Biblio

In this paper, a novel method is proposed to assess the power system resilience considering the impacts of hurricanes. Firstly, the transmission line outage model correlated to wind speed is developed. Then, Probability Load Flow (PLF) considering the random outage of lines and the variation of loads is designed, and Latin Hypercube Sampling (LHS) is used to improve the efficiency of Monte Carlo Simulation (MCS) in solving PLF. Moreover, risk indices, including line overloading, node voltage exceeding limit, load shedding and system collapse, are established to assess the resilience of power systems during hurricanes. The method is tested with a modified IEEE 14-bus system, and simulation results indicate the effectiveness of the proposed approach.

This paper proposes a power network vulnerability analysis method based on topological approach considering of uncertainties from high-penetrated wind generations. In order to assess the influence of the impact of wind generation owing to its variable wind speed etc., the Quasi Monte Carlo based probabilistic load flow is adopted and performed. On the other hand, an extended stochastic topological vulnerability method involving Complex Network theory with probabilistic load flow is proposed. Corresponding metrics, namely stochastic electrical betweenness and stochastic net-ability are proposed respectively and applied to analyze the vulnerability of power network with wind generations. The case study of CIGRE medium voltage benchmark network is performed for illustration and evaluation. Furthermore, a cascading failures model considering the stochastic metrics is also developed to verify the effectiveness of proposed methodology.

False data injection attack (FDIA) destroys the automatic generation control (AGC) system and leads to unstable operation of the power system. Fast and accurate detection can help prevent and disrupt malicious attacks. This paper proposes an improved detection method, which is combined with fuzzy theory and support vector machine (SVM) to identify various types of attacks. The impacts of different types of FDIAs on the AGC system are analyzed, and the reliability of the method is proved by a large number of experimental data. This experiment is simulated on a single-area LFC system and the effects of adding a wind storage system were compared in a dynamic model. Simulation studies also show a higher accuracy of fuzzy support vector machine (FSVM) than traditional SVM and fuzzy pattern trees (FPTs).

In this paper, we propose a theoretical framework to investigate the eavesdropping behavior in underwater acoustic sensor networks. In particular, we quantify the eavesdropping activities by the eavesdropping probability. Our derived results show that the eavesdropping probability heavily depends on acoustic signal frequency, underwater acoustic channel characteristics (such as spreading factor and wind speed) and different hydrophones (such as isotropic hydrophones and array hydrophones). Simulation results have further validate the effectiveness and the accuracy of our proposed model.

Small sized unmanned aerial vehicles (UAV) play major roles in variety of applications for aerial explorations and surveillance, transport, videography/photography and other areas. However, some other real life applications of UAV have also been studied. One of them is as a 'Disaster Response' component. In a post disaster situation, the UAVs can be used for search and rescue, damage assessment, rapid response and other emergency operations. However, in a disaster response situation it is very challenging to predict whether the climatic conditions are suitable to fly the UAV. Also it is necessary for an efficient dynamic path planning technique for effective damage assessment. In this paper, such dynamic path planning algorithms have been proposed for micro-jet, a small sized fixed wing UAV for data collection and dissemination in a post disaster situation. The proposed algorithms have been implemented on paparazziUAV simulator considering different environment simulators (wind speed, wind direction etc.) and calibration parameters of UAV like battery level, flight duration etc. The results have been obtained and compared with baseline algorithm used in paparazziUAV simulator for navigation. It has been observed that, the proposed navigation techniques work well in terms of different calibration parameters (flight duration, battery level) and can be effective not only for shelter point detection but also to reserve battery level, flight time for micro-jet in a post disaster scenario. The proposed techniques take approximately 20% less time and consume approximately 19% less battery power than baseline navigation technique. From analysis of produced results, it has been observed that the proposed work can be helpful for estimating the feasibility of flying UAV in a disaster response situation. Finally, the proposed path planning techniques have been carried out during field test using a micro-jet. It has been observed that, our proposed dynamic path planning algorithms give proximate results compare to simulation in terms of flight duration and battery level consumption.

As a clean energy, wind power is massively utilized in net recent years, which significantly reduced the pollution emission created from unit. This article referred to the concept of energy-saving and emission reducing; built a multiple objective function with represent of the emission of CO2& SO2, the coal-fired from units and the lowest unit fees of commitment; Proposed a algorithm to improving NSGA-D (Non-dominated Sorting Genetic Algorithm-II) for the dynamic characteristics, consider of some constraint conditions such as the shortest operation and fault time and climbing etc.; Optimized and commitment discrete magnitude and Load distribution continuous quantity with the double-optimization strategy; Introduced the fuzzy satisfaction-maximizing method to reaching a decision for Pareto solution and also nested into each dynamic solution; Through simulation for 10 units of wind power, the result show that this method is an effective way to optimize the Multi-objective unit commitment modeling in wind power integrated system with Mixed-integer variable.