Generating Contextual Load Profiles Using a Conditional Variational Autoencoder

Generating power system states that have similar distribution and dependency to the historical ones is essential for the tasks of system planning and security assessment, especially when the historical data is insufficient. In this paper, we described a generative model for load profiles of industrial and commercial customers, based on the...

Detection of False Data Injection Attacks Using the Autoencoder Approach

State estimation is of considerable significance for the power system operation and control. However, well-designed false data injection attacks can utilize blind spots in conventional residual-based bad data detection methods to manipulate measurements in a coordinated manner and thus affect the secure operation and economic dispatch of grids....

Training Strategies for Autoencoder-based Detection of False Data Injection Attacks

The security of energy supply in a power grid critically depends on the ability to accurately estimate the state of the system. However, manipulated power flow measurements can potentially hide overloads and bypass the bad data detection scheme to interfere the validity of estimated states. In this paper, we use an autoencoder neural network to...

Active Affordance Learning in Continuous State and Action Spaces

Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action space, the robot learns a forward model to...

3D APTV measurements on microbubble streaming

Ultrasound-driven gas bubbles can be used as active actuators to create or modify the flow in microfluidic devices. Oscillating bubbles are able to create a steady streaming flow that can be used to perform several tasks in microfluidic devices. In this work, we focus on a specific configuration with a bubble located at a side wall of a...

A knowledge intensive parametric modelling method to support ship layout design