Dynamic Data Injection Attack Detection of Cyber Physical Power Systems With Uncertainties

Wang, Huaizhi; Ruan, Jiaqi; Zhou, Bin; Li, Canbing; Wu, Qiuwei; Raza, Muhammad Qamar; Cao, Guang-Zhong

doi:10.1109/tii.2019.2902163

Cited by 91 publications

(44 citation statements)

References 45 publications

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“…where p i and q i are the active and reactive power injected into bus i. p ij and q ij are the active and reactive power flows of line i-j out from the attack region. From (27) and 28, we see that the measurements in the non-attack region are not attacked. Thus,p ij andq ij in (25) and (26) are of the given values, which will change the Jacobian matrix of the power injected into the boundary buses.…”

Section: Fdi Attack With Complete Network Informationmentioning

confidence: 99%

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A review of cyber security risks of power systems: from static to dynamic false data attacks

2020

Prot Control Mod Power Syst

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With the rapid development of the smart grid and increasingly integrated communication networks, power grids are facing serious cyber-security problems. This paper reviews existing studies on the impact of false data injection attacks on power systems from three aspects. First, false data injection can adversely affect economic dispatch by increasing the operational cost of the power system or causing sequential overloads and even outages. Second, attackers can inject false data to the power system state estimator, and this will prevent the operators from obtaining the true operating conditions of the system. Third, false data injection attacks can degrade the distributed control of distributed generators or microgrids inducing a power imbalance between supply and demand. This paper fully covers the potential vulnerabilities of power systems to cyber-attacks to help system operators understand the system vulnerability and take effective countermeasures.

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Section: Fdi Attack With Complete Network Informationmentioning

confidence: 99%

“…To account for the dynamic behavior of FDI, (17) can be easily reformulated as a summation of z − Hx over T snapshots, and the resulting optimization problem can be solved in a similar way. The details can be found in [27].…”

Section: Fdi Attack With Complete Network Informationmentioning

confidence: 99%

A review of cyber security risks of power systems: from static to dynamic false data attacks

2020

Prot Control Mod Power Syst

View full text Add to dashboard Cite

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“…The input-output table of HLCA is the same as that of EIOLCA. The advantage of HLCA is that it can eliminate the truncation error, and can also incorporate the usage and recycling stages into the evaluation scope [31], [32]. However, HLCA is still in its infancy stage for practical application because it has high requirements for matrix calculations.…”

Section: B Life Cycle Assessmentmentioning

confidence: 99%

Eco-Cost Analysis of Split Air-Conditioner Using Activity-Based Costing Method

Liu

Yang³

et al. 2020

IEEE Access

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Split air conditioner (SAC) plays a critical role for temperature control of buildings. In recent years, the manufacturing process of SAC tends to consider energy-saving and environmental protection factors to reduce air pollution and alleviate energy crisis. However, the design of environmental-friendly SAC will increase the manufacturing cost, thereby increasing the burden on airconditioning companies. Therefore, the eco-cost analysis of SAC is of great significance for air conditioner manufacturers. To this end, a new SAC eco-cost assessment method based on activity based costing method is innovatively proposed in this paper. In this method, a K-nearest neighbor algorithm is used to deal with the missing data in SAC samples. An environmental and non-environmental cost assessment approach is developed based on the activity-based costing method to estimate the eco-cost of SAC over its whole life cycle. In addition, the impact of energy efficiency deviation on SAC eco-cost is numerically analyzed. Finally, the proposed ecocost assessment method is programmed on a Gabi software, and validated using real SAC data from a Chinese airconditioning company. Simulation results show that the proposed method can provide an estimate of the eco-cost of SAC, thus helping airconditioning companies to improve their competitiveness in the future where energy-saving and emission reduction are increasingly important. INDEX TERMS Eco-cost analysis, split air conditioner, life cycle assessment, activity-based costing method, Gabi software.

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“…Therefore, how to reduce the energy consumption of airconditioning systems has received great attention from both academics and industry. In addition, the advancement of communication and power electronics technology has led the development of power systems from centralized to distributed [4], and new technologies such as microgrid have emerged. Microgrid refers to a small power generation and distribution system composed of distributed generator, energy storage, loads and protection devices [5].…”

Section: Introductionmentioning

confidence: 99%

Air-Conditioning Load Forecasting for Prosumer Based on Meta Ensemble Learning

Chen¹,

2020

IEEE Access

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Accurate and reliable prediction of airconditioning load plays a significant role in prosumer energy management system (EMS), because airconditioning load accounts for a large proportion of the building's total energy consumption. This paper proposes a new meta ensemble learning method to realize short-term prediction of airconditioning load for prosumers. This method is a hybrid of meta ensemble learning and stacked auto-encoder (SAE). First, we design multiple different forecasting structures based on SAE to achieve point prediction of airconditioning loads. SAE is used to learn the deep features in airconditioning load data. Second, a new meta ensemble learning prediction model is proposed. Meta ensemble learning is used to learn the nonlinear features and invariant structures in data, and determine the coefficients of each SAE-based point forecaster. Finally, the prediction results of each point forecaster are aggregated and integrated to estimate the final airconditioning load prediction result. Airconditioning load data from a commercial building in Singapore are used to validate the feasibility and effectiveness of the proposed method, demonstrating that the proposed meta ensemble learning method is attractive in prosumer energy management. INDEX TERMS Airconditioning load, load prediction, meta learning, ensemble learning, prosumer energy management system.

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Dynamic Data Injection Attack Detection of Cyber Physical Power Systems With Uncertainties

Cited by 91 publications

References 45 publications

A review of cyber security risks of power systems: from static to dynamic false data attacks

A review of cyber security risks of power systems: from static to dynamic false data attacks

Eco-Cost Analysis of Split Air-Conditioner Using Activity-Based Costing Method

Air-Conditioning Load Forecasting for Prosumer Based on Meta Ensemble Learning

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