Erratum to: Analysis, Control and Optimal Operations in Hybrid Power Systems

2013 ◽  
pp. E1-E1 ◽  
Author(s):  
Nicu Bizon ◽  
Naser Mahdavi Tabatabaei ◽  
Hossein Shayeghi
Keyword(s):  
Power Systems ◽  
Hybrid Power Systems ◽  
Hybrid Power

Holomorphic Embedding Power Flow for AC/DC Hybrid Power Systems Using Bauer's Eta Algorithm

2020 ◽  
pp. 1-1
Author(s):  
Yudi Zhao ◽  
Chongtao Li ◽  
Tao Ding ◽  
Zhiguo Hao ◽  
Fangxing Li
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Hybrid Power Systems ◽  
Hybrid Power ◽  
Holomorphic Embedding

Impact of forecasting error characteristics on battery sizing in hybrid power systems

2021 ◽  
Vol 39 ◽  
pp. 102567
Author(s):  
Yuqing Yang ◽  
Stephen Bremner ◽  
Chris Menictas ◽  
Merlinde Kay
Keyword(s):  
Power Systems ◽  
Hybrid Power Systems ◽  
Hybrid Power ◽  
Error Characteristics ◽  
Forecasting Error

Source diagram: A new approach for hybrid power systems design

2021 ◽  
Vol 47 ◽  
pp. 101429
Author(s):  
Ana Carolina de Lira Quaresma ◽  
Flávio S. Francisco ◽  
Fernando L.P. Pessoa ◽  
Eduardo M. Queiroz
Keyword(s):  
Power Systems ◽  
Systems Design ◽  
Hybrid Power Systems ◽  
New Approach ◽  
Hybrid Power

Load frequency control of isolated wind diesel hybrid power systems

1997 ◽  
Vol 38 (9) ◽  
pp. 829-837 ◽  
Author(s):  
T.S. Bhatti ◽  
A.A.F. Al-Ademi ◽  
N.K. Bansal
Keyword(s):  
Power Systems ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Hybrid Power Systems ◽  
Hybrid Power ◽  
Load Frequency

scholarly journals Optimal Sizing for Wind/PV/Battery System Using Fuzzy c-Means Clustering with Self-Adapted Cluster Number

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Xin Liu ◽  
Hong-Kun Chen ◽  
Bing-Qing Huang ◽  
Yu-Bo Tao
Keyword(s):  
Power Systems ◽  
Clustering Algorithm ◽  
Hybrid Power Systems ◽  
Cluster Number ◽  
Battery System ◽  
Optimal Sizing ◽  
Hybrid Power ◽  
Trade Offs ◽  
Fuzzy C Means Clustering ◽  
System States

Integrating wind generation, photovoltaic power, and battery storage to form hybrid power systems has been recognized to be promising in renewable energy development. However, considering the system complexity and uncertainty of renewable energies, such as wind and solar types, it is difficult to obtain practical solutions for these systems. In this paper, optimal sizing for a wind/PV/battery system is realized by trade-offs between technical and economic factors. Firstly, the fuzzy c-means clustering algorithm was modified with self-adapted parameters to extract useful information from historical data. Furthermore, the Markov model is combined to determine the chronological system states of natural resources and load. Finally, a power balance strategy is introduced to guide the optimization process with the genetic algorithm to establish the optimal configuration with minimized cost while guaranteeing reliability and environmental factors. A case of island hybrid power system is analyzed, and the simulation results are compared with the general FCM method and chronological method to validate the effectiveness of the mentioned method.

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