Performance evaluation of metaheuristic techniques for optimal sizing of a stand-alone hybrid PV/wind/battery system

2022 ◽  
Vol 305 ◽  
pp. 117823
Author(s):  
Dalila Fares ◽  
Mohamed Fathi ◽  
Saad Mekhilef
Keyword(s):  
Performance Evaluation ◽  
Battery System ◽  
Optimal Sizing ◽  
Metaheuristic Techniques

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.

scholarly journals Optimal Sizing of PV-Diesel-Battery System Using Different Inverter Types

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 133561-133573
Author(s):  
Erica M. Ocampo ◽  
Wen-Ching Chang ◽  
Cheng-Chien Kuo
Keyword(s):  
Battery System ◽  
Optimal Sizing

Intelligent approach for optimal sizing in photovoltaic panel-battery system and optimizing smart grid energy

2021 ◽  
pp. 014233122110270
Author(s):  
Ferdaws Ben Naceur ◽  
Chokri Ben Salah ◽  
Achraf Jabeur Telmoudi ◽  
Mohamed Ali Mahjoub
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Optimal Algorithm ◽  
Estimation Algorithm ◽  
Weather Data ◽  
Battery System ◽  
Inference System ◽  
Photovoltaic Panel ◽  
Optimal Sizing ◽  
Photovoltaic Power

Renewable energy plays a very important role in solving energy problems, and solar energy is one of the most important renewable sources, especially in sunny countries. This paper deals with two problems: The first one is about optimal sizing in a photovoltaic panel (PVP)-battery system, and the second consists in energy management in smart grids. To achieve the first objective, an adaptive neuro-fuzzy inference system (ANFIS) estimation algorithm is developed in order to estimate a database of instantaneous photovoltaic power. The estimated instantaneous photovoltaic power is used in an optimal algorithm to size a PVP-battery power station to supply a 1.5 kW AC load. For the second objective, a deep learning forecasting algorithm is realized to estimate the smart grid parameters so as to optimize the consumption energy. All results are checked carrying out Matlab simulation using real weather data. The simulation results give a good performance of our proposed sizing and management systems.

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