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Smart Grid security has motivated numerous researches from multiple disciplines. Among the recently discovered security challenges, the False Data Injection (FDI) has drawn great attention from power and energy, computer, and communication research community, because of its potential to manipulate measurements in state estimation (SE) without being identified by conventional bad data detection (BDD)...
In recent years, renewable energy has been largely integrated into power grids as well as micro-grids. The intermittent power injection will affect the stability of the systems, especially for the small-scale ones, such as the micro-grids. Among all the stability issues, load frequency control (LFC) of smart grid with renewable energy integration has become critical in the community. This paper studies...
In this paper, the impact of signal transmission delays on static VAR compensator (SVC) based power system damping control using reinforcement learning is investigated. The SVC is used to damp low-frequency oscillation between interconnected power systems under fault conditions, where measured signals from remote areas are first collected and then transmitted to the controller as the inputs. Inevitable...
In this paper, we integrate a goal network into the existing dual heuristic dynamic programming (DHP) architecture, and study its damping performance on the multi-machine power system. There are four types of neural network in our proposed design: a goal network, a critic network, an action network and a model network. The motivation of this design is to build a general mapping between the system...
Recently, the sequential attack, where multiple malignant contingencies are launched by attackers sequentially, has revealed power grid vulnerability under cascading failures. This paper systematically analyzes properties and features of N-k cascaded- based sequential line-switching attacks using a DC power flow based cascading failure simulator (DC- CFS). This paper first explains the key factors...
In this paper, a particle swarm optimization with ε-greedy (ePSO) algorithm and group search optimizer (GSO) algorithm are compared with the classic PSO algorithm for the optimal control of DFIG wind generation based on small signal stability analysis (SSSA). In the modified ePSO algorithm, the cooperative learning principle among particles has been introduced, namely, particles not only adjust its...
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