Tao Bao^*, Xiyuan Ma, Zhuohuan Li, Duotong Yang, Pengyu Wang, Changcheng Zhou

Energy Engineering, Vol.121, No.6, pp. 1713-1737, 2024, DOI:10.32604/ee.2023.046150

Abstract The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases. In order to improve and ensure the stable operation of the novel power system, this study proposes an artificial emotional lazy Q-learning method, which combines artificial emotion, lazy learning, and reinforcement learning for static security and stability analysis of power systems. Moreover, this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able More >

Wei Chen, Ming Li^*, Tingting Pei, Cunyu Sun, Huan Lei

Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812

Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the… More >

Qun Li, Ningyu Zhang^*, Jianhua Zhou, Xinyao Zhu, Peng Li

Energy Engineering, Vol.120, No.6, pp. 1485-1502, 2023, DOI:10.32604/ee.2023.022856

Abstract The access of unified power flow controllers (UPFC) has changed the structure and operation mode of power grids all across the world, and it has brought severe challenges to the traditional real-time calculation of security correction based on traditional models. Considering the limitation of computational efficiency regarding complex, physical models, a data-driven power system security correction method with UPFC is, in this paper, proposed. Based on the complex mapping relationship between the operation state data and the security correction strategy, a two-stage deep neural network (DNN) learning framework is proposed, which divides the offline training… 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

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 >

K. Sukanya^*, P. Vijayakumar

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 971-982, 2023, DOI:10.32604/iasc.2023.028047

Abstract Frequency deviation has to be controlled in power generation units when there are fluctuations in system frequency. With several renewable energy sources, wind energy forecasting is majorly focused in this work which is a tough task due to its variations and uncontrollable nature. Whenever there is a mismatch between generation and demand, the frequency deviation may arise from the actual frequency 50 Hz (in India). To mitigate the frequency deviation issue, it is necessary to develop an effective technique for better frequency control in wind energy systems. In this work, heuristic Fuzzy Logic Based Controller… More >

Ziwei Jiang¹, Shuaibing Li^1,*, Xiping Ma², Xingmin Li², Yongqiang Kang¹, Hongwei Li³, Haiying Dong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 295-317, 2022, DOI:10.32604/cmes.2022.019996

Abstract

The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid. To improve the prediction accuracy of power systems with source-load two-terminal uncertainties, an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix Q0 is proposed in this paper. In the algorithm, the Q0 is used to offset the modeling error, and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems.

More >

Emad M. Ahmed^1,*, Mohamed A. Ahmed¹, Ziad M. Ali^2,3, Imran Khan⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 231-254, 2022, DOI:10.32604/cmc.2022.022005

Abstract The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances.… More >

Bing Wang^1,2, Kailei Deng¹, Liting He¹, Zhenming Sun^1,*

Energy Engineering, Vol.118, No.5, pp. 1333-1351, 2021, DOI:10.32604/EE.2021.014258

Abstract China has implemented both quantitative and policy incentives for renewable energy development since 2019 and is currently in the policy transition stage. The implementation of renewable portfolio standards (RPSs) is difficult due to the interests of multiple stakeholders, including power generation enterprises, power grid companies, power users, local governments, and the central government. Based on China’s RPS policy and power system reform documents, this research sorted out the core game decision problems of China’s renewable energy industry and established a conceptual game decision model of the renewable energy industry from the perspective of local governments,… More >

Tharam S. Dillon^1,2,∗, Yi-Ping Phoebe Chen^1,†, Elizabeth Chang^2,‡, Mukesh Mohania^3,§, Vish Ramakonar⁴

Computer Systems Science and Engineering, Vol.35, No.5, pp. 321-334, 2020, DOI:10.32604/csse.2020.35.321

Abstract In Digital Enterprises Structured Data and Semi/Unstructured Content are normally stored in two different repositories, with the first often being stored in relational Databases and the second in a content manager which is frequently at an external outsourcer. This storage of complementary information in two different silos has led to the information being processed and data mined separately which is undesirable. Effective knowledge and information use requires seamless access and intelligent analysis of information in its totality to allow enterprises to gain enhanced insights. In this paper, we develop techniques to carry out correlation of More >

Wei Zhang¹, Weifeng Shi², Bing Sun³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 423-431, 2019, DOI:10.31209/2018.100000045

Abstract An intelligent optimization algorithm for a marine generator excitation controller is proposed to improve dynamic performance of shipboard power systems. This algorithm combines a belief–desire–intention agent with a quantum-behaved particle swarm optimization (QPSO) algorithm to optimize a marine generator excitation controller. The shipboard zonal power system is simulated under disturbance due to load change or severe fault. The results show that the proposed optimization algorithm can improve marine generator stability compared with conventional excitation controllers under various operating conditions. Moreover, the proposed intelligent algorithm is highly robust because its performance is insensitive to the accuracy More >