50 citations · 52 across the 4 of their papers we have counts for
5 papers
Bidirectional Multimodal Fusion of Sky Images and Time-Series for Solar Forecasting with Large Language Models
Ken Chen, Maneesha Perera, Wei Wang +3
Short-term photovoltaic (PV) power and global horizontal irradiance (GHI) forecasts are essential for effective dispatch, reserve scheduling, and grid operations. At these forecast…
NeST: Neighborhood-aware semantic alignment and temporal modulation for LLM based time series forecasting
Jayanie Bogahawatte, Sachith Seneviratne, Maneesha Perera +1
Adapting Large Language Models (LLMs) trained on discrete text data, to forecast continuous time series signals is challenging. While finetuning the LLMs enables such adaptation, e…
Distributed solar generation forecasting using attention-based deep neural networks for cloud movement prediction
Maneesha Perera, Julian De Hoog, Kasun Bandara +2
Accurate forecasts of distributed solar generation are necessary to maintain grid stability amid the increased uptake of distributed solar photovoltaic (PV) systems. However, the h…
Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data
Maneesha Perera, Julian De Hoog, Kasun Bandara +2
Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various st…
Multi-Resolution, Multi-Horizon Distributed Solar PV Power Forecasting with Forecast Combinations
Maneesha Perera, Julian De Hoog, Kasun Bandara +1
Distributed, small-scale solar photovoltaic (PV) systems are being installed at a rapidly increasing rate. This can cause major impacts on distribution networks and energy markets.…