Compressive Sensing-Based Harmonic Sources Identification in Smart Grids

A compressive sensing-based approach for Preisach hysteresis model identification

The Preisach hysteresis model has been adopted extensively in magnetic and smart materialbased systems. Fidelity of the model hinges on accurate identification of the Preisach density function. Existing work on the identification of the density function usually involves applying an input that provides sufficient excitation and measuring a large set of output data. In this paper, we propose a no...

Coherence Pattern-Guided Compressive Sensing with Unresolved Grids

Highly coherent sensing matrices arise in discretization of continuum imaging problems such as radar and medical imaging when the grid spacing is below the Rayleigh threshold. Algorithms based on techniques of band exclusion (BE) and local optimization (LO) are proposed to deal with such coherent sensing matrices. These techniques are embedded in the existing compressed sensing algorithms such ...

Robust Agent Based Distribution System Restoration with Uncertainty in Loads in Smart Grids

This paper presents a comprehensive robust distributed intelligent control for optimum self-healing activities in smart distribution systems considering the uncertainty in loads. The presented agent based framework obviates the requirements for a central control method and improves the reliability of the self-healing mechanism. Agents possess three characteristics including local views, decentr...

Smart Grids

Smart - Grids

We build a system dynamics model to evaluate the potential dynamics of consumer adoption of “Smart Energy Behaviour”. Within this term we include different levels of: i) shift in electricity consumption towards less costly-less polluting and congestioning hours; ii) the reduction of mainly wasteful electricity consumption, that maintains similar levels of comfort; iii) the enrolment in demand r...