Security attacks on smart grid scheduling and their defences: a game-theoretic approach

Pilz, Matthias; Naeini, Fariborz Baghaei; Grammont, Ketil; Smagghe, C.; Davis, Mark J.; Nebel, Jean‐Christophe; Al‐Fagih, Luluwah; Pfluegel, Eckhard

doi:10.1007/s10207-019-00460-z

Cited by 29 publications

(14 citation statements)

References 45 publications

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“…A greedy implicit enumeration algorithm was also employed to find the global optimum. The impact of FDI attacks on compromising the forecasted demand data was investigated in [44]. To assist the utilities in preventing such attacks, a Game Theory model was proposed, and the Nash equilibrium was determined.…”

Section: Other Methodsmentioning

confidence: 99%

Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review

Mohammadi

2021

Energies

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In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is no all-inclusive solution to fit all power systems requirements. Therefore, the recently proposed cyber-attack detection and identification methods are quantitatively compared and discussed.

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Section: Other Methodsmentioning

confidence: 99%

Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review

Mohammadi

2021

Energies

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“…Random errors ( ϵ t pv , t = 1, …, T ) were generated in a normal distribution and a standard deviation of 10%kWp. Then, a simple smoothing method was applied to each error i th to make the forecast more realistic :

ϵ_{t}^{italicpv} = (ϵ_{i - 1}^{italicpv} + ϵ_{i}^{italicpv} + ϵ_{i + 1}^{italicpv}) / 3

. Adding these errors into the 5‐min averaged values of the real solar power condition forms the forecast.…”

Section: Case Studymentioning

confidence: 99%

“…, T ) were generated in a normal distribution and a standard deviation of 10%kWp. Then, a simple smoothing method was applied to each error i th to make the forecast more realistic [39]:…”

Section: Data For Simulation Real Conditionmentioning

confidence: 99%

Home Energy Management Systems under Effects of Solar‐Battery Smart Inverter Functions

Dao

Ishii

Takenobu

et al. 2020

IEEJ Transactions Elec Engng

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Rooftop solar panels paired with home‐scale batteries are increasingly popular in the residential area and they bring a fantastic opportunity to households, considered as prosumers, to make benefits from trading electricity. Unlike research in the literature, we consider the trading with technical influences of utility requirements: Volt‐Watt and Volt‐Var functions. As possible active power curtailments may occur and lead to economic losses to households, our work reveals how a home energy management system (HEMS) maximizes profit from trading energy with an aggregator and an electricity retailer. Appropriate optimization problems are formulated with technical constraints, these functions, and home appliances. HEMS responses are optimized in two phases. The first phase is for planning an optimal day‐ahead energy commitment to the aggregator with a consideration of the predicted power curtailments. On the day of operation, the second phase tries to follow the commitment by reoptimizing the responses in the real condition. Simulation of a practical power system shows that addressing these functions can mitigate power curtailment, reduce economic loss, and improve home profits. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…Game theory has been applied to a variety of subject areas such as biology [16], economics [17], computer science [18] and energy [19,20]. In general, game theory is used to mathematically model systems of competing agents.…”

Section: Introductionmentioning

confidence: 99%

Game theory to enhance stock management of Personal Protective Equipment (PPE) during the COVID-19 outbreak

et al. 2021

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Since the outbreak of the COVID-19 pandemic, many healthcare facilities have suffered from shortages in medical resources, particularly in Personal Protective Equipment (PPE). In this paper, we propose a game-theoretic approach to schedule PPE orders among healthcare facilities. In this PPE game, each independent healthcare facility optimises its own storage utilisation in order to keep its PPE cost at a minimum. Such a model can reduce peak demand considerably when applied to a variable PPE consumption profile. Experiments conducted for NHS England regions using actual data confirm that the challenge of securing PPE supply during disasters such as COVID-19 can be eased if proper stock management procedures are adopted. These procedures can include early stockpiling, increasing storage capacities and implementing measures that can prolong the time period between successive infection waves, such as social distancing measures. Simulation results suggest that the provision of PPE dedicated storage space can be a viable solution to avoid straining PPE supply chains in case a second wave of COVID-19 infections occurs.

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Security attacks on smart grid scheduling and their defences: a game-theoretic approach

Cited by 29 publications

References 45 publications

Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review

Emerging Challenges in Smart Grid Cybersecurity Enhancement: A Review

Home Energy Management Systems under Effects of Solar‐Battery Smart Inverter Functions

Game theory to enhance stock management of Personal Protective Equipment (PPE) during the COVID-19 outbreak

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