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Ravikumar, Gelli, Hyder, Burhan, Govindarasu, Manimaran.  2020.  Efficient Modeling of IEC-61850 Logical Nodes in IEDs for Scalability in CPS Security Testbed. 2020 IEEE/PES Transmission and Distribution Conference and Exposition (T D). :1–5.

Though the deep penetration of cyber systems across the smart grid sub-domains enrich the operation of the wide-area protection, control, and smart grid applications, the stochastic nature of cyber-attacks by adversaries inflict their performance and the system operation. Various hardware-in-the-loop (HIL) cyber-physical system (CPS) testbeds have attempted to evaluate the cyberattack dynamics and power system perturbations for robust wide-area protection algorithms. However, physical resource constraints and modular integration designs have been significant barriers while modeling large-scale grid models (scalability) and have limited many of the CPS testbeds to either small-scale HIL environment or complete simulation environments. This paper proposes a meticulous design and efficient modeling of IEC-61850 logical nodes in physical relays to simulate large-scale grid models in a HIL real-time digital simulator environment integrated with industry-grade hardware and software systems for wide-area power system applications. The proposed meticulous design includes multi-breaker emulation in the physical relays, which extends the capacity of a physical relay to accommodate more number of CPS interfaces in the HIL CPS security testbed environment. We have used our existing HIL CPS security testbed to demonstrate scalability by the real-time performance of ten simultaneous IEEE-39 CPS grid models. The experiments demonstrated significant results by 100% real-time performance with zero overruns, and low latency while receiving and executing control signals from physical SEL relays via IEC-61850 and DNP-3 protocols to real-time digital simulator, substation remote terminal unit (RTU) software and supervisory control and data acquisition (SCADA) software at control center.

Hossain, Md. Turab, Hossain, Md. Shohrab, Narman, Husnu S..  2020.  Detection of Undesired Events on Real-World SCADA Power System through Process Monitoring. 2020 11th IEEE Annual Ubiquitous Computing, Electronics Mobile Communication Conference (UEMCON). :0779—0785.
A Supervisory Control and Data Acquisition (SCADA) system used in controlling or monitoring purpose in industrial process automation system is the process of collecting data from instruments and sensors located at remote sites and transmitting data at a central site. Most of the existing works on SCADA system focused on simulation-based study which cannot always mimic the real world situations. We propose a novel methodology that analyzes SCADA logs on offline basis and helps to detect process-related threats. This threat takes place when an attacker performs malicious actions after gaining user access. We conduct our experiments on a real-life SCADA system of a Power transmission utility. Our proposed methodology will automate the analysis of SCADA logs and systemically identify undesired events. Moreover, it will help to analyse process-related threats caused by user activity. Several test study suggest that our approach is powerful in detecting undesired events that might caused by possible malicious occurrence.
Cao, S., Zou, J., Du, X., Zhang, X..  2020.  A Successive Framework: Enabling Accurate Identification and Secure Storage for Data in Smart Grid. ICC 2020 - 2020 IEEE International Conference on Communications (ICC). :1–6.
Due to malicious eavesdropping, forgery as well as other risks, it is challenging to dispose and store collected power data from smart grid in secure manners. Blockchain technology has become a novel method to solve the above problems because of its de-centralization and tamper-proof characteristics. It is especially well known that data stored in blockchain cannot be changed, so it is vital to seek out perfect mechanisms to ensure that data are compliant with high quality (namely, accuracy of the power data) before being stored in blockchain. This will help avoid losses due to low-quality data modification or deletion as needed in smart grid. Thus, we apply the parallel vision theory on the identification of meter readings to realize accurate power data. A cloud-blockchain fusion model (CBFM) is proposed for the storage of accurate power data, allowing for secure conducting of flexible transactions. Only power data calculated by parallel visual system instead of image data collected originally via robot would be stored in blockchain. Hence, we define the quality assurance before data uploaded to blockchain and security guarantee after data stored in blockchain as a successive framework, which is a brand new solution to manage efficiency and security as a whole for power data and data alike in other scenes. Security analysis and performance evaluations are performed, which prove that CBFM is highly secure and efficient impressively.
Nuqui, Reynaldo, Hong, Junho, Kondabathini, Anil, Ishchenko, Dmitry, Coats, David.  2018.  A Collaborative Defense for Securing Protective Relay Settings in Electrical Cyber Physical Systems. 2018 Resilience Week (RWS). :49—54.
Modern power systems today are protected and controlled increasingly by embedded systems of computing technologies with a great degree of collaboration enabled by communication. Energy cyber-physical systems such as power systems infrastructures are increasingly vulnerable to cyber-attacks on the protection and control layer. We present a method of securing protective relays from malicious change in protective relay settings via collaboration of devices. Each device checks the proposed setting changes of its neighboring devices for consistency and coordination with its own settings using setting rules based on relay coordination principles. The method is enabled via peer-to-peer communication between IEDs. It is validated in a cyber-physical test bed containing a real time digital simulator and actual relays that communicate via IEC 61850 GOOSE messages. Test results showed improvement in cyber physical security by using domain based rules to block malicious changes in protection settings caused by simulated cyber-attacks. The method promotes the use of defense systems that are aware of the physical systems which they are designed to secure.
Hong, Junho, Nuqui, Reynaldo F., Kondabathini, Anil, Ishchenko, Dmitry, Martin, Aaron.  2019.  Cyber Attack Resilient Distance Protection and Circuit Breaker Control for Digital Substations. IEEE Transactions on Industrial Informatics. 15:4332—4341.
This paper proposes new concepts for detecting and mitigating cyber attacks on substation automation systems by domain-based cyber-physical security solutions. The proposed methods form the basis of a distributed security domain layer that enables protection devices to collaboratively defend against cyber attacks at substations. The methods utilize protection coordination principles to cross check protection setting changes and can run real-time power system analysis to evaluate the impact of the control commands. The transient fault signature (TFS)-based cross-correlation coefficient algorithm has been proposed to detect the false sampled values data injection attack. The proposed functions were verified in a hardware-in-the-loop (HIL) simulation using commercial relays and a real-time digital simulator (RTDS). Various types of cyber intrusions are tested using this test bed to evaluate the consequences and impacts of cyber attacks to power grid as well as to validate the performance of the proposed research-grade cyber attack mitigation functions.
Chen, Yu-Cheng, Gieseking, Tim, Campbell, Dustin, Mooney, Vincent, Grijalva, Santiago.  2019.  A Hybrid Attack Model for Cyber-Physical Security Assessment in Electricity Grid. 2019 IEEE Texas Power and Energy Conference (TPEC). :1–6.
A detailed model of an attack on the power grid involves both a preparation stage as well as an execution stage of the attack. This paper introduces a novel Hybrid Attack Model (HAM) that combines Probabilistic Learning Attacker, Dynamic Defender (PLADD) model and a Markov Chain model to simulate the planning and execution stages of a bad data injection attack in power grid. We discuss the advantages and limitations of the prior work models and of our proposed Hybrid Attack Model and show that HAM is more effective compared to individual PLADD or Markov Chain models.
Babay, Amy, Tantillo, Thomas, Aron, Trevor, Platania, Marco, Amir, Yair.  2018.  Network-Attack-Resilient Intrusion-Tolerant SCADA for the Power Grid. 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :255–266.
As key components of the power grid infrastructure, Supervisory Control and Data Acquisition (SCADA) systems are likely to be targeted by nation-state-level attackers willing to invest considerable resources to disrupt the power grid. We present Spire, the first intrusion-tolerant SCADA system that is resilient to both system-level compromises and sophisticated network-level attacks and compromises. We develop a novel architecture that distributes the SCADA system management across three or more active sites to ensure continuous availability in the presence of simultaneous intrusions and network attacks. A wide-area deployment of Spire, using two control centers and two data centers spanning 250 miles, delivered nearly 99.999% of all SCADA updates initiated over a 30-hour period within 100ms. This demonstrates that Spire can meet the latency requirements of SCADA for the power grid.
Liu, Dongqi.  2018.  A Creditability-based Intrusion Tolerant Method for Protection Equipment in Transformer Substations. 2018 China International Conference on Electricity Distribution (CICED). :1489–1492.
With the development of the interconnection of all things(IoT), a large number of mobile terminal devices with multiple users access the distribution network, and gradually form an open and interconnected network environment, which brings new challenges to the security and protection of the distribution network. In this paper, a method of analyzing the sensing data of the digital substation is proposed, which can prevent the abnormal data from causing the malfunction of the protective relays by calculating the creditability of the sensing data. Creditability calculation algorithm as well as the implementation of the intrusion tolerance strategy are studied throughout the paper. The simulation results show that the proposed creditability-based intrusion-tolerant(CIT) algorithm can ensure that the protective equipment have no protective malfunction from the false instructions or false data attacks, and the proposed intrusion tolerant algorithm has little affect on the real-time performance of the original protection algorithm, hence it has some practical value.
Obert, James, Chavez, Adrian.  2019.  Graph-Based Event Classification in Grid Security Gateways. 2019 Second International Conference on Artificial Intelligence for Industries (AI4I). :63—66.
In recent years the use of security gateways (SG) located within the electrical grid distribution network has become pervasive. SGs in substations and renewable distributed energy resource aggregators (DERAs) protect power distribution control devices from cyber and cyber-physical attacks. When encrypted communications within a DER network is used, TCP/IP packet inspection is restricted to packet header behavioral analysis which in most cases only allows the SG to perform anomaly detection of blocks of time-series data (event windows). Packet header anomaly detection calculates the probability of the presence of a threat within an event window, but fails in such cases where the unreadable encrypted payload contains the attack content. The SG system log (syslog) is a time-series record of behavioral patterns of network users and processes accessing and transferring data through the SG network interfaces. Threatening behavioral pattern in the syslog are measurable using both anomaly detection and graph theory. In this paper it will be shown that it is possible to efficiently detect the presence of and classify a potential threat within an SG syslog using light-weight anomaly detection and graph theory.
Rudolph, Hendryk, Lan, Tian, Strehl, Konrad, He, Qinwei, Lan, Yuanliang.  2019.  Simulating the Efficiency of Thermoelectrical Generators for Sensor Nodes. 2019 4th IEEE Workshop on the Electronic Grid (eGRID). :1—6.

In order to be more environmentally friendly, a lot of parts and aspects of life become electrified to reduce the usage of fossil fuels. This can be seen in the increased number of electrical vehicles in everyday life. This of course only makes a positive impact on the environment, if the electricity is produced environmentally friendly and comes from renewable sources. But when the green electrical power is produced, it still needs to be transported to where it's needed, which is not necessarily near the production site. In China, one of the ways to do this transport is to use High Voltage Direct Current (HVDC) technology. This of course means, that the current has to be converted to DC before being transported to the end user. That implies that the converter stations are of great importance for the grid security. Therefore, a precise monitoring of the stations is necessary. Ideally, this could be accomplished with wireless sensor nodes with an autarkic energy supply. A role in this energy supply could be played by a thermoelectrical generator (TEG). But to assess the power generated in the specific environment, a simulation would be highly desirable, to evaluate the power gained from the temperature difference in the converter station. This paper proposes a method to simulate the generated power by combining a model for the generator with a Computational Fluid Dynamics (CFD) model converter.

Castillo, Anya, Arguello, Bryan, Cruz, Gerardo, Swiler, Laura.  2019.  Cyber-Physical Emulation and Optimization of Worst-Case Cyber Attacks on the Power Grid. 2019 Resilience Week (RWS). 1:14–18.

In this paper we report preliminary results from the novel coupling of cyber-physical emulation and interdiction optimization to better understand the impact of a CrashOverride malware attack on a notional electric system. We conduct cyber experiments where CrashOverride issues commands to remote terminal units (RTUs) that are controlling substations within a power control area. We identify worst-case loss of load outcomes with cyber interdiction optimization; the proposed approach is a bilevel formulation that incorporates RTU mappings to controllable loads, transmission lines, and generators in the upper-level (attacker model), and a DC optimal power flow (DCOPF) in the lower-level (defender model). Overall, our preliminary results indicate that the interdiction optimization can guide the design of experiments instead of performing a “full factorial” approach. Likewise, for systems where there are important dependencies between SCADA/ICS controls and power grid operations, the cyber-physical emulations should drive improved parameterization and surrogate models that are applied in scalable optimization techniques.

Boakye-Boateng, Kwasi, Lashkari, Arash Habibi.  2019.  Securing GOOSE: The Return of One-Time Pads. 2019 International Carnahan Conference on Security Technology (ICCST). :1—8.

IEC 61850 is an international standard that is widely used in substation automation systems (SAS) in smart grids. During its development, security was not considered thus leaving SAS vulnerable to attacks from adversaries. IEC 62351 was developed to provide security recommendations for SAS against (distributed) denial-of-service, replay, alteration, spoofing and detection of devices attacks. However, real-time communications, which require protocols such as Generic Object-Oriented Substation Event (GOOSE) to function efficiently, cannot implement these recommendations due to latency constraints. There has been researching that sought to improve the security of GOOSE messages, however, some cannot be practically implemented due to hardware requirements while others are theoretical, even though latency requirements were met. This research investigates the possibility of encrypting GOOSE messages with One- Time Pads (OTP), leveraging the fact that encryption/decryption processes require the random generation of OTPs and modulo addition (XOR), which could be a realistic approach to secure GOOSE while maintaining latency requirements. Results show that GOOSE messages can be encrypted with some future work required.

Zou, Zhenwan, Chen, Jia, Hou, Yingsa, Song, Panpan, He, Ling, Yang, Huiting, Wang, Bin.  2019.  Design and Implementation of a New Intelligent Substation Network Security Defense System. 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 1:2709–2713.
In order to enhance the network security protection level of intelligent substation, this paper puts forward a model of intelligent substation network security defense system through the analysis of intelligent substation network security risk and protection demand, and using example proved the feasibility and effectiveness of the defense system. It is intelligent substation network security protection provides a new solution.
Farquharson, J., Wang, A., Howard, J..  2012.  Smart Grid Cyber Security and Substation Network Security. 2012 IEEE PES Innovative Smart Grid Technologies (ISGT). :1–5.

A successful Smart Grid system requires purpose-built security architecture which is explicitly designed to protect customer data confidentiality. In addition to the investment on electric power infrastructure for protecting the privacy of Smart Grid-related data, entities need to actively participate in the NIST interoperability framework process; establish policies and oversight structure for the enforcement of cyber security controls of the data through adoption of security best practices, personnel training, cyber vulnerability assessments, and consumer privacy audits.

Sahu, Abhijeet, Huang, Hao, Davis, Katherine, Zonouz, Saman.  2019.  SCORE: A Security-Oriented Cyber-Physical Optimal Response Engine. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–6.

Automatic optimal response systems are essential for preserving power system resilience and ensuring faster recovery from emergency under cyber compromise. Numerous research works have developed such response engine for cyber and physical system recovery separately. In this paper, we propose a novel cyber-physical decision support system, SCORE, that computes optimal actions considering pure and hybrid cyber-physical states, using Markov Decision Process (MDP). Such an automatic decision making engine can assist power system operators and network administrators to make a faster response to prevent cascading failures and attack escalation respectively. The hybrid nature of the engine makes the reward and state transition model of the MDP unique. Value iteration and policy iteration techniques are used to compute the optimal actions. Tests are performed on three and five substation power systems to recover from attacks that compromise relays to cause transmission line overflow. The paper also analyses the impact of reward and state transition model on computation. Corresponding results verify the efficacy of the proposed engine.

Zou, Zhenwan, Hou, Yingsa, Yang, Huiting, Li, Mingxuan, Wang, Bin, Guo, Qingrui.  2019.  Research and Implementation of Intelligent Substation Information Security Risk Assessment Tool. 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). :1306–1310.

In order to improve the information security level of intelligent substation, this paper proposes an intelligent substation information security assessment tool through the research and analysis of intelligent substation information security risk and information security assessment method, and proves that the tool can effectively detect it. It is of great significance to carry out research on industrial control systems, especially intelligent substation information security.

He, Zecheng, Raghavan, Aswin, Hu, Guangyuan, Chai, Sek, Lee, Ruby.  2019.  Power-Grid Controller Anomaly Detection with Enhanced Temporal Deep Learning. 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :160–167.
Controllers of security-critical cyber-physical systems, like the power grid, are a very important class of computer systems. Attacks against the control code of a power-grid system, especially zero-day attacks, can be catastrophic. Earlier detection of the anomalies can prevent further damage. However, detecting zero-day attacks is extremely challenging because they have no known code and have unknown behavior. Furthermore, if data collected from the controller is transferred to a server through networks for analysis and detection of anomalous behavior, this creates a very large attack surface and also delays detection. In order to address this problem, we propose Reconstruction Error Distribution (RED) of Hardware Performance Counters (HPCs), and a data-driven defense system based on it. Specifically, we first train a temporal deep learning model, using only normal HPC readings from legitimate processes that run daily in these power-grid systems, to model the normal behavior of the power-grid controller. Then, we run this model using real-time data from commonly available HPCs. We use the proposed RED to enhance the temporal deep learning detection of anomalous behavior, by estimating distribution deviations from the normal behavior with an effective statistical test. Experimental results on a real power-grid controller show that we can detect anomalous behavior with high accuracy (\textbackslashtextgreater99.9%), nearly zero false positives and short (\textbackslashtextless; 360ms) latency.
Wright, James G., Wolthusen, Stephen D..  2018.  Stealthy Injection Attacks Against IEC61850's GOOSE Messaging Service. 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). :1–6.
IEC61850 and IEC62351 combined provide a set of security promises for the communications channels that are used to run a substation automation system (SAS), that use IEC61850 based technologies. However, one area that is largely untouched by these security promises is the generic object oriented substation events (GOOSE) messaging service. GOOSE is designed to multicast commands and data across a substation within hard real time quality of service (QoS) requirements. This means that GOOSE is unable to implement the required security technologies as the added latency to any message would violate the QoS.
Obert, J., Chavez, A., Johnson, J..  2018.  Behavioral Based Trust Metrics and the Smart Grid. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :1490-1493.

To ensure reliable and predictable service in the electrical grid it is important to gauge the level of trust present within critical components and substations. Although trust throughout a smart grid is temporal and dynamically varies according to measured states, it is possible to accurately formulate communications and service level strategies based on such trust measurements. Utilizing an effective set of machine learning and statistical methods, it is shown that establishment of trust levels between substations using behavioral pattern analysis is possible. It is also shown that the establishment of such trust can facilitate simple secure communications routing between substations.

Iqbal, A., Mahmood, F., Shalaginov, A., Ekstedt, M..  2018.  Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems. 2018 IEEE International Conference on Big Data (Big Data). :3079–3087.
Power systems domain has generally been very conservative in terms of conducting digital forensic investigations, especially so since the advent of smart grids. This lack of research due to a multitude of challenges has resulted in absence of knowledge base and resources to facilitate such an investigation. Digitalization in the form of smart grids is upon us but in case of cyber-attacks, attribution to such attacks is challenging and difficult if not impossible. In this research, we have identified digital forensic artifacts resulting from a cyber-attack on Wide Area Monitoring, Protection and Control (WAMPAC) systems, which will help an investigator attribute an attack using the identified evidences. The research also shows the usage of sandboxing for digital forensics along with hardware-in-the-loop (HIL) setup. This is first of its kind effort to identify and acquire all the digital forensic evidences for WAMPAC systems which will ultimately help in building a body of knowledge and taxonomy for power system forensics.
Hasan, S., Ghafouri, A., Dubey, A., Karsai, G., Koutsoukos, X..  2018.  Vulnerability analysis of power systems based on cyber-attack and defense models. 2018 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Reliable operation of power systems is a primary challenge for the system operators. With the advancement in technology and grid automation, power systems are becoming more vulnerable to cyber-attacks. The main goal of adversaries is to take advantage of these vulnerabilities and destabilize the system. This paper describes a game-theoretic approach to attacker / defender modeling in power systems. In our models, the attacker can strategically identify the subset of substations that maximize damage when compromised. However, the defender can identify the critical subset of substations to protect in order to minimize the damage when an attacker launches a cyber-attack. The algorithms for these models are applied to the standard IEEE-14, 39, and 57 bus examples to identify the critical set of substations given an attacker and a defender budget.

Dhunna, G. S., Al-Anbagi, I..  2017.  A Low Power Cybersecurity Mechanism for WSNs in a Smart Grid Environment. 2017 IEEE Electrical Power and Energy Conference (EPEC). :1–6.

Smart Grid cybersecurity is one of the key ingredients for successful and wide scale adaptation of the Smart Grid by utilities and governments around the world. The implementation of the Smart Grid relies mainly on the highly distributed sensing and communication functionalities of its components such as Wireless Sensor Networks (WSNs), Phasor Measurement Units (PMUs) and other protection devices. This distributed nature and the high number of connected devices are the main challenges for implementing cybersecurity in the smart grid. As an example, the North American Electric Reliability Corporation (NERC) issued the Critical Infrastructure Protection (CIP) standards (CIP-002 through CIP-009) to define cybersecurity requirements for critical power grid infrastructure. However, NERC CIP standards do not specify cybersecurity for different communication technologies such as WSNs, fiber networks and other network types. Implementing security mechanisms in WSNs is a challenging task due to the limited resources of the sensor devices. WSN security mechanisms should not only focus on reducing the power consumption of the sensor devices, but they should also maintain high reliability and throughput needed by Smart Grid applications. In this paper, we present a WSN cybersecurity mechanism suitable for smart grid monitoring application. Our mechanism can detect and isolate various attacks in a smart grid environment, such as denial of sleep, forge and replay attacks in an energy efficient way. Simulation results show that our mechanism can outperform existing techniques while meeting the NERC CIP requirements.

Salles-Loustau, G., Garcia, L., Sun, P., Dehnavi, M., Zonouz, S..  2017.  Power Grid Safety Control via Fine-Grained Multi-Persona Programmable Logic Controllers. 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm). :283–288.

Trustworthy and safe operation of the power grid critical infrastructures relies on secure execution of low-level substation controller devices such as programmable logic controllers (PLCs). Currently, there are very few security protection solutions deployed on these devices to ensure provenance control: to execute controller code on the device that is developed by trusted parties and complies with safety/security policies that are defined by the code developer as well as the power grid operators. Resource-limited PLC controllers have been becoming increasingly popular among not only legitimate system operators, but also malicious adversaries such as the most recent Stuxnet and BlackEnergy malware that caused various damages such as unauthorized infrastructural safety and integrity violations. We present PLCtrust, a domain-specific solution that deploys virtual micro security-perimeters, so-called capsules, and the corresponding device-level runtime power system-safety policy enforcement dynamically. PLCtrust makes use of data taint analysis to monitor and control data flow among the capsules based on data owner-defined policies. PLCtrust provides the operators with a transparent and lightweight solution to address various safety-critical data protection requirements. PLCtrust also provides the legitimate third-party controller code developers with a taint-aware programming interface to develop applications in compliance with the dynamic power system safety/security policies. Our experimental results on real-world settings show that PLCtrust is transparent to the end-users while ensuring the power grid safety maintenance with minimal performance overhead.

Lan, T., Wang, W., Huang, G. M..  2017.  False data injection attack in smart grid topology control: Vulnerability and countermeasure. 2017 IEEE Power Energy Society General Meeting. :1–5.
Cyber security is a crucial factor for modern power system as many applications are heavily relied on the result of state estimation. Therefore, it is necessary to assess and enhance cyber security for new applications in power system. As an emerging technology, smart grid topology control has been investigated in stability and reliability perspectives while the associated cyber security issue is not studied before. In successful false data injection attack (FDIA) against AC state estimation, attacker could alter online stability check result by decreasing real power flow measurement on the switching target line to undermine physical system stability in topology control. The physical impact of FDIA on system control operation and stability are illustrated. The vulnerability is discussed on perfect FDIA and imperfect FDIA against residue based bad data detection and corresponding countermeasure is proposed to secure critical substations in the system. The vulnerability and countermeasure are demonstrated on IEEE 24 bus reliability test system (RTS).
Wiest, P., Groß, D., Rudion, K., Probst, A..  2017.  Security-constrained dynamic curtailment method for renewable energy sources in grid planning. 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). :1–6.

This paper presents a new approach for a dynamic curtailment method for renewable energy sources that guarantees fulfilling of (n-1)-security criteria of the system. Therefore, it is applicable to high voltage distribution grids and has compliance to their planning guidelines. The proposed dynamic curtailment method specifically reduces the power feed-in of renewable energy sources up to a level, where no thermal constraint is exceeded in the (n-1)-state of the system. Based on AC distribution factors, a new formulation of line outage distribution factors is presented that is applicable for outages consisting of a single line or multiple segment lines. The proposed method is tested using a planning study of a real German high voltage distribution grid. The results show that any thermal loading limits are exceeded by using the dynamic curtailment approach. Therefore, a significant reduction of the grid reinforcement can be achieved by using a small amount of curtailed annual energy from renewable energy sources.