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  • 1.
    Borenius, Seppo
    et al.
    Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
    Gopalakrishnan, Pavithra
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems. Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
    Bertling Tjernberg, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Kantola, Raimo
    Aalto Univ, Sch Elect Engn, Dept Commun & Networking, Espoo 02150, Finland..
    Expert-Guided Security Risk Assessment of Evolving Power Grids2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 9, p. 3237-, article id 3237Article in journal (Refereed)
    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.

  • 2.
    Gopalakrishnan, Pavithra
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Alikhani, Parnian
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Shafique, Hamza
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bertling Tjernberg, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Hallinder, Jonathan
    EON, Stockholm, Sweden..
    Engström, Adam
    EON, Stockholm, Sweden..
    He, Ying
    Vattenfall, Stockholm, Sweden..
    Peak Demand Shaving Based on Solar and Load Forecasting at Port of Gavle2022In: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference 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.

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