• Energy Research
• Embargo close
• ES close
• US close
• Applied Energy close

The increasing proportion of renewable energy introduces both long-term and short-term uncertainty to power systems, which restricts the implementation of energy management systems (EMSs) with high dependency on accurate prediction techniques. A hierarchical online EMS (HEMS) is proposed in this paper to economically operate the Hybrid hydrogen–electricity Storage System (HSS) in a residential microgrid (RMG). The HEMS dispatches an electrolyzer-fuel cell-based hydrogen energy storage (ES) unit for seasonal energy shifting and an on-site battery stack for daily energy allocation against the uncertainty from the renewable energy source (RES) and demand side. The online decision-making of the proposed HEMS is realized through two parallel fuzzy logic (FL)-based controllers which are decoupled by different operating frequencies. An original local energy estimation model (LEEM) is specifically designed for the decision process of FL controllers to comprehensively evaluate the system status and quantify the electricity price expectation for the HEMS. The proposed HEMS is independent of RES prediction or load forecasting, and gives the optimal operation for HSS in separated resolutions: the hydrogen ES unit is dispatched hourly and the battery is operated every minute. The performance of the proposed method is verified by numerical experiments fed by real-world datasets. The superiority of the HEMS in expense-saving manner is validated through comparison with PSO-based day-ahead optimization methods, fuzzy logic EMS, and rule-based online EMS.

[EN] Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real-world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi-physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle¿s Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time-resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively. This research is part of the project TED2021-131463B-I00 (DI-VERGENT) funded by MCIN/AEI/10.13039/501100011033 and the European Union "NextGenerationEU"/PRTR. It has also been partially funded by the Spanish Ministry of Science, Innovation, and University through the University Faculty Training (FPU) program (FPU19/00550) . Toby Rockstroh and Ram Vijayagopal acknowledge support through the US DOE Vehicle Technologies Program. Argonne National Laboratory is operated by UChicago Argonne, LLC under Contract no. DE-AC02-06CH11357. The US Government retains for itself, and others acting on its behalf, a paid-up non-exclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly, by or on behalf of the Government. The authors would like to express their gratitude to Kevin Stutenberg from Argonne National Laboratory for the informative discussions surrounding the experimental test campaign.

Nowadays, the increase in electric power coverage worldwide is a priority scope of the study, where Microgrids (MG) emerge as feasible solutions to supply electricity. The use of MG to provide energy to isolated communities, especially its use as Isolated Multi-Microgrid (IMMG) systems, has become an object of study worldwide. Different control techniques have been developed to improve and optimize the energy management system (EMS) associated with an isolated MG and new alternatives for energy exchange between IMMGs. However, the geographical location of a possible implementation of an MG directly affects the optimal dimensioning, the operating cost, and the environmental impact, among others. In this context, this work proposes a novel design of an EMS based on a fuzzy logic controller focusing on power exchange between IMMG systems. The proposed EMS aims to minimize the consumption of fossil fuels, reduce the total energy wasted by the power generation units, and keep the state-of-charge of the energy storage system (ESS) at safe levels to extend its useful life. Moreover, an ESS state of health analysis is presented to determine its degradation over time when applying the proposed EMS. In addition, the proposed EMS considers the uncertainties in the disconnection of any MG, ensuring the independent operation of each one. Simulation results are performed for a case study of an isolated community in the Amazon region of Ecuador. For this purpose, a group of microgrids is considered in three different scenarios. In the first scenario, there is no power exchange between the microgrids. In the second scenario, the microgrids exchange power using a simple EMS based on a set of analytical rules, and in the third scenario, the microgrids exchange power using the proposed EMS. The results show an improvement in the overall performance of the third scenario compared to the first two, both in reducing the energy wasted by the PV system and in the cost of fossil fuel. Finally, the experimental validation, using Typhoon Hardware-in-the-loop HIL-402 devices in real-time operation, highlights the proposed EMS's effectiveness and feasibility for IMMG systems. Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles::11.1 - Per a 2030, assegurar l’accés de totes les persones a habitatges i a serveis bàsics adequats, segurs i assequibles, i millorar els barris marginal Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.1 - Per a 2030, garantir l’accés universal a serveis d’energia assequibles, confiables i moderns © 2024 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles Peer Reviewed

[EN] The battery electric vehicle is the leading technology for reducing greenhouse gas emissions using clean and renewable energy. However, concerns due to battery thermal runaway are becoming more severe as the battery energy density increases. Fast-calculation models capable of predicting the heat released during the thermal runaway phenomenon can help to develop safety mechanisms according to the battery chemistry. The current study assesses the battery thermal runaway variability for two different battery chemistries, nickel cobalt aluminium oxides and nickel manganese cobalt oxides, for 3 different states of charge (100%, 80% and 50%), two different battery sizes (18,650 and 21,700), and two different battery health (pristine and aged). The tests are performed in the accelerating rate calorimeter using the heat-wait-seek protocol and repeated 5 times (each battery condition) for statistical analysis of the main thermal runaway parameters. A model using the Arrhenius equation was developed, calibrated, and validated. The model was developed considering 5 steps during temperature evolution to the reliable prediction of thermal runaway characteristics, considering inputs as states of charge, capacity fade (solid electrolyte interface growth), energy density, battery end mass and initial voltage. The experimental tests show that temperature rise rate, when the exothermic is detected, and battery end mass play an important role in the self-heating duration and maximum temperature, respectively, which are key parameters to understanding scattering behaviour. Considering these effects during modelling, the model can forecast the primary features of a thermal runaway, including maximum temperature, onset temperature, and duration of the whole battery thermal runaway process, all within the average difference of no more than 3%. For this reason, the model proposed seems to be a suitable tool for battery safety mechanism design as it considers the state of charge, energy density and ageing effects. The authors acknowledge the Vicerrectorado de investigacion de la Universitat Politecnica de Valencia for supporting this research through Programa de Ayudas de Investigacion y desarrollo (PAID-01-22). This research is part of the projects TED2021-132220B-C21 and TED2021-130488 A-I00, funded by the MCIN/AEI/10.13039/501100011033 and the European Union "NextGenerationEU"/PRTR. This research is part of the project PID2021-124696OB-C21, funded by Ministerio de Ciencia e Innovacion, Agencia Estatal de Investigacion and FEDER (MCIN/AEI/1 0.13039/501100011033/FEDER, UE).

The recent international agreements signed by the majority of developed countries, such as those reached at the Climate Change Conferences in Paris’15 and Dubai’23, propose an increasingly rapid transition toward an energy ecosystem with a clear predominance of renewable energy in electrical power systems. The development of such ambitious energy programs should deal with the inherited stochasticity that renewable energy systems entail, which, when coupled with uncertainty about the capacity of the grid to maintain a power supply owing to increasing demands, decarbonization processes and the widespread closure of nuclear power plants, pose a serious threat to the normal functioning of energy systems. When combined with the escalation of armed conflicts that imply the loss of supply as a result of attacks or cyberattacks on power plants and distribution networks, it becomes clear that the current energy paradigm in which there is a centralized grid supplying numerous consumers, many of whom do not have their own generation capacity, must shift toward increasing the deployment of renewable-energy-based self-consumption facilities. The continuous advances toward a decentralized energy system of this nature will also lead to more cooperation, increasing the presence of energy communities with a great need to strengthen internal resilience as a sustaining factor. Considering the challenging framework of smart grids and energy transition, Microgrids would appear to be the key technology for the aggregation of generation, load and energy storage systems, and a cornerstone with which to provide the resilience and flexibility required for this new renewable-energy-based scenario. In addition to the complexity of the microgrid control problem, the issue of resilience energy management also has to be considered, which refers to the ability to adapt and supply loads during a specified period after a disruptive event with a loss of grid supply. This paper introduces an innovative method based on Model Predictive Control (MPC) techniques with the aim of enhancing resilience in microgrids by maximizing the energy surplus and reducing the aforementioned critical instants at which the capacity to feed loads is minimum in the case of power grid outages. The results obtained show that the proposed algorithm enhances the energy resilience in microgrids while the overall operational cost is optimized. A method with which to enhance the resilience of interconnected microgrids through cooperative optimization methods is also developed and validated. Embargado hasta 01/09/2026

[EN] The internal combustion engine's (ICE) electrification calls to question ICE concepts nowadays, leading to new engine architectures conceived to operate as series hybrids. This is the case of the unit analyzed in this work; a 2stroke, spark-ignited, rod-less opposed-piston engine (2S-ROPE). Previous results revealed some efficiency and maximum power drawbacks, which motivated the development of the supercharged or turbocharged engine version. Supercharging the engine results in a straightforward task; however, turbocharging the engine reveals serious stability problems due to the thermo-fluid-dynamic coupling between the intake and exhaust lines. This work presents a method to study and identify the exhaust line geometry since the impact of pressure pulse propagation on the scavenging process is one of the most critical points to be considered from the very first steps. Finally, despite the difficulties of turbocharging the presented 2S engine, the parametric study revealed a suitable geometrical configuration and the engine operative range. Compared to the supercharged engine version, the turbocharged one presents more difficulties but diminishes the mechanical compressor power consumption, implying an advantage in efficiency terms. This research has been supported by Grant PID2020-114289RB-I00 funded by MCIN/AEI/10.13039/501100011033. This research has been partially supported by Grant CIPROM/2021/061 funded by Generalitat Valenciana through project DEVOCO2C.