Renewable energy system with low pass filter

Muhammad Khalid; Miswar Akhtar Syed

Renewable energy system with low pass filter

Muhammad Khalid (Inventor), Miswar Akhtar Syed (Inventor)

Research output: Patent

Abstract

A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System (BESS). The MR filter, SoC feedback control and BESS are configured to provide smoothing of solar PV variabilities. The MR filter is a non-parametric smoother that utilizes a machine learning concept of linear regression to smooth out solar PV variations at every time step.

Original language	American English
Patent number	US12040745
State	Published - 16 Jul 2024

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Renewable energy system with low pass filter",

abstract = "A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System (BESS). The MR filter, SoC feedback control and BESS are configured to provide smoothing of solar PV variabilities. The MR filter is a non-parametric smoother that utilizes a machine learning concept of linear regression to smooth out solar PV variations at every time step. ",

author = "Muhammad Khalid and Syed, \{Miswar Akhtar\}",

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T1 - Renewable energy system with low pass filter

AU - Khalid, Muhammad

AU - Syed, Miswar Akhtar

PY - 2024/7/16

Y1 - 2024/7/16

N2 - A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System (BESS). The MR filter, SoC feedback control and BESS are configured to provide smoothing of solar PV variabilities. The MR filter is a non-parametric smoother that utilizes a machine learning concept of linear regression to smooth out solar PV variations at every time step.

AB - A system, method, and solar photovoltaic (PV) network for solar PV variability reduction with reduced time delays and battery storage optimization are described. The system includes a Moving Regression (MR) filter; a State of Charge (SoC) feedback control; and a Battery Energy Storage System (BESS). The MR filter, SoC feedback control and BESS are configured to provide smoothing of solar PV variabilities. The MR filter is a non-parametric smoother that utilizes a machine learning concept of linear regression to smooth out solar PV variations at every time step.

M3 - Patent

M1 - US12040745

ER -

Renewable energy system with low pass filter

Abstract

UN SDGs

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