Frequency-constrained unit commitment problem with considering dynamic ramp rate limits in the presence of wind power generation

• Published in: Neural computing & applications Vol. 31; no. 9; pp. 5241 - 5254
• Main Authors: Safari, Amin, Shahsavari, Hossein
• Format: Journal Article
• Language: English
• Published: London Springer London 01.09.2019; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Computer simulation; Constraints; Data Mining and Knowledge Discovery; Electric power generation; Image Processing and Computer Vision; Original Article; Particle swarm optimization; Probability and Statistics in Computer Science; Unit commitment; Wind power; Wind power generation; Frequency-constrained unit commitment problem; Binary particle swarm optimization; Dynamic ramping; Wind generation penetration
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-018-3363-y

An increased use of variable generation technologies such as wind power generation can have important effects on system frequency performance during normal operation as well as contingencies. This has led to new challenges for system operators in terms of improving frequency characteristics during contingencies. This subject is stated within the framework of frequency-constrained unit commitment problem (FCUCP) in this study by augmenting the frequency characteristic in the multi-thermal units. The ramp rate is proposed as dynamic constraint, and FCUCP is solved efficiently by binary particle swarm optimization (BPSO) based heuristic optimization algorithms. The influence of the proposed ramping on FCUCP is simulated, and it can be shown that the costs of the system under considering practical limitations that are solved by BPSO are minimized.