AI for Cyber-Physical Power Systems Operation and Control

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 2004

Special Issue Editors


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Guest Editor
KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
Interests: power system dynamics; future power networks; microgrids; renewable energy network; control systems
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Guest Editor
Faculty of Electrical Engineering,Federal University of Para—UFPA,Belem, PA 66075-110, Brazil
Interests: wind; energy

Special Issue Information

Dear Colleagues,

Existing power networks are changing rapidly due to the large deployment of non-synchronous integration. Thus, requiring innovative methods that guarantee the system stability. Moreover, Artificial Intelligence (AI) developments are no longer a myth for industry and are the current frontier of research with enormous possibilities of application in power systems. This migration to AI implementation requires the combination of different research areas and a deep study that helps the Transmission/Distribution System Operators (TSO/DSOs) to provide continuous operation and control.

Authors are welcome to contribute in the following topics:

- Low-inertia power systems

- Power system dynamics

- Applied power systems control theory and Machine Learning

- Power dominated converter systems

- Recent advancements in DC/AC microgrids

- Renewable energy

- Anomaly detection

- Smart power technologies

- Data-driven methods

- Optimization in power and distribution systems

Dr. Harold Rene Chamorro Vera
Prof. Carolina de Mattos Affonso
Guest Editors

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Keywords

  • Low-inertia power systems
  • Power system dynamics
  • Applied power systems control theory and Machine Learning
  • Power dominated converter systems
  • Recent advancements in DC/AC microgrids
  • Renewable energy
  • Anomaly detection
  • Smart power technologies
  • Data-driven methods
  • Optimization in power and distribution systems

Published Papers (1 paper)

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Research

15 pages, 420 KiB  
Article
On the Optimal Selection and Integration of Batteries in DC Grids through a Mixed-Integer Quadratic Convex Formulation
by Federico Martin Serra, Oscar Danilo Montoya, Lázaro Alvarado-Barrios, Cesar Álvarez-Arroyo and Harold R. Chamorro
Electronics 2021, 10(19), 2339; https://doi.org/10.3390/electronics10192339 - 24 Sep 2021
Cited by 8 | Viewed by 1407
Abstract
This paper deals with the problem of the optimal selection and location of batteries in DC distribution grids by proposing a new mixed-integer convex model. The exact mixed-integer nonlinear model is transformed into a mixed-integer quadratic convex model (MIQC) by approximating the product [...] Read more.
This paper deals with the problem of the optimal selection and location of batteries in DC distribution grids by proposing a new mixed-integer convex model. The exact mixed-integer nonlinear model is transformed into a mixed-integer quadratic convex model (MIQC) by approximating the product among voltages in the power balance equations as a hyperplane. The most important characteristic of our proposal is that the MIQC formulations ensure the global optimum reaching via branch & bound methods and quadratic programming since each combination of the binary variables generates a node with a convex optimization subproblem. The formulation of the objective function is associated with the minimization of the energy losses for a daily operation scenario considering high renewable energy penetration. Numerical simulations show the effectiveness of the proposed MIQC model to reach the global optimum of the optimization model when compared with the exact optimization model in a 21-node test feeder. All the validations are carried out in the GAMS optimization software. Full article
(This article belongs to the Special Issue AI for Cyber-Physical Power Systems Operation and Control)
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