Biblio

An unobservable false data injection (FDI) attack on AC state estimation (SE) is introduced and its consequences on the physical system are studied. With a focus on understanding the physical consequences of FDI attacks, a bi-level optimization problem is introduced whose objective is to maximize the physical line flows subsequent to an FDI attack on DC SE. The maximization is subject to constraints on both attacker resources (size of attack) and attack detection (limiting load shifts) as well as those required by DC optimal power flow (OPF) following SE. The resulting attacks are tested on a more realistic non-linear system model using AC state estimation and ACOPF, and it is shown that, with an appropriately chosen sub-network, the attacker can overload transmission lines with moderate shifts of load.

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).

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.

As societies are becoming more dependent on the power grids, the security issues and blackout threats are more emphasized. This paper proposes a new graph model for online visualization and assessment of power grid security. The proposed model integrates topology and power flow information to estimate and visualize interdependencies between the lines in the form of line dependency graph (LDG) and immediate threats graph (ITG). These models enable the system operator to predict the impact of line outage and identify the most vulnerable and critical links in the power system. Line Vulnerability Index (LVI) and Line Criticality Index (LCI) are introduced as two indices extracted from LDG to aid the operator in decision making and contingency selection. This package can be useful in enhancing situational awareness in power grid operation by visualization and estimation of system threats. The proposed approach is tested for security analysis of IEEE 30-bus and IEEE 118-bus systems and the results are discussed.

The inherent heterogeneity in the uncertainty of variable generations (e.g., wind, solar, tidal and wave-power) in electric grid coupled with the dynamic nature of distributed architecture of sub-systems, and the need for information synchronization has made the problem of resource allocation and monitoring a tremendous challenge for the next-generation smart grid. Unfortunately, the deployment of distributed algorithms across micro grids have been overlooked in the electric grid sector. In particular, centralized methods for managing resources and data may not be sufficient to monitor a complex electric grid. This paper discusses a decentralized constrained decomposition using Linear Programming (LP) that optimizes the inter-area transfer across micro grids that reduces total generation cost for the grid. A test grid of IEEE 14-bus system is sectioned into two and three areas, and its effect on inter-transfer is analyzed.

Physical consequences to power systems of false data injection cyber-attacks are considered. Prior work has shown that the worst-case consequences of such an attack can be determined using a bi-level optimization problem, wherein an attack is chosen to maximize the physical power flow on a target line subsequent to re-dispatch. This problem can be solved as a mixed-integer linear program, but it is difficult to scale to large systems due to numerical challenges. Three new computationally efficient algorithms to solve this problem are presented. These algorithms provide lower and upper bounds on the system vulnerability measured as the maximum power flow subsequent to an attack. Using these techniques, vulnerability assessments are conducted for IEEE 118-bus system and Polish system with 2383 buses.

Cascading failure is an intrinsic threat of power grid to cause enormous cost of society, and it is very challenging to be analyzed. The risk of cascading failure depends both on its probability and the severity of consequence. It is impossible to analyze all of the intrinsic attacks, only the critical and high probability initial events should be found to estimate the risk of cascading failure efficiently. To recognize the critical and high probability events, a cascading failure analysis model for power transmission grid is established based on complex network theory (CNT) in this paper. The risk coefficient of transmission line considering the betweenness, load rate and changeable outage probability is proposed to determine the initial events of power grid. The development tendency of cascading failure is determined by the network topology, the power flow and boundary conditions. The indicators of expected percentage of load loss and line cut are used to estimate the risk of cascading failure caused by the given initial malfunction of power grid. Simulation results from the IEEE RTS-79 test system show that the risk of cascading failure has close relations with the risk coefficient of transmission lines. The value of risk coefficient could be useful to make vulnerability assessment and to design specific action to reduce the topological weakness and the risk of cascading failure of power grid.

The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.