Title: A novel bio-inspired stochastic framework to solve energy management problem in hybrid AC-DC microgrids with uncertainty

Authors: Sattar Shojaeiyan; Taher Niknam; Mehdi Nafar

Addresses: Department of Electrical Engineering, Islamic Azad University, Marvdasht Branch, Marvdasht, Iran ' Department of Electrical Engineering, Islamic Azad University, Marvdasht Branch, Marvdasht, Iran ' Department of Electrical Engineering, Islamic Azad University, Marvdasht Branch, Marvdasht, Iran

Abstract: This paper introduces an effective intelligent framework for the optimal energy management of hybrid AC-DC microgrids in the presence of varied renewable energy sources and storage units. In order to consider the uncertainty effects, a new stochastic framework based on cloud drops and fuzzy set theory is devised. In the proposed stochastic scheme, the uncertainties of the forecast error in the wind unit output power, photovoltaics output power, electrical power demands and the market price are modelled. Such a model reveals an entropy-entropy concept which can help for capturing the standard deviation uncertainty of the uncertain parameters. In accordance with the high complexity of the proposed formulation, a new optimisation algorithm based on modified firefly algorithm and a three-phase modification method is proposed. The high capability and effectiveness of the proposed framework is assessed using a revised IEEE test system.

Keywords: evolutionary algorithm; energy management problem; hybrid AC-DC microgrid; firefly algorithm; cloud theory; uncertainty; optimisation.

DOI: 10.1504/IJBIC.2021.119200

International Journal of Bio-Inspired Computation, 2021 Vol.18 No.3, pp.165 - 175

Accepted: 22 Dec 2020
Published online: 29 Nov 2021 *

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