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Original scientific paper

https://doi.org/10.30765/er.2688

Two stage energy management for maximizing renewable energy penetration

V.B. Murali Krishna orcid id orcid.org/0000-0003-0643-8217 ; National Institute of Technology, Andhra Pradesh *
Vidyadhar S. Melkeri ; Department of Applied Electronics, Gulbarga University Kalaburagi, Karnataka 585 106, India.
Sonali Goel ; Department of Electrical Engineering, ITER, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, India.
K. R. K. V. Prasad ; Aditya University, Surampalem 533 437, Andhra Pradesh, India.

* Corresponding author.


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Abstract

For environmentally friendly and sustainable power generation, it is essential to maximize the penetration of renewable energy in energy management systems. In order to maximize the integration of renewable energy sources into the grid, this article suggests a two-stage energy management strategy. The methodology combines day-ahead and real-time energy management using stochastic optimization techniques to efficiently utilize renewable energy sources while maintaining grid stability and dependability. The goal of the first stage, or day-ahead, is to minimize operational costs. To this end, a framework for scenario generation, such as Monte Carlo simulation, is used to generate multiple scenarios that consider the uncertainties related to the generation of renewable energy, demand patterns, and external factors. These scenarios facilitate an in-depth assessment of the integration of renewable energy sources by representing a variety of potential future states of the energy system. The efficiency of the proposed methodology is demonstrated through case studies, showcasing its ability to increase renewable energy penetration in microgrid or grid-connected systems while maintaining reliability and cost-efficiency.

Keywords

renewable energy sources; microgrid; stochastic optimization; monte carlo simulation; golden jackal optimization (GJO)

Hrčak ID:

328555

URI

https://hrcak.srce.hr/328555

Publication date:

27.2.2025.

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