Optimal Capacity of a Battery Energy Storage System based on Solar Variability Index to Smooth out Power Fluctuations in PV-Diesel Microgrids

TL;DR

This paper develops an empirical model to estimate the optimal battery capacity for PV-diesel microgrids based on solar variability, aiding in smoothing power fluctuations and enhancing microgrid stability.

Contribution

It introduces a linear regression-based empirical model linking solar irradiance variability to battery capacity, validated with real data and simulations.

Findings

Empirical model accurately estimates battery capacity with moving average smoothing.

Model has limited accuracy with ramp rate control.

Provides a practical tool for microgrid design without extensive simulations.

Abstract

Battery energy storage systems can be integrated with photovoltaic (PV)-diesel microgrids, as an enabling technology to increase the penetration of PV systems and aid microgrid stability by smoothing out the power fluctuations of the PV systems. The aim of this paper is to derive correlations between the optimal capacity of the smoothing batteries and variabilities in daily solar irradiance. Two commonly used smoothing techniques of moving average and ramp rate control are applied on a real solar irradiance dataset with a 1-minute resolution for a full calendar year across 11 sites in Australia. The paper then presents the developed empirical model, based on linear regressions, to estimate the optimal capacity of the batteries without requiring the use of detailed simulation studies. The performance of the developed technique is validated by numerical simulation studies in MATLAB. The study demonstrates that the empirical model provided reasonably accurate estimates when using the moving average smoothing technique, but had limited accuracy under the ramp rate control technique.