Intermittent Renewable Energy Research Articles

Iridium-Based Electrocatalysts for Oxygen Evolution Reaction in Proton Exchange Membrane Water Electrolyzers

Proton exchange membrane water electrolyzers (PEMWEs) show the fast response to a wide electrical load range, making them compatible to couple with intermittent renewable energy systems such as wind and solar power. However, the low efficiency, instability, and high cost of anodic electrocatalysts for the oxygen evolution reaction (OER) severely hinder the widespread deployment of PEMWEs. Hitherto, iridium-based catalysts still play an irreplaceable role for their trade-off catalytic activity and stability. To meet the scarcity of iridium, reducing the iridium loading and designing low iridium-based electrocatalysts have become the mainstream. Particularly, perovskite-type oxides possess flexible compositions, enabling them ideal material platform for the optimization of catalytic performance. In this work, several materials of iridium-based perovskite-type oxides were acquired by coupling iridium with various transition elements in B-site and regulating A-site cations, which both diluted the usage of iridium and utilized the multi-metallic synergistic effect to achieve high activity and stability. Evolution of the surface structure was monitored by in-situ Raman spectroscopy to identify the active site and to uncover the catalytic mechanism. Besides, density functional theory (DFT) calculation was used as an auxiliary tool to analyze the local structure and electrochemical behavior of the electrode surface for its cost-effectiveness. Furthermore, membrane electrode assembly (MEA) based on the optimum composition was assembled to evaluate the performance of novel electrocatalysts for PEMWEs. Results of this work provide a new perspective of designing low iridium content electrocatalysts for OER in PEMWEs. Acknowledgement This work is funded by the National Natural Science Foundation of China (No. 22002089, 52072239).

(Battery Student Slam 8 Award Winner) Evaluating Electrodeposited Tin and Antimony-Based Anodes for Sodium-Ion Batteries

The widescale adaption of intermittent renewable energy sources, such as wind and solar, must be accompanied by a grid storage network to store energy when it is abundant and redistribute it as needed for on-demand use. Short-term storage in the form of rechargeable batteries is an attractive avenue for meeting these storage needs. The dominant technology in today’s market, the lithium-ion battery (LIB), is cost-prohibitive due to the need for rare-earth materials. Using the same working principle as LIBs, sodium-ion batteries (NIBs) utilize earth-abundant, low-cost sodium compounds instead of lithium compounds. Tin (Sn) and antimony (Sb) alone are promising anode materials for sodium-ion batteries with high theoretical capacities (847 and 660 mAh/g for Sn and Sb with Na, respectively) relative to current LIB anode chemistry (372 mAh/g) [1,2]. When combined, SnSb has shown to have increased stability relative to Sn or Sb alone [3]. Here, we synthesized Sn-Sb thin films with varied Sn and Sb atomic ratios by co-electrodeposition from a deep eutectic solvent by modifying solution stoichiometry and electrodeposition parameters. Using a combination of X-ray photoelectron spectroscopy (XPS), X-ray diffraction, and energy dispersive X-ray spectroscopy (EDS), phases and compositions of Sn-Sb synthesized by electrodeposition were identified. Once synthesized, we sought to determine the influence of morphology, surface chemistry, and composition on the capacity retention and rate capabilities of Sn and Sb-based anodes in NIBs. An optimized electrode composition was identified using a carbonate-based electrolyte, which resulted in stable capacity retention cycling at a rate of C/2 for 270 cycles.[1] W. T. Jing, C. C. Yang, and Q. Jiang, Journal of Materials Chemistry A, 8, 2913–2933 (2020).[2] S. Megahed and B. Scrosati, Journal of Power Sources, 51, 79–104 (1994).[3] W. P. Kalisvaart, H. Xie, B. C. Olsen, E. J. Luber, and J. M. Buriak, ACS Applied Energy Materials, 2, 5133–5139 (2019).

Influence of Different Operating Conditions on Iridium Dissolution in a Proton Exchange Membrane Water Electrolyzer

Polymer electrolyte membrane (PEM) water electrolysis plays a key role in the global decarbonization scheme by coupling the intermittent renewable energy sources to the production of high-purity hydrogen. Its deployment onto a GW scale, however, is hindered by the cost and availability of the precious metal catalysts utilized in today’s commercial systems, primarily by that of Ir used as the anode catalyst for the oxygen evolution reaction (OER). With the continuous increase in the demand for carbon-free hydrogen, drastic reductions from the current Ir loading of 1 – 2 mgIr cm-2 by at least an order of magnitude, without compromising the overall electrolyzer performance, are of crucial importance.1 In the recent years, significant efforts have been focused on understanding PEM electrolyzer degradation mechanisms and developing the necessary mitigation strategies, with a special focus being placed on the anode catalyst layer (CL).2-4 Recent results from our group showed that there are two main pathways for Ir to be removed from the anode CL: dissolution into the anode water line and transport through the membrane and the cathode CL.5 In the present work, we aim to shed light onto the effects influencing Ir dissolution under intermittent operation by quantitative analysis of the main Ir sinks within an electrolyzer and the determination of the charge of the dissolved Ir species.5, 6 Various accelerated stress tests with square-wave configuration aimed at accelerating Ir-based anode CL degradation were performed and the results were compared to those obtained during steady-state operation of the electrolyzer cell, which was used as a reference point. The influence of electro-diffusion, electroosmotic drag and Ir redeposition back to the ACL onto Ir dissolution were analyzed in detail to obtain deeper understanding on the Ir degradation processes. M. Clapp, C. M. Zalitis, M. Ryan, Perspectives on current and future iridium demand and iridium oxide catalysts for PEM water electrolysis. Catal Today 420, (2023). S. M. Alia et al., Electrolyzer Performance Loss from Accelerated Stress Tests and Corresponding Changes to Catalyst Layers and Interfaces. J Electrochem Soc 169, (2022). Z. Q. Zeng et al., Degradation Mechanisms in Advanced MEAs for PEM Water Electrolyzers Fabricated by Reactive Spray Deposition Technology. J Electrochem Soc 169, (2022). A. Weiss et al., Impact of Intermittent Operation on Lifetime and Performance of a PEM Water Electrolyzer. J Electrochem Soc 166, F487-F497 (2019). M. Milosevic et al., In Search of Lost Iridium: Quantification of Anode Catalyst Layer Dissolution in Proton Exchange Membrane Water Electrolyzers. Acs Energy Lett 8, 2682-2688 (2023). A. P. Dam, B. Y. A. Abuthaher, G. Papakonstantinou, K. Sundmacher, Insights into the Path-Dependent Charge of Iridium Dissolution Products and Stability of Electrocatalytic Water Splitting. J Electrochem Soc 170, (2023).

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value.In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M ± 1.09M USD and 104.99M ± 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

Profile of Round-Trip Efficiency of Lithium-Ion Battery Energy Storage System

Lithium-ion battery energy storage systems (Li-BESSs) are expected to adjust variable renewable energies such as photovoltaic energy. In the viewpoint of the energy management cost, profiles of round-trip efficiency (RTE) are important characteristics of Li-BESSs. The profiles of RTE are related to the characteristics of both LIBs and inverters installed on Li-BESSs. The characteristics of Li-BESSs would be various because of reusing and degradation of lithium-ion batteries (LIBs). And inverters made by a lot of manufacturers would be so on. Accordingly, it could be said that the understanding of the profile of each Li-BESS’s RTE is complex and difficult. Therefore, we studied the time series analysis of operation data and tried to estimate the characteristics of both LIBs and inverters. The important ones of LIB are full-charge capacity (FCC), open-circuit voltage (OCV), and internal resistance (R). In addition, characteristics of OCV and R can be expressed as function profiles with state of charge (SOC) as elements. Similarly, the important one of inverter is the typical efficiency curve. In this study, we proposed the estimation method of the profiles of OCV and R and inverter efficiency curve. On the other hand, FCC was given as assuming that general diagnosis results would be provided. Then, a RTE profile of Li-BESS (including 9.94kWh LIB and 10kW inverter) was tried to establish from the results of it. The profiles of OCV and R were estimated by the method called MGFFD (Modified Gaussian Free-Form Deformation) that we have been established [1]. The novelty of this study could be described as: Development of the estimation method of an efficiency curve of inverter installed on BESS during operation (Fig.1). Quantitatively visualized profile of RTE of Li-BESS by combining results of MGFFD estimation applied for LIBs and inverter (Fig.2). The profile described on Fig.2 is the relationship between SOC, input-output power rate of inverter, and RTE of Li-BESS. To understand Li-BESS’s charge-discharge efficiency of from state at that time to the end of an operation plan, it would be necessary information. This proposed method could clarify various RTE of Li-BESSs, consequently, be useful for its efficient operation by information communication technology.Reference[1] M. Arima, L. Lin, and M. Fukui, "Kalman-Filter-Based Learning of Characteristic Profiles of Lithium-Ion Batteries", Sensors, vol. 22, no. 14, 5156. Figure 1

In 50 Shades of Orange: Germany’s Photovoltaic Power Generation Landscape

Spatiotemporally resolved data on photovoltaic (PV) power generation are very helpful to analyze the multiple impacts of this variable renewable energy on regional and local scales. In the absence of such disaggregated data for Germany, numerical simulations are needed to obtain the electricity production from PV systems for a time period and region under study. This manuscript presents how a physical simulation model, which uses open access weather and plant data as input vectors, can be created. The developed PV model is then applied to an ensemble of approximately 1.95 million PV systems, consisting of ground-mounted and rooftop installations, in order to compute their electricity production in Germany for the year 2020. The resulting spatially aggregated time series closely matches the measured PV feed-in pattern of Germany throughout the simulated year. Such disaggregated data can be applied to investigate the German PV power generation landscape at various spatiotemporal levels, as each PV system is taken into account with its technical data and the weather conditions at its geo-location. Furthermore, the German PV power generation landscape is presented as detailed maps based on these simulation results, which can also be useful for many other scientific fields such as energy system modeling.

The political economy of electricity market coupling: Comparing experiences from Europe and the United States

Advancing the integration of neighbouring power markets is widely identified in the literature as a key enabler of power system efficiency, flexibility, and variable renewable energy integration. Nonetheless, the existing economic literature offers only partial explanations of why greater market integration is difficult to achieve in the real world despite its evident advantages in terms of overall welfare, supply security, and competitiveness. It is argued that power market coupling is an inherently political process involving significant institutional contestation and adaptation, and hence requires a more nuanced political analysis to be fully understood. This paper adds to the existing literature by conducting a comparative political economy analysis of electricity market coupling processes in Britain, Italy, and California, spanning from 2013 to 2021. It seeks to unpack how differences in the political economy contexts of these jurisdictions influenced the electricity market coupling process with their respective neighbouring systems. The analysis draws on 86 key policy documents, and 53 in-depth interviews with senior power system stakeholders in the three jurisdictions. Results widely align with claims in the political economy literature that market coupling outcomes do not simply reflect the most efficient solution. While all three jurisdictions have shown a commitment to enhance regional integration of short-term wholesale energy markets, there is considerable variation in policy outcomes, particularly the extent to which different segments of the market have been coupled. These differences can largely be attributed to variations in the political economy contexts of the three jurisdictions, including multi-level governance structures, diplomatic relations with neighbouring countries, and interactions with national political priorities and contexts. The main implications for the governance of electricity market coupling are discussed in the conclusion.

Long-Duration Energy Storage—A Literature Review on the Link between Variable Renewable Energy Penetration and Market Creation

The relationship between a region’s dependency on variable renewable energy (VRE) and the viability of long-duration energy storage (LDES) technologies is recognised through various electricity grid modelling efforts in the contemporary literature. Numerous studies state a specific VRE penetration level in total electricity generation as an indicator of the emergence of an LDES market. However, there is considerable variability across studies when comparing VRE penetration levels in conjunction with LDES technology utilisation, and significant diversity exists in electricity grid modelling approaches. This review aims to highlight these inconsistencies by offering an overview of disparate findings and dissecting the influencing variables. Sixteen parameters are identified from reviewed studies, complemented by an additional five recognised through in-depth analysis. This comprehensive examination not only sheds light on critical aspects overlooked in previous reviews, requiring further investigation, but also provides novel insights into the complexity of this correlation, elevating the understanding of LDES market creation by unravelling the factors that influence the technology adoption across various contexts. Furthermore, it provides clarity in LDES research terminology by rectifying ambiguous language in the existing literature. Altogether, seven databases were explored to produce a trustworthy foundation for the study.

Increasing variable renewables in coal-based energy systems under high electrification in the transport and heating sectors: The case of Kosovo

The increasing penetration of variable renewables poses major challenges in energy systems with limited flexibility. However, there are many solutions to support variable renewable integration when utilizing potential synergies among the different energy sectors. This research examines the technical and environmental effects of electrifying the transport and heating sectors in a coal-based energy system with limited flexibility, aiming to support the integration of variable renewable energy. Scenario analysis is employed to evaluate the use of heat pumps with thermal storage (power-to-heat) for individual heating solutions, electric vehicles, and Vehicle-to-Grid in the transport sector. These measures are evaluated as the primary means for enhancing the energy system flexibility to accommodate a larger share of variable renewables. Additionally, a dynamic analysis was conducted on thermal power plant operational capacities and efficiencies under varying electrification rates and renewable energy shares. The analysis is developed in the EnergyPLAN model using Kosovo energy system as a case study. The results confirm that the electrification of the heating and transport sectors positively impacts the integration of variable renewable energy by reducing critical excess electricity production and CO2 emissions, while power-to-heat and Vehicle-to-Grid facilitate synergies among different energy sectors. However, scenarios with high shares of variable renewable energy present challenges for the nominal operation of thermal power plants, potentially leading to lower operational efficiencies and slightly higher CO2 emissions compared to scenarios where thermal power plant part-load efficiency remains unchanged.

Fabrication, Modeling, and Testing of a Prototype Thermal Energy Storage Containment

Abstract Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output year round; lithium-ion batteries are uneconomical at these durations. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (>1100 ∘C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A laboratory-scale silo prototype was built and validated the congruent transient finite element analysis (FEA) model. The performance of a commercial-scale silo was then characterized using the validated model. The commercial-scale model predicted a storage efficiency above 95% after 5 days of storage with a design storage temperature of 1200 ∘C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

Fundamental benchmarking of the discharge properties of negative electrodes in lead acid batteries

The unprecedented scale of energy storage deployment needed to allow high penetration of intermittent renewable energy sources into the electrical grid places significant economic cost and performance targets on battery technologies. Lead batteries, owing to their highly abundant and inexpensive raw materials, can be considered an important solution to grid storage as long as they achieve high material utilization, fast recharge rates, and long cycle life. To address the limitations in material utilization, we need to revisit the electrochemical processes during the discharge step and answer the following question: what are the fundamental limits of the discharge reaction? In this work we discuss how well-defined lead metal surfaces with nanometer scale roughness allow us to resolve the accessible discharge capacity for both faradaic and non-faradaic processes as a function of electrolyte concentration and in the presence of traditional additives. The direct connection between PbSO4 layer morphology and discharge rates gives us important insights on the mechanism of discharge as related to the dissolution and passivation events. This work sets the stage for reimagining the design of lead batteries with implications to grid storage applications.

Renewable-battery hybrid power plants in congested electricity markets: Implications for plant configuration

Examining coupled renewable-battery power plants (“hybrids”) in congested areas provides insights into a future of increased wind and solar penetration. Our study focuses on two types of congested regions, Variable Renewable Energy (VRE)-rich Areas and Load Centers, and explores likely plant configuration choices for developers and transmission network planners. This paper examines how hybrid value, comprising energy and capacity value, varies by plant configuration and congested region type considering factors such as storage duration, battery degradation, and ability to charge from the grid. We select plant locations from across the seven main U.S. independent system operators (ISOs). Hybrid value for each configuration is computed based on profit-maximizing plant operation given perfect foresight, according to observed wholesale power market real time prices from 2018 to 2021. In VRE-rich Areas, the median increase in energy value from extending storage duration from one to 4 h is 29.4 % for solar and 26.8 % for wind, assuming low battery degradation costs and storage sized to 100 % of the plant's nameplate generation capacity. Increasing storage duration beyond 4 h does not substantially increase its value from energy markets, even in VRE-rich Areas. We find that solar hybrids reach a 90 % capacity credit with 4 h of storage, while wind hybrids require 8 h of storage, based on the capacity factor of each hybrid during the top 100 net load hours.

Multifaceted impact of renewable energy on achieving global climate targets: Technological innovations, policy frameworks, and international collaborations

This review comprehensively examines the multifaceted impact of renewable energy on achieving global climate targets, focusing on technological innovations, policy frameworks, and international collaborations. The study aims to highlight the critical role of renewable energy in mitigating climate change and promoting sustainable development. Methodologically, the paper synthesizes findings from the latest research and case studies to inform policymakers, industry stakeholders, and researchers. The main findings indicate significant advancements in renewable energy technologies, such as improvements in solar photovoltaics and wind turbines, which have enhanced efficiency and affordability. Energy storage solutions and smart grid technologies are crucial for integrating variable renewable energy sources into existing energy grids. Effective policy frameworks, including feed-in tariffs, tax incentives, and renewable portfolio standards, have been instrumental in driving renewable energy adoption. The role of international collaborations, facilitated by organizations like IRENA and agreements such as the Paris Agreement, is vital in promoting global renewable energy deployment. Conclusions drawn from the study emphasize that achieving global climate targets requires a multifaceted approach encompassing technological innovation, supportive policy frameworks, and robust international collaboration. Future research should focus on advancing renewable energy technologies, optimizing policy frameworks, enhancing international cooperation, and addressing socio-economic and environmental challenges. Recommendations include increased investment in renewable energy R&D, implementation of comprehensive policy measures that promote social equity, and strengthening international mechanisms for technology transfer and financial support. By addressing these areas, the global community can accelerate the transition to a sustainable and resilient energy system, ensuring a prosperous and climate-resilient future for all. Keywords: Renewable Energy, Climate Targets, Technological Innovations, Policy Frameworks, International Collaborations, Sustainable Development.

Efficient multi-objective rolling strategy of photovoltaic/hydrogen system via short-term photovoltaic power forecasting

Green hydrogen serves as an effective energy carrier for achieving sustainable development goals. However, the high production cost and intermittent renewable energy output cause obstacles to hydrogen production. Various electrolyzer control methods have been proposed to promote electrolyzers' efficiency. Traditional electrolyzer control methods may lead to significant differences in electrolyzer wear among large-scale hydrogen production systems. Hence, this paper proposes a multi-objective rolling strategy based on photovoltaic power forecasting to mitigate electrolyzer switch fluctuations, enhance hydrogen production efficiency, and better manage the electrolyzers. Initially, the trend of photovoltaic output is calculated based on the predicted values of the photovoltaic output from the particle swarm algorithm (PSO)-backpropagation (BP) model, and during the power ramp-up phase, some electrolyzers are activated in advance to expedite the cold start process and enhance the hydrogen production. Simultaneously, the electrolyzers' power distribution and operational status are adjusted in conjunction with the real-time power situation. Finally, a multi-objective rolling strategy is proposed to balance the operational indicators of the electrolyzers. The results indicate that the proposed method yields 4,952,642 Nm3 hydrogens over six months, which has increased by 5.37% and 9.00% compared to the simple start-stop and rotation strategy, respectively. Moreover, switch action times are reduced by 27.68% and 43.22%, respectively. These results demonstrate the effectiveness of the proposed method in significantly enhancing hydrogen production and improving the economic feasibility of photovoltaic/hydrogen systems.

Concurrent PV production and consumption load forecasting using CT‐Transformer deep learning to estimate energy system flexibility

AbstractThe integration of renewable energy sources (RESs) into power systems has increased significantly due to technical, economic, and environmental factors, necessitating greater flexibility to manage variable consumption loads and renewable energy generation. Accurate forecasting of solar energy production and consumption load is critical for enhancing power system flexibility. This study introduces a novel deep learning model, a spatial‐temporal hybrid convolutional‐transformer (CT‐Transformer) network with unique features and extended memory capacity. Additionally, a flexibility index (FI) is introduced to evaluate power system flexibility (PSF) based on the forecasting results. The CT‐Transformer forecasts PSF for the next 24 and 168 hours, using the FI to evaluate PSF based on forecasting results. The input data includes meteorological, solar energy production, load demand, and pricing data from France, comprising hourly data from 2015 and 2016 (about 17,520 entries). Data preprocessing involves correcting incomplete and irrelevant segments. The CT‐Transformer's performance is compared to other deep learning techniques, showing superior results with the lowest prediction error (2.5%) and a maximum error of 10.1% (MAE). It also achieved a prediction error of 0.08% for system flexibility, compared to the highest error of 0.96%. This research highlights the CT‐Transformer's potential for accurate RES and load forecasting and PSF evaluation.

Advancements and Policy Implications of Green Hydrogen Production from Renewable Sources

With the increasingly severe climate change situation and the trend of green energy transformation, the development and utilization of hydrogen energy has attracted extensive attention from government, industry, and academia in the past few decades. Renewable energy electrolysis stands out as one of the most promising hydrogen production routes, enabling the storage of intermittent renewable energy power generation and supplying green fuel to various sectors. This article reviews the evolution and development of green hydrogen policies in the United States, the European Union, Japan, and China, and then summarizes the key technological progress of renewable energy electrolysis while introducing the progress of hydrogen production from wind and photovoltaic power generation. Furthermore, the environmental, social, and economic benefits of different hydrogen production routes are analyzed and compared. Finally, it provides a prospective analysis of the potential impact of renewable energy electrolysis on the global energy landscape and outlines key areas for future research and development.

Performance study of a compressed air energy storage system incorporating abandoned oil wells as air storage tank

With the rapid development of intermittent renewable energy, large-scale compressed air energy storage technology represented by Adiabatic Compressed Air Energy Storage (A-CAES) has attracted much attention. In order to simultaneously solve the problems of reuse of decommissioned oil wells and low efficiency of A-CAES system, a compressed air energy storage system incorporating abandoned oil wells as Air Storage Tank (AST) is proposed in this paper. The system performance of underground Oil Well CAES (OW-CAES), aboveground Steel Pipeline CAES (SP-CAES), and aboveground Storage Tank CAES (ST-CAES) is comparatively analyzed based on a thermodynamic model, focusing on the impact of heat transfer characteristic parameters of the AST wall on the system performance. The results show that recoverable heat and round-trip efficiency are significantly affected by the heat transfer characteristics of the AST wall. More recoverable heat and higher round-trip efficiency can be achieved by increasing the wall temperature and the surface area of the AST, respectively. The round-trip efficiency and energy storage density of the OW-CAES system are higher than those of the ST-CAES system, which are increased by 8.3 % and 18.45 % respectively. This study provides theoretical support for the feasibility of the OW-CAES system and has certain engineering guiding significance.

Probabilistic assessment of short‐term voltage stability under load and wind uncertainty

AbstractContemporary electricity networks are exposed to operational uncertainties, which may jeopardise the stability of the power grid. More specifically, the increasing penetration level of variable renewable energy generation and uncertainty in load demand are key catalysts for these emerging stability issues. A mathematical relationship is established to track the system voltage trajectory with respect to variations in uncertain inputs (associated with wind speed, system load, and wind power penetration levels). Additionally, it demonstrates the consequences of varying uncertain inputs on the short‐term voltage response across different potential operating conditions. The theoretical proposition has further been verified by the simulation studies with two test power networks in DIgSILENT PowerFactory software. The simulation results revealed that uncertain injection sources significantly impacted the system voltage at the receiving end. High uncertainty in wind speed and system loads increased voltage recovery variation, causing delays in voltage response during low wind speeds and high system loads. Additionally, increased wind power penetration levels expanded voltage recovery uncertainties, resulting in decreased system voltage and potentially leading to voltage violations and instability at 30% wind power levels. Moreover, the results showed that the system's response time increased, and in some cases, it collapsed due to increased system capacity (>80%) and dynamic load (>75%), as well as encountering a large disturbance under uncertain circumstances.

Energy management in gyms microgrid: Nonlinear control of stationary bikes and treadmills with parallel rectifiers and AC/DC conversion

This article presents the complete design of a nonlinear control system for multiple stationary bikes connected to a mechanical energy conversion system equipped with squirrel cage induction generators (SIGs) linked to AC/DC converters. The primary objective of this study is to investigate the feasibility of powering multiple treadmills using the DC bus via DC/AC converters. The novelty of our approach lies in the integration of a new strategy of control system to achieve multiple control objectives within a gym microgrid environment, and an energy management algorithm to ensure the energy flow between intermittent generation and the considered, somewhat random, demand. The system is composed of several subsystems: i) stationary bikes connected to the DC bus via inverters acting as intermittent power sources; ii) a Li-ion battery-based energy storage system interfaced through a Buck-Boost converter; iii) electromechanical loads, including treadmills, powered by DC/AC converters, in addition to other DC loads. The main control objectives are as follows: a) each stationary bike extracts energy from the DC network by regulating the torque applied by the athlete, ensuring that the torque follows the reference torque; b) the treadmill’s speed must follow the reference generated based on the athlete’s condition; c) ensuring the protection of the energy storage system by monitoring its current and voltage; d) all mentioned objectives are achieved while maintaining the DC bus voltage at a reference value. To achieve these objectives, a nonlinear control approach based on Lyapunov theory is used to design the controllers. A formal analysis is conducted to assess the performance of the studied system. The system’s performance is demonstrated using the MATLAB/Simulink environment. Numerous simulations demonstrate that every control objective is achieved. Specifically, the system maintained the DC bus voltage at 500 V with a maximum deviation of 1 V, and the treadmill speed followed the reference within a margin of 0.1 m/s.

The role of hydrogen as long-duration energy storage and as an international energy carrier for electricity sector decarbonization

With countries and economies around the globe increasingly relying on non-dispatchable variable renewable energy (VRE), the need for effective energy storage and international carriers of low-carbon energy has intensified. This study delves into hydrogen’s prospective, multifaceted contribution to decarbonizing the electricity sector, with emphasis on its utilization as a scalable technology for long-duration energy storage and as an international energy carrier. Using Japan as a case study, based on its ambitious national hydrogen strategy and plans to import liquefied hydrogen as a low-carbon fuel source, we employ advanced models encompassing capacity expansion and hourly dispatch. We explore diverse policy scenarios to unravel the timing, quantity, and operational intricacies of hydrogen deployment within a power system. Our findings highlight the essential role of hydrogen in providing a reliable power supply by balancing mismatches in VRE generation and load over several weeks and months and reducing the costs of achieving a zero-emission power system. The study recommends prioritizing domestically produced hydrogen, leveraging renewables for cost reduction, and strategically employing imported hydrogen as a risk hedge against potential spikes in battery storage and renewable energy costs. Furthermore, the strategic incorporation of hydrogen mitigates system costs and enhances energy self-sufficiency, informing policy design and investment strategies aligned with the dynamic global energy landscape.