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Register a new userImpact of EV Charging Stations in Power Grids in Italy and its Mitigation Mechanisms
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Global warming leads the world to think of a different way of transportation: avoiding internal combustion engines and electrifying the transportation sector. With a high penetration of electric vehicle (EV) charging stations on an existing power distribution network, the impact may be consistent. The loads of the fast-charging stations would potentially result in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. The degrading performance of the power system due to the negative impact of the EV charging stations can even lead to penalties to be paid by the distribution system operator (DSO). This paper: i) investigates the impact of the ac{ev} charging station on the distribution network for what concerns voltage drop on MV feeders and loading of transformers in primary substations, and ii) proposes a mitigation mechanism. A realistic typical Italian grid has been used to assess the impact of EV charging stations and to validate the mitigation mechanism.
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A power system electromechanical wave propagates from the disturbance location to the rest of system, influencing various types of protections. In addition, since more power-electronics-interfaced generation and energy storage devices are being integrated into power systems, electromechanical wave propagation speeds in the future power systems are likely to change accordingly. In this paper, GPS-synchronized measurement data from a wide-area synchrophasor measurement system FNET/GridEye are used to analyze the characteristics of electromechanical wave propagation in the U.S. Eastern Interconnection (EI) system. Afterwards, high levels of photovoltaic (PV) penetration are modeled in the EI to investigate the influences of a typical power-electronics--interfaced resource on the electromechanical wave propagation speed. The result shows a direct correlation between the local penetration level of inverter-based generation and the electromechanical wave propagation speed.
Even with state-of-the-art defense mechanisms, cyberattacks in the electric power distribution sector are commonplace. Particularly alarming are load-altering (demand-side) cyberattacks launched through high-wattage assets, which are not continuously monitored by electric power utilities. Electric Vehicle Charging Stations (EVCSs) are among such high-wattage assets and, therefore, cyber insurance can be an effective mechanism to protect EVCSs from economic losses caused by cyberattacks. This paper presents a data-driven cyber insurance design model for public EVCSs. Under some mildly restrictive assumptions, we derive an optimal cyber insurance premium. Then, we robustify this optimal premium against uncertainty in data and investigate the risk of insuring the EVCSs using Conditional Value-at-Risk. A case study with data from EVCSs in Manhattan, New York illustrates our results.
The frequent occurrences of cascading failures in power grids have been receiving continuous attention in recent years. An urgent task for us is to understand the cascading failure vulnerability of power grids against various kinds of attacks. We consider a cost restrained hybrid attack problem in power grids, in which both nodes and links are targeted with a limited total attack cost. We propose an attack centrality metric for a component (node or link) based on the consequence and cost of the removal of the component. Depending on the width of cascading failures considered, the attack centrality can be a local or global attack centrality. With the attack centrality, we further provide a greedy hybrid attack, and an optimal hybrid attack with the Particle Swarm Optimization (PSO) framework. Simulation results on IEEE bus test data show that the optimal hybrid attack is more efficient than the greedy hybrid attack. Furthermore, we find counterintuitively that the local centrality based algorithms are better than the global centrality based ones when the cost constraint is considered in the attack problem.
Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not economically viable to install measurement systems on every node and branch of a power grid, though they need to be monitored. An overwhelming number of strategies have been developed to meet oftentimes multiple conflicting objectives. The prime challenge in formulating the problem lies in developing a heuristic or an optimization model that, though mathematically tractable and constrained in cost, leads to trustworthy technical solutions. Further, large-scale, long-term deployments pose additional challenges because the boundary conditions change as technologies evolve. For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions. Also, the placement strategies developed for transmission grids might not be suitable for distribution grids, and vice versa, because of unique characteristics. Therefore, the strategies need to be flexible, to a certain extent, because no two power grids are alike. Despite the extensive literature on the present topic, the focus of published works tends to be on a specific subject, such as the optimal placement of measurements to ensure observability in transmission grids. There is a dearth of work providing a comprehensive picture for developing optimal placement strategies. Because of the ongoing efforts on the modernization of electric power grids, there is a need to consolidate the status quo while exposing its limitations to inform policymakers, industry stakeholders, and researchers on the research-and-development needs to push the boundaries for innovation.
In modern power grids, a local failure or attack can trigger catastrophic cascading failures, which make it challenging to assess the attack vulnerability of power grids. In this Brief, we define the $K$-link attack problem and study the attack vulnerability of power grids under cascading failures. Particularly, we propose a link centrality measure based on both topological and electrical properties of power grids. According to this centrality, we propose a greedy attack algorithm and an optimal attack algorithm. Simulation results on standard IEEE bus test data show that the optimal attack is better than the greedy attack and the traditional PSO-based attack in fracturing power grids. Moreover, the greedy attack has smaller computational complexity than the optimal attack and the PSO-based attack with an adequate attack efficiency. Our work helps to understand the vulnerability of power grids and provides some clues for securing power grids.
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