Combining Data-Driven and Model-Driven Approaches for Optimal Distributed Control of Standalone Microgrid

نویسندگان

چکیده

This paper focuses on the comprehensive restoration of both voltage and frequency in a standalone microgrid (SAMG). In SAMG, power balance is achieved through traditional methods such as droop control for sharing among distributed generators (DGs). However, when microgrids (MGs) are subjected to perturbations coming from stochastic renewables, parameters deviate their specified values. this paper, novel hybrid-type consensus-based controller proposed restoration. Data-based communication ensured DGs controlling parameters. Different voltage, frequency, active reactive converge successfully nominal values using algorithms, thereby ensuring smooth operation inverter-dominated DGs. Additionally, machine-learning-based long short-term memory (LSTM) algorithm implemented renewable forecasting historical data location visualising insolation profile. The effectiveness our approach demonstrated which consists four inverters, showing that can improve system stability, increase efficiency reliability, reduce costs compared methods. complete study performed Python MATLAB environments. Our results highlight potential data-driven approaches revolutionise control.

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ژورنال

عنوان ژورنال: Sustainability

سال: 2023

ISSN: ['2071-1050']

DOI: https://doi.org/10.3390/su151612286