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Thermodynamics
Wenqiang Yang, Xinxin Zhu, Qinge Xiao, Zhile Yang
Summary: This paper proposes an improved version of the multi-objective marine predator algorithm (IMOMPA) for solving the optimization of multi-objective dynamic economic-grid fluctuation dispatch (MODEGD). The IMOMPA algorithm improves population diversity, convergence speed, and global search ability. Numerical experiments on benchmark functions and generation units demonstrate the superiority of the IMOMPA algorithm, and plug-in electric vehicles (PEVs) connected to the grid (V2G) can help mitigate grid fluctuations.
Article
Computer Science, Artificial Intelligence
Xinlin Xu, Zhongbo Hu, Qinghua Su, Zenggang Xiong, Mianfang Liu
Summary: The paper introduces a multi-objective learning backtracking search algorithm (MOLBSA) to solve the environmental/economic dispatch (EED) problem, with two novel learning strategies designed: leader-choosing strategy and leader-guiding strategy. Simulation results demonstrate the capability of MOLBSA in generating well-distributed and high-quality approximation of true Pareto front for the EED problem.
Article
Thermodynamics
Zhi-Feng Liu, Ling-Ling Li, Yu-Wei Liu, Jia-Qi Liu, Heng-Yi Li, Qiang Shen
Summary: This study developed a mathematical model for HDEED considering renewable energy and proposed a solving approach based on an enhanced moth-flame optimization algorithm, resulting in a reduction in fuel costs and pollutant emissions, and an increase in the utilization of renewable energy.
Article
Green & Sustainable Science & Technology
Lei Zhu, Hao Ren, Mostafa Habibi, Khidhair Jasim Mohammed, Mohamed Amine Khadimallah
Summary: This paper proposes a novel swarm-based metaheuristic method called Chimp Optimization Algorithm (ChOA) to tackle the environmental, economic dispatch issue and reducing the waste nonrenewable materials. The result of ChOA is compared with other benchmark algorithms to confirm its efficiency, showing superior performance in both single- and multi-objective optimization.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Electrical & Electronic
Aamir Ali, Ghulam Abbas, Muhammad Usman Keerio, Mohsin Ali Koondhar, Kiran Chandni, Sohrab Mirsaeidi
Summary: This paper proposes a hybrid two-phase algorithm for solving the OPF problem, which combines single and multi-objective evolutionary algorithms to achieve better convergence and evenly distributed PF. The effectiveness of the algorithm is demonstrated through validation on the IEEE 30 and 300-bus network.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2023)
Article
Computer Science, Information Systems
Kai Zhang, Chaonan Shen, Juanjuan He, Gary G. Yen
Summary: The proposed MMO-EvoKnee algorithm incorporates MCDM strategy to efficiently search for a complete set of global knee solutions for MMOPs. It outperforms existing state-of-the-art MMOEAs and provides decision makers with well-converged alternative solutions.
INFORMATION SCIENCES
(2021)
Article
Energy & Fuels
Yixuan Chen, Yunhe Hou
Summary: This paper proposes a novel multi-timescale multi-objective economic-environmental dispatch (MTMO-EED) method to solve the fast computation or good balancedilemma. The method includes a new framework with intra-day offline-online coordination and a new multi-objective algorithm to improve computational efficiency. Case studies on a modified IEEE 39-bus system validate the effectiveness of the proposed method.
Article
Energy & Fuels
Masoud Dashtdar, Aymen Flah, Seyed Mohammad Sadegh Hosseinimoghadam, Ch. Rami Reddy, Hossam Kotb, Kareem M. AboRas, Elzbieta Jasinska, Michal Jasinski
Summary: This study uses a hybrid firefly algorithm and genetic algorithm to address the problem of environmental economic dispatch in power plants, aiming to reduce operating costs and environmental pollution. The proposed algorithm combines the advantages of these two optimization algorithms and improves the uniformity of the Pareto curve. Experimental results on a real system demonstrate the good performance of the algorithm compared to other methods.
Article
Computer Science, Artificial Intelligence
Zhi-Xuan Zhang, Wei-Neng Chen, Xiao-Min Hu
Summary: Portfolio optimization is a crucial model for financial decision making, but it becomes more challenging when considering real-world constraints, especially cardinality constraints. This study proposes a knowledge-based constructive estimation of distribution algorithm (KC-EDA) to solve the mixed-integer quadratic multi-objective optimization problem. The KC-EDA incorporates a hybrid design of ACO and EDA, a knowledge accumulation mechanism, and a constructive approach to effectively guide asset selection, utilize historical information, and construct portfolios under constraints. Experimental results on real datasets demonstrate the effectiveness of KC-EDA in solving portfolio optimization problems with cardinality constraints.
APPLIED SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Hossein Nourianfar, Hamdi Abdi
Summary: Due to environmental concerns and high penetration of wind power and electric vehicles (EVs), reducing generation costs and emissions while coordinating EV charging and addressing wind power uncertainty are challenging issues in power system control. This paper proposes an enhanced multi-objective exchange market algorithm to solve the multi-objective dynamic economic emission dispatch problem integrated with EVs and wind farms. The algorithm introduces a novel point-to-point distance technique for finding Pareto front solutions and proposes a smart strategy for charging and discharging EVs to smooth the load curve. Simulation results show that the proposed method effectively extracts the Pareto front solutions with uniformity and diversity. The presence of EVs and the application of the smart strategy lead to significant reductions in operation costs and emissions, as well as improvements in load factors.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
V. P. Sakthivel, M. Suman, P. D. Sathya
Summary: This paper proposes a new multi-objective squirrel search algorithm to solve the combined economic and environmental power dispatch problem, which generates non-dominated solutions by integrating squirrel search algorithm and Pareto-dominance principle. The algorithm uses an external elitist depository mechanism and a fuzzy decision-making strategy, and also solves the power dispatch problem using a weighted sum approach. Through performance testing on complex test systems, it is confirmed that the algorithm achieves a better trade-off between fuel cost and emission objectives.
APPLIED SOFT COMPUTING
(2021)
Article
Biotechnology & Applied Microbiology
S. D. Sundarsingh Jebaseelan, N. B. Muthu Selvan, C. Kumar, A. Kalaimurugan, A. Srujana, C. N. Ravi
Summary: This paper addresses the optimization problem of reducing both emission and generation cost in the thermal power plant industry. Intelligent algorithms are utilized to solve these practical problems, with a hybrid approach of firefly algorithm and differential evolution technique being adopted for constrained emission minimization and cost minimization. The aim of the research work is to reduce the carbon foot print and generation cost of the power system.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2021)
Article
Engineering, Electrical & Electronic
Yuanzheng Li, Jingjing Huang, Yun Liu, Zhixian Ni, Yu Shen, Wei Hu, Lei Wu
Summary: This paper proposes a multi-objective economic dispatch model to tackle the economic dispatch problem in a high wind power penetration environment. The model considers three indices: generation cost, upside potential, and downside risk, and uses a group search optimizer for solving. The optimal solution is selected using a fuzzy decision-making method. Case studies demonstrate the effectiveness of the proposed model and algorithm.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Multidisciplinary Sciences
Ning Li, Guo Zhou, Yongquan Zhou, Wu Deng, Qifang Luo
Summary: This paper studies the multi-objective optimal power flow (MOOPF) problem with optimization objectives of generation cost, emission, real power loss, and voltage deviation. Three renewable energy sources, wind energy, solar energy, and tidal energy, are introduced. Weibull, lognormal, and Gumbel probability distributions are used to calculate the instability and intermittency of the renewable energy sources. The proposed multi-objective pathfinder algorithm (MOPFA) based on elite dominance and crowding distance outperforms other algorithms in terms of optimization accuracy and speed.
SCIENTIFIC REPORTS
(2023)
Article
Mathematics
Mokhtar Said, Ali M. El-Rifaie, Mohamed A. Tolba, Essam H. Houssein, Sanchari Deb
Summary: Economic Load Dispatch is a critical issue in power engineering, aiming to minimize production costs and reduce emissions. The Chameleon Swarm Algorithm showed promising performance in addressing this problem.
Article
Engineering, Electrical & Electronic
Junpeng Zhan, Q. H. Wu, Chuangxin Guo, Xiaoxin Zhou
IEEE TRANSACTIONS ON POWER SYSTEMS
(2015)
Article
Engineering, Electrical & Electronic
Junpeng Zhan, Q. H. Wu, Chuangxin Guo, Xiaoxin Zhou
IEEE TRANSACTIONS ON POWER SYSTEMS
(2015)
Article
Engineering, Electrical & Electronic
Junpeng Zhan, C. Y. Chung, Alireza Zare
IEEE TRANSACTIONS ON POWER SYSTEMS
(2017)
Article
Engineering, Electrical & Electronic
Yunfeng Wen, Junpeng Zhan, C. Y. Chung, Wenyuan Li
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Alireza Zare, C. Y. Chung, Junpeng Zhan, Sherif Omar Faried
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
Article
Engineering, Electrical & Electronic
Junpeng Zhan, Weijia Liu, C. Y. Chung
IEEE TRANSACTIONS ON POWER SYSTEMS
(2019)
Article
Engineering, Electrical & Electronic
L. L. Zhang, M. S. Li, T. Y. Ji, Q. H. Wu, L. Jiang, J. P. Zhan
IEEE TRANSACTIONS ON POWER DELIVERY
(2014)
Article
Engineering, Electrical & Electronic
J. P. Zhan, Q. H. Wu, C. X. Guo, X. X. Zhou
IEEE TRANSACTIONS ON POWER SYSTEMS
(2014)
Article
Energy & Fuels
Junpeng Zhan, Osama Aslam Ansari, Weijia Liu, C. Y. Chung
Article
Engineering, Electrical & Electronic
Weijia Liu, Junpeng Zhan, C. Y. Chung
IEEE TRANSACTIONS ON POWER SYSTEMS
(2019)
Article
Green & Sustainable Science & Technology
Weijia Liu, Junpeng Zhan, C. Y. Chung, Yang Li
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2019)
Article
Engineering, Electrical & Electronic
Weijia Liu, Junpeng Zhan, C. Y. Chung, Lei Sun
IEEE TRANSACTIONS ON POWER SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Junpeng Zhan, Weijia Liu, C. Y. Chung, Jiajia Yang
IEEE TRANSACTIONS ON SMART GRID
(2020)
Article
Engineering, Electrical & Electronic
Jiajia Yang, Zhao Yang Dong, Fushuan Wen, Qixin Chen, Fengji Luo, Weijia Liu, Junpeng Zhan
IEEE TRANSACTIONS ON SMART GRID
(2020)
Proceedings Paper
Energy & Fuels
Shiqi Zhang, Amirthagunaraj Yogarathinam, Junpeng Zhan, Meng Yue, Guang Lin
2020 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM)
(2020)
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.
