Moving Regression Filtering With Battery State of Charge Feedback Control for Solar PV Firming and Ramp Rate Curtailment

The surge in energy demand needs to be met with environmentally pleasant resources reduce the production of greenhouse gases. Solar Photovoltaic (PV) power is a widespread choice as it accessible plenty and comparatively inexpensive. However, large-scale penetration intermittent PV causes multiple variabilities grid such frequency issues voltage deviations. To counteract these instabilities, Battery Energy Storage System (BESS) integrated into reduces fluctuations promotes optimal operation. Nevertheless, storage systems are expensive, thus smoothing filters coupled BESS for cost reduction smoothing. Formerly, traditional Low Pass Filters (LPF), Moving Average (MA), Median (MM) have been proposed inadequate tracking capabilities particularly longer window sizes (W.S) time constants, which subsequently depreciates system performance. compensate delayed tracking, larger required turn adds overall operational costs. This paper proposes Regression (MR) filter combined state charge (SoC) feedback control solar variability reduction, reduced delay, decreased battery charging/discharging power, ramp rate. Simulation results attest that MR achieves better without increasing capacity. Also, performance less affected increase sizes. Additionally, execution introduced was found superior when assessed against LPF, MA, MM, Savitsky-Golay (SG), Gaussian filter. In comparison SG (W.S = 53), 45) by approximately 30.48% opposed LPF (T.C 48), peak SoC 19.1%.