Zhong-kai Feng
Huazhong University of Science and Technology
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Publication
Featured researches published by Zhong-kai Feng.
Journal of Water Resources Planning and Management | 2017
Zhong-kai Feng; Wen-jing Niu; Jianzhong Zhou; Chuntian Cheng
AbstractIn order to satisfy the practical requirement of the power grid in China, this paper presents a multiobjective operation model for a cascaded hydropower system simultaneously considering th...
Journal of Hydrologic Engineering | 2018
Wen-jing Niu; Zhong-kai Feng; Chuntian Cheng; Jianzhong Zhou
AbstractAccurate hydrologic time-series prediction plays an important role in modern water resource planning, water supply management, environmental protection, and power system operation. In gener...
Journal of Water Resources Planning and Management | 2017
Zhong-kai Feng; Wen-jing Niu; Chuntian Cheng
AbstractAs an important renewable energy resource, hydropower plays an irreplaceable role in reducing power shortages in modern electrical systems throughout the world. This study focuses on the fi...
Applied Soft Computing | 2017
Zhong-kai Feng; Wen-jing Niu; Jianzhong Zhou; Chuntian Cheng; Yongchuan Zhang
Abstract With the growing concerns on energy and environment, the short-term hydrothermal scheduling (SHTS) which minimizes the fuel cost and pollutant emission simultaneously is playing an increasing important role in the modern electric power system. Due to the complicated operation constraints and objectives, SHTS is classified as a multi-objective optimization problem. Thus, to efficiently resolve this problem, this paper develops a novel parallel multi-objective differential evolution (PMODE) combining the merits of parallel technology and multi-objective differential evolution. In PMODE, the population with larger size is first divided into several smaller subtasks to be concurrently executed in different computing units, and then the main thread collects the results of each subpopulation to form the final Pareto solutions set for the SHTS problem. During the evolutionary process of each subpopulation, the mutation crossover and selection operators are modified to enhance the performance of population. Besides, an external archive set is used to conserve the Pareto solutions and provide multiple evolutionary directions for individuals, while the constraint handling method is introduced to address the complicated operational constraints. The results from a mature hydrothermal system indicate that when compared with several existing methods, PMODE can obtain satisfactory solutions in both fuel cost and environmental pollutant, which is an effective tool to generate trade-off schemes for the hydrothermal scheduling problem.
Journal of Water Resources Planning and Management | 2018
Zhong-kai Feng; Wen-jing Niu; Chuntian Cheng; Jay R. Lund
AbstractThe progressive optimality algorithm (POA) is commonly used to identify optimal hydropower operation schedules in China. However, POA may not converge within a reasonable time for large and...
Journal of Water Resources Planning and Management | 2018
Wen-jing Niu; Zhong-kai Feng; Chuntian Cheng
AbstractBecause of the growing demand for energy in recent years, multireservoir system operation with a power deficit aspect is becoming an increasingly important problem in electrical power syste...
Applied Soft Computing | 2018
Wen-jing Niu; Zhong-kai Feng; Chuntian Cheng; Xinyu Wu
Abstract Due to the expanding system scale and increasing operational complexity, the cascade hydropower reservoir operation balancing benefit and firm output is becoming one of the most important problems in China’s hydropower system. To handle this problem, this paper presents a parallel multi-objective particle swarm optimization where the swarm with large population size is divided into several smaller subswarms to be simultaneously optimized by different worker threads. In each subtask, the multi-objective particle swarm optimization is adopted to finish the entire evolutionary process, where the leader particles, external archive set and computational parameters are all dynamically updated. Besides, a novel constraint handling strategy is used to identify the feasible search space while the domination strategy based on constraint violation is used to enhance the convergence speed of swarm. The presented method is applied to Lancang cascade hydropower system in southwest China. The results show that PMOPSO can provide satisfying scheduling results in different cases. For the variation coefficient of generation in 30 independent runs, the presented method can bettered the serial algorithm with about 66.67% and 61.29% reductions in normal and dry years, respectively. Hence, this paper provides an effective tool for multi-objective operation of cascade hydropower system.
Energy | 2017
Zhong-kai Feng; Wen-jing Niu; Chuntian Cheng; Shengli Liao
Energy | 2017
Zhong-kai Feng; Wen-jing Niu; Chuntian Cheng; Xinyu Wu
Energy | 2017
Zhong-kai Feng; Wen-jing Niu; Chuntian Cheng