Related papers: Optimizing Smart Grid Aggregators and Measuring De…
The next-generation energy network, the so-called smart grid (SG), promises a tremendous increase in efficiency, safety and flexibility of managing the electricity grid as compared to the legacy energy network. This is needed today more…
State estimation is routinely being performed in high-voltage power transmission grids in order to assist in operation and to detect faulty equipment. In low- and medium-voltage power distribution grids, on the other hand, few real-time…
Smart power grids offer to revolutionize power distribution by sharing granular power usage data, though this same data sharing can reveal a great deal about users, and there are serious privacy concerns for customers. In this paper, we…
Smart metering is an essential feature of smart grids, allowing residential customers to monitor and reduce electricity costs. Devices called smart meters allows residential customers to monitor and reduce electricity costs, promoting…
This paper presents a new privacy-preserving smart metering system. Our scheme is private under the differential privacy model and therefore provides strong and provable guarantees. With our scheme, an (electricity) supplier can…
Cybersecurity and privacy are of the utmost importance for safe, reliable operation of the electric grid. It is well known that the increased connectivity/interoperability between all stakeholders (e.g., utilities, suppliers, and consumers)…
Smart meters enable improvements in electricity distribution system efficiency at some cost in customer privacy. Users with home batteries can mitigate this privacy loss by applying charging policies that mask their underlying energy use. A…
Smart-meters are a key component of energy transition. The large amount of data collected in near real-time allows grid operators to observe and simulate network states. However, privacy-preserving rules forbid the use of such data for any…
We revisit the problem of designing scalable protocols for private statistics and private federated learning when each device holds its private data. Locally differentially private algorithms require little trust but are (provably) limited…
Utilities around the world are reported to invest a total of around 30 billion over the next few years for installation of more than 300 million smart meters, replacing traditional analog meters [1]. By mid-decade, with full country wide…
Frequent metering of electricity consumption is crucial for demand side management in smart grids. However, metered data can be processed fairly easily by employing well-established nonintrusive appliance load monitoring techniques to infer…
In this paper, we present a comprehensive survey of privacy-preserving schemes for Smart Grid communications. Specifically, we select and in-detail examine thirty privacy preserving schemes developed for or applied in the context of Smart…
Recent advancements in research have shown the efficacy of employing sensor measurements, such as voltage and power data, in identifying line outages within distribution grids. However, these measurements inadvertently pose privacy risks to…
Privacy-preserving data aggregation in ad hoc networks is a challenging problem, considering the distributed communication and control requirement, dynamic network topology, unreliable communication links, etc. Different from the widely…
In this paper, we present a multidimensional, highly effective method for aggregating data for wireless sensor networks while maintaining privacy. The suggested system is resistant to data loss and secure against both active and passive…
Smart grid is a self-sufficient system. That tracks how the energy is used from its source to its final destination. The smart grid can increase the service quality while reducing the consumption of electricity. However, the safety and…
End-user privacy in smart meter measurements is a well-known challenge in the smart grid. The solutions offered thus far have been tied to specific technologies such as batteries or assumptions on data usage. Existing solutions have also…
Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of…
Energy theft poses a significant threat to the stability and efficiency of smart grids, leading to substantial economic losses and operational challenges. Traditional centralized machine learning approaches for theft detection require…
Smart meters (SMs) measure and report users' energy consumption to the utility provider (UP) in almost real-time, providing a much more detailed depiction of the consumer's energy consumption compared to their analog counterparts. This…