barforoushi
Summary: This study proposes a framework for optimal scheduling of electrical appliances and energy sources in a smart home, utilizing renewable energy and combined heat and power technology. Uncertainties are modeled using scenario analysis, with the objective of minimizing the expected cost. Simulation results show significant cost reduction through the cogeneration of electricity and heat in the smart home.
Article
Agriculture, Multidisciplinary
Fernando Montenegro-Dos Santos, Francisco Perez-Galarce, Carlos Monardes-Concha, Alfredo Candia-Vejar, Marcelo Seido-Nagano, Javier Gomez-Lagos
Summary: Agriculture has evolved from a human-intensive activity to a highly automated process, with multiple technological advances being incorporated to increase harvest efficiency. However, uncertainty from weather conditions and crop characteristics pose challenges. This study proposes a non-myopic rolling horizon method to reschedule agricultural harvest plans, exemplified by olive oil production, and formulates a bi-objective problem to maximize production and minimize plan variability.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Transportation Science & Technology
Istenc Tarhan, Konstantinos G. Zografos, Juliana Sutanto, ac Ahmed Kheiri, Heru Suhartanto
Summary: The workload of emergency response services after natural disasters is huge, but there is limited availability of personnel, resulting in imbalances in supply and demand and detrimental effects on the provision of services. To address this issue, we propose a novel Disaster Response Personnel Routing and Scheduling (DRPRS) model that aims to meet demand efficiently and fairly, while considering constraints related to working and resting.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Electrical & Electronic
Mohsen Banaei, Francesco D'Ettorre, Razgar Ebrahimy, S. Ali Pourmousavi, Emma M. V. Blomgren, Henrik Madsen
Summary: In this study, a new approach is proposed to determine a group of contract hour sets to provide maximum flexibility of swimming pool heating systems. The proposed approach is validated through simulation studies and cost-benefit analysis.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Jorge L. Angarita, Hossein Jafari, Mojtaba Mohseni, Ameena Saad Al-Sumaiti, Ehsan Heydarian-Forushani, Rajesh Kumar
Summary: This paper proposes a robust investment and operation model for a microgrid connected to the distribution system, optimizing the investment and operation of combined heat and power, boilers, PV power generation, and battery energy storage systems. The model, using stochastic programming, considers uncertainty in parameters and aims to minimize annual operational costs by sharing power and heat facilities among adjacent consumers, achieving potential cost savings of up to 17%. The results demonstrate the benefits of employing different technologies and the synergies of all technologies operating together.
IET RENEWABLE POWER GENERATION
(2021)
Article
Construction & Building Technology
Madad Komeili, Peyman Nazarian, Amin Safari, Majid Moradlou
Summary: This paper presents a day-ahead scheduling method for multi-carrier microgrids, which uses information gap decision theory and a scenario-based stochastic approach to address the uncertainties of renewable sources and electricity prices. It proposes a hybrid optimization problem for optimal energy management, making the operation of multi-carrier microgrids robust against uncertainties. Results show that risk-averse operators can change their decision-making.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Engineering, Multidisciplinary
Abouzar Samimi, Hossein Shateri
Summary: This paper introduces a network constrained optimal operation model for both grid-connected and isolated microgrids, encouraging DER units to provide reactive power and considering the dependency between heat and active power generation by CHP and DER units. The main goal is to find the optimal economic dispatch of active and reactive powers as well as heat energy in microgrids, taking into account network constraints such as AC power flow limitations.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Thermodynamics
Lei Tang, Jue Guo, Boyang Zhao, Xiuli Wang, Chengcheng Shao, Yifei Wang
Summary: A novel planning model based on the rolling horizon optimal approach is proposed to address the multi-market equilibrium and multi-period coupling planning problem in system dynamics. By constructing the Hamilton function and developing an approximate gradient, the continuous optimization of power mix and updating of planning information are achieved.
Article
Engineering, Multidisciplinary
Fernando Santos, Ricardo Fukasawa, Luis Ricardez-Sandoval
Summary: This study successfully addressed machine scheduling and personnel allocation problems simultaneously, proposing a mathematical formulation and solution method to evaluate optimal solutions more efficiently. The results showed overall improvements of up to 11.6% compared to previous cases without considering personnel allocation decisions within the scheduling problem.
OPTIMIZATION AND ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Jia Feng, Guowei Li, Yuxin Shi, Zhengzhong Li, Shanshan Liu
Summary: This paper presents a coordinated model to optimize the rolling stock scheduling of two urban rail transit lines with a shared train depot. The proposed integrated and extended integrated optimization problems are transformed into mixed integer linear programming problems, which can be efficiently solved by an ant colony optimization algorithm. Numerical examples based on the Beijing Subway System are implemented to demonstrate the performance of the proposed models and solution approach.
Article
Chemistry, Analytical
Younes Al Younes, Martin Barczyk
Summary: The study introduces a method that combines local path planning with a graph-based planner to enable autonomous navigation of unmanned vehicles in GPS-denied subterranean environments. By utilizing the Nonlinear Model Predictive Horizon method, feasible, optimal, smooth, and collision-free paths are generated. The design also includes computationally efficient algorithms for global path planning and dynamic obstacle mapping and avoidance.
Article
Energy & Fuels
Alberto Dolara, Sonia Leva, Giampaolo Manzolini, Riccardo Simonetti, Iacopo Trattenero
Summary: Organic photovoltaic (OPV) solar cells are an emerging and promising solution for low-cost clean energy production, with significant advantages over conventional PV technologies. However, the commercialization of this technology has been hindered by relatively low efficiencies, poor long-term stability, and thermal issues.
Article
Engineering, Civil
Matteo Simoncini, Douglas Coimbra de Andrade, Leonardo Taccari, Samuele Salti, Luca Kubin, Fabio Schoen, Francesco Sambo
Summary: In this paper, a novel deep learning architecture is proposed to classify unsafe driving maneuvers using dashcam and IMU data. The architecture combines object detection algorithm output with raw video frames and GPS/IMU data, and utilizes a Spatio-Temporal Attention Selector (STAS) module to extract and select features for classification. Experimental results show that the proposed method outperforms other approaches applying attention over single frames.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Luca Bravi, Luca Kubin, Stefano Caprasecca, Douglas Coimbra de Andrade, Matteo Simoncini, Leonardo Taccari, Francesco Sambo
Summary: This article introduces a novel machine learning pipeline for automatic detection of stop sign violations from dashcam videos, leveraging deep convolutional neural networks and IMU/GPS data. The proposed two-step approach includes a Stop Sign Detector and a Stop Violation Classifier, which together achieve a high precision-recall curve area of 94% on real-world videos.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Editorial Material
Energy & Fuels
Matteo C. Romano, Cristina Antonini, Andre Bardow, Valentin Bertsch, Nigel P. Brandon, Jack Brouwer, Stefano Campanari, Luigi Crema, Paul E. Dodds, Stefania Gardarsdottir, Matteo Gazzani, Gert Jan Kramer, Peter D. Lund, Niall Mac Dowell, Emanuele Martelli, Luca Mastropasqua, Russell C. McKenna, Juliana Garcia Moretz-Sohn Monteiro, Nicola Paltrinieri, Bruno G. Pollet, Jeffrey G. Reed, Thomas J. Schmidt, Jaap Vente, Dianne Wiley
Summary: This paper responds to a previous study on blue hydrogen, highlighting the method and assumptions used. By analyzing the mass and energy balances of two blue hydrogen plants, the impact of methane leakage rate on the CO2 emissions is shown. The study concludes that blue hydrogen can have significantly lower CO2 emissions with proper CO2 capture technologies and low-emission natural gas supply chains.
ENERGY SCIENCE & ENGINEERING
(2022)
Article
Engineering, Civil
Luca Kubin, Tommaso Bianconcini, Douglas Coimbra de Andrade, Matteo Simoncini, Leonardo Taccari, Francesco Sambo
Summary: The article introduces a novel deep learning method for detecting vehicle accidents from on-board sensor data, which outperforms other approaches in terms of accuracy and can be easily deployed on embedded devices. The method utilizes neural architecture, multimodal self-supervised training, and data augmentation techniques to improve generalization capabilities and counteract extreme class imbalance.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Flavia Basile, Lorenzo Pilotti, Marco Ugolini, Giovanni Lozza, Giampaolo Manzolini
Summary: This paper applies an innovative optimization methodology to study the supply chain of biomethanol production in Sweden. The research considers the collection and transportation of biomass as well as the size of the biorefinery plant. The results show that the size of the biodiesel plants limits the collection of forestry residues. The study also finds that the low carbon intensity of Swedish electricity contributes to the low CO2 emissions of biomethanol.
Review
Green & Sustainable Science & Technology
Michael Dieterle, Peter Fischer, Marie-Noelle Pons, Nick Blume, Christine Minke, Aldo Bischi
Summary: This study reviewed 20 life cycle assessment studies for different flow battery systems and explored the sustainability issues. Recommendations for comparative life cycle assessment studies were derived, which are also relevant to the amendment of the Batteries Directive.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Energy & Fuels
Nan Zheng, Hanfei Zhang, Liqiang Duan, Qiushi Wang, Aldo Bischi, Umberto Desideri
Summary: The present study proposes a novel multi-generation system that integrates various renewable energy sources for efficient energy production and utilization. The system consists of a solar-driven proton exchange membrane electrolysis cell, a solid-oxide fuel cell, a parabolic trough photovoltaic thermal collector, and thermal energy storage. The system stores surplus solar electricity as high-pressure green hydrogen and utilizes it with a hydrogen-fueled solid-oxide fuel cell to meet the electricity demand at night. The system also utilizes solar heat and waste heat for cooling/heating and domestic hot water production. The techno-economic feasibility of the system is evaluated, and the results show excellent energy and economic performance.
Article
Energy & Fuels
Pietro Bartocci, Alberto Abad, Aldo Bischi, Lu Wang, Arturo Cabello, Margarita de Las Obras Loscertales, Mauro Zampilli, Haiping Yang, Francesco Fantozzi
Summary: This paper presents a simple methodology to optimize the design of the air reactor in a chemical looping combustor when connected to a turbo expander for power production. Considerations such as solid inventory, gas velocity, transport disengaging height, and pressure drop are taken into account. The reactor in this study had a height of 9.5 m and a diameter of 1.8 m, with a total inventory of 10,880 kg and a circulation rate of 110 kg/s. The operating pressure and temperature were 12 bar and 1200 degrees C, respectively, with an average gas velocity of 4 m/s. The fluidization regime was found to be between turbulent and fast fluidization. Further work is needed to estimate the reactor's pressure drop, which will significantly affect plant efficiency.
Article
Energy & Fuels
Diana Cremoncini, Guido Francesco Frate, Aldo Bischi, Lorenzo Ferrari
Summary: Redox Flow Batteries, particularly the vanadium redox flow battery, are a promising option for large-scale stationary energy storage due to their versatility and durability. This research aims to optimize the scheduling of a vanadium redox flow battery used to store energy from renewable sources, taking into account the battery's performance characteristics and degradation effects. By considering a detailed battery characterization, the optimization model provides more accurate predictions on the optimal number of cycles and revenue, compared to simpler models that assume constant efficiency and neglect capacity fade effects. The proposed model uses convex hulls and is solved as a Mixed-Integer Linear Program (MILP) to ensure global optimality.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Sebastian Schaer, Aldo Bischi, Andrea Baccioli, Umberto Desideri, Jutta Geldermann
Summary: Many arid and semi-arid regions face freshwater scarcity and rely on seawater desalination. Seawater reverse osmosis (RO) is widely used due to its efficiency and low costs, but the energy sources are often from fossil fuels. The substitution by renewable energy sources (RES) is critical, but obstacles such as volatility and cost of electrical energy storage (EES) need to be overcome.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Materials Science, Characterization & Testing
Igor Matteo Carraretto, Vincenzo Ruzzi, Filippo Lodigiani, Rosemary Colciaghi, Riccardo Simonetti, Stefano Buzzaccaro, Luca Molinaroli, Luigi Pietro Maria Colombo, Roberto Piazza, Giampaolo Manzolini
Summary: Forward osmosis is a promising desalination method that requires a detailed characterization of the thermo-physical properties of the draw agent for accurate and realistic system performance predictions.
Article
Energy & Fuels
Wang Lu, Pietro Bartocci, Alberto Abad, Aldo Bischi, Haiping Yang, Arturo Cabello, Margarita de las Obras Loscertales, Mauro Zampilli, Francesco Fantozzi
Summary: Bioenergy with Carbon Capture and Storage (BECCS) technologies play a crucial role in achieving negative CO2 emissions by removing and storing CO2 underground. Pressurized Chemical Looping Combustion (CLC) is a promising solution for implementing BECCS, which involves coupling a pressurized CLC reactor system to a turboexpander. This paper presents a methodology using Aspen Plus software for designing pressurized Chemical Looping Combustors coupled to gas turbines for power generation.
Article
Energy & Fuels
Lukas Koester, Atse Louwen, Sascha Lindig, Giampaolo Manzolini, David Moser
Summary: Daylight photoluminescence (DPL) is a novel imaging technique used for photovoltaic system inspection. This study presents a DPL-ready inverter that allows switching between different operating points of connected PV modules. An algorithm is developed to identify operating point switches in field images. The research also investigates the quantification of luminescence signal intensity in DPL images and explores its application in performance loss analysis.
Article
Energy & Fuels
Cody B. Anderson, Giovanni Picotti, Michael E. Cholette, Bruce Leslie, Theodore A. Steinberg, Giampaolo Manzolini
Summary: This study presents a novel methodology for characterizing and predicting soiling losses in concentrated solar power operations. It found that the soiling rate is influenced by seasons and the position of heliostats, and analyzed the cost composition and the impact of different cleaning strategies on the total cleaning cost.
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
