Article
Thermodynamics
Zhongbo Hu, Canyun Dai, Qinghua Su
Summary: In this paper, an adaptive backtracking search optimization algorithm (DABSA) is proposed for solving the dynamic economic dispatch problem with valve-point effect (DED_vpe). DABSA utilizes a dual-learning strategy and an adaptive parameter control mechanism to improve solution accuracy and overcome premature convergence. Experimental results demonstrate that DABSA is competitive in terms of low fuel costs and high robustness.
Article
Thermodynamics
Canyun Dai, Zhongbo Hu, Qinghua Su
Summary: This paper proposes an adaptive hybrid backtracking search optimization algorithm (AHBSA) for solving dynamic economic dispatch with valve-point effects (DED_vpe). By designing a suitable coupling structure and an improved mutation operator, AHBSA improves the solution accuracy while ensuring algorithm robustness, and achieves good performance in experiments.
Article
Thermodynamics
Shengping Xu, Guojiang Xiong, Ali Wagdy Mohamed, Houssem R. E. H. Bouchekara
Summary: This paper presents an improved comprehensive learning particle swarm optimization (CLPSO) named FV-ICLPSO to solve the optimization problem of economic dispatch in power systems. The proposed method demonstrates a significant advantage in convergence speed and is validated in multiple practical cases.
Article
Computer Science, Information Systems
Vedik Basetti, Shriram S. Rangarajan, Chandan Kumar Shiva, Harish Pulluri, Ritesh Kumar, Randolph E. Collins, Tomonobu Senjyu
Summary: In this paper, a novel meta-heuristic algorithm called QOPO is proposed to solve non-convex single and bi-objective economic and emission load dispatch problems. By simultaneously performing opposite estimate candidate solutions on each candidate solution, QOPO can find better solutions effectively. The results from applying QOPO on different systems and comparing with other techniques show that QOPO has good exploration and exploitation capabilities for determining optimal global solutions.
Article
Engineering, Multidisciplinary
Muhammad Farhan Tabassum, Muhammad Saeed, Nazir Ahmad Chaudhry, Javaid Ali, Muhammad Farman, Sana Akram
Summary: Economic load dispatch problems involve linear equality constraints and non-linear objective functions, posing a challenge for optimization techniques, especially deterministic methods.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Computer Science, Information Systems
Tianping Liu, Guojiang Xiong, Ali Wagdy Mohamed, Ponnuthurai Nagaratnam Suganthan
Summary: The paper proposes an improved differential evolution (DE) algorithm OMLIDE based on opposition-mutual learning, hybrid mutation strategy, and parameters adaptive mechanism, effectively solving the economic load dispatch (ELD) problem in power systems.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Aiming Xia, Xuedong Wu, Yingjie Bai
Summary: In this study, a hybrid multi-objective algorithm combining Harris hawks optimization and differential evolution is proposed to solve the economic emission dispatch problem in power systems with valve-point effect. Experimental results demonstrate that the quality of solutions obtained by the suggested approach is superior to several existing algorithms.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Bishwajit Dey, Fausto Pedro Garcia Marquez, Aniruddha Bhattacharya
Summary: This research uses a hybrid intelligence method to reduce the total cost of microgrid systems and incorporates demand-side management to optimize the demand model and adjust the timing of elastic loads, resulting in energy cost savings.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Computer Science, Artificial Intelligence
Derong Lv, Guojiang Xiong, Xiaofan Fu, Mohammed Azmi Al-Betar, Jing Zhang, Houssem R. E. H. Bouchekara, Hao Chen
Summary: Economic dispatch is a critical issue for optimal power system operation and control, and becomes more challenging as the system grows. This study proposes an exponential hybrid mutation differential evolution method to address this issue, achieving a balance between exploitation and exploration through improved strategies during the iteration process.
APPLIED INTELLIGENCE
(2023)
Article
Engineering, Multidisciplinary
Mohamed H. Hassan, Salah Kamel, Ahmad Eid, Loai Nasrat, Francisco Jurado, Mohamed F. Elnaggar
Summary: This article proposes a new effective technique called ESCSDO algorithm, which utilizes eagle strategy and chaotic maps to solve the economic load dispatch problem in power systems. The algorithm improves population diversity, balance between local and global search, and premature convergence. Through testing and comparison, the algorithm demonstrates efficient performance and accuracy in solving economic load dispatch problems.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Xueping Li, Jian Xu, Zhigang Lu
Summary: The paper introduces a differential evolution algorithm called DE-STA, which utilizes state transition and specific individuals to solve economic dispatch problems with valve-point effects, demonstrating better robustness, convergence speed, and accuracy compared to traditional methods.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Loic Van Hoorebeeck, P. -A. Absil, Anthony Papavasiliou
Summary: The economic dispatch problem is fundamental in power system operations, with research focused on providing fast and robust algorithms for solving it. This work proposes an algorithm that efficiently provides solutions to a non-smooth and non-convex instance of the economic dispatch problem, which outperforms state-of-the-art methods in providing solutions with lower deviation from power balance constraint within comparable computation time.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Thermodynamics
Thabo G. Hlalele, Jiangfeng Zhang, Raj M. Naidoo, Ramesh C. Bansal
Summary: This paper proposes a combined economic dispatch and demand response optimization model, which is tested using real data and shows good performance. Specifically, the model utilizes a renewable obligation policy and direct load control to minimize generation costs while maximizing renewable penetration.
Article
Multidisciplinary Sciences
Yilin Long, Yong Li, Yahui Wang, Yijia Cao, Lin Jiang, Yicheng Zhou, Youyue Deng, Yosuke Nakanishi
Summary: This paper proposed a low-carbon economic dispatch model for multi-energy microgrid (MEMG) to minimize the daily operation cost by considering integrated demand response (IDR) and multistep carbon trading, which can effectively reduce carbon emission while greatly decreasing the operation cost.
SCIENTIFIC REPORTS
(2022)
Article
Energy & Fuels
Di Wu, Xu Ma, Patrick Balducci, Dhruv Bhatnagar
Summary: This paper discusses the challenges faced by Hawaii with increasing solar generation and the potential of demand response. The Hawaii Public Utilities Commission has approved the Hawaiian Electric Company's revised portfolio of DR programs. Research shows that pairing BESS with PV can generate multiple value streams for Hawaii's power grid, with compensation from DR programs playing a significant role in improving cost-effectiveness.
Article
Computer Science, Information Systems
Chao-Hong Chen, Ying-ping Chen
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
(2014)
Article
Computer Science, Software Engineering
Chao-Hong Chen, Amr Sabry
Summary: This research demonstrates the construction of compact closed categories for conventional sum and product types by defining new types, and establishes operational semantics for negative and fractional types. By extending a reversible language and proving operational semantics, it is shown that each extension forms a compact closed category.
PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Fang-Yi Lo, Chao-Hong Chen, Ying-ping Chen
2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
(2020)
Proceedings Paper
Mathematics, Interdisciplinary Applications
Fang-Yi Lo, Chao-Hong Chen, Ying-ping Chen
PROCEEDINGS OF THE 2019 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCCO'19 COMPANION)
(2019)
Article
Computer Science, Theory & Methods
Jacques Carette, Chao-Hong Chen, Vikraman Choudhury, Amr Sabry
ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE
(2018)
Proceedings Paper
Computer Science, Software Engineering
Chao-Hong Chen, Vikraman Choudhury, Ryan R. Newton
ACM SIGPLAN NOTICES
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Li-An Yang, Jui-Pin Liu, Chao-Hong Chen, Ying-ping Chen
2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
(2016)
Proceedings Paper
Computer Science, Artificial Intelligence
Chao-Hong Chen, Ying-ping Chen
GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2
(2007)