A ConvLSTM trained on Ceará satellite data from 2000–2023 captured regional land-degradation trends better than changes in individual 2.2-kilometre cells. The researchers say cell-level changes remained largely unpredictable.
Source: arXiv, Desertification Forecasting in Semi-Arid Regions: Using Deep Learning to Probe the Observability Limits of Land Degradation Dynamics (arXiv:2610.13406)
Researchers at the universities of Oslo and Xi’an presented a graph neural network for probabilistic power-flow estimates when grid topology changes after line outages. The model outperformed baselines on phase-angle error in two test networks.
Source: arXiv, Hierarchical Graph Neural Network for Probabilistic Power Flow with Grid Topology Contingencies (arXiv:2610.13495)
Researchers in the United States and Canada presented SecFD-FL, a method for forecasting electric-vehicle charging loads without centralizing distributed data. The study tested forecasts and gradient-inversion attacks on Palo Alto station records and EV WATTS data.
Source: arXiv, SecFD-FL: Frequency-Decoupled Federated Learning with Secure Aggregation for Charging Load Forecasting in Internet of Electric Vehicles (arXiv:2610.12909)
Construction is under way on the 350 MW/1,400 MWh storage project, backed by more than EUR 270 million, with commercial operation expected in early 2028.
The Dajaj Al-Khair feed factory project combines 1 MW of solar electricity with a separate 1 MW PV-to-Heat unit capable of producing up to 1.35 tonnes of steam per hour.
ARE and the African Development Bank said workshops ending on 25 September validated a cost-of-service study, tariff methodology and grid code for the DRC electricity sector.
Source: Autorité de Régulation du secteur de l’Électricité (ARE)
Egypt’s Cabinet information center outlined six pillars of the Industry Ministry’s 2026–2030 strategy, covering strategic programmes, skills, products, procedures, implementation mechanisms and performance indicators.
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