Article
Energy & Fuels
Mehrdad Aslani, Mehdi Mashayekhi, Hamed Hashemi-Dezaki, Abbas Ketabi
Summary: While the energy hub concept has various benefits, uncertainties within the system can impact decision making. Studies have focused on optimizing the operation of energy hubs while considering uncertainties, but there is a gap in research regarding robust optimal operation under different EV charging modes and integrated demand response programs. This research aims to address this gap by using robust optimization methods to account for uncertainties in renewable energy resources and electricity prices, as well as studying hybrid storage systems in the robust framework. Simulation results demonstrate cost savings by implementing integrated thermal and electrical demand response programs and utilizing electric heat pumps and hybrid storage systems. Sensitivity analyses show the advantages of the proposed method when uncertainties within the energy hub increase.
Article
Energy & Fuels
Mehrdad Aslani, Mehdi Mashayekhi, Hamed Hashemi-Dezaki, Abbas Ketabi
Summary: This paper proposes a robust optimization method and uses Monte Carlo simulation to study the optimal operation of an energy hub under different charging modes of electric vehicles. The study also explores different schemes of hybrid energy storage systems. The simulation results show that integrating thermal and electrical demand response programs and using electric heat pumps can significantly reduce the operation cost of the energy hub.
Article
Thermodynamics
Xinhui Lu, Haobin Li, Kaile Zhou, Shanlin Yang
Summary: This paper proposes an optimal load dispatch model for EH system by considering the coupling relationship of electric and thermal energy, and adopts robust optimization method to deal with the uncertainty of renewable energies (REs) and demand response (DR) programs. Simulation experiments demonstrate that the total cost of EH system can be effectively reduced by installing energy storage systems and implementing DR programs.
Article
Green & Sustainable Science & Technology
Monir Sadat AlDavood, Abolfazl Mehbodniya, Julian L. Webber, Mohammad Ensaf, Mahdi Azimian
Summary: This paper presents a new robust scheduling model for an islanded microgrid considering demand response, which can minimize the total costs of the microgrid under uncertainties.
Article
Thermodynamics
Zihao Guo, Ren Zhang, Li Wang, Shunqi Zeng, Yajun Li
Summary: This paper proposes a regional integrated energy system model considering demand response and uses an improved genetic optimization algorithm to solve the model, obtaining optimization results of load demand response and energy networks. Finally, a case study in an industrial park in Guangzhou shows that user-side demand response can reduce the total cost of the regional integrated energy system and play a role in peak shaving and filling valleys in the energy system.
APPLIED THERMAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
V. V. Thang, Thanhtung Ha, Qinhao Li, Yongjun Zhang
Summary: This paper proposes a stochastic scheduling framework for multi-energy hub systems to optimize the operation cost and reduce CO2 emissions. By modeling uncertainties and employing clustering and scenario reduction techniques, the computational burden is reduced and the system operation is optimized.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Junjie Zhong, Yong Li, Yan Wu, Yijia Cao, Zhengmao Li, Yanjian Peng, Xuebo Qiao, Yong Xu, Qian Yu, Xusheng Yang, Zuyi Li, Mohammad Shahidehpour
Summary: This paper proposes a low-carbon operation model for an energy hub (EH) by combining the distributionally robust optimization (DRO) method with the Stackelberg game. The model incorporates a bilevel single-leader-multi-follower Stackelberg game and a Kullback-Leibler (KL) divergence-based DRO model to handle the uncertainty of renewable generation in the EH. The proposed method is validated through numerical case studies.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Peng Li, Zixuan Wang, Nan Wang, Weihong Yang, Mingzhe Li, Xichao Zhou, Yunxing Yin, Jiahao Wang, Tianyu Guo
Summary: This paper focuses on the optimal operation of community integrated energy system (CIES) using integrated demand response. Different energy loads are analyzed to introduce strategies for complementary substitution and time shifting, while a stochastic robust optimal operation model is established. The proposed method effectively reduces operation costs, promotes energy supply-demand balance, and achieves economical, flexible, and efficient operation of CIES.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Asghar Iranpour Mobarakeh, Ramtin Sadeghi, Hadi Saghafi Esfahani, Majid Delshad
Summary: This research presents a two-level structure for the optimal planning and operation of an energy hub (EH) based on demand uncertainty and renewable energy resources (RES). The primary level focuses on optimal planning using stochastic-probability models, while the secondary level focuses on optimal operation. The proposed method uses a problem-solving approach in continuous and discrete space, with objectives such as determining optimal capacity and minimizing costs.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Thermodynamics
Seyyed Aliasghar Ghappani, Ali Karimi
Summary: This article proposes an energy hub structure based on ammonia fuel and other sources to supply electricity, thermal energy, and hydrogen demands. It also presents an optimal stochastic framework for the daily operation of this energy hub, considering demand response programs. Case studies show that the proposed structure with ammonia fuel reduces operating costs and increases electricity sales compared to the base case.
Article
Engineering, Electrical & Electronic
Jing Wang, Haijun Xing, Huaxin Wang, Baojiang Xie, Yangfan Luo
Summary: In this study, an optimal operation model and strategy considering integrated demand response (IDR) and exergy efficiency in the regional integrated energy system (RIES) is proposed. The economic cost and exergy efficiency of RIES are analyzed, and a model considering IDR is established. The multi-objective optimization model of RIES is established to minimize economic cost and maximize exergy efficiency. The results show that comprehensive demand response can effectively reduce system cost and improve exergy efficiency on the demand side.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Yu Huang, Peng Ding, Yutao Wang, Shuqin Li, Kai Yang, Yongling Li
Summary: The study established an optimal operation model to address the issue of low participation in demand response programs, achieving the goal of increased revenue on the supply side and decreased costs on the demand side.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Environmental Sciences
Gal Perelman, Avi Ostfeld, Barak Fishbain
Summary: The operation of water distribution systems (WDS) is an energy-intensive process that faces constraints such as consumer demands, water quality, and pressure domains. Finding an operational strategy that meets these constraints while minimizing energy costs is the primary objective for water utilities. Robust optimization (RO) is a promising approach for optimization under uncertainty, and this study presents an RO-based method for optimizing pump scheduling considering uncertainties in consumer demands and pumping costs.
Article
Thermodynamics
Javad Salehi, Amin Namvar, Farhad Samadi Gazijahani, Miadreza Shafie-khah, Joao P. S. Catalao
Summary: Natural gas is considered a key player in the transition to a lower-carbon economy, serving as an alternative to coal and a backup resource to intermittent renewable energy sources. An innovative model was proposed to optimally manage electricity and natural gas grids, utilizing various technologies to reduce operational costs and alleviate gas network congestion while improving energy efficiency. The model incorporates demand response programs and Power-to-X technologies, demonstrating significant reductions in operation costs and improved performance in addressing network congestions.
Article
Construction & Building Technology
Abbas Dalimi-Asl, Shahram Javadi, Amir Ahmarinejad, Payam Rabbanifar
Summary: This study presents a multi-objective planning approach based on stochastic-probability optimization algorithms for energy hubs, addressing technical, economic, and environmental challenges. By considering uncertainties such as electricity carrier prices, renewable power generation, and electrical load uncertainty, the proposed method reduces the total operation cost in different scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2023)
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.