World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
58
Citations
10838
World Ranking
2537
National Ranking
512

Overview

Chuntian Cheng is affiliated with the Dalian University of Technology in China and has an extensive publication record in the field of engineering, with a particular focus on electrical and electronic engineering. Their research spans several subfields including ocean engineering, water science and technology, civil and structural engineering, and control and systems engineering.

The scientist's research primarily addresses topics related to electric power system optimization, water resources management and optimization, smart grid energy management, water systems and optimization, water-energy-food nexus studies, integrated energy systems optimization, and energy load and power forecasting.

Chuntian Cheng's recent academic contributions include the following publications:

  • Annual Streamflow Time Series Prediction Using Extreme Learning Machine Based on Gravitational Search Algorithm and Variational Mode Decomposition, 2020, Journal of Hydrologic Engineering
  • Preliminary feasibility analysis for remaking the function of cascade hydropower stations to enhance hydropower flexibility: A case study in China, 2022, Energy
  • Sharing hydropower flexibility in interconnected power systems: A case study for the China Southern power grid, 2021, Applied Energy
  • Impacts, challenges and suggestions of the electricity market for hydro-dominated power systems in China, 2022, Renewable Energy
  • Chance-constrained co-optimization for day-ahead generation and reserve scheduling of cascade hydropower-variable renewable energy hybrid systems, 2022, Applied Energy

The frequent coauthors collaborating with Cheng include Xinyu Wu, Shengli Liao, Benxi Liu, Jianjian Shen, and Huaying Su. This demonstrates ongoing collaborative research efforts in their area of expertise.

Cheng's work has been published predominantly in recognized scientific journals such as Renewable Energy, Journal of Water Resources Planning and Management, Applied Energy, Journal of Hydrology, and Energies.

  • Renewable Energy (14 publications)
  • Journal of Water Resources Planning and Management (10 publications)
  • Applied Energy (7 publications)
  • Journal of Hydrology (6 publications)
  • Energies (6 publications)

The concentration of Cheng's research on electric power system optimization and water-related engineering demonstrates an integrated approach to managing and optimizing resources and energy systems, especially under the context of hydropower and renewable energy sources.

Best Publications

  • A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

    Wen-Chuan Wang;Kwok-Wing Chau;Chun-Tian Cheng;Lin Qiu

  • Using support vector machines for long-term discharge prediction

    Jian-Yi Lin;Chun-Tian Cheng;Kwok-Wing Chau

  • Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration

    Chuntian Cheng;Chunping Ou;Kwok-wing Chau

  • Optimizing Hydropower Reservoir Operation Using Hybrid Genetic Algorithm and Chaos

    Chun Tian Cheng;Wen Chuan Wang;Dong Mei Xu;Kwok Wing Chau

  • Multiple criteria data envelopment analysis for full ranking units associated to environment impact assessment

    Ming Yan Zhao;Chun Tian Cheng;Kwok Wing Chau;Gang Li

  • A Parallel Ant Colony Algorithm for Bus Network Optimization

    Unknown

  • Optimal power peak shaving using hydropower to complement wind and solar power uncertainty

    Benxi Liu;Jay R. Lund;Shengli Liao;Xiaoyu Jin

  • Operation challenges for fast-growing China's hydropower systems and respondence to energy saving and emission reduction

    Chun Tian Cheng;Jian Jian Shen;Xin Yu Wu;Kwok Wing Chau

  • Long-Term prediction of discharges in manwan reservoir using artificial neural network models

    Chuntian Cheng;Kwokwing Chau;Yingguang Sun;Jianyi Lin

  • Three-person multi-objective conflict decision in reservoir flood control

    Cheng Chuntian;Kwok Wing Chau

  • Operation rule derivation of hydropower reservoir by k-means clustering method and extreme learning machine based on particle swarm optimization

    Zhong-kai Feng;Wen-jing Niu;Rui Zhang;Sen Wang

  • Comparison of Multiple Linear Regression, Artificial Neural Network, Extreme Learning Machine, and Support Vector Machine in Deriving Operation Rule of Hydropower Reservoir

    Wen-Jing Niu;Zhong-Kai Feng;Bao-Fei Feng;Yao-Wu Min

  • A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy

    Zhong-kai Feng;Wen-jing Niu;Wen-chuan Wang;Jian-zhong Zhou

  • Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng;Sheng-li Liao

  • China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Forecasting reservoir monthly runoff via ensemble empirical mode decomposition and extreme learning machine optimized by an improved gravitational search algorithm

    Wen-jing Niu;Zhong-kai Feng;Ming Zeng;Bao-fei Feng

  • Comparison of particle swarm optimization and dynamic programming for large scale hydro unit load dispatch

    Chun-tian Cheng;Sheng-li Liao;Zi-Tian Tang;Ming-yan Zhao

  • Flood control management system for reservoirs

    Chun Tian Cheng;Kwok Wing Chau

  • A parallel multi-objective particle swarm optimization for cascade hydropower reservoir operation in southwest China

    Wen-jing Niu;Zhong-kai Feng;Chun-tian Cheng;Xin-yu Wu

  • Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • A comparison of performance of several artificial intelligence

    Wen-Chuan Wang;Kwok-Wing Chau;Chun-Tian Cheng

Frequent Co-Authors

Zhong-kai Feng
Zhong-kai Feng Hohai University
Kwok-wing Chau
Kwok-wing Chau Hong Kong Polytechnic University
Jay R. Lund
Jay R. Lund University of California, Davis
Jianzhong Zhou
Jianzhong Zhou Huazhong University of Science and Technology
Kaveh Madani
Kaveh Madani Yale University
William W.-G. Yeh
William W.-G. Yeh University of California, Los Angeles
Licheng Sun
Licheng Sun Royal Institute of Technology

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