Frontiers in Energy Research | New and Recent Articles

IntroductionHydro-dominant power systems in Latin America are recurrently exposed to ENSO-driven hydrological scarcity, creating adequacy risks precisely when firm energy is most valuable.MethodsThis paper proposes a Monte Carlo-based methodology to accredit nuclear firm energy for small modular reactors (SMRs) under climatic stress, using an explicit stress-month definition derived from long-run…

IntroductionDecarbonizing energy production is essential for achieving greenhouse gas mitigation goals. To date, most of the work on decarbonizing energy has been focused on electricity. The decarbonization of heat is also critical, as the heat demand from current industries is expected to grow and be supplemented by demand in emerging sectors (e.g. carbon dioxide removal). Despite this need, hea…

As photovoltaic (PV) power plants expand, UAV-based infrared thermography has become a standard tool for efficient and safe fault diagnosis. However, most deep learning models are too large and computationally heavy for real-time deployment on edge devices. We propose NanoDistillNet, a lightweight model based on knowledge distillation designed for on-board processing. The framework utilizes a tea…

Road piezoelectric energy harvesting technology has been widely studied and applied. However, after long-term use, the piezoelectric ceramics inside the harvester will be broken, which seriously affects the use of the piezoelectric system. A reliable recycling process can be adopted to reuse the transducer. Therefore, this study focuses on the feasibility of field application of road piezoelectri…

IntroductionSolar energy plays a critical role in meeting global energy demands and combating climate change. While meteorological factors are widely used in solar radiation forecasting models, the impact of air pollution parameters remains underexplored, particularly in the Western Mediterranean Region of Türkiye.MethodsRegression models were developed using four machine learning algorithms: Sup…

Capacity planning in highway multi-energy systems faces significant challenges due to the high uncertainty of renewable energy generation and the limited availability of historical data during the planning stage. This paper proposes an integrated framework that combines photovoltaic (PV) scenario generation using a Conditional Variational Autoencoder (CVAE) with a Wasserstein-type distributionall…

To fully and effectively exploit the spatiotemporal correlations among multi-user loads, this paper proposes an online short-term multi-user load forecasting method based on dynamic recognition of spatiotemporal dependencies. A hybrid graph convolutional network-bidirectional long short-term memory (GCN-BiLSTM) model is employed to capture the complex spatiotemporal relationships among multi-user…

This article studies the load frequency control (LFC) problem of multi-area interconnected power systems under the threat of denial-of-service (DoS) attacks. Due to the open communication network of control regions, interconnected power systems are particularly vulnerable to Dos attacks, which can undermine the stable operation of the power system. To deal with this problem, we design a novel sel…

The high penetration of renewable energy significantly increases the stochasticity and complexity of power system operating scenarios, imposing challenges on voltage stability assessment such as high data dimensionality, heavy computational burden, and insufficient pertinence of reactive power configuration. To address the voltage support optimization problem in current systems, this paper propos…

In oil-immersed transformers, cellulose insulating paper deteriorates when exposed to electric field, moisture, and high temperature for a long time, leading to decrease in mechanical strength and insulating performance, which affects the service life and operational reliability. In this paper, dielectric barrier discharge (DBD) is adopted to generate atmospheric pressure low-temperature plasma f…

ObjectiveTo develop and validate a quantitative framework for optimizing maritime renewable energy integration, advancing SDG 7 targets through improved deployment efficiency and socioeconomic impact assessment.Theoretical FrameworkThis research integrates resource optimization theory with sustainable development paradigms, addressing the gap between technical efficiency metrics and SDG 7 impleme…

China’s power industry faces critical challenges in balancing rapid economic growth with environmental sustainability amidst surging electricity demand from artificial intelligence (AI), cloud computing, and data centers. This study introduces the Data Center Energy Consumption Ratio (DCECR) as a quantitative metric and comprehensively evaluates China’s “East-to-West Computing” (ETWC) strategy th…

IntroductionDriven by the global energy transition and the “Dual-Carbon” strategy, the electrification of heavy-duty logistics has introduced massive mobile energy storage resources Electric Trucks (ETs) into dairy industrial park (DIP). However, the random charging/discharging behaviors of ETs, coupled with multi-energy flow coupling and conflicting stakeholder interests, exacerbate system peak–…

Mpumalanga, South Africa’s coal-dependent province, faces acute socio-economic risks from coal exit, yet the transition also presents substantial renewable-energy employment opportunities. This paper synthesises evidence on the economic barriers and opportunities for community adaptation to renewable-energy employment in coal-dependent regions of Mpumalanga, and identifies policy levers to achiev…

As climate change accelerates, buildings must adopt not only efficient envelopes and systems but also operational strategies that enhance sustainability. Building Energy Flexibility (BEF) becomes particularly valuable when scaled to Energy Clusters (ECs), where multiple buildings coordinate energy use. This study evaluates a cluster of 202 single-family houses in Lodz, Poland, where each building…

The world is facing ongoing efforts to rely more on Renewable energy sources (RES) to reduce carbon emissions and protect the environment. However, integrating RES can be challenging due to their variable nature. With the development of Artificial Intelligence (AI), RES management can be enhanced and improved to overcome limitations. However, AI is often viewed as a “black box” because it lacks e…

Recently, hydrogen energy has been increasingly considered for decarbonization, and it could drive technological convergence in diverse areas. This study examines technological convergence in hydrogen energy and analyzes how technological characteristics are associated with survival using triadic patent data. FP-growth, an association rule mining technique, identifies convergent patterns of hydro…

This work investigates desalination salt thermal energy storage (TES) using a benchtop air-to-salt module and a complementary CFD study of an electro-thermal concept with embedded electrical heaters. Experiments were conducted at inlet air temperatures of 200, 300, and 400 °C for charging, storage, and discharge performance of the TES module. Dimensionless analysis using the Fourier number captur…

To address the challenges of voltage deviation and increased network losses arising from the high integration of photovoltaic (PV) systems in distribution networks, this paper proposes a bi-level optimisation model for configuring distributed energy storage systems (ESS) tailored to high-penetration PV distribution networks. In the proposed model, the upper-level operational layer minimises volta…

Nuclear energy is considered an important carbon-free and reliable energy source. However, ionizing radiation associated with nuclear power plants is a long-standing public concern. National surveys have been conducted over the last 30 years—in 1991, 2001, 2008, 2011, and 2022—to assess the trends in public perceptions about radiation associated with nuclear energy, as well as to investigate whic…