Article
Green & Sustainable Science & Technology
Swaraj Sanjay Deshmukh, Joshua M. Pearce
Summary: This study investigates the energy related aspects of developing electric vehicle (EV) charging stations powered with solar photovoltaic (PV) canopies built on the parking infrastructure of large-scale retailers. The results show that Walmart could potentially deploy a significant amount of solar canopies in the U.S., providing solar electricity for a large number of EV charging stations for their customers, covering 90% of the American public living within 15 miles of a Walmart.
Article
Energy & Fuels
Saad Ullah Khan, Khawaja Khalid Mehmood, Zunaib Maqsood Haider, Muhammad Kashif Rafique, Muhammad Omer Khan, Chul-Hwan Kim
Summary: This paper proposes a coordination method for multiple electric vehicle (EV) aggregators to smooth the system load profile by adjusting peak demands and charging during off-peak periods. The results show that the system load profile is smoothed under peak shaving and valley filling goals while ensuring EVs are fully charged before departure.
Article
Energy & Fuels
Mohamad K. Daryabari, Reza Keypour, Hessam Golmohamadi
Summary: This paper proposes a novel structure for parking lot microgrids to provide demand flexibility for power systems using the power storage capacity of electric vehicles. By utilizing smart charging stations and a data-driven approach for classifying electric vehicles and determining optimal procurement strategies, the microgrid aims to enhance flexibility and profitability in the Iran Power Grid through robust optimization and mixed integer linear programming techniques.
Article
Construction & Building Technology
Yanchong Zheng, Ziyun Shao, Linni Jian
Summary: The user-oriented V2G scheme with multiple operation modes is proposed to increase EVs' participation in coordinated charging, which varies depending on individual users' preferences and charging urgency.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Engineering, Electrical & Electronic
Hilmi Cihan Guldorum, Ibrahim Sengor, Ozan Erdinc
Summary: This study investigates the integration of electric vehicles and renewable energy sources into power systems, particularly focusing on the role of demand response strategies in this integration. It also addresses the issue of comfort for EV owners. A model using mixed-integer linear programming and a machine learning-based structure is developed to mitigate comfort violation during vehicle-to-grid and peak load limitation operations. The results highlight the importance of vehicle-to-vehicle transactions and PV generation in minimizing comfort violation during demand response operations.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Computer Science, Information Systems
Usama Bin Irshad, Mohammad Sohrab Hasan Nizami, Sohaib Rafique, M. Jahangir Hossain, Subhas Chandra Mukhopadhyay
Summary: This article proposes a method for estimating the size of a stationary BESS for parking lots, considering the intermittent charging demand of EVs and using nonlinear optimization to minimize the capital and operational costs. The approach ensures maximum utilization of the BESS, avoids over/undersizing, reduces operational costs, and maintains system reliability, as demonstrated through simulations with real travel survey and car park occupancy data.
IEEE SYSTEMS JOURNAL
(2021)
Article
Energy & Fuels
Mahdi Ghafoori, Moatassem Abdallah, Serena Kim
Summary: This study presents the development of a system that can predict building electricity demand and determine optimal schedules for charging and discharging electric vehicles to minimize peak demand. The system uses machine learning models to predict electrical power demand and an optimization model to identify the best charging and discharging schedules. The implementation of this system provides practical solutions for managing electricity demand in commercial buildings.
Article
Construction & Building Technology
Khalil Gorgani Firouzjah
Summary: This paper addresses the issue of charging and discharging electric vehicles in public parking lots and proposes a controlled scheduling algorithm. It compares the effectiveness of the proposed strategy with two uncontrolled strategies. By considering uncertainty factors, a comprehensive database is generated and evaluated through financial analysis.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Energy & Fuels
Abdullah Kuersat Aktar, Akin Tascikaraoglu, Sirri Sunay Gurleyuk, Joao P. S. Catalao
Summary: The future planning of energy supply and transportation requires the consideration of various stakeholders, including institutions, distribution companies, and new technology developers. Their collaboration is crucial for anticipating and addressing potential challenges and reaping mutual benefits.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
Gilles Van Kriekinge, Cedric De Cauwer, Nikolaos Sapountzoglou, Thierry Coosemans, Maarten Messagie
Summary: This paper investigates uni- and bi-directional electric vehicle charging schedulers using model predictive control algorithms and different charging strategies to minimize electricity bills and peak powers. Testing on real charging events from a charging location in Brussels, the results show that bi-directional charging performs the best.
Article
Energy & Fuels
Zekun Guo, Bozheng Li, Gareth Taylor, Xin Zhang
Summary: To achieve net-zero emissions in aviation, electric propulsion system is seen as an attractive technology. This study develops a bi-objective infrastructure planning framework for airport microgrid to accommodate electric vehicles and electric aircraft. The impact of vehicle-to-grid (V2G) on the microgrid is assessed, and different charging strategies for electric aircraft are compared. The results show that adopting V2G strategy can improve the microgrid's economic performance.
Article
Transportation Science & Technology
Hossein Nasr Esfahani, Zhaocai Liu, Ziqi Song
Summary: As EVs become more prevalent, the use of bidirectional charging lanes can optimize transportation and power systems by utilizing EVs as additional energy storage sources. This study introduces a new user equilibrium model to depict the equilibrium conditions in a road network with bidirectional charging lanes. By formulating the optimization problem, the study demonstrates that bidirectional charging lanes have the potential to reduce peak load and charging costs associated with EVs. The developed meta-heuristic solution algorithm based on gray wolf optimizer and manifold suboptimization efficiently solves the model and provides numerical evidence for the effectiveness of this approach.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Electrical & Electronic
Yee Ting Chai, Hang Seng Che, ChiaKwang Tan, Wooi-Nee Tan, Sook-Chin Yip, Ming-Tao Gan
Summary: A two-stage optimization technique is proposed in this paper to determine the charging and discharging schedule for EVs participating in a V2G program at an office building. The proposed model focuses on the travel convenience of EV owners by providing them with two V2G options. It is able to adjust the EV charging or discharging in real-time and maintain the EV SOC as planned when prediction deviation occurs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Mahyar Alinejad, Omid Rezaei, Reza Habibifar, Mahdi Azimian
Summary: This paper presents an optimal scheduling scheme for an intelligent parking lot, considering the random decisions of EV drivers and the V2V and V2G energy transfer modes. The proposed algorithm improves the profits of IPL and EV owners and reduces the demand for energy from the distribution system during peak times.
Article
Automation & Control Systems
Bo Zeng, Jiahuan Feng, Nian Liu, Yixian Liu
Summary: This study proposes a new framework for optimal allocation of parking lot charging infrastructure to facilitate the efficient integration of plug-in electric vehicles. It introduces a regret-matching technique to model the bounded rationality of PEV owners in choosing charging options, considering both endogenous incentive policy uncertainties and exogenous PEV demand randomness.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Dimitrios Thomas, Jalal Kazempour, Athanasios Papakonstantinou, Pierre Pinson, Olivier Deblecker, Christos S. Ioakimidis
IEEE TRANSACTIONS ON POWER SYSTEMS
(2020)
Article
Thermodynamics
Konstantinos N. Genikomsakis, Nikolaos-Fivos Galatoulas, Christos S. Ioakimidis
Summary: This paper discusses the potential of holiday cycling as a mode of tourism transportation, emphasizing the importance of hotels providing e-bike rental services based on renewable energy sources to enhance environmental friendliness. The research findings show that this service has good techno-economic feasibility in different scenarios, making it a promising business investment venture.
Article
Energy & Fuels
Ali Bagheri, Konstantinos N. Genikomsakis, Veronique Feldheim, Christos S. Ioakimidis
Summary: Data-driven models are widely used for energy assessment in buildings and districts, but the uncertainty of estimated parameters in resistance-capacitance models remains a challenge. Sensitivity analysis of parameters with respect to different geometric characteristics can examine model accuracy. Results show that the 4R3C model can accurately estimate indoor temperature.
Article
Green & Sustainable Science & Technology
Tunzeel Iqbal, Shahid Iqbal, Fozia Batool, Dimitrios Thomas, Malik Muhammad Hassnain Iqbal
Summary: In this study, an adsorption process utilizing a novel hematite-based nanomaterial loaded onto biochar was used for the remediation of toxic cadmium ions from aqueous media. Experimental results showed that the hematite-loaded Saccharum munja biochar and Saccharum munja biochar were more effective in Cd(II) removal compared to raw Saccharum munja. The thermodynamic studies indicated the adsorption process was feasible, spontaneous, and endothermic, with physiosorption being the predominant mechanism.
Article
Energy & Fuels
Paulina Rodriguez Fiscal, Rallou Taratori, Marie Abigail Pacho, Christos S. Ioakimidis, Sesil Koutra
Summary: The literature focuses on planning smart solutions to address rapid urbanization issues in developing countries, highlighting the importance of adaptative patterns for global climate change pressures and uncontrolled urban growth.
Review
Green & Sustainable Science & Technology
Rallou Taratori, Paulina Rodriguez-Fiscal, Marie Abigail Pacho, Sesil Koutra, Montserrat Pareja-Eastaway, Dimitrios Thomas
Summary: Despite the increasing interest in smart city initiatives worldwide, there is a lack of literature on governmental theories and managerial perspectives of city planning. This paper points out the need for more comprehensive analyses on methodological investigation, identification, and adoption of the most appropriate governance models.
Article
Engineering, Chemical
Christos S. Ioakimidis, Hana Gerbelova, Ali Bagheri, Sesil Koutra, Nikolaos Koukouzas
Summary: This study presents a roadmap for modeling carbon capture and storage technology in 2010, analyzing different scenarios with varying taxation and CO2 permit prices in the context of Greek national plans. The results suggest that implementing CCS technology in new power plants from 2010 onwards could lead to a smoother transition towards a lignite-free economy in Greece.
Article
Energy & Fuels
Dimitrios Thomas, Ioannis Kounelis, Evangelos Kotsakis, Antonio De Paola, Gianluca Fulli
Summary: This paper proposes a local market framework for allocating storage rights, which allows for efficient dispatch of storage in real-time markets, thus increasing the benefits for market participants and reducing overall system costs.
JOURNAL OF ENERGY STORAGE
(2022)
Review
Environmental Studies
Sesil Koutra, Christos S. Ioakimidis
Summary: In the digitalized era, artificial intelligence and Machine Learning are gaining interest due to their applications in various fields. This work presents a comprehensive review on the opportunities and constraints of using Machine Learning in urban planning strategies. It discusses the potential and complexities of applying Machine Learning to urban environments based on theoretical views and practical analyses.
Article
Engineering, Electrical & Electronic
Antonio De Paola, Dimitrios Thomas, Alexandros Paspatis, Edmund Widl, Antonios Marinopoulos, Evangelos Kotsakis, Alkistis Kontou, Panos Kotsampopoulos, Nikolaos Hatziargyriou
Summary: This article presents a new method for the open-source design and documentation of benchmark network models. The method includes different phases of model development, a conceptual framework for model documentation based on holistic test description and PreCISE paradigms, and practical examples on how to translate the conceptual framework into a complete model description. The method is validated through a complete model documentation for a developed low-voltage network.
IEEE OPEN JOURNAL OF THE INDUSTRIAL ELECTRONICS SOCIETY
(2023)
Article
Construction & Building Technology
Ali Bagheri, Konstantinos N. Genikomsakis, Christos S. Ioakimidis
Summary: This paper develops a hierarchy of thermal models with increasing complexity to identify the simplest structure that can effectively represent the thermal behavior of a building. By comparing the model outputs to TRNSYS simulations and measurements, the best structure is selected. The proposed models are able to accurately predict the indoor temperature, peak power, and total heat demand.
Article
Construction & Building Technology
Ali Bagheri, Konstantinos N. Genikomsakis, Sesil Koutra, Vasileios Sakellariou, Christos S. Ioakimidis
Summary: EU directives and commitments are driving building owners and stakeholders to adopt renewable energy sources for net zero energy buildings, but high renovation costs and expensive technology installations are hindering small to medium-sized buildings. Sharing computational and data storage resources could be an alternative approach to smart buildings and cities.
Article
Environmental Studies
Sesil Koutra, Noemie Denayer, Nikolaos-Fivos Galatoulas, Vincent Becue, Christos S. Ioakimidis
Summary: Transforming cities for cleaner energy is a significant global initiative to address challenges such as rapid urbanization, resource depletion, climate change, and post-industrial impacts. This study introduces a comprehensive toolkit for urban planning towards energy transition, validated through a case study in Cuesmes, Belgium. The research also explores the feasibility of the zero-energy concept at an urban scale, building on previous empirical analyses.
INTERNATIONAL JOURNAL OF URBAN SUSTAINABLE DEVELOPMENT
(2021)
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.
