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Gopalakrishnan, Pavithra
Publications (2 of 2) Show all publications
Borenius, S., Gopalakrishnan, P., Bertling Tjernberg, L. & Kantola, R. (2022). Expert-Guided Security Risk Assessment of Evolving Power Grids. Energies, 15(9), 3237, Article ID 3237.
Open this publication in new window or tab >>Expert-Guided Security Risk Assessment of Evolving Power Grids
2022 (English)In: Energies, E-ISSN 1996-1073, Vol. 15, no 9, p. 3237-, article id 3237Article in journal (Refereed) Published
Abstract [en]

Electric power grids, which form an essential part of the critical infrastructure, are evolving into highly distributed, dynamic networks in order to address the climate change. This fundamental transition relies on extensive automation solutions based on communications and information technologies. Thus, it also gives rise to new attack points for malicious actors and consequently, increases the vulnerability of the electric energy system. This study presents a qualitative assessment of power grid cybersecurity through expert interviews across countries in Europe and the U.S. to gain understanding of the latest developments and trends in the cybersecurity of future electric energy systems. The horizon of the assessment is 10 years spanning until the early 2030s. Thereafter, the study identifies how and to which extent the risks identified to be most significant are understood and addressed in the latest research and industry publications aiming at identifying areas deserving specific further attention. The most significant threats based on the assessment are False Data Injection (FDI), Denial of Service (DoS) supply chain, and ransomware and malware attacks.

Place, publisher, year, edition, pages
MDPI AG, 2022
Keywords
smart grids, power grids, cybersecurity, security risk assessment
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-313050 (URN)10.3390/en15093237 (DOI)000794482600001 ()2-s2.0-85129724090 (Scopus ID)
Note

QC 20220531

Available from: 2022-05-31 Created: 2022-05-31 Last updated: 2024-03-15Bibliographically approved
Gopalakrishnan, P., Alikhani, P., Shafique, H., Bertling Tjernberg, L., Hallinder, J., Engström, A. & He, Y. (2022). Peak Demand Shaving Based on Solar and Load Forecasting at Port of Gavle. In: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022: . Paper presented at 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Manchester, 12 June 2022, through 15 June 2022. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Peak Demand Shaving Based on Solar and Load Forecasting at Port of Gavle
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2022 (English)In: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper, Published paper (Refereed)
Abstract [en]

Solar energy is considered as one of the most promising solutions to prevent climate change, and optimal utilization of solar energy contributes to reducing dependence on non-renewable energy sources. Distributed generation can help support the delivery of clean and reliable power to consumers. In this paper, an Energy Management System (EMS) is developed along with load and Photovoltaic (PV) generation forecasting to perform peak shaving of electricity demand. The results from the proposed method are implemented in a real case study, in Port of Gavle in Sweden. Total revenue generated from services of peak-shaving and frequency regulation is maximum in the scenario considering high PV generation and high consumption on a selected experimental day in July. The results show that PV-battery storage systems are effective options to increase the integration of renewable energies in the grid, flatten the load, and achieve stabilized operation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Series
International Conference on Probabilistic Methods Applied to Power Systems, ISSN 2642-6730
Keywords
electricity generation, forecast, frequency regulation, peak shaving, XGBoost
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-320422 (URN)10.1109/PMAPS53380.2022.9810648 (DOI)000853744900091 ()2-s2.0-85135074197 (Scopus ID)
Conference
17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Manchester, 12 June 2022, through 15 June 2022
Note

QC 20221021

Part of proceedings: ISBN 978-166541211-7

Available from: 2022-10-21 Created: 2022-10-21 Last updated: 2022-10-21Bibliographically approved
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