Detailed Investigation of Persistence Technique for Microgrid Load and Renewable Energy Forecasting

Malik Yasir Shamim; Krishna Tomar

doi:10.55524/ijirem.2022.9.3.22

Abstract

A micro-grid system, whether linked to the utility grid or self-contained, often comprises of a combination of renewable and non-renewable production, controllable or non-controllable loads, and Energy Storage Systems (ESSs) such as batteries or flywheels. To estimate how much power is used from controlled resources such as ESS, diesel generators, micro-turbines, or gas turbines, we must first identify how much demand exists or how much renewable energy sources provide, which is performed by forecasting techniques. Due to the intermittent nature of renewable resources such as wind energy or solar energy, precise forecasting of wind power or solar power is challenging. These projections are heavily reliant on weather predictions. It is obvious that forecasting any data based on forecasting other factors would result in increased inaccuracy, even if the relationship between the inputs and outputs could be predicted using regression methods. As a result, this research demonstrates a method for producing short-term forecast results using historical power data rather than numerical weather projections. Forecasting power generation from renewable energy sources (RESs) has become critical in micro-grid applications to improve asset scheduling and dispatching.

Keywords

Micro-grid, renewable energy, power forecasting, forecasting algorithms, MATLAB

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Cites this article as

M. Y. Shamim, K. Tomar, "Detailed Investigation of Persistence Technique for Microgrid Load and Renewable Energy Forecasting", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-9, Issue-3, Page No-142-148, 2022. Available from: https://doi.org/10.55524/ijirem.2022.9.3.22