Jiangang Lu, Ruifeng Zhao^*, Zhiwen Yu, Yue Dai, Kaiwen Zeng

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4453-4469, 2024, DOI:10.32604/cmc.2024.048020 - 26 March 2024

Abstract Time synchronization (TS) is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things (IoT). Multi-clock source time synchronization (MTS) has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales, and the coupling of synchronization latency jitter and pulse phase difference. In this paper, the multi-timescale MTS model is conducted, and the reinforcement learning (RL) and analytic hierarchy process (AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of More >

Hongliang Wang¹, Jiahua Hu¹, Danhuang Dong¹, Cenfeng Wang¹, Feixia Tang², Yizheng Wang¹, Changsen Feng^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1137-1158, 2023, DOI:10.32604/cmes.2022.021965 - 31 August 2022

Abstract With the rapid and wide deployment of renewable energy, the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance. The output power of renewable energy is uncertain, and thus flexible regulation for the power balance is highly demanded. Considering the multi-timescale output characteristics of renewable energy, a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper. Through the multi-timescale decomposition algorithm on the basis of mathematical morphology, the multi-timescale components are separated More >