Assessing the impact of cybersecurity attacks on energy systems

This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios...
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Autor*in:	Vijayshankar, Sanjana [verfasserIn] Chang, Chin-Yao [verfasserIn] Utkarsh, Kumar [verfasserIn] Wald, Dylan [verfasserIn] Ding, Fei [verfasserIn] Balamurugan, Sivasathya Pradha [verfasserIn] King, Jennifer [verfasserIn] Macwan, Richard [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control

Übergeordnetes Werk:	Enthalten in: Applied energy - Amsterdam [u.a.] : Elsevier Science, 1975, 345
Übergeordnetes Werk:	volume:345

DOI / URN:	10.1016/j.apenergy.2023.121297

Katalog-ID:	ELV010471766

Internformat


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520			\|a This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.
650		4	\|a Model predictive control
650		4	\|a Energy systems
650		4	\|a Optimization
650		4	\|a Buildings
650		4	\|a Distributed energy resources (DERs)
650		4	\|a Distributed control
700	1		\|a Chang, Chin-Yao \|e verfasserin \|4 aut
700	1		\|a Utkarsh, Kumar \|e verfasserin \|0 (orcid)0000-0002-3270-8244 \|4 aut
700	1		\|a Wald, Dylan \|e verfasserin \|0 (orcid)0000-0002-9742-5288 \|4 aut
700	1		\|a Ding, Fei \|e verfasserin \|0 (orcid)0000-0002-2500-1275 \|4 aut
700	1		\|a Balamurugan, Sivasathya Pradha \|e verfasserin \|0 (orcid)0000-0003-0241-1316 \|4 aut
700	1		\|a King, Jennifer \|e verfasserin \|4 aut
700	1		\|a Macwan, Richard \|e verfasserin \|0 (orcid)0000-0002-1740-5907 \|4 aut
773	0	8	\|i Enthalten in \|t Applied energy \|d Amsterdam [u.a.] : Elsevier Science, 1975 \|g 345 \|h Online-Ressource \|w (DE-627)320406709 \|w (DE-600)2000772-3 \|w (DE-576)256140251 \|x 1872-9118 \|7 nnns
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936	b	k	\|a 52.50 \|j Energietechnik: Allgemeines \|q VZ
951			\|a AR
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Indexfelder

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publishDate	2023
allfields	10.1016/j.apenergy.2023.121297 doi (DE-627)ELV010471766 (ELSEVIER)S0306-2619(23)00661-X DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Vijayshankar, Sanjana verfasserin aut Assessing the impact of cybersecurity attacks on energy systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks. Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control Chang, Chin-Yao verfasserin aut Utkarsh, Kumar verfasserin (orcid)0000-0002-3270-8244 aut Wald, Dylan verfasserin (orcid)0000-0002-9742-5288 aut Ding, Fei verfasserin (orcid)0000-0002-2500-1275 aut Balamurugan, Sivasathya Pradha verfasserin (orcid)0000-0003-0241-1316 aut King, Jennifer verfasserin aut Macwan, Richard verfasserin (orcid)0000-0002-1740-5907 aut Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 345 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:345 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 345
spelling	10.1016/j.apenergy.2023.121297 doi (DE-627)ELV010471766 (ELSEVIER)S0306-2619(23)00661-X DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Vijayshankar, Sanjana verfasserin aut Assessing the impact of cybersecurity attacks on energy systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks. Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control Chang, Chin-Yao verfasserin aut Utkarsh, Kumar verfasserin (orcid)0000-0002-3270-8244 aut Wald, Dylan verfasserin (orcid)0000-0002-9742-5288 aut Ding, Fei verfasserin (orcid)0000-0002-2500-1275 aut Balamurugan, Sivasathya Pradha verfasserin (orcid)0000-0003-0241-1316 aut King, Jennifer verfasserin aut Macwan, Richard verfasserin (orcid)0000-0002-1740-5907 aut Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 345 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:345 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 345
allfields_unstemmed	10.1016/j.apenergy.2023.121297 doi (DE-627)ELV010471766 (ELSEVIER)S0306-2619(23)00661-X DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Vijayshankar, Sanjana verfasserin aut Assessing the impact of cybersecurity attacks on energy systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks. Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control Chang, Chin-Yao verfasserin aut Utkarsh, Kumar verfasserin (orcid)0000-0002-3270-8244 aut Wald, Dylan verfasserin (orcid)0000-0002-9742-5288 aut Ding, Fei verfasserin (orcid)0000-0002-2500-1275 aut Balamurugan, Sivasathya Pradha verfasserin (orcid)0000-0003-0241-1316 aut King, Jennifer verfasserin aut Macwan, Richard verfasserin (orcid)0000-0002-1740-5907 aut Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 345 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:345 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 345
allfieldsGer	10.1016/j.apenergy.2023.121297 doi (DE-627)ELV010471766 (ELSEVIER)S0306-2619(23)00661-X DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Vijayshankar, Sanjana verfasserin aut Assessing the impact of cybersecurity attacks on energy systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks. Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control Chang, Chin-Yao verfasserin aut Utkarsh, Kumar verfasserin (orcid)0000-0002-3270-8244 aut Wald, Dylan verfasserin (orcid)0000-0002-9742-5288 aut Ding, Fei verfasserin (orcid)0000-0002-2500-1275 aut Balamurugan, Sivasathya Pradha verfasserin (orcid)0000-0003-0241-1316 aut King, Jennifer verfasserin aut Macwan, Richard verfasserin (orcid)0000-0002-1740-5907 aut Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 345 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:345 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 345
allfieldsSound	10.1016/j.apenergy.2023.121297 doi (DE-627)ELV010471766 (ELSEVIER)S0306-2619(23)00661-X DE-627 ger DE-627 rda eng 620 VZ 52.50 bkl Vijayshankar, Sanjana verfasserin aut Assessing the impact of cybersecurity attacks on energy systems 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks. Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control Chang, Chin-Yao verfasserin aut Utkarsh, Kumar verfasserin (orcid)0000-0002-3270-8244 aut Wald, Dylan verfasserin (orcid)0000-0002-9742-5288 aut Ding, Fei verfasserin (orcid)0000-0002-2500-1275 aut Balamurugan, Sivasathya Pradha verfasserin (orcid)0000-0003-0241-1316 aut King, Jennifer verfasserin aut Macwan, Richard verfasserin (orcid)0000-0002-1740-5907 aut Enthalten in Applied energy Amsterdam [u.a.] : Elsevier Science, 1975 345 Online-Ressource (DE-627)320406709 (DE-600)2000772-3 (DE-576)256140251 1872-9118 nnns volume:345 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 52.50 Energietechnik: Allgemeines VZ AR 345
language	English
source	Enthalten in Applied energy 345 volume:345
sourceStr	Enthalten in Applied energy 345 volume:345
format_phy_str_mv	Article
bklname	Energietechnik: Allgemeines
institution	findex.gbv.de
topic_facet	Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control
dewey-raw	620
isfreeaccess_bool	false
container_title	Applied energy
authorswithroles_txt_mv	Vijayshankar, Sanjana @@aut@@ Chang, Chin-Yao @@aut@@ Utkarsh, Kumar @@aut@@ Wald, Dylan @@aut@@ Ding, Fei @@aut@@ Balamurugan, Sivasathya Pradha @@aut@@ King, Jennifer @@aut@@ Macwan, Richard @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320406709
dewey-sort	3620
id	ELV010471766
language_de	englisch
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author	Vijayshankar, Sanjana
spellingShingle	Vijayshankar, Sanjana ddc 620 bkl 52.50 misc Model predictive control misc Energy systems misc Optimization misc Buildings misc Distributed energy resources (DERs) misc Distributed control Assessing the impact of cybersecurity attacks on energy systems
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topic_title	620 VZ 52.50 bkl Assessing the impact of cybersecurity attacks on energy systems Model predictive control Energy systems Optimization Buildings Distributed energy resources (DERs) Distributed control
topic	ddc 620 bkl 52.50 misc Model predictive control misc Energy systems misc Optimization misc Buildings misc Distributed energy resources (DERs) misc Distributed control
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title	Assessing the impact of cybersecurity attacks on energy systems
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title_full	Assessing the impact of cybersecurity attacks on energy systems
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author_browse	Vijayshankar, Sanjana Chang, Chin-Yao Utkarsh, Kumar Wald, Dylan Ding, Fei Balamurugan, Sivasathya Pradha King, Jennifer Macwan, Richard
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title_sort	assessing the impact of cybersecurity attacks on energy systems
title_auth	Assessing the impact of cybersecurity attacks on energy systems
abstract	This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.
abstractGer	This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.
abstract_unstemmed	This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.
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title_short	Assessing the impact of cybersecurity attacks on energy systems
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author2	Chang, Chin-Yao Utkarsh, Kumar Wald, Dylan Ding, Fei Balamurugan, Sivasathya Pradha King, Jennifer Macwan, Richard
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doi_str	10.1016/j.apenergy.2023.121297
up_date	2024-07-06T18:06:33.105Z
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