Enhanced Linear Exponential Smoothing Technique with Minimum Energy Storage Capacity for PV Distributed Generations

Abstract

This paper proposes a new technique to smooth out fluctuating power generated by photovoltaics (PV). It is named “enhanced linear exponential smoothing” or ELES. Compared among other smoothing methods, ELES requires a minimum energy storage capacity to alleviate the same level of power variation. ELES has been derived from a well-known financial forecasting method so-called “linear exponential smoothing (LES)”. This paper presents how LES can overcome disadvantages of the existing techniques. However, in case of PV power generation, a phase delay introduced in LES yet leads to an increment of required storage capacity. To further improve the system performance, ELES has been proposed to shorten LES surplus phase delay. Importantly, this paper presents how the positive factor of LES can be optimized and how an appropriated weighted averaging constant can be chosen. To verify the performance of the proposed technique, a battery energy storage system with ELES technique is simulated under a set of measured PV generated power profiles. The key results indicate that ELES effectively performs, when compared to others, especially the energy storage capacity reduction feature.
Copyright © 2014 Praise Worthy Prize - All rights reserved.