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Risk-Based operation of soft open points in distribution grids integrated with photovoltaic resources and energy storage systems

Gholami, K., Azizivahed, A., Arefi, A.ORCID: 0000-0001-9642-7639, Rahman, M.M. and Islam, Md.R. (2022) Risk-Based operation of soft open points in distribution grids integrated with photovoltaic resources and energy storage systems. In: 2022 IEEE IAS Global Conference on Emerging Technologies (GlobConET), 20 - 22 May 2022, Arad, Romania

Link to Published Version: https://doi.org/10.1109/GlobConET53749.2022.987243...
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Abstract

Electronic-based technologies are becoming more interesting because of their advantages, such as quick response, higher lifespan, etc. Soft open point is a cutting-edge device that has been recently introduced for distribution grids. It is generally installed in tie switches, resulting in a transfer of the powers among two regions of the network. However, there are other distributed generation resources in the active distribution networks, like smart photovoltaic inverters (SPIs), energy storage systems (ESSs), diesel generators (DGs), etc. Accordingly, taking into account the coordination among mentioned technologies is essential. This paper aims to provide a strategy for simultaneous management of all mentioned resources based on a convex model, leading to taking advantage of commercial solvers, e.g., CPLEX. The uncertainties of loads and renewable energies directly affect such management schemes in addition to mentioned coordination. This paper, therefore, uses a robust framework entitled information-gap decision theory, which leads to reaching the solutions under harsh uncertainties. Here, the risk-averse strategy is utilized to model the uncertainties to achieve a robust model. The proposed method is finally evaluated under various cases by executing on a modified IEEE 33-bus test network. Through the results, SOP in the presence of SPIs, ESSs, and DGs can be an excellent remedy to improve the efficiency of networks.

Item Type: Conference Paper
Murdoch Affiliation(s): School of Engineering and Information Technology
URI: http://researchrepository.murdoch.edu.au/id/eprint/66246
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