THE INTERNET IS THINKING
Earlier sources: Energy
Energy research and engineering concern how power is produced, stored, delivered, and consumed. Follow solar and nuclear power, fusion, geothermal systems, batteries, electricity grids, and changing power demand.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗698 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Computational and machine learning analysis of bio-convective magnetized Ree–Eyring nanofluid flow on Riga plate with thermal radiation and activation energy ↗
This work examines bio-convective magnetized Ree-Eyring nanofluid flow on a convectively heated Riga surface. Thermal diffusion is controlled through use of Cattaneo-Christov thermal flux and Brownian motion effects along with thermal radiations. The flow is also affected by Darcy-Forchheimer model, activation energy and presence of microorganisms. The leading equations have valuated initially using bvp4c technique. The obtained set from this numerical technique is then used as a dataset to implement ANN technique in current problem. It has deduced in this work that, optimal Mean Squared Error…
- OpenAlex · Published · First archived
Artificial intelligence for forecasting, optimization, and energy storage in energy communities: a review ↗
Abstract Energy communities (ECs) are emerging as a key paradigm for decentralized, consumer-centric energy systems, yet their operation is challenged by uncertainty, asset heterogeneity, and the need for coordinated decision-making. Artificial intelligence (AI) has been widely applied to forecasting, optimization, and management of energy storage systems (ESSs) in ECs, but existing studies remain fragmented across decision layers. This paper presents a comprehensive and systematic review of 130 peer-reviewed studies on AI-based forecasting, optimization, and ESS management in ECs. By jointly…
- OpenAlex · Published · First archived
Superior flexible Zn-ion battery using vanadium oxide nanobelts cathode enables medium temperature range and ultrafast Zn2+ intercalation ↗
The development of flexible and wearable energy storage systems demands zinc-ion batteries with high capacity, mechanical robustness, and long-term electrochemical stability. Vanadium oxide (V 6 O 13 .nH 2 O), with its high theoretical capacity, is a promising cathode material for aqueous and flexible Zn-ion batteries. However, its practical application is hindered by structural instability, vanadium dissolution, and sluggish Zn 2+ reaction kinetics, mainly under mechanical deformation. To address these challenges, nanoscale engineering has emerged as an effective strategy to improve both elec…
- OpenAlex · Published · First archived
System Integration and Sea Trials of a Containerized Ocean Thermal Energy Conversion Prototype ↗
Ocean Thermal Energy Conversion (OTEC) is a promising renewable energy technology for remote islands, offshore platforms, and maritime infrastructure, yet its commercialization is constrained by low cycle efficiency, high auxiliary energy demand, and the engineering challenges associated with large-scale seawater transport. This study presents the integration and experimental evaluation of a 20 kW class containerized OTEC prototype using R134a in a closed Rankine cycle. The working fluid circulates within the power-generation module, while warm surface seawater supplies the evaporator and cold…
- OpenAlex · Published · First archived
A Resilience Enhancement Method for Distribution Networks Under Extreme-Event Scenarios Considering Flexible Interconnection via Energy Routers ↗
An energy router (ER), featuring flexible multi-port access, bidirectional power regulation, and cross-regional energy exchange, provides versatile control capabilities for fault isolation, critical-load supply, and post-disaster restoration in distribution networks under extreme-event scenarios. However, existing studies have not fully exploited the dynamic relocation and flexible power-transfer capabilities of ER ports when post-disaster network fragmentation and multiple islands coexist; moreover, existing distribution-network resilience optimization methods depend on assumptions about the…
- OpenAlex · Published · First archived
Deep Learning Benchmarks for Multi-Step Photovoltaic Power Forecasting: Comparative Assessment of GRU, LSTM, and BiLSTM Architectures ↗
Accurate photovoltaic (PV) power forecasting is essential for renewable energy integration, dynamic reserve allocation, and generation scheduling. Unpredicted generation ramps induce substantial voltage and frequency deviations on grid-connected distribution networks. This paper provides an objective benchmark among three deep learning architectures: Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM). Telemetry spanning one year from an operational 175 kW plant in Reggane, Algeria, is evaluated across 72 h horizons (H=288 steps at 15 min resolution) usin…
- OpenAlex · Published · First archived
Tax coal or subsidize clean capacity? A differential game of incumbent utilities’ energy transition ↗
Electricity decarbonization requires both replacement investment and decisions about the remaining life of coal assets. This paper develops a Stackelberg differential-game benchmark with an incumbent utility that builds clean capacity and retires coal, and an independent clean developer. Binding organizational constraints make construction and closure substitutes; binding finance can instead make them complements when retirement releases net funds. Annual numerical experiments compare five policy classes using a common post-window continuation rule, incumbent-value limits and explicit capacity…
- OpenAlex · Published · First archived
MA-YOLO for robust multimodal feature fusion under weak cross-modal alignment in remote sensing object detection ↗
Abstract Multimodal remote sensing object detection benefits from the complementary characteristics of visible and infrared modalities. However, owing to the heterogeneous imaging mechanisms of RGB and infrared sensors, feature representations from the two modalities progressively become semantically inconsistent during hierarchical feature extraction, even when the input image pairs are geometrically registered. Such feature-level semantic inconsistency weakens the robustness of multimodal feature fusion and ultimately degrades object localization accuracy. To address this issue, we propose M…
- OpenAlex · Published · First archived
Optimal design of distributed energy systems in cold regions across renewable energy penetration rates ↗
The low-carbon transition of integrated power systems drives a continuous rise in renewable energy penetration rate (REPR), which profoundly influences the optimal design and operation of grid-connected distributed energy systems (DES). Aiming at the issue that existing studies rarely consider the dynamic variation of REPR in optimal design, this paper establishes a multi-objective bi-level stochastic optimization model incorporating REPR on the power supply side. Typical scenarios are constructed using the Copula function, Latin Hypercube Sampling, and Wasserstein distance-based scenario redu…
- OpenAlex · Published · First archived
A cloud-edge collaborative dual-modal fault detection block for battery packs: Enabling intelligent safety management in electric vehicle battery systems ↗
Intelligent diagnosis of battery pack faults using real-world data has become a key research focus in the era of vehicle-cloud integration. While cloud-based deep learning diagnostics have shown strong capability, edge-based fault diagnosis is increasingly preferred for its real-time responsiveness, lower communication bandwidth demand, and enhanced data privacy. This study aims to address the challenge of simultaneously achieving model light-weighting and high diagnostic accuracy for onboard deployment. To this end, we propose a novel battery-pack fault detection block with dual modeling mode…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Energy
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
Follow a thread
Explore related regions
These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.