ModellingStochastic Adaptive MPC for Load Frequency Control in MicrogridsarXiv — Systems and Control (eess.SY) · yesterdayForecastingCritical Review of LLMs for HVAC Operations in BuildingsarXiv — Systems and Control (eess.SY) · yesterdayDigital twinCyber-physical systems lab opens at Voronezh State UniversityВоронежский госуниверситет · 20hDigital twinAI-Powered CPS Urban Transportation Digital TwinarXiv — Systems and Control (eess.SY) · yesterdayModellingSelectel and ITMO JV develops multi-agent system technologies for businessspbIT · yesterdayForecastingGrid-Aware MPC for Smoothing AI Data Center Power DemandarXiv — Systems and Control (eess.SY) · yesterdayEnergyComparison of Direct vs Indirect Net Load Forecasting with RenewablesarXiv — Systems and Control (eess.SY) · yesterdayDigital twinBayesian thermal digital twin for space habitat under impactarXiv API — полнотекстовый поиск "digital twin" · 4dDigital twinData-driven transient forecasting for generator digital twin decision supportarXiv API — полнотекстовый поиск "digital twin" · 3dMarket & productsKorea and Africa Discuss AI and Digital Infrastructure at KOAFECAfDB Africa Newsroom (пресс-релизная витрина) · 4dModellingSeed-Anchored Graph Rendering for QA on Power-Grid CIM/CGMES ModelsarXiv — Systems and Control (eess.SY) · 5dDigital twinDNative-Twin: Graph-Native Digital Twins for Reconstructable Agentic DecisionsarXiv API — полнотекстовый поиск "digital twin" · 4d
Grid-Aware MPC for Smoothing AI Data Center Power Demand
US & West ·
A model predictive control framework for a hybrid energy storage system (battery plus supercapacitor) is proposed, embedding band-pass filter dynamics to smooth grid-side power demand of AI data centers. The receding-horizon optimization mitigates load-induced grid oscillations.
Why it matters
Relevant to balancing models and load management in power systems with volatile consumers.
Two headroom-aware adaptive MPC strategies are developed for PV-dominated microgrids, accounting for stochastic and time-varying reserve headroom of inverter-based resources to avoid control saturation and improve load frequency control.
A systematic review of 66 studies (2023-2026) on LLMs for HVAC operations classifies methods and applications, revealing concentration on building energy modeling but few pilot-level deployments and no sustained operational use.
Methods for urban traffic digital twins are presented, emphasizing prediction and decision-making capabilities, powered by AI and cyber-physical systems, distinguishing them from traditional simulators.
