Optimal sizing of stand-alone hybrid wind/PV system with battery storage

2007 ◽  
Author(s):  
Rachid Belfkira ◽  
Omessad Hajji ◽  
Cristian Nichita ◽  
Georges Barakat
Keyword(s):  
Battery Storage ◽  
Pv System ◽  
Optimal Sizing

scholarly journals A New Approach for Optimal Sizing of Standalone Photovoltaic Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Tamer Khatib ◽  
Azah Mohamed ◽  
K. Sopian ◽  
M. Mahmoud
Keyword(s):  
Energy Flow ◽  
New Method ◽  
Photovoltaic Systems ◽  
Kuala Lumpur ◽  
Battery Storage ◽  
Pv System ◽  
New Approach ◽  
Optimal Sizing ◽  
Pv Array ◽  
System Energy

This paper presents a new method for determining the optimal sizing of standalone photovoltaic (PV) system in terms of optimal sizing of PV array and battery storage. A standalone PV system energy flow is first analysed, and the MATLAB fitting tool is used to fit the resultant sizing curves in order to derive general formulas for optimal sizing of PV array and battery. In deriving the formulas for optimal sizing of PV array and battery, the data considered are based on five sites in Malaysia, which are Kuala Lumpur, Johor Bharu, Ipoh, Kuching, and Alor Setar. Based on the results of the designed example for a PV system installed in Kuala Lumpur, the proposed method gives satisfactory optimal sizing results.

Time Series Model of Wind Power Forecasting Error by using Beta Distribution for Optimal Sizing of Battery Storage

2019 ◽  
Vol 139 (3) ◽  
pp. 212-224
Author(s):  
Xiaowei Dui ◽  
Masakazu Ito ◽  
Yu Fujimoto ◽  
Yasuhiro Hayashi ◽  
Guiping Zhu ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Power ◽  
Beta Distribution ◽  
Time Series Model ◽  
Battery Storage ◽  
Wind Power Forecasting ◽  
Optimal Sizing ◽  
Forecasting Error ◽  
Power Forecasting

scholarly journals Evaluation of Photovoltaic and Battery Storage Effects on the Load Matching Indicators Based on Real Monitored Data

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2727 ◽  
Author(s):  
Sofiane Kichou ◽  
Nikolaos Skandalos ◽  
Petr Wolf
Keyword(s):  
Storage System ◽  
The Self ◽  
Electrical Performance ◽  
Electricity Production ◽  
Solar Pv ◽  
Battery Storage ◽  
Pv System ◽  
Load Matching ◽  
Self Sufficiency ◽  
Pv Generation

This paper reports on the electrical performance of two bloc-of-flats buildings located in Prague, Czech Republic. Measured data of electrical consumption were used to investigate the effect of photovoltaic (PV) and battery energy storage system (BESS) systems on the overlap between generation and demand. Different PV array configurations and battery storage capacities were considered. Detailed solar analysis was carried out to analyze the solar potential of the building and to assess the PV electricity production. The evaluation of the building performance was done through MATLAB simulations based on one-year monitored data. The simulation results were used for the calculation of the load matching indices: namely, the self-consumption and self-sufficiency. It was found that optimized array tilt and orientation angles can effectively contribute to a better adjustment between electricity demand and solar PV generation. The addition of a façade PV system increases significantly the PV generation and thus the load matching during winter months. Mismatch is further reduced by using the energy flexibility provided by the BESS. Depending on the PV size and BESS capacity, the self-consumption and the self-sufficiency of the building could increase from 55% to 100% and from 24% up to 68%, respectively.

scholarly journals Optimal Sizing of Standalone Photovoltaic System Using Improved Performance Model and Optimization Algorithm

2020 ◽  
Vol 12 (6) ◽  
pp. 2233
Author(s):  
Tamer Khatib ◽  
Dhiaa Halboot Muhsen
Keyword(s):  
Life Cycle Cost ◽  
Optimal Solution ◽  
Cost Effective ◽  
Performance Model ◽  
Photovoltaic System ◽  
Optimal Solutions ◽  
Pv System ◽  
Optimal Sizing ◽  
Pv Systems ◽  
Improved Performance

A standalone photovoltaic system mainly consists of photovoltaic panels and battery bank. The use of such systems is restricted mainly due to their high initial costs. This problem is alleviated by optimal sizing as it results in reliable and cost-effective systems. However, optimal sizing is a complex task. Artificial intelligence (AI) has been shown to be effective in PV system sizing. This paper presents an AI-based standalone PV system sizing method. Differential evolution multi-objective optimization is used to find the optimal balance between system’s reliability and cost. Two objective functions are minimized, the loss of load probability and the life cycle cost. A numerical algorithm is used as a benchmark for the proposed method’s speed and accuracy. Results indicate that the AI algorithm can be successfully used in standalone PV systems sizing. The proposed method was roughly 27 times faster than the numerical method. Due to AI algorithm’s random nature, the proposed method resulted in the exact optimal solution in 6 out of 12 runs. Near-optimal solutions were found in the other six runs. Nevertheless, the nearly optimal solutions did not introduce major departure from optimal system performance, indicating that the results of the proposed method are practically optimal at worst.

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