A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm

doi:10.1007/s11708-017-0484-4

Front. Energy

2020, Vol. 14

Issue (1) : 139-151 https://doi.org/10.1007/s11708-017-0484-4

RESEARCH ARTICLE

A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm

Aeidapu MAHESH(

), Kanwarjit Singh SANDHU(

)

Department of Electrical Engineering, National Institute of Technology, Kurukshetra 136119, India

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Abstract

In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

Keywords PV-wind-battery hybrid system size optimization genetic algorithm

Corresponding Author(s): Aeidapu MAHESH,Kanwarjit Singh SANDHU

Online First Date: 25 July 2017 Issue Date: 16 March 2020

Cite this article:

Aeidapu MAHESH,Kanwarjit Singh SANDHU. A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm[J]. Front. Energy, 2020, 14(1): 139-151.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-017-0484-4
https://academic.hep.com.cn/fie/EN/Y2020/V14/I1/139

Fig.1 Block diagram representation of hybrid PV-wind-battery system

Fig.2 Wind turbine characteristics

Fig.3 Proposed optimal sizing strategy

Tab.1 Parameters used for GA

Fig.4 Proposed energy filter algorithm

Fig.5 Meteorological data and load patterns

Tab.2 Parameters of system components

Tab.3 Results of optimal sizing without energy filter

Fig.6 Power generated by the hybrid system

Fig.7 Power supplied to the grid without filter

Tab.4 Results of optimal sizing with energy filter

Fig.8 Comparison of power injected into the grid

Fig.9 Battery power with energy filter

Tab.5 Results of optimal sizing with proposed energy filter

Fig.10 Power injected into the grid with proposed energy filter

Fig.11 No. of iterations versus cost function plot

Fig.12 Battery state of charge

Fig.13 Probability of fluctuation rate

Tab.6 Comparison of three strategies

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