4 citations · 4 across the 1 of their papers we have counts for
3 papers
cs.LG2026
Physics-Informed State Space Models for Day-Ahead Photovoltaic Power Forecasting
Phil Aupke, Muhammad Hassan, Khalid Ali +3
Accurate day-ahead photovoltaic (PV) power forecasting requires both strong temporal modeling and adherence to physical PV system constraints. Purely data-driven models often ignor…
cs.CR2026
Robustness of Local Energy Markets to Cyberattacks: Case Study of False Data Injection
Mehran Moradi, Reza Zamani, Phil Aupke +2
Market clearing in community-based local energy markets relies on power demand and PV forecasts, making it vulnerable to coordinated false data injection (FDI) attacks. This paper…
cs.LG2023★ 4 cited
DA-LSTM: A Dynamic Drift-Adaptive Learning Framework for Interval Load Forecasting with LSTM Networks
Firas Bayram, Phil Aupke, Bestoun S. Ahmed +3
Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role in optimizing energy scheduling and enabling more flexible and intelligent power grid s…