Hasil untuk "Renewable energy sources"

Fan Zhang, Pengcheng Zhao, Meng Niu et al.

V. Palomares, P. Serras, I. Villaluenga et al.

Bin Zhou, Wentao Li, K. Chan et al.

P. Denholm, E. Ela, B. Kirby et al.

N. Lewis, D. Nocera

M. Guney, Yalçın Tepe

M. Deshmukh, S. Deshmukh

Staffan Jacobsson, Anna Bergek

A. Gallo, J. Simões-Moreira, H. Costa et al.

P. Menanteau, D. Finon, Marie-Laure Lamy

M. Argyrou, P. Christodoulides, S. Kalogirou

Renewable Energy Sources have been growing rapidly over the last few years. The spreading of renewables has become stronger due to the increased air pollution, which is largely believed to be irreversible for the environment. On the other hand, the penetration of renewable energy technologies causes major problems to the stability of the grid. Along with the fluctuations of the renewable energy technologies production, storage is important for power and voltage smoothing. Energy storage is also important for energy management, frequency regulation, peak shaving, load leveling, seasonal storage and standby generation during a fault. Thus, storage technologies have gained an increased attention and have become more than a necessity nowadays. This paper presents an up to date comprehensive overview of energy storage technologies. It incorporates characteristics and functionalities of each storage technology, as well as their advantages and disadvantages compared with other storage technologies. Comparison tables with several characteristics of each storage method are included, while different applications of energy storage technologies are described as well. Finally, several hybrid energy storage applications are analyzed and different combinations of energy storage technologies are reviewed.

P. Poizot, F. Dolhem

German Gamazo

S. Dawoud, Xiangning Lin, Merfat I. Okba

Richard York

Yi Wang, Junyong Wu

The high penetration of distributed photovoltaic (DPV) systems in distribution networks (DNs) can lead to a series of issues such as reverse power flows and voltage violations, posing a significant threat to the safe operation of DNs. Achieving the minimum curtailment of DPV in DNs is one of the most direct and cost-effective means to ensure their safe operation and effectively utilize renewable energy sources under existing conditions. Introducing the concepts of PV moments and load moments, the moment difference analysis theory (MDAT) for DNs with DPV is proposed. This theory transforms the integration challenge of DPV into a problem of balancing the moment difference (MD) equations for power restoration and maintenance. For a given DN, when the highest node voltage reaches the specified voltage limit, the MD, defined as the difference between PV moments and load moments, approximates a constant known as the critical moment difference (CMD). This CMD is determined by the topological structure and line parameters of the DN, independent of load distribution and PV deployment. The theoretical derivations and case studies confirm this concept. The CMD represents the limit of a DN’s capacity to integrate DPV. The DPV moment is the quantity that the DN needs to accommodate, while the load moment serves as the resource for accommodating the PV moment. Based on MDAT, a method for the minimum curtailment of DPV in DNs is proposed and applied to the analysis and calculations of a 10 kV feeder line at Sichakou of the State Grid Shandong Electric Power Company and the 12.66 kV IEEE 33 bus and 69 systems. The case studies demonstrate that, compared to traditional particle swarm optimization (PSO) methods, the minimum PV curtailment strategy presented in this paper increases optimization speed by 4736.82 times under an error margin of 0.6 %. This validates the correctness and rapidity of the method, making it suitable for real-time optimization and scheduling for minimum PV curtailment in DNs.

Eunice Estrella De Guzman, Tzu‐Hsuan Wang, Michael Angelo B. Promentilla et al.

Green electricity‐driven electrocatalytic CO2 reduction (e‐CO2RR) has emerged as a promising approach to upcycle CO2 into valuable chemicals and fuels, paving the way for a carbon‐neutral economy. The success of such a device relies on the development of cost‐effective catalysts that can efficiently and selectively catalyze e‐CO2RR. In the present contribution, the high activity and selectivity of graphene‐supported CoPc (graphene‐CoPc) are demonstrated toward CO generation from e‐CO2RR by encapsulating graphene|CoPc into Perlite–Metakaolin‐based geopolymer (geopolymer|graphene‐CoPc). The high electric conductivity (3.52 ± 0.4 S m−1) and CO2 adsorption capability (0.16 mmol CO2 g−1) of the geopolymer matrix, obtained through the systematic investigation and optimization of synthetic conditions, facilitate the charge transfer and provide high local CO2 concentration. Consequently, this significantly enhancing both turnover frequency (2.3 ± 0.3 s−1) and Faradaic efficiency (93.7 ± 3.1%) of geopolymer|graphene‐CoPc for CO production from the low‐concentration CO2 (≈40%) in simulated biogas atmosphere at a low η of 0.69 V as compared to the pristine graphene‐CoPc (turnover frequency: 1.37 ± 0.1 s−1 and Faradic efficiency: 46.3 ± 2.0%).

Shumet Geremew Asabie, Adamu Sheferie Tadesse

Abstract Energy access remains a sensitive issue for sustainable development, especially in developing countries where energy crises are widespread. This study explores the influence of socioeconomic variables on renewable energy access and examines the current status, challenges, and solutions for clean energy in the Alemwach refugee camp. 50 households were assessed through structured cross-sectional questionnaires. Education and income level affected energy access significantly (p < 0.05), whereas gender and age indicated no significant relationship (p > 0.05). The energy sources available in the camp are firewood, charcoal, diesel generator, and solar, with affordability of 44%, 24%, 32%, 24% respectively. According to the survey, the main reliable energy types were charcoal for cooking and solar for lighting and phone charging. The main challenges were a lack of awareness, low income, the absence of diesel oil and solar storage around the camp, and a skill gap in maintenance. These challenges should be addressed in the short term by fixing socio-economic variables, providing improved cookstoves, solar funding, and training for capacity building. Installing solar mini-grids, improving infrastructure, incorporating refugees in national energy policy, and strengthening all institutions and community organizations to participate in energy access programs should be considered in the long term. The results of this paper give important insights for energy policy experts in the Ethiopian government, research institutions, NGOs, and emergency relief organizations to address problems regarding renewable energy access in refugee camps.

Ali Forootani, Mohammad Sadr, Danial Esmaeili Aliabadi et al.

Energy system models are increasingly employed to guide long-term planning in multi-sectoral environments where decisions span electricity, heat, transport, land use, and industry. While these models provide rigorous quantitative insights, their outputs are often highly technical, making them difficult to interpret for non-expert stakeholders such as policymakers, planners, and the public. This communication gap limits the accessibility and practical impact of scenario-based modeling, particularly as energy transitions grow more complex with rising shares of renewables, sectoral integration, and deep uncertainties. To address this challenge, we propose the Renewable Energy Large Language Model (RE-LLM), a hybrid framework that integrates Large Language Models (LLMs) directly into the energy system modeling workflow. RE-LLM combines three core elements: (i) optimization-based scenario exploration, (ii) machine learning surrogates that accelerate computationally intensive simulations, and (iii) LLM-powered natural language generation that translates complex results into clear, stakeholder-oriented explanations. This integrated design not only reduces computational burden but also enhances inter-pretability, enabling real-time reasoning about trade-offs, sensitivities, and policy implications. The framework is adaptable across different optimization platforms and energy system models, ensuring broad applicability beyond the case study presented. By merging speed, rigor, and interpretability, RE-LLM advances a new paradigm of human-centric energy modeling. It enables interactive, multilingual, and accessible engagement with future energy pathways, ultimately bridging the final gap between data-driven analysis and actionable decision-making for sustainable transitions.

Joseph Le Bihan, Thomas Lapi, José Halloy

The global energy transition depends on large-scale photovoltaic (PV) and wind power deployment. While 2050 targets suggest a transition endpoint, maintaining these systems beyond mid-century requires continuous renewal, marking a fundamental yet often overlooked shift in industrial dynamics. This study examines the transition from initial deployment to long-term renewal, using a two-phase growth model: an exponential expansion followed by capacity stabilization. By integrating this pattern with a Weibull distribution of PV panel and wind turbine lifespans, we estimate the annual production required for both expansion and maintenance. Our findings highlight two key factors influencing production dynamics: deployment speed and lifespan. When deployment occurs faster than the average lifespan, production overshoots and exhibits damped oscillations due to successive installation and replacement cycles. In contrast, gradual deployment leads to a smooth increase before stabilizing at the renewal rate. Given current scenarios, the PV industry is likely to experience significant oscillations - ranging from 15 % to 60 % of global production - while wind power follows a monotonic growth trajectory. These oscillations, driven by ambitious energy targets, may result in cycles of overproduction and underproduction, affecting industrial stability. Beyond solar and wind, this study underscores a broader challenge in the energy transition: shifting from infrastructure expansion to long-term maintenance. Addressing this phase is crucial for ensuring the resilience and sustainability of renewable energy systems beyond 2050.