Article
Energy & Fuels
Seyed Alireza Alavi Matin, Seyed Amir Mansouri, Mohammad Bayat, Ahmad Rezaee Jordehi, Pouria Radmehr
Summary: This paper proposes a dynamic model for multi-microgrids maintenance planning over a 10-year period, taking into account daily operating conditions. The results demonstrate that maintenance services can significantly reduce operating costs, distribution feeder reconfiguration can reduce maintenance costs and operating costs, and coordinated operation of storage systems and demand response programs can reduce operating costs.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Green & Sustainable Science & Technology
Mahdi Mehrtash, Florin Capitanescu, Per Kvols Heiselberg, Thomas Gibon
Summary: This paper introduces a new bi-objective optimization model for sizing key devices in zero energy buildings, considering environmental impacts and prioritizing energy storage. The solution relies on McCormick relaxation linearization and an augmented epsilon-constraint method to select the optimal device size.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Seyed Babak Ebrahimi, Ehsan Bagheri
Summary: This study designs a multi-echelon network for oil and gas supply chain and formulates a biobjective mathematical model to optimize profit and reliability. The proposed model is validated through a real-world case study and sensitivity analysis, demonstrating its effectiveness and feasibility.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Huali Sun, Yang Wang, Yaofeng Xue
Summary: This paper presents a bi-objective robust optimization model for strategic and operational response in emergency situations, considering uncertainties in facility location, resource allocation, and casualty transportation plans. The model aims to minimize the sum of ISS for all casualties and total system costs, while maximizing the transport number of casualties and satisfaction of supplies demand. Through robust optimization and case studies based on the Yushu Earthquake, the feasibility and validity of the model is demonstrated, along with sensitivity analyses to balance optimization and robustness.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Civil
Weixuan Shi, Nengmin Wang, Meng Zhang, Bin Jiang
Summary: The logistics industry is a major contributor to global carbon emissions and energy consumption. This study introduces cooperative logistics and split delivery as effective methods for reducing emissions and improving efficiency. By integrating decentralised cooperation and split delivery, this research offers a new approach to pollution routing problems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Energy & Fuels
Regina Lamedica, Alessandro Ruvio, Enrico Tanzi, Laura Palagi
Summary: The paper presents a methodology for determining the optimal size and position of an energy storage system (ESS) in a railway line using supercapacitors and considering economic benefits. A bi-objective nonlinear mathematical model is used to solve the problem of ESS siting and sizing, with the constraint of siting at electrical substations. The Pareto frontiers are obtained using a fully enumerative algorithm, and economic analysis is conducted based on the purchase price of energy. A real Italian underground railway line is simulated to estimate the power flow between trains, considering commercially available energy storage systems. A good Pareto solution shows an energy saving of 1730 kWh, equivalent to approximately 11% profit each year for the case study.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Kexing Lai, Xuan Wu, Antonio J. Conejo
Summary: This paper presents an optimization model for distribution system planners to determine the location and size of battery energy storage systems (BESSs) and isolation devices. The model aims to improve system reliability and generate revenue through energy arbitrage. It fills a research gap by addressing the optimal coordination of BESS and isolation device siting. The proposed model is successfully applied in a real-world case study.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Green & Sustainable Science & Technology
Seyed Zeinab Aliahmadi, Farnaz Barzinpour, Mir Saman Pishvaee
Summary: In this study, a bi-objective vehicle routing mathematical model was proposed and solved using Non-dominated Sorting Genetic Algorithm II, which achieved significant optimization results in terms of total economic cost and total time for waste collection.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Operations Research & Management Science
Alexandre D. Jesus, Luis Paquete, Arnaud Liefooghe
Summary: The study presents a theoretical model that characterizes the optimal trade-off between runtime and solution quality in bi-objective optimization, which approximates the behavior of an optimal model and can improve the anytime behavior of an epsilon-constraint algorithm.
JOURNAL OF GLOBAL OPTIMIZATION
(2021)
Article
Green & Sustainable Science & Technology
Hooman Khaloie, Mojgan Mollahassani-Pour, Amjad Anvari-Moghaddam
Summary: The coordinated operation of various energy sources, including a Concentrating Solar Power Plant (CSPP) in a Hybrid Power Producer (HPP) alongside a wind power station, Compressed Air Energy Storage (CAES) unit, and Demand Response Provider (DRP), has been studied for optimal participation in Day-Ahead (DA) and intraday electricity markets. The use of Conditional Value-at-Risk (CVaR) based on the epsilon-constraint technique has been shown to improve risk-averse strategies and system profitability.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Thermodynamics
Ozlem Karsu, Ayse Selin Kocaman
Summary: This study proposes a bi-objective framework to help decision makers investigate trade-offs between conflicting criteria in rural electrification, considering two different methods to find Pareto solutions.
Article
Automation & Control Systems
Y. J. Qin, J. H. Zheng, Q. H. Wu
Summary: This study presents a multi-objective distribution network expansion planning model considering distributed generation, and develops a preference-based ε-constraint method for optimization and decision-making. Simulation studies demonstrate the effectiveness of the improved model and method.
CONTROL ENGINEERING PRACTICE
(2021)
Article
Automation & Control Systems
Binghai Zhou, Jingrao Bian
Summary: This paper proposes a sustainable robotic disassembly line balancing problem and applies the epsilon constraint algorithm and the modified bi-objective Harris Hawks optimization algorithm to solve the problem. The results show that the proposed algorithms are effective and superior in improving disassembly efficiency and environmental friendliness.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Engineering, Chemical
Eduardo Carrera, Catherine Azzaro-Pantel
Summary: This study proposes a methodological design framework for Hydrogen and Methane Supply Chains based on Power-to-Gas systems, considering specific hydrogen demand for electromobility and performing bi-objective optimization. The approach uses Mixed Integer Linear Programming with augmented epsilon constraint to minimize Total Annual Cost and greenhouse gas emissions related to the entire HMSC over the study period.
CHEMICAL ENGINEERING SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Binghai Zhou, Jingrao Bian
Summary: This paper investigates the resource-constraint mixed-model multi-manned disassembly line balancing problem and proposes a mixed-integer programming model and a self-adaptive salp swarm algorithm with sine cosine algorithm. Computational experiments show that the algorithm achieves superior results in multiple evaluation indexes and demonstrates practicality.
APPLIED SOFT COMPUTING
(2022)
Article
Chemistry, Physical
Yun Wang, Milad Kazemi, Sayyad Nojavan, Kittisak Jermsittiparsert
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2020)
Article
Green & Sustainable Science & Technology
Dongmin Yu, Abdol Ghaffar Ebadi, Kittisak Jermsittiparsert, Noor H. Jabarullah, Marina Vladimirovna Vasiljeva, Sayyad Nojavan
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2020)
Article
Chemistry, Physical
Sayyad Nojavan, Alireza Akbari-Dibavar, Amir Farahmand-Zahed, Kazem Zare
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2020)
Article
Chemistry, Physical
Qun Guo, Sayyad Nojavan, Shi Lei, Xiaodan Liang
Summary: This paper proposes a novel robust energy management approach for multi-energy industrial parks, integrating various energy technologies to enhance energy supply flexibility and efficiency, while minimizing total operation costs.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Chemistry, Physical
Tingting Cai, Mingyu Dong, Huanan Liu, Sayyad Nojavan
Summary: The penetration of renewable energy sources in power systems is increasing globally to address current challenges, especially environmental issues. Utilizing energy storage systems with renewable energy sources and demand response programs can help cope with uncertain and intermittent power outputs. Minimizing worst-case costs or regrets is important in evaluating system operations under uncertain parameters.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Green & Sustainable Science & Technology
Qun Guo, Sayyad Nojavan, Shi Lei, Xiaodan Liang
Summary: The unsustainable and uncontrolled development of urbanization has led to increased environmental challenges worldwide. Constructing industrial energy parks may be an appropriate solution to reduce carbon dioxide emissions and optimize energy sources, but accurate techno-economic-environmental assessment and coordinated operations are challenging tasks.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Chemistry, Physical
Qun Guo, Yuxuan Chen, Yunbao Xu, Sayyad Nojavan, Hasan Bagherzadeh, Esmaeil Valipour
Summary: The peer-to-peer (P2P) energy trading strategy is a hopeful solution for dealing with high electricity costs during peak demand periods in residential areas. In this study, three buildings, two with solar panels and one with a hydrogen source, are considered and the system operator is investigated under uncertain conditions. By utilizing P2P energy trading and renewable energy resources, reliable electricity can be provided to customers in remote areas.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Energy & Fuels
Xinghua Guo, Qun Guo, Esmaeil Valipour, Sayyad Nojavan
Summary: Due to the increasing level of greenhouse gas emissions, it is crucial for the power industry to utilize renewable energy resources and environmentally friendly methods for electricity generation. An integrated biomass-concentrated solar (IBCS) system, combined with biomass boiler and thermal storage, can generate dispatchable power and improve the principles of renewable-based networks. This study provides a day-ahead and intra-day dispatch procedure for the IBCS system, aiming to maximize system profit by manipulating the association of system components in a cooperative manner. The stochastic dominance (SD) method is used to assess the system performance and address uncertainties. The results show that the proposed dispatch procedure is profitable for the system operator.
Article
Energy & Fuels
Peiru Jian, Wenyao Hu, Esmaeil Valipour, Sayyad Nojavan
Summary: This study explores the application of an integrated biomass-concentrated solar system in the electric power industry to maximize system profitability. By considering the system function under risk-averse and risk-neutral strategies, simulation results demonstrate that the proposed dispatch model can achieve considerable profit.
Article
Chemistry, Physical
Jing Jiang, Liwei Zhang, Xuan Wen, Esmaeil Valipour, Sayyad Nojavan
Summary: This paper proposes an optimal scheduling method using an energy hub system to increase the reliability of power systems, reducing operational costs and risk levels by considering load shifting strategies and demand response programs.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Energy & Fuels
Kasra Saberi-Beglar, Kazem Zare, Heresh Seyedi, Mousa Marzband, Sayyad Nojavan
Summary: This paper investigates the integration of combined cooling, heat and power (CCHP) system and electric vehicle parking lot (EVPL) with photovoltaic (PV) technology as renewable energy (RE). Stochastic programming and demand response are used to optimize the system's operation and reduce carbon emissions. A risk-aversion strategy is implemented to mitigate the risks associated with uncertainties. The results show that demand response can reduce operation costs by 5% in summer and 8% in winter.
Article
Energy & Fuels
Esmaeil Valipour, Ramin Nourollahi, Kamran Taghizad-Tavana, Sayyad Nojavan, As'ad Alizadeh
Summary: This paper examines the importance of P2P energy transaction with on-site flexibility resources for an industrial site in Norway. The study analyzes the effects of P2P energy transaction under uncertain parameters and applies a downside risk constraint approach for risk assessment.
Review
Energy & Fuels
Kamran Taghizad-Tavana, As'ad Alizadeh, Mohsen Ghanbari-Ghalehjoughi, Sayyad Nojavan
Summary: With the rapid expansion of electric vehicles, they are expected to be a major contributor to transportation. The increasing use of fossil fuels has led to greenhouse gas emissions, making it crucial to achieve sustainable transportation. Countries around the world are implementing long-term plans and policies to replace internal combustion vehicles with EVs and generate electricity using renewable energy sources, resulting in an increase in charging stations.
Review
Green & Sustainable Science & Technology
Kamran Taghizad-Tavana, Mohsen Ghanbari-Ghalehjoughi, Nazila Razzaghi-Asl, Sayyad Nojavan, As'ad Alizadeh
Summary: The role of smart machines in our lives is increasingly valuable, especially with the advancement of IoT technologies. Implementing IoT-based smart homes has become a prominent research field, focusing on the remote control of home appliances. The creation of rules and standards is crucial to prevent incompatibilities between devices. Energy consumption management, privacy and security, and smart homes are vital for the evolution of smart cities.
Article
Green & Sustainable Science & Technology
Lumin Shi, Man-Wen Tian, As'ad Alizadeh, Ardashir Mohammadzadeh, Sayyad Nojavan
Summary: This research investigates the optimal management of electric and heat energies in a hybrid energy system, addressing the uncertainties in renewable generation, demand levels, and energy prices. A comprehensive information-gap decision theory (IGDT) approach is proposed to deal with these overlapping uncertainties and derive risk-averse and risk-seeking strategies. The problem is modeled as mixed-integer linear programming and solved using the GAMS optimization package. Simulation results show the impact of uncertainty on operating costs from the perspectives of risk-seeking and risk-averse decision makers.
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.
