Abdelrahman S. Heikal, Ibrahim Mohamed Diaaeldin, Niveen M. Badra
et al.
Integrating more renewable energy sources into dc microgrids necessitates the addition of control layers and communication channels, which can introduce vulnerabilities to cyberattacks. This paper presents an AI-based approach for detecting and countering False Data Injection Attacks (FDIAs) in these systems. The approach uses an Artificial Neural Network (ANN), specifically feedforward neural networks, to identify FDIAs and classify them as related to current or voltage. Additionally, a Long Short-Term Memory (LSTM) network is employed to mitigate the attacks by inferring and filtering out false voltage or current measurements. The method was validated on the Distributed Generator Unit (DGU) system using MATLAB/Simulink. To enhance the accuracy, the approach considers the impact on all grid lines and measurement points, supported by statistical analyses demonstrating the convergence and effectiveness of the response to cyberattacks. ANN successfully detected voltage attacks with an accuracy of 93% to 99% and identified current attacks with 99% accuracy. LSTM successfully overcame the false voltage injection attack with a 99.6% accuracy rate. LSTM effectively mitigates 90% of false current injection attacks.
Incentivizing flexible consumption of end-users is key to maximizing the value of local exchanges within Renewable Energy Communities. If centralized coordination for flexible resources planning raises concerns regarding data privacy and fair benefits distribution, state-of-the-art approaches (e.g., bi-level, ADMM) often face computational complexity and convexity challenges, limiting the precision of embedded flexible models. This work proposes an iterative resolution procedure to solve the decentralized flexibility planning with a central operator as a coordinator within a community. The community operator asks for upward or downward flexibility depending on the global needs, while members can individually react with an offer for flexible capacity. This approach ensures individual optimality while converging towards a global optimum, as validated on a 20-member domestic case study for which the gap in terms of collective bill is not more than 3.5% between the decentralized and centralized coordination schemes.
Arega Getaneh Abate, Xiaobing Zhang, Xiufeng Liu
et al.
Integrating electric mobility, including electric vehicles (EVs), electric trucks (ETs), and renewable energy sources (RES) with the power grid is paramount for decarbonization, efficiency, and stability. A critical gap remains, however: existing smart-grid and e-mobility cost-benefit analysis (CBA) approaches do not yet provide a unified framework for appraising AI-driven operational digital platforms (ODPs) that jointly coordinate EV/ET charging, renewable generation, and grid operations across sectoral and national boundaries. This paper develops a seven-step CBA framework tailored to this class of platform. The framework maps each layer of a multi-layered AI architecture to traceable, monetizable benefit streams-panning economic efficiency, grid reliability, and environmental externalities--while explicitly accounting for AI-specific capital and operational expenditures that conventional appraisals omit. Applied to a ten-year, three-country deployment across Austria, Hungary, and Slovenia, the analysis indicates a robust positive investment case under the modeled assumptions, confirmed through scenario sensitivity analysis, one-way parameter ranking, and probabilistic simulation. Benefit composition and country-level drivers differ systematically across national contexts, yet the economic rationale is preserved in each, reflecting the framework's adaptability to heterogeneous electrification trajectories. The findings indicate the economic viability of AI-driven digital platforms for cross-sectoral energy--mobility integration and highlight the critical role of ODPs in advancing decarbonization in the mobility--power nexus. To that end, they have direct implications for the design and appraisal of digital infrastructure investments under the EU's Fit for 55 and REPowerEU programmes.
Variational autoencoders (VAEs) are among leading approaches to address the problem of learning disentangled representations. Typically a single VAE is used and disentangled representations are sought within its single continuous latent space. In this paper, we propose and provide a proof of concept for a novel Multi-Stream Variational Autoencoder (MS-VAE) that achieves disentanglement of sources by combining discrete and continuous latents. The discrete latents are used in an explicit source combination model, that superimposes a set of sources as part of the MS-VAE decoder. We formally define the MS-VAE approach, derive its inference and learning equations, and numerically investigate its principled functionality. The MS-VAE model is very flexible and can be trained using little supervision (we use fully unsupervised learning after pretraining with some labels). In our numerical experiments, we explored the ability of the MS-VAE approach in separating both superimposed hand-written digits as well as sound sources. For the former task we used superimposed MNIST digits (an increasingly common benchmark). For sound separation, our experiments focused on the task of speaker diarization in a recording conversation between two speakers. In all cases, we observe a clear separation of sources and competitive performance after training. For digit superpositions, performance is particularly competitive in complex mixtures (e.g., three and four digits). For the speaker diarization task, we observe an especially low rate of missed speakers and a more precise speaker attribution. Numerical experiments confirm the flexibility of the approach across varying amounts of supervision, and we observed high performance, e.g., when using just 10% of the labels for pretraining.
Maksym Koltunov, Filippo Beltrami, Luigi Grossi
et al.
This paper evaluates the economic impact of Renewable Energy Communities (RECs) on the Italian wholesale power market. Combining a bottom-up engineering approach with a short-run economic impact assessment, the study begins by mapping existing and emerging RECs in Italy. We identify key characteristics of RECs, such as average installed capacity, institutional profiles of members, types of renewable systems used, and transmission across Italy's electricity market zones. This mapping yields representative REC configurations, which are employed within a bottom-up engineering model to generate energy injection and self-consumption profiles for different REC prosumer and producer categories (residential, public, small and medium enterprise, non-profit organization, and standalone installation), considering the different levels of solar irradiance in Italy based on latitude. These zonal results, aggregated on an hourly basis, inform the implementation of the synthetic counterfactual approach, which develops alternative scenarios (e.g., 5 GW target for REC-driven capacity set by Italian policy for 2027) to assess the impact of REC-driven injection and self-consumption on the Italian day-ahead power market. The findings suggest that REC deployment can increase equilibrium quantities during daylight in most of the time, while decreasing equilibrium quantities mostly during the cold months, as electrified heating drives greater self-consumption and offsets lower grid injections. Both positive and negative effects on equilibrium quantities suggest that REC deployment also has a potential to reduce wholesale electricity prices. Moreover, by reducing grid exchanges through higher self-consumption, REC proliferation can alleviate pressure on the distribution system.
We present a comprehensive global temporal dataset of commercial solar photovoltaic (PV) farms and onshore wind turbines, derived from high-resolution satellite imagery analyzed quarterly from the fourth quarter of 2017 to the second quarter of 2024. We create this dataset by training deep learning-based segmentation models to identify these renewable energy installations from satellite imagery, then deploy them on over 13 trillion pixels covering the world. For each detected feature, we estimate the construction date and the preceding land use type. This dataset offers crucial insights into progress toward sustainable development goals and serves as a valuable resource for policymakers, researchers, and stakeholders aiming to assess and promote effective strategies for renewable energy deployment. Our final spatial dataset includes 375,197 individual wind turbines and 86,410 solar PV installations. We aggregate our predictions to the country level -- estimating total power capacity based on construction date, solar PV area, and number of windmills -- and find an $r^2$ value of $0.96$ and $0.93$ for solar PV and onshore wind respectively compared to IRENA's most recent 2023 country-level capacity estimates.
(English) Modern power systems are increasingly integrating a larger share of renewable energy resources to mitigate climate change. These renewable resources are gradually replacing conventional power plants, which employ synchronous machines for power generation. Synchronous generators behave as voltage sources governed by their electromechanical dynamics. Moreover, they possess intrinsic inertia, which stabilizes the network frequency. In contrast, renewable energy sources primarily use power electronics converters to connect to the electrical grid. The behavior of power electronics is dominated by their implemented control strategies, as their physical dynamics are substantially faster. Currently, the most widely used control approach for converters is grid‐following control. This strategy drives converters to behave as current sources. However, the AC network requires voltage sources for operation and stability. Thus, the integration of grid-following converters displaces voltage-source generators with current-source devices, potentially affecting system stability and dynamics. To improve overall network stability, grid‐forming control was introduced. Grid-forming converters operate as voltage sources and may incorporate virtual inertia. Virtual inertia is emulated because power electronics lack rotating mass. Moreover, by behaving as voltage sources, grid-forming converters contribute to system stability. The present thesis provides a fundamental assessment of both grid‐following and grid‐forming control strategies. First, the internal controls of grid-following converters are analyzed, and their key components are defined. Then, different implementations of the internal control strategies of grid-forming converters (synchronization control and voltage control) are explored, and the most suitable configuration is assessed in different chapters. Specifically, a tuning methodology for the voltage control is presented, which accounts for the power electronics' inherent limitations. This methodology is employed to identify the optimal control structure based on the specific configuration of the implemented AC connection filter. Later, the industry-class synchronization controls are examined, focusing on their behavior when employing a frequency estimator. Afterwards, the limitations of renewable resources when operating the power electronics in grid‐forming mode are investigated. To allow renewable energy sources to operate in grid-forming mode despite their limitations, this thesis introduces a Resource‐Aware Grid‐Forming (RAGFM) control. RAGFM strategy aims to maximize the frequency response, considering the resource limitations. The proposed control is validated through various analytical studies and simulations. RAGFM control is also simulated for a single-stage photovoltaic power plant. This topology exhibits a non-linear relationship between the DC-link voltage and power generation, which introduces significant control challenges. Thus, RAGFM operation is validated under this specific operating condition. Finally, the proposed control structure is further validated through experimental results. This work contributes to enhancing the integration of renewable resources through grid-forming control, supporting the transition to a more sustainable energy future. (Català) Els sistemes elèctrics de potència cada vegada inclouen una proporció més gran de recursos renovables per tal de mitigar el canvi climàtic. Aquests recursos renovables substitueixen progressivament les plantes de generació convencionals, les quals utilitzen màquines síncrones per generar electricitat. Els generadors síncrons es comporten com a font de tensió gràcies a les seves dinàmiques electromecàniques. A més, disposen d’una inèrcia intrínseca que contribueix a estabilitzar la freqüència de la xarxa. En canvi, les fonts d'energia renovables generalment es connecten a la xarxa mitjançant convertidors d'electrònica de potència. El comportament d’aquests convertidors està determinat pel control implementat, ja que les seves dinàmiques físiques són molt més ràpides. Actualment, l'estratègia de control més estesa en electrònica de potència és el control grid-following. Aquesta estratègia fa que els convertidors actuïn com a fonts de corrent. El problema és que les xarxes elèctriques requereixen de fonts de tensió per garantir-ne l'operació i l'estabilitat. Per tant, la integració de convertidors grid-following desplaça generadors que actuen com a fonts de tensió per dispositius que actuen com a fonts de corrent, fet que pot comprometre l’estabilitat i les dinàmiques del sistema. Amb l'objectiu d'incrementar l'estabilitat de la xarxa, es presenta el control grid-forming. Els convertidors amb control grid-forming es comporten com a fonts de tensió i poden incorporar inèrcia virtual. Aquesta inèrcia és emulada, ja que l'electrònica de potència no disposa de massa rotatòria. Gràcies al comportament com a font de tensió, els convertidors grid-forming contribueixen positivament a l'estabilitat del sistema elèctric. Aquesta tesi es presenta de manera fonamental tant el control grid-following com el control grid-forming. Primer, s’estudien els controls interns dels convertidors grid-following i se’n defineixen els components clau. A continuació, s’exploren diferents implementacions dels controls interns dels convertidors grid-forming, concretament el control de sincronització i el control de tensió, avaluant quina configuració és la més adequada en diferents capítols. En particular, es presenta una metodologia de sintonització del control de tensió que té en compte les limitacions del convertidor. S'aprofita aquesta metodologia per definir l'estructura de control més adient en funció del filtre que s'ha utilitzat. Seguidament, s'analitzen els controls de sincronització d'ús industrial, centrant-se en el seu comportament quan s'hi incorpora un estimador de freqüència. Posteriorment, s'aborden les limitacions dels recursos renovables a l'hora d'operar amb el control grid-forming. Per tal de permetre que aquests recursos operin en mode grid-forming, la tesi presenta un control grid-forming que és conscient del recurs renovable (RAGFM). El RAGFM maximitza la resposta freqüencial tenint en compte les restriccions del recurs. Aquesta estratègia de control s'ha validat amb diversos estudis analítics i simulacions. El control RAGFM també s'ha simulat amb una planta fotovoltaica d'etapa única. Aquesta topologia presenta una relació no lineal entre la tensió del bus de corrent continu i la generació de potència, cosa que introdueix reptes de control significatius. Així, l’operació del RAGFM s’ha validat en aquestes condicions específiques. Finalment, el RAGFM també ha estat validat mitjançant resultats experimentals. Aquest treball contribueix a la integració dels recursos renovables mitjançant el control grid-forming, donant suport a la transició cap a un futur energètic més sostenible. (Español) Los sistemas eléctricos de potencia incluyen cada vez una mayor proporción de recursos renovables con el objetivo de mitigar el cambio climático. Estos recursos renovables sustituyen progresivamente a las plantas de generación convencionales, las cuales utilizan máquinas síncronas para generar electricidad. Los generadores síncronos se comportan como fuentes de tensión gracias a sus dinámicas electromecánicas. Además, disponen de una inercia intrínseca que contribuye a estabilizar la frecuencia del sistema eléctrico. En cambio, las fuentes de energía renovables generalmente se conectan a la red mediante convertidores de electrónica de potencia. El comportamiento de estos convertidores está determinado por el control implementado, ya que sus dinámicas físicas son mucho más rápidas. Actualmente, la estrategia de control más extendida en electrónica de potencia es el control grid-following. Esta estrategia hace que los convertidores actúen como fuentes de corriente. El problema es que las redes eléctricas requieren fuentes de tensión para garantizar su operación y estabilidad. Por lo tanto, la integración de convertidores grid-following desplaza generadores que actúan como fuentes de tensión por dispositivos que actúan como fuentes de corriente, lo cual puede comprometer la estabilidad y las dinámicas del sistema. Con el objetivo de incrementar la estabilidad del sistema eléctrico, se presenta el control grid-forming. Los convertidores con control grid-forming se comportan como fuentes de tensión y pueden incorporar inercia virtual. Esta inercia es emulada, ya que la electrónica de potencia no dispone de masa rotatoria. Gracias a su comportamiento como fuente de tensión, los convertidores grid-forming contribuyen positivamente a la estabilidad del sistema eléctrico. Esta tesis presenta de forma fundamental tanto el control grid-following como el control grid-forming. Primero, se estudian los controles internos de los convertidores grid-following y se definen sus componentes clave. A continuación, se exploran diferentes implementaciones de los controles internos de los convertidores grid-forming, concretamente el control de sincronización y el control de tensión, evaluando cuál es la configuración más adecuada en distintos capítulos. En particular, se presenta una metodología de sintonización del control de tensión que tiene en cuenta las limitaciones del convertidor. Se aprovecha esta metodología para definir la estructura de control más adecuada en función del filtro que se haya utilizado. Seguidamente, se analizan los controles de sincronización de uso industrial, centrándose en su comportamiento cuando se incorpora un estimador de frecuencia. Posteriormente, se abordan las limitaciones de los recursos renovables a la hora de operar con control grid-forming. Para permitir que estos recursos operen en modo grid-forming, la tesis presenta un control grid-forming consciente del recurso renovable (RAGFM). El RAGFM maximiza la respuesta frecuencial teniendo en cuenta las restricciones del recurso. Esta estrategia de control ha sido validada mediante diversos estudios analíticos y simulaciones. El control RAGFM también ha sido simulado con una planta fotovoltaica de etapa única. Esta topología presenta una relación no lineal entre la tensión del bus de corriente continua y la generación de potencia, lo que introduce retos de control significativos. Así, el funcionamiento del RAGFM ha sido validado en estas condiciones específicas. Finalmente, el RAGFM también ha sido validado mediante resultados experimentales. Este trabajo contribuye a la integración de los recursos renovables mediante el control grid-forming, apoyando la transición hacia un futuro energético más sostenible.
Abstract The fibrids in aramid insulation paper exhibit good adhesion ability. However, the effects of fibrids morphology on the mechanical and electrical properties of aramid insulation paper remains poorly understood. Aramid fibrids with different morphological structures were prepared by modifying the preparation process, and then they were used to fabricate aramid composite insulation paper under the same condition. The results showed that increasing the shear rate and aramid solution concentration affected the magnitude of the shear force and double diffusion process, thus affecting the average length, specific surface area, and crystallinity of the fibrids. When the rotor frequency is 25–30 Hz and the solution concentration is 15%, the fibrid has a large specific surface area while ensuring high crystallinity, which is beneficial to the improvement of breakdown strength. When the average length of fibrids is 0.8–1.4 mm, the fine content is 1.3%–2.3%, specific surface area is 57.5–62 m2 g−1, and crystallinity is 18.5%–27%, the aramid composite insulation paper has the optimal mechanical and electrical properties. Combined with the micromorphology test results, the influence mechanism of fibrids properties on the mechanical properties, dielectric properties, and AC and DC breakdown strength of aramid composite insulation paper was obtained. The result is of great theoretical significance and practical value for the preparation and application of high‐performance aramid composite insulation paper.
Materials of engineering and construction. Mechanics of materials
Daniel Ilk, Viktoria Frick, Christopher Hänel
et al.
Humidification of polymer electrolyte membranes in fuel cells is essential for high proton conductivity and lifetime, therefore often membrane humidifier modules are used. We report about the degradation of polyimide humidifier membranes under the influence of airborne ozone traces: during operation we tracked the membranes humidifier performance in 5 modules for up to 1000 h with trace levels of ozone (100 ppb) and conducted characterization tests at 200 h intervals. Operating the humidifier with ozone resulted in a linear decrease in the membrane's ability to transfer moisture over time. Moreover, the glass transition temperature of the membrane material decreases linearly with longer exposure to ozone, while the mechanical strength in terms of breaking force and elongation at break decreases too. Infrared spectra of the tested fibers showed no changes. The reduced water vapor flux would limit fuel cell performance, while the reduced mechanical properties of the membrane can lead to rupture.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Samy Aittahar, Adrien Bolland, Guillaume Derval
et al.
We propose in this paper an optimal control framework for renewable energy communities (RECs) equipped with controllable assets. Such RECs allow its members to exchange production surplus through an internal market. The objective is to control their assets in order to minimise the sum of individual electricity bills. These bills account for the electricity exchanged through the REC and with the retailers. Typically, for large companies, another important part of the bills are the costs related to the power peaks; in our framework, they are determined from the energy exchanges with the retailers. We compare rule-based control strategies with the two following control algorithms. The first one is derived from model predictive control techniques, and the second one is built with reinforcement learning techniques. We also compare variants of these algorithms that neglect the peak power costs. Results confirm that using policies accounting for the power peaks lead to a significantly lower sum of electricity bills and thus better control strategies at the cost of higher computation time. Furthermore, policies trained with reinforcement learning approaches appear promising for real-time control of the communities, where model predictive control policies may be computationally expensive in practice. These findings encourage pursuing the efforts toward development of scalable control algorithms, operating from a centralised standpoint, for renewable energy communities equipped with controllable assets.
Shigeo S. Kimura, Kengo Tomida, Masato I. N. Kobayashi
et al.
The origin of PeV cosmic rays is a long-standing mystery, and ultrahigh-energy gamma-ray observations would play a crucial role in identifying it. Recently, LHAASO reported the discovery of ``dark'' gamma-ray sources that were detected above 100 TeV without any GeV--TeV gamma-ray counterparts. The origins of these dark gamma-ray sources are unknown. We propose isolated black holes (IBHs) wandering in molecular clouds as the origins of PeV cosmic rays and LHAASO dark sources. An IBH accretes surrounding dense gas, which forms a magnetically arrested disk (MAD) around the IBH. Magnetic reconnection in the MAD can accelerate cosmic-ray protons up to PeV energies. Cosmic-ray protons of GeV-TeV energies fall to the IBH, whereas cosmic-ray protons at sub-PeV energies can escape from the MAD, providing PeV CRs into the interstellar medium. The sub-PeV cosmic-ray protons interact with the surrounding molecular clouds, producing TeV-PeV gamma rays without emitting GeV-TeV gamma rays. This scenario can explain the dark sources detected by LHAASO. Taking into account the IBH and molecular cloud distributions in our Galaxy, we demonstrate that IBHs can provide a significant contribution to the PeV cosmic rays observed on Earth. Future gamma-ray detectors in the southern sky and neutrino detectors would provide a concrete test to our scenario.
The possibilities of using energy-resource solid household waste, agricultural waste, logging waste from forestry enter-prises, green waste from landscaping and growing energy crops as alternative renewable fuels to meet the goals of small-scale heat and power generation in Poltava Oblast are investigated. To study this issue, the specialists from the Departments of Applied Ecology and Nature Management and Heat and Gas Supply, Ventilation and Heat Power En-gineering of National University "Yuri Kondratyuk Poltava Polytechnic" were invited to join the project and a new specialization "Renewable Heat and Power Engineering, Alternative Fuels and Environmental Protection" was opened in the specialty 183 "Environmental Protection Technologies". The problem was included in the strategic development plan of Poltava region and included in the development of the Action Plan for Sustainable Energy Development and Climate of Poltava City Territorial Community until 2030 in accordance with the European initiative "Covenant of Mayors for Climate and Energy". The assessment of the bioenergy potential may become a significant environmental and economic basis for improving the regional bioenergy sector in Poltava Oblast in the future. A complex of methods of system analysis and the method of data analysis has been applied to achieve the goal of the research. An analysis of modern international literary sources, an analysis of the morphological composition of municipal and green waste, and an analysis of the energy potential of plant biomass were reviewed. As a result of research, the scientific and applied task of using local energy resources at the level of each individual community of the Poltava region, taking into account ecological, economic and social development, has been formulated and substantiated. Ref. 10, figure.
Solar energy is considered a sustainable solution that has proven its technological competence for electricity generation among renewable energy sources. While green resources provide high energy security, they also reduce environmental pollution and support the use of local resources. In this article, a dual axis solar tracker that can operate with high accuracy in harsh operating conditions is proposed using the Stewart platform. The Stewart platform is designed using linear actuators using direct current (DC) motors. An embedded controller is designed to control the motors and to realize the sun tracking algorithm of the system. An STM32 board is adopted as a real-time controller to implement the decoupled control algorithm. Therefore, the proposed solar tracker panel control system monitors the daily trajectory of the sun by the photovoltaic panel, ensuring that the system’s energy production remains at its maximum throughout the day. First, the Simulink model of the system was created and the proportional derivative integral (PID) control algorithms were simulated. Experimental studies were carried out by producing the system; the experimental results exhibited a better performance, with an increase in the collected energy of about 32% compared with the fixed one.
Annalisa Liccardo, Davide Lauria, Francesco Bonavolonta
et al.
The paper deals with the separation of power system into coherent areas; this is a relevant issue for managing the network in both normal operating conditions and during anomalous events. In particular, the attention is focused on partitioning the power system in such a way as to group together frequency signals, measured by means of phasor measurement units (PMU), exhibiting similar oscillatory behavior after the occurrence of a fault or disturbance. Unfortunately, the increasingly massive presence of renewable energy sources is undermining the clustering methods defined so far, requiring new solutions to the problem. To overcome the considered drawbacks, the authors propose hereinafter to (<inline-formula> <tex-math notation="LaTeX">${i}$ </tex-math></inline-formula>) improve the grouping capabilities of an iterative spectral clustering method thanks to the definition of new parameters for similarity estimation (Modified Bray Curtis index) and cluster thresholding (weighted Fiedler value) as well as (ii) enhance its robustness with respect to both measurement noise and uncertainty affecting the PMUs by means of a deep test procedure. To this aim, particular attention is paid in the design and assessment stage to the definition of both filtering algorithm and measurement parameters (e.g., the length of the analysis window). Once defined these parameters, the method is capable of 100% correctly separating transmission network sections oscillating with similar trends in a number of tests conducted on simulated and actual signals, so highlighting the promising performance of the method highlighting its reliability and efficacy in different test conditions.
<p>As a consequence of the rapid growth of the globally installed offshore wind energy capacity, the size of individual wind farms is increasing. This poses a challenge to models that predict energy production. For instance, the current generation of wake models has mostly been calibrated on existing wind farms of much smaller size. This work analyzes annual energy production and wake losses for future, multi-gigawatt wind farms with atmospheric large-eddy simulation. To that end, 1 year of actual weather has been simulated for a suite of hypothetical 4 GW offshore wind farm scenarios. The scenarios differ in terms of applied turbine type, installed capacity density, and layout. The results suggest that production numbers increase significantly when the rated power of the individual turbines is larger while keeping the total installed capacity the same. Even for turbine types with similar rated power but slightly different power curves, significant differences in production were found. Although wind speed was identified as the most dominant factor determining the aerodynamic losses, a clear impact of atmospheric stability and boundary layer height has been identified. By analyzing losses of the first-row turbines, the yearly average global-blockage effect is estimated to between 2 and 3 %, but it can reach levels over 10 % for stably stratified conditions and wind speeds around 8 m s<span class="inline-formula"><sup>−1</sup></span>. Using a high-fidelity modeling technique, the present work provides insights into the performance of future, multi-gigawatt wind farms for a full year of realistic weather conditions.</p>
Olexandr Shavolkin, Iryna Shvedchykova, Michal Kolcun
et al.
Improvement of the principles of the implementation of a hybrid solar-wind system equipped with a battery for self-consumption of a local object, with the control of power consumed from the grid, is considered. The aim is to increase the degree of energy use from renewable energy sources for consumption while limiting the degree of battery discharge, taking into account deviations in the load schedule and generation of energy sources relative to the calculated (forecast) values. The possibility of compensating for deviations in the load schedule and renewable energy sources generation relative to the calculated (forecast) values is shown when electricity consumption decreases and the degree of energy use increases. Compliance of the schedule of the battery state of charge with the calculated schedule is achieved by correcting the consumption of active power according to the deviation of the state of charge with a given discreteness of time. The algorithm of the control was improved by taking into account the measured value of the load power with an increase in the degree of energy use. Also, the use of correction allows you to limit the depth of discharge of the battery at the accepted value. A mathematical 24 h model of energy processes was developed, taking into account the error in estimating the state of charge. The results of the modeling using archival data on renewable sources generation confirm that the proposed solutions are effective. For the considered application with average monthly generation in February, the correction allows reducing electricity consumption by 16–21% and payment costs at three tariffs by 24–27%.
Jannik Neumann, Rodolfo Cavaliere Da Rocha, Paulo Debiagi
et al.
Effective usage of renewable energy requires ways of storage and delivery to balance energy demand and availability divergences. Carbon-free chemical energy carriers are proposed solutions, converting clean electricity into stable media for storage and long-distance energy trade. Hydrogen (H$_2$) is the subject of significant investment and research. Metal fuels, such as iron (Fe), are promising solutions for a clean energy supply, but establishing an interconnected ecosystem still requires considerable research and development. A model is proposed to assess the supply chain of hydrogen and iron as clean, carbon-free energy carriers and then examines case studies of possible trade routes between the potential energy exporters Morocco, Saudi Arabia, and Australia and importers Germany and Japan. The work comprehends the assessment of economic (levelized cost of electricity - LCOE), energetic (thermodynamic efficiency) and environmental (CO$_2$ emissions) aspects, quantified by the comprehensive model accounting for the most critical processes in the supply chain. Sensitivity and uncertainty analyses identify the main drivers for energy costs. Iron is shown to be lower-cost and more efficient to transport in longer routes and for long-term storage, but potentially more expensive and less efficient than H$_2$ to produce and convert. Uncertainties related to the supply chain specifications and the sensitivity to the used variables indicate that the path to viable energy carriers fundamentally depends on efficient synthesis, conversion, storage, and transport. A break-even analysis demonstrated that clean energy carriers could be competitive with conventional energy carriers at low renewable energy prices, while carbon taxes might be needed to level the playing field. Thereby, green iron is an important potential energy carrier for long-distance trade in a globalized clean energy market.
Abstract Quinone‐based aqueous redox flow batteries (RFBs) have drawn much attention due to their high safety, two‐electron involvement, rapid reaction kinetics, property tunability, and potentially low cost. RFBs operating in neutral solution feature a wide electrochemical window of around 2.5 V, which provides much more space for the design of redox‐active materials (RAMs) to realize a high voltage. However, it is still challenging to achieve low potential in the neutral condition for quinone‐based RAMs, owing to inherently pH‐dependent behaviors and deep LUMO (the lowest unoccupied molecular orbital) energy level. Herein, we report three low‐potential quinone‐based RAMs (1,4‐BDPAQCl2, 1,5‐BDPAQCl2, and 1,8‐BDPAQCl2) by bis‐dimethylamino substitution. The half‐wave potential of the quinones in 0.5 M KCl is approximately −0.55 to −0.57 V versus a normal hydrogen electrode. The low potential is ascribed to the introduced functional groups with two effects. First, the intramolecular hydrogen bonds formed between C=O and H−N can weaken the association between protons and dianion Q2−, resulting in a favorable distribution of products. Second, the functional groups can effectively increase the LUMO over 0.22 eV, compared with anthraquinone. Paired with Fe(glycine)2Cl2, the theoretical open‐circuit voltage of full RFBs is achieved at 1.27–1.29 V. We test full batteries using these quinones as negative RAMs at a lower concentration (0.1 M). The results show that 1,8‐BDPAQCl2 displays stability during 300 charge‐discharge cycles. In contrast, the other two quinones exhibit poor cycling stability due to side reactions. We further execute a higher concentration (0.4 M) for 1,8‐BDPAQCl2. The cycling stability of the quinone−iron RFBs is outstanding, with 0.048 % capacity decay per cycle and 0.88 % capacity decay per day. Our finding offers a feasible strategy to design low‐potential quinone molecules for the neutral RFBs.