Search

An increased energy demand, and environmental pressure to accommodate higher levels of renewable energy and flexible loads like electric vehicles have led to numerous smart transformations in the modern power systems. These transformations make the cyber-physical power system highly susceptible to cyber-adversaries targeting its numerous operations. In this work, a novel black box adversarial attack strategy is proposed targeting the AC state estimation operation of an unknown power system using historical data. Specifically, false data is injected into the measurements obtained from a small subset of the power system components which leads to significant deviations in the state estimates. Experiments carried out on the IEEE 39 bus and 118 bus test systems make it evident that the proposed strategy, called DeeBBAA, can evade numerous conventional and state-of-the-art attack detection mechanisms with very high probability.

For the purpose of DC fault identification in multi-terminal modular multilevel converter (MMC) high voltage DC (HVDC) systems, the proposed work addresses the issues of localized protection schemes. The proposed work is focused on selectivity issues such as differentiating between forward external and internal faults, and classification of type of fault contingency i.e., pole to pole (PTP) or pole to ground (PTG) in the system. The scheme uses equivalent network of multi-terminal MMC-HVDC systems for DC fault identification. Modal transformation is used to analyse line-mode and zero-mode voltage across the current limiting reactor (CLR) for different possible contingencies in the system. A maloperation region has been defined to address the issue of selectivity of internal HIFs and external low impedance faults (LIFs). Rate of change of DC voltage (dUdc/dt) is used as the mitigation technique to differentiate a HIF as high as 1000Ω. Further, a sensitivity function is formulated which gives the variation of decisive parameters i.e., line-mode voltage and zero-mode voltage with respect to change in fault resistance and value of current limiting reactor. PSCAD/EMTDC based simulations are used to validate the performance of the proposed scheme. The scheme is validated in terms of detection time, robustness to WGN in measurement, security for AC faults, DC circuit breakers (DCCB) operation, power reversal (load transients).

Power system simulations should be adapted to be applicable to the trends that are currently evoked by the energy transition. This transition is pushing our power system from a traditional hierarchical system to a modern interactive system. In order to keep the supply and transport of energy safe and reliant, we need to change the way we perform power system simulations. This requires a comprehensive framework in which both transmission and distribution systems are simultaneously analyzed. This chapter describes how transmission and distribution networks are modeled together as an integrated network and used to do steady-state operation analysis in order to assess the interaction of these two networks. Furthermore, we investigate the influence of the increasing amount of imbalance at distribution level on the transmission network that is evoked by the increase of highly variable resources and loads at distribution level. This influence is not taken into account in traditional power system simulations as power networks are analyzed on its own. We show that the hybrid network representation is a powerful tool to analyze modern power systems and that the effects of increased PV penetration under normal operating conditions are limited

We propose a localized protection scheme based on modal analysis in multi-terminal modular multilevel converter (MMC) based high voltage DC (HVDC) systems. The paper addresses the issues of localized protection scheme based DC fault identification, such as differentiating between external and internal faults, classification of type of fault contingency i.e., pole to pole (\textit{PTP}) or pole to ground (\textit{PTG}) for high impedance faults (HIFs) in the system. The scheme works on equivalent network of multi-terminal MMC-HVDC system for a DC fault, using phase-modal transformation to analyse line-mode and zero-mode voltage across the current limiting reactor (CLR) for different possible contingencies in the presence of fault resistance. The protection scheme is validated to be reliable for HIFs and in the presence of White Gaussian Noise (WGN) in measurement. The scheme operation is validated to be intact for varying fault location, fault resistances and system transients.

As the penetration levels of Photovoltaic Generators (PVG) progresses in the utility scale distribution networks, the effective inertia due to the constant power factor ’Negative Loading’ is also reduced. One important regulation featured in the ’Network Codes’ of the ENTSO-E is the requirement of frequency response by the renewable energy sources. This is generally provided by the Photovoltaic Generators (PVG) at the sub-transmission levels. However, when the grid size is small, the dominating system is substantially a low or a medium voltage network. Due to the rising number of the PVGs in such networks, the voltage is not constant at the PCC, acerbated with a significant value of impedance as seen by the source. Therefore, rooftop PVGs also must cater to the frequency response services. These services are provided, generally with the help of a negative drooping of the active power. However, the droop control is a proportional controller, which can have detrimental small signal stability effects, and hence, for the grid connected operation of the PVG, a P-D control or an inertial control, which mimics the swing equation of the synchronous generator, is deployed for harnessing inertial response from the PVG in case of over frequencies. The efficacy of the controller has been tested for different frequency conditions, and it is observed that the PVG, even under weak grid conditions, can deliver frequency response, enhanced by an inertial support.

The fuel cell technologies are advancing and maturing for commercial markets. However proper diagnostic tools needs to be developed in order to insure reliability and durability of fuel cell systems. This paper presents a design of a data driven method to detect CO content in the anode gas of a high temperature fuel cell. In this work the fuel cell characterization is based on an experimental equivalent electrical circuit, where model parameters are mapped as a function of the load current. The designed general likelihood ratio test detection scheme detects whether a equivalent electrical circuit parameter differ from the non-faulty operation. It is proven that the general likelihood ratio test detection scheme, with a very low probability of false alarm, can detect CO content in the anode gas of the fuel cell.