Hasil untuk "Renewable energy sources"

Eyup Dogan, Fahri Seker

M. Bailera, P. Lisbona, L. Romeo et al.

Power to Gas (PtG) processes have appeared in the last years as a long-term solution for renewable electricity surplus storage through methane production. These promising techniques will play a significant role in the future energy storage scenario since it addresses two crucial issues: electrical grid stability in scenarios with high share of renewable sources and decarbonisation of high energy density fuels for transportation. There is a large number of pathways for the transformation of energy from renewable sources into gaseous or liquid fuels through the combination with residual carbon dioxide. The high energy density of these synthetic fuels allows a share of the original renewable energy to be stored in the long-term. The first objective of this review is to thoroughly gather and classify all these energy storage techniques to define in a clear manner the framework which includes the Power to Gas technologies. Once the boundaries of these PtG processes have been evidenced, the second objective of the work is to detail worldwide existing projects which deal with this technology. Basic information such as main objectives, location and launching date is presented together with a qualitative description of the plant, technical data, budget and project partners. A timeline has been built for every project to be able of tracking the evolution of research lines of different companies and institutions.

Agustín Álvarez-Herranz, D. Balsalobre-lorente, Muhammad Shahbaz et al.

Shaopeng Guo, Qibin Liu, Jie Sun et al.

The utilization of renewable energy is significantly important for the world because global energy consumption is increasing, while conventional energy sources are no longer sufficient to meet the energy demand, triggering energy crises. However, variation in solar radiation and wind speed caused by climate and weather conditions restricts the stable operation of renewable energy systems, therefore, causing the output to fluctuate. A hybrid renewable energy (HRE) system can be highly efficient by combining multiple renewable energy sources and is regarded as a promising solution to the above issue. In this review, a comprehensive summary and discussion of the uses of HRE in terms of space heating, cooling, hot water usage, power generation, hydrogen production, drying and multi-generation are conducted. Hybrid system configurations, specific devices, application procedures, and performance are reviewed. Moreover, the challenges and outlook for HRE utilization are discussed, including the following points: proper use of the local sources in view of disperse and regional distribution of renewable energy; development of hybrid storage subsystems for HRE to improve the stability of the energy supply; further optimization of the operation strategy and system size to minimize the cost in order to promote the application; and, clear identification of the supporting local policies of renewable energy, especially considering HRE. Furthermore, the research potential is described for HRE utilization integrating direct CO2 reduction.

T. Johansson, H. Kelly, A. Reddy et al.

Kamal Anoune, M. Bouya, Abdelali Astito et al.

Abstract Solar and wind energy are considered as promising electrical generating sources. These renewable energies are omnipresent, with free access, and a friendly environmental impact. Their integration remains technically and economically advantageous for electrical generation in isolated areas (IS). In several cases, the separate use of solar and wind energy sources may result in considerable over-sizing, which makes the single renewable energy sources in implementation very costly. It is found that the use of one of the optimization sizing techniques could help to guarantee the maximum power reliability and the minimum system cost for the future hybrid implementation. Moreover, a remarkable interest is manifesting for the use of solar and wind renewable energy sources (RES), which provide a realistic form of electrical generation in isolated areas. This paper provides an updated literature review, of the most applied method and techniques used in sizing and optimization of PV-Wind based hybrid system (PWHS) for an isolated area aiming to reach the best compromise between power reliability and hybrid system costs. Furthermore, this work discusses a comparison of the most common topologies used for the implementation of PWHS, then, presents a mathematical model of the hybrid system components with an emphasis on the importance of power reliability and system cost, Finally, provides an extensive analysis of software tools and algorithm approach used in sizing optimization.

S. Paramati, Di Mo, Rakesh Gupta

F. H. Gandoman, A. Ahmadi, A. Sharaf et al.

A. Aliyu, Babangida Modu, Chee Wei Tan

Stamatios Ntanos, M. Skordoulis, Grigorios L. Kyriakopoulos et al.

This paper aims at examining the relationship between energy consumption deriving from renewable energy sources, and countries’ economic growth expressed as GDP per capita concerning 25 European countries. The used dataset involves European countries’ data for the period from 2007 to 2016. The statistical analysis is based on descriptive statistics, cluster analysis, and autoregressive distributed lag (ARDL), and reveals that all variables are related; this suggests a correlation between the dependent variable of GDP and the independents of renewable energy sources (RES) and Non-RES energy consumption, gross fixed capital formation, and labor force in the long-run. Furthermore, the results show that there is a higher correlation between RES’ consumption and the economic growth of countries of higher GDP than with those of lower GDP. The obtained results are consistent with other papers reviewed in this study.

Lamia Benahmed, Khaled Aliane, Brahim Rostane et al.

<p>This work focuses on geothermal energy recovery using a vertical geothermal heat exchanger coupled with a heat pump for heating applications. The primary objective of this study is to conduct a 3D numerical simulation to evaluate the effects of baffles on the thermal performance of a U-shaped heat exchanger. These baffles, designed to alter flow characteristics, were implemented to enhance heat transfer and optimize overall system efficiency. The mathematical model is based on the governing equations of fluid mechanics and thermodynamics, solved using the finite volume method in the Ansys CFX software. Various baffle configurations were investigated, focusing on their placement (on the inlet and outlet tube), geometry, and the use of perforations with decreasing diameters. Simulations were conducted for a Reynolds number of Re=3600, capturing the flow behavior under specific conditions. The analysis revealed that the optimal configuration, involving baffles strategically placed on the outlet tube with decreasing perforation diameters, significantly improved thermal performance. These findings highlight the potential for designing more efficient heat exchangers in geothermal systems, paving the way for advancements in sustainable energy solutions.</p>

Zhiqiang Dai, Rungroj Chanajaree, Chengwu Yang et al.

Traditional aqueous electrolyte systems in zinc-ion batteries (ZIBs) often face challenges such as sluggish ion transfer kinetics, dendrite formation, and sudden battery failures in harsh temperature environments. Herein, we introduce a pioneering approach by integrating a bifunctional additive composed of ethylene glycol (EG) and sodium gluconate (Ga) into ZnSO4 (ZSO) electrolyte to overcome these obstacles. The polyhydroxy structures of EG and Ga can reconstruct the hydrogen bond network of H2O to improve its liquid stability, and also adjust the coordination environment around hydrated Zn2+. Additionally, Ga in the H2O–EG mixture leads to the formation of a robust protective layer that promotes uniform deposition of Zn2+ ions and minimizes unwanted side reactions. Therefore, Zn anodes with 40% ZSO–Ga electrolyte can cycle for more than 3,000 h at 25 °C and 800 h at 50 °C. Furthermore, Zn||NH4V4O10 (NVO) full batteries demonstrate remarkable cycle stability, lasting up to 10,000 cycles at 1 A g−1 with a capacity retention of 79.1%. The multifunctional electrolyte additive employed in this study emerges as a promising candidate for enabling highly stable zinc anodes under diverse temperature conditions.

Junda Lu, Xiangwu Yan, Jiaoxin Jia et al.

In a traditional distribution network, the weak grid structure and high penetration of renewable energy sources restrict the carrying capacity. Flexible interconnection devices (FIDs) and energy storage systems (ESSs) offer a valuable solution to these challenges by coordinating and optimizing them regarding time and space. This paper proposes a coordinated bi-level planning method for the rotary power flow controller (RPFC) and ESS. The goal is to improve both economic efficiency and the comprehensive carrying capacity of the distribution network. First, the economic advantages of RPFC over traditional FIDs are analyzed. Then, mathematical models for the RPFC and ESS are developed. A bi-level planning framework is established. The upper level minimizes total costs by optimizing the siting and sizing of RPFC and ESS. The lower level is the coordinated operation optimization level, where a comprehensive carrying capacity index system for flexible interconnection is constructed, considering system stability, economy, and flexibility. A hybrid algorithm is introduced to solve the model efficiently. It combines the improved gravitation field algorithm (IGFA) with second-order cone programming (SOCP). The algorithm uses a tent chaos map for initialization and adopts an elite retention strategy to enhance convergence. The simulation is based on a three-feeder distribution network using MATLAB and the GUROBI solver. Compared to Scheme 1, the total cost is reduced by 22.6 %, and the carrying capacity index is improved by 22.3 %, demonstrating enhanced economic performance and carrying capacity through coordinated planning of RPFC and ESS.

Mezulis Marcis, Arbidans Lauris, Nikolajeva Vizma et al.

Timber harvesting of coniferous trees (the most abundant species in the Northern Hemisphere) leaves significant greenery side streams – coniferous needles and branches (pine, spruce and other species). Coniferous needles have been widely used in ethnomedicine, and recent research characterizes them as rich sources of biologically active compounds with immunostimulatory and anti-inflammation activities, as well as they are traditionally used to treat inflammation of the respiratory tract, colds and flu. However, new sustainable extraction methods should be proposed to obtain coniferous needle extracts with biomedical application potential. Classical extraction methods (stirring and heating) were used in this study and compared with ultrasonic treatment, and process duration and temperature optimisation were performed. During extraction, glycerol and propylene glycol, solvents widely used in the food and pharmaceutical industries, were used to improve the extracts’ stability. Obtained coniferous needle and branch extracts were characterized by their antiradical activities (17–82 % Trolox eq.) and total polyphenol concentration (6–22 % gallic acid eq.) was analysed. The extracts were tested for antibacterial and antifungal activity, which demonstrates activities comparable to synthetic drugs with potentially lower side effects caused by drugs.

Nida Arshad, Elizabeth Jayex Panakkal, Palani Bharathy Kalivarathan et al.

The global reliance on fossil fuels has caused severe environmental challenges, emphasizing the urgent need for sustainable and renewable energy sources. Bioethanol production from lignocellulosic biomass has emerged as a promising alternative due to its abundance, renewability, and carbon-neutral footprint. However, its economic feasibility remains a major obstacle owing to high production costs, particularly those associated with low ethanol titers and the energy-intensive distillation process costs for low titers. High-solid loading processes (≥15% <i>w</i>/<i>w</i> or <i>w</i>/<i>v</i>) have demonstrated potential to overcome these limitations by minimizing water and solvent consumption, enhancing sugar concentrations, increasing ethanol titers, and lowering downstream processing cost. Nevertheless, high-solid loading also introduces operational bottlenecks, such as elevated viscosity, poor mixing, and limited mass and heat transfer, which hinder enzymatic hydrolysis efficiency. This review critically examines emerging pretreatment and enzymatic hydrolysis strategies tailored for high-solid loading conditions. It also explores techniques that improve sugar yields and conversion efficiency while addressing key technical barriers, including enzyme engineering, process integration, and optimization. By evaluating these challenges and potential mitigation strategies, this review provides actionable insights to intensify lignocellulosic ethanol production and advance the development of scalable, cost-effective biorefinery platforms.

Loan Thi Do, Trung Ngoc Nguyen, Quynh T. Tran et al.

Batteries energy storage systems (BESS) are becoming a common trend worldwide supporting an increase in the power system's renewable energy (RE). Storing energy is not applied and has been in the research process in Vietnam. This study aims to evaluate the economic performance of a solar power plant (SPP) in Vietnam both before and after integrating a BESS through key metrics including the levelized cost of electricity (LCOE), net present value (NPV), and electrical productivity. Furthermore, this study incorporates sensitivity analysis to the metrics under variations in transmission line limitation (TLL), capital expenditure (CAPEX), and subsidies in this project. The results show that the solar photovoltaic (PV) system in the chosen SPP has an LCOE of 6.13 cents/kWh and an NPV of 7.52 million USD. The NPV will decrease to zero in the TLL from 22.2 MW. If this SPP is installed with a BESS of 2 MW 2 MWh, the LCOE increases to 6.38 cents/kWh, the NPV decreases to 5.5 million USD, and the levelized storage cost (LCOS) of 126.61 cents/kWh. The PV-BESS system is no longer economically efficient when the BESS reaches 12 MWh or larger. When TLL falls below 24 MW, BESS holds a significant role in improving the system's output. CAPEX's reductions of BESS have a negligible impact on LCOE, but a significant on LCOS. Investment-based incentives (IBI) starting at 7 %, or Capital-based incentives (CBI) starting at 4 cents/W can enhance the financial attractiveness of the PV-BESS system.

devan Rozali, Rachma Prilian Eviningsih, Novie Ayub Windarko

Abstract- Short Term Load Forecasting (STLF) is becoming very important as the use of distributed energy sources, renewable energy, and demand side management increases. Electrical energy is one of the most widely used energy, especially in households. To avoid excessive electricity consumption, we propose a household electricity consumption forecasting system using Convolutional Neural Network (CNN) method. The input of CNN is the power of several household loads measured for one week at 10-minute intervals. This data is used to train the model and predict household electricity consumption for the next week. Forecasting results for a week show a difference in consumption of 3.623 kWh, while with the load management method the difference is 3.439 kWh. With an electricity tariff of Rp1.352/kWh, the estimated electricity cost for the following week is Rp4.892.00, and with load management, the cost drops to about Rp4.649.52 (5% savings).The testing method is done by comparing the forecasting results and actual data for one week. The results show an average difference of only 1.57W with an average error of 0.07%. The CNN method is also compared with the Long Short-Term Memory (LSTM) method. As a result, CNN has better performance with CNN RMSE value of 3.688, CNN management of 3.354, while LSTM RMSE of 12.603, and LSTM management of 13.132. CNN is proven to be more accurate for household short-term electricity load forecasting..

Mengjiao Wang, Gui-zhou Wang, Zhen Sun et al.

Abstract In this review, we primarily analyze the hydrogen production technologies based on water and biomass, including the economic, technological, and environmental impacts of different types of hydrogen production technologies based on these materials, and comprehensively compare them. Our analyses indicate that all renewable energy-based approaches for hydrogen production are more environmentally friendly than fossil-based hydrogen generation approaches. However, the technical ease and economic efficiency of hydrogen production from renewable sources of energy needs to be further improved in order to be applied on a large scale. Compared with other renewable energy-based methods, hydrogen production via biomass electrolysis has several advantages, including the ease of directly using raw biomass. Furthermore, its environmental impact is smaller than other approaches. Moreover, using a noble metal, catalyst-free anode for this approach can ensure a considerably low power consumption, which makes it a promising candidate for clean and efficient hydrogen production in the future.

R. Haas, C. Panzer, G. Resch et al.

Siyang Xu, Jiebei Zhu, Bingsen Li et al.

With large-scale grid integration of renewable energy sources (RES), power grid operations gradually exhibit the new characteristics of high-order uncertainty, leading to significant challenges for system operational security. Traditional model-driven generation dispatch methods require large computational resources, whereas the widely concerned Reinforcement Learning (RL)-based methods lead to issues such as slow training speed due to the high complexity and dimension of processed grid state information. For this reason, this paper proposes a novel Grid Expert Strategy Imitation Learning (GESIL)-based real-time (5 min intervals in this paper) dispatch method. Firstly, a grid model is established based on the graph theory. Secondly, a pure rule-based grid expert strategy (GES) considering detailed power grid operations is proposed. Then, the GES is combined with the established model to obtain a GESIL agent using imitation learning by offline–online training, which can produce specific grid dispatch decisions for real-time. By designing a graph theory-based grid model, a model-driven purely rule-based GES, and embedding a penalty factor-based loss function into IL offline–online training, GESIL ultimately achieves high training speed, high solution speed, and strong generalization capability. A modified IEEE 118-node system is employed to compare the proposed GESIL to traditional dispatch method and RL method. Results show that GESIL has significantly improved computational efficiency by approximately 17 times and training speed by 14.5 times. GESIL can more stably and efficiently compute real-time dispatch decisions of grid operations, enhancing the optimization effect in terms of transmission overloading mitigation, transmission loading optimization, and power balancing control.