Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Khosrojerdi, F.; Akhigbe, O.; Gagnon, S.; Ramirez, A.; Richards, G.
Integrating artificial intelligence and analytics in smart grids: a systematic literature review Journal Article
In: International Journal of Energy Sector Management, vol. 16, no. 2, pp. 318–338, 2022.
Abstract | Links | BibTeX | Tags: Advanced Analytics, Automation, Building energy consumption, Data Analytics, Design/methodology/approach, Dynamic energy managements, Electric power system control, Electric power transmission networks, Energy management, Energy management systems, Energy utilization, Extract, Home energy management systems, Information management, Intelligent systems, Project management, quality control, Real time systems, SCADA systems, Smart power grids, Solar buildings, Supervisory control and dataacquisition systems (SCADA), System stability, Systematic literature review, transform and loads, Voltage stability assessment
@article{khosrojerdi_integrating_2022,
title = {Integrating artificial intelligence and analytics in smart grids: a systematic literature review},
author = {F. Khosrojerdi and O. Akhigbe and S. Gagnon and A. Ramirez and G. Richards},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112559126&doi=10.1108%2fIJESM-06-2020-0011&partnerID=40&md5=7052f94c993368405955c1d33d87043c},
doi = {10.1108/IJESM-06-2020-0011},
year = {2022},
date = {2022-01-01},
journal = {International Journal of Energy Sector Management},
volume = {16},
number = {2},
pages = {318–338},
abstract = {Purpose: The purpose of this study is to explore the latest approaches in integrating artificial intelligence and analytics (AIA) in energy smart grid projects. Empirical results are synthesized to highlight their relevance from a technology and project management standpoint, identifying several lessons learned that can be used for planning highly integrated and automated smart grid projects. Design/methodology/approach: A systematic literature review leads to selecting 108 research articles dealing with smart grids and AIA applications. Keywords are based on the following research questions: What is the growth trend in Smart Grid projects using intelligent systems and data analytics? What business value is offered when AI-based methods are applied? How do applications of intelligent systems combine with data analytics? What lessons can be learned for Smart Grid and AIA projects? Findings: The 108 selected articles are classified according to the following four research issues in smart grids project management: AIA integrated applications; AI-focused technologies; analytics-focused technologies; architecture and design methods. A broad set of smart grid functionality is reviewed, seeking to find commonality among several applications, including as follows: dynamic energy management; automation of extract, transform and load for Supervisory Control And Data Acquisition (SCADA) systems data; multi-level representations of data; the relationship between the standard three-phase transforms and modern data analytics; real-time or short-time voltage stability assessment; smart city architecture; home energy management system; building energy consumption; automated fault and disturbance analysis; and power quality control. Originality/value: Given the diversity of issues reviewed, a more capability-focused research agenda is needed to further synthesize empirical findings for AI-based smart grids. Research may converge toward more focus on business rules systems, that may best support smart grid design, proof development, governance and effectiveness. These AIA technologies must be further integrated with smart grid project management methodologies and enable a greater diversity of renewable and non-renewable production sources. © 2021, Emerald Publishing Limited.},
keywords = {Advanced Analytics, Automation, Building energy consumption, Data Analytics, Design/methodology/approach, Dynamic energy managements, Electric power system control, Electric power transmission networks, Energy management, Energy management systems, Energy utilization, Extract, Home energy management systems, Information management, Intelligent systems, Project management, quality control, Real time systems, SCADA systems, Smart power grids, Solar buildings, Supervisory control and dataacquisition systems (SCADA), System stability, Systematic literature review, transform and loads, Voltage stability assessment},
pubstate = {published},
tppubtype = {article}
}
Purpose: The purpose of this study is to explore the latest approaches in integrating artificial intelligence and analytics (AIA) in energy smart grid projects. Empirical results are synthesized to highlight their relevance from a technology and project management standpoint, identifying several lessons learned that can be used for planning highly integrated and automated smart grid projects. Design/methodology/approach: A systematic literature review leads to selecting 108 research articles dealing with smart grids and AIA applications. Keywords are based on the following research questions: What is the growth trend in Smart Grid projects using intelligent systems and data analytics? What business value is offered when AI-based methods are applied? How do applications of intelligent systems combine with data analytics? What lessons can be learned for Smart Grid and AIA projects? Findings: The 108 selected articles are classified according to the following four research issues in smart grids project management: AIA integrated applications; AI-focused technologies; analytics-focused technologies; architecture and design methods. A broad set of smart grid functionality is reviewed, seeking to find commonality among several applications, including as follows: dynamic energy management; automation of extract, transform and load for Supervisory Control And Data Acquisition (SCADA) systems data; multi-level representations of data; the relationship between the standard three-phase transforms and modern data analytics; real-time or short-time voltage stability assessment; smart city architecture; home energy management system; building energy consumption; automated fault and disturbance analysis; and power quality control. Originality/value: Given the diversity of issues reviewed, a more capability-focused research agenda is needed to further synthesize empirical findings for AI-based smart grids. Research may converge toward more focus on business rules systems, that may best support smart grid design, proof development, governance and effectiveness. These AIA technologies must be further integrated with smart grid project management methodologies and enable a greater diversity of renewable and non-renewable production sources. © 2021, Emerald Publishing Limited.
2.
Khosrojerdi, F.; Gagnon, S.; Valverde, R.
Applications of Artificial Intelligence in Smart Grids: Present and Future Research Domains Proceedings Article
In: 2021 9th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2021, pp. 7–12, Institute of Electrical and Electronics Engineers Inc., 2021, ISBN: 978-073814535-8 (ISBN), (Journal Abbreviation: IEEE Int. Conf. Smart Energy Grid Eng., SEGE).
Abstract | Links | BibTeX | Tags: AI research, Artificial intelligence, Artificial intelligence research, Electric network analysis, Electric power transmission networks, EV, Network operations, Power network operation, Power networks, Research domains, Research opportunities, Scholar, scholars, Smart grid, Vehicle to grids, Vehicle-to-grid, Vehicles
@inproceedings{khosrojerdi_applications_2021,
title = {Applications of Artificial Intelligence in Smart Grids: Present and Future Research Domains},
author = {F. Khosrojerdi and S. Gagnon and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115988707&doi=10.1109%2fSEGE52446.2021.9534914&partnerID=40&md5=a55eba3a0bc91b6381600a3a24de963f},
doi = {10.1109/SEGE52446.2021.9534914},
isbn = {978-073814535-8 (ISBN)},
year = {2021},
date = {2021-01-01},
booktitle = {2021 9th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2021},
pages = {7–12},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {In the last decade, Artificial Intelligence (AI) have been applied overwhelmingly in various research domains in the context of smart grid. It has been one of the main streams of advanced technological approaches that the research community offered for developing smart grids. However, the broad scope of the subject matter has launched complexity for scholars to identify effective research approaches. In this paper, we present a literature review about utilizing AI in the key elements of smart grids including grid-connected vehicles, data-driven components, and the power system network. This will result in highlighting technical challenges of the integration of electric vehicles to the grid and the power network operation as well. Moreover, we discuss the four key research areas in the context of AI and its applications in intelligent power grids. The proposed research fields aid PhD candidates to consider these areas as the promising domains for investigation. © 2021 IEEE.},
note = {Journal Abbreviation: IEEE Int. Conf. Smart Energy Grid Eng., SEGE},
keywords = {AI research, Artificial intelligence, Artificial intelligence research, Electric network analysis, Electric power transmission networks, EV, Network operations, Power network operation, Power networks, Research domains, Research opportunities, Scholar, scholars, Smart grid, Vehicle to grids, Vehicle-to-grid, Vehicles},
pubstate = {published},
tppubtype = {inproceedings}
}
In the last decade, Artificial Intelligence (AI) have been applied overwhelmingly in various research domains in the context of smart grid. It has been one of the main streams of advanced technological approaches that the research community offered for developing smart grids. However, the broad scope of the subject matter has launched complexity for scholars to identify effective research approaches. In this paper, we present a literature review about utilizing AI in the key elements of smart grids including grid-connected vehicles, data-driven components, and the power system network. This will result in highlighting technical challenges of the integration of electric vehicles to the grid and the power network operation as well. Moreover, we discuss the four key research areas in the context of AI and its applications in intelligent power grids. The proposed research fields aid PhD candidates to consider these areas as the promising domains for investigation. © 2021 IEEE.