Biblio

Transient stability accidents induced by converter-based resources have been emerging frequently around the world. In this paper, the transient stability of the grid-tied voltage source converter (VSC) system is studied through estimating the basin of attraction (BOA) based on the hyperplane or hypersurface method. Meanwhile, fault critical clearing times are estimated, based on the approximated BOA and numerical fault trajectory. Further, the dynamic security region (DSR), an important index in traditional power systems, is extended to power-electronics-dominated power systems in this paper. The DSR of VSC is defined in the space composed of active current references. Based on the estimated BOA, the single-VSC-infinite-bus system is taken as an example and its DSR is evaluated. Finally, all these analytical results are well verified by several numerical simulations in MATLAB/Simulink.

This study will be focused on efforts to increase the reliability of the Bangka Electricity System by designing the interconnection of the Bangka system with another system that is stronger and has a better energy mix, the Sumatra System. The novelty element in this research is the design of system protection using Special Protection System (SPS) as well as a different assessment method using the Fuzzy Technique This research will analyze the implementation of the SPS event-based and parameter-based as a new defense scheme by taking corrective actions to keep the system stable and reliable. These actions include tripping generators, loads, and reconfiguring the system automatically and quickly. The performance of this SPS will be tested on 10 contingency events with four different load profiles and the system response will be observed in terms of frequency stability, voltage, and rotor angle. From the research results, it can be concluded that the SPS performance on the Bangka-Sumatra Interconnection System has a better and more effective performance than the existing defense scheme, as evidenced by the results of dynamic security assessment (DSA) testing using Fuzzy Techniques.

Owing to the decreasing costs of distributed energy resources (DERs) as well as decarbonization policies, power systems are undergoing a modernization process. The large deployment of DERs together with internet of things (IoT) devices provide a platform for peer-to-peer (P2P) energy trading in active distribution networks. However, P2P energy trading with IoT devices have driven the grid more vulnerable to cyber-physical threats. To this end, in this paper, a resilience-oriented P2P energy exchange model is developed considering three phase unbalanced distribution systems. In addition, various scenarios for vulnerability assessment of P2P energy exchanges considering adverse prosumers and consumers, who provide false information regarding the price and quantity with the goal of maximum financial benefit and system operation disruption, are considered. Techno-economic survivability analysis against these attacks are investigated on a IEEE 13-node unbalanced distribution test system. Simulation results demonstrate that adverse peers can affect the physical operation of grid, maximize their benefits, and cause financial loss of other agents.

Physical-layer key (PLK) generation scheme is a new key generation scheme based on wireless channel reciprocity. However, the security of physical layer keys still lacks sufficient theoretical support in the presence of eavesdropping attacks until now, which affects the promotion in practical applications. By analyzing the propagation mode of multipath signals under non-line-of-sight (nLoS), an improved spatial cross-correlation model is constructed, where the spatial cross-correlation is between eavesdropping channel and legitimate channel. Results show that compared with the multipath and obstacle distribution of the channel, the azimuth and distance between the eavesdropper and the eavesdropped user have a greater impact on the cross-correlation.

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.

Flush-based cache attacks like Flush+Reload and Flush+Flush are highly precise and effective. Most of the flush-based attacks provide high accuracy in controlled and isolated environments where attacker and victim share OS pages. However, we observe that these attacks are prone to low accuracy on a noisy multi-core system with co-running applications. Two root causes for the varying accuracy of flush-based attacks are: (i) the dynamic nature of core frequencies that fluctuate depending on the system load, and (ii) the relative placement of victim and attacker threads in the processor, like same or different physical cores. These dynamic factors critically affect the execution latency of key instructions like clflush and mov, rendering the pre-attack calibration step ineffective.We propose DABANGG, a set of novel refinements to make flush-based attacks resilient to system noise by making them aware of frequency and thread placement. First, we introduce pre-attack calibration that is aware of instruction latency variation. Second, we use low-cost attack-time optimizations like fine-grained busy waiting and periodic feedback about the latency thresholds to improve the effectiveness of the attack. Finally, we provide victim-specific parameters that significantly improve the attack accuracy. We evaluate DABANGG-enabled Flush+Reload and Flush+Flush attacks against the standard attacks in side-channel and covert-channel experiments with varying levels of compute, memory, and IO-intensive system noise. In all scenarios, DABANGG+Flush+Reload and DABANGG+Flush+Flush outperform the standard attacks in stealth and accuracy.

The electromagnetic energy harvesting technology is a new and effective way to supply power to the condition monitoring sensors installed on or near the transmission line. We will use Computer Simulation Technology Software to simulate the different designs of stand-alone electromagnetic energy harvesters The power generated by energy harvesters of different design structures is compared and analyzed through simulation and experimental results. We then propose an improved design of energy harvester.

In this paper we propose a novel integrated DC/DC converter featuring a single-input-multiple-output architecture for emerging System-on-Chip applications to improve load transient response and power side-channel security. The converter is able to provide multiple outputs ranging from 0.3V to 0.92V using a global 1V input. By using modularized circuit blocks, the converter can be extended to provide higher power or more outputs with minimal design complexity. Performance metrics including power efficiency and load transient response can be well maintained as well. Implemented in 32nm technology, single output efficiency can reach to 88% for the post layout models. By enabling delay blocks and circuits sharing, the Pearson correlation coefficient of input and output can be reduced to 0.1 under rekeying test. The reference voltage tracking speed is up to 31.95 V/μs and peak load step response is 53 mA/ns. Without capacitors, the converter consumes 2.85 mm2 for high power version and only 1.4 mm2 for the low power case.

The focus of this work is the transient modelling of the DC-arc voltage on a Hybrid Switch (a mechanical switch in parallel with a static switch) of a key protection component called Fast Discharge Unit (FDU) in the Divertor Tokamak Test (DTT). The DTT facility is an experimental tokamak in advanced design and realization phase, which will be built in the ENEA Research Centre in Frascati (Italy). The FDU allows the safe discharge of the Toroidal Field (TF) superconducting magnets when a quench is detected or a failure occurs in the power supply or in the cryogenic system. In this work, the arc conductance of the mechanical By-Pass Switch (BPS) of the Hybrid Switch is modelled using the well-known Mayr-Cassie equations and the Paukert arc parameters. The simulations show a good agreement with the expected results in terms of voltage and current transient from the mechanical switch to the static switch.

This paper introduces a robust random number generator that based on Bernoulli discrete chaotic map. An eight bit SAR ADC is used with discrete time chaotic map to generate random bit sequences. Compared to RNGs that use the continuous time chaotic map, sensitivity to process, voltage and temperature (PVT) variations are reduced. Thanks to utilizing switch capacitor circuits to implement Bernoulli chaotic map equations, power consumption decreased significantly. Proposed design that has a throughput of 500 Kbit/second is implemented in TSMC 180 nm process technology. Generated bit sequences has successfully passed all four primary tests of FIPS-140-2 test suite and all tests of NIST 820–22 test suite without post processing. Furthermore, data rate can be increased by sacrificing power consumption. Hence, proposed architecture could be utilized in high speed cryptography applications.

Steady-state response of the grid under a predefined set of credible contingencies is an important component of power system security assessment. With the growing complexity of electrical networks, fast and reliable methods and tools are required to effectively assist transmission grid operators in making decisions concerning system security procurement. In this regard, a Convolutional Neural Network (CNN) based approach to develop prediction models for static security assessment under N-1 contingency is investigated in this paper. The CNN model is trained and applied to classify the security status of a sample system according to given node voltage magnitudes, and active and reactive power injections at network buses. Considering a set of performance metrics, the superior performance of the CNN alternative is demonstrated by comparing the obtained results with a support vector machine classifier algorithm.