activity
20172026
most citedIRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications

7 citations · 11 across the 14 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.LG2023★ 1 cited

A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market

Cameron Cornell, Nam Trong Dinh, S. Ali Pourmousavi

The South Australia region of the Australian National Electricity Market (NEM) displays some of the highest levels of price volatility observed in modern electricity markets. This…

eess.SY2023

On the Financial Consequences of Simplified Battery Sizing Models without Considering Operational Details

Nam Trong Dinh, Sahand Karimi-Arpanahi, S. Ali Pourmousavi +3

Optimal battery sizing studies tend to overly simplify the practical aspects of battery operation within the battery sizing framework. Such assumptions may lead to a suboptimal bat…

eess.SP2023★ 1 cited

A New Time Series Similarity Measure and Its Smart Grid Applications

Rui Yuan, Hossein Ranjbar, S. Ali Pourmousavi +4

Many smart grid applications involve data mining, clustering, classification, identification, and anomaly detection, among others. These applications primarily depend on the measur…

eess.SY2023★ 1 cited

Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes

Nam Trong Dinh, Sahand Karimi-Arpanahi, Rui Yuan +4

Demand response (DR) plays a critical role in ensuring efficient electricity consumption and optimal use of network assets. Yet, existing DR models often overlook a crucial element…

cs.LG2023★ 1 cited

Efficient anomaly detection method for rooftop PV systems using big data and permutation entropy

Sahand Karimi-Arpanahi, Ali Pourmousavi

The number of rooftop photovoltaic (PV) systems has significantly increased in recent years around the globe, including in Australia. This trend is anticipated to continue in the n…