Advancements and future outlook of Artificial Intelligence in energy and climate change modeling

Advances in Applied Energy, Journal Year: 2025, Volume and Issue: unknown, P. 100211 - 100211

Published: Jan. 1, 2025

Language: Английский

---

Energy Management in Residential Microgrid Based on Non-Intrusive Load Monitoring and Internet of Things

Smart Cities, Journal Year: 2024, Volume and Issue: 7(4), P. 1907 - 1935

Published: July 23, 2024

Recently, various strategies for energy management have been proposed to improve efficiency in smart grids. One key aspect of this is the use microgrids. To effectively manage a residential microgrid, advanced computational tools are required maintain balance between supply and demand. The concept load disaggregation through non-intrusive monitoring (NILM) emerging as cost-effective solution optimize utilization these systems without need extensive sensor infrastructure. This paper presents an system based on NILM Internet Things (IoT) including photovoltaic (PV) plant battery storage device. goal develop efficient increase microgrid’s independence from traditional electrical grid. microgrid model developed electromagnetic transient program PSCAD/EMTDC analyze performance. Load obtained by combining artificial neural networks (ANNs) particle swarm optimization (PSO) identify appliances demand-side management. An ANN applied identification task, PSO used algorithm. combination enhances technique’s accuracy, which verified using mean absolute error method assess difference predicted measured power consumption appliances. output then transferred consumers ThingSpeak IoT platform, enabling them monitor control their save costs.

Language: Английский

---

Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review

Batteries, Journal Year: 2025, Volume and Issue: 11(3), P. 107 - 107

Published: March 13, 2025

Artificial Neural Networks (ANNs) improve battery management in electric vehicles (EVs) by enhancing the safety, durability, and reliability of electrochemical batteries, particularly through improvements State Charge (SOC) estimation. EV batteries operate under demanding conditions, which can affect performance and, extreme cases, lead to critical failures such as thermal runaway—an exothermic chain reaction that may result overheating, fires, even explosions. Addressing these risks requires advanced diagnostic strategies, machine learning presents a powerful solution due its ability adapt across multiple facets management. The versatility ML enables application material discovery, model development, quality control, real-time monitoring, charge optimization, fault detection, positioning it an essential technology for modern systems. Specifically, ANN models excel at detecting subtle, complex patterns reflect health performance, crucial accurate SOC effectiveness applications this domain, however, is highly dependent on selection datasets, relevant features, suitable algorithms. Advanced techniques active are being explored enhance improving models’ responsiveness diverse nuanced behavior. This compact survey consolidates recent advances estimation, analyzing current state field highlighting challenges opportunities remain. By structuring insights from extensive literature, paper aims establish ANNs foundational tool next-generation systems, ultimately supporting safer more efficient EVs robust safety protocols. Future research directions include refining dataset quality, optimizing algorithm selection, precision, thereby broadening ANNs’ role ensuring reliable vehicles.

Language: Английский

---

HVAC System Energy Retrofit for a University Lecture Room Considering Private and Public Interests

Energies, Journal Year: 2025, Volume and Issue: 18(6), P. 1526 - 1526

Published: March 19, 2025

The operation of Heating Ventilation and Air Conditioning (HVAC) systems in densely occupied spaces results considerable energy consumption. In the post-pandemic context, stricter indoor air quality standards higher ventilation rates further increase demand. this paper, retrofit a partial recirculation all-air HVAC system serving university lecture room located Southern Italy is analyzed. Multi-Objective Optimization (MOO) Multi-Criteria Decision-Making (MCDM) approaches are used to find optimal design alternatives rank these considering two different decision-makers, i.e., public private stakeholders. Among Pareto solutions obtained from optimization, alternative identified, encompassing three Key Performance Indicators using new robust MCDM approach based on four methods, TOPSIS, VIKOR, WASPAS, MULTIMOORA. show that, era, baseline scenarios for infection reduction that do not involve introduction demand control strategies cause consumption negligible values up 59%. On contrary, involving decrease between 5% 38%. findings offer valuable guidance retrofits education similar buildings, emphasizing potential balance occupant health, efficiency, cost reduction. also highlight significant CO2 reductions minimal impacts thermal comfort, showcasing substantial savings through targeted retrofits.

Language: Английский

---

Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1724 - 1724

Published: March 30, 2025

The integration of renewable energy systems into modern buildings is essential for enhancing efficiency, reducing carbon footprints, and advancing intelligent management. However, optimizing RES operations within building management introduces significant complexity, requiring advanced control strategies. One branch algorithms concerns reinforcement learning, a data-driven strategy capable dynamically managing sources other subsystems under uncertainty real-time constraints. current review systematically examines RL-based strategies applied in BEMS frameworks integrating technologies between 2015 2025, classifying them by algorithmic approach evaluating the role multi-agent hybrid methods improving adaptability occupant comfort. Following thorough explanation rigorous selection process—which targeted most impactful peer-reviewed publications from last decade, paper presents mathematical concepts RL RL, along with detailed summaries summary tables integrated works to facilitate quick reference key findings. For evaluation, outlines different attributes field considering following: methodologies RL; agent types; value-action networks; reward functions; baseline approaches; typologies. Grounded on findings presented evaluation section, offers structured synthesis emerging research trends future directions, identifying strengths limitations

Language: Английский

---

Overview of Sensing and Data Processing Technologies for Smart Building Services and Applications

Sustainability, Journal Year: 2025, Volume and Issue: 17(9), P. 4029 - 4029

Published: April 29, 2025

Internet of things (IoT) and big data technologies are increasingly gaining significance in the implementation various services applications. Consequently, much research focused on energy efficiency building management revolves around integrating IoT for collection processing. Occupancy detection, comfort, most important optimizing consumption smart buildings, environmental play a key role improving these services. Furthermore, integration advanced recent techniques, such as IoT, data, machine learning, is progressively becoming more vital both researchers industries. This paper presents discusses emerging that will contribute to designing novel IoT-based architectures improve These offer innovative solutions address challenges interoperability, scalability, real-time processing within intelligent environments, paving way efficient, adaptive, user-centric systems. The main aim this help define an optimal architecture all layers, from sensing stream We established comparative criteria between popular techniques select appropriate framework developing platforms managing services, occupancy detection systems occupants’ comfort management, further, enhance deployment digital twins critical environment monitoring anomaly detection. proposed uses Apache Kafka, Storm, SAMOA its core components, creating comprehensive platform efficient collection, monitoring, with high performance terms fault tolerance low latency.

Language: Английский

---

Green buildings: requirements, features, life cycle, and relevant intelligent technologies

Internet of Things and Cyber-Physical Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

---

Sociotechnical Design of Building Energy Management Systems in the Public Sector: Five Design Principles

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

---

Sociotechnical design of building energy management systems in the public sector: Five design principles

Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124628 - 124628

Published: Oct. 18, 2024

Language: Английский

---

Municipal Energy Efficiency in Portugal: An Analysis of Electricity and Natural Gas Consumption

International Journal of Religion, Journal Year: 2024, Volume and Issue: 5(10), P. 4099 - 4111

Published: July 15, 2024

Analysing energy consumption efficiency is essential for understanding resource patterns, identifying the economic consequences, and developing effective public policies. The study investigates levels in Portuguese municipalities order to analyse disparities efficiency. aim observe possible relationship between population density consumed by residents. uses DEA model detect benchmarking inefficiencies, opportunities improvement practices. results suggest that there are serious a significant positive correlation amount of consumed. can be attributed different adoption efficient point need define policies aimed at promoting more research emphasises importance implementing encourage sustainable practices conclusions have important practical implications formulation local development consumption.

Language: Английский

---