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Thermal energy storage (TES) plays a key role in concentrating solar power (CSP) plants by enhancing dispatchability and improving overall system efficiency. This study presents a comparative techno-economic analysis of three TES configurations integrated into CSP plants: (i) the conventional two-tank molten salt system, (ii) a phase change material (PCM)-based system with a cascade arrangement, and (iii) a concrete-based system. While technical performance simulations indicate similar annual energy production across all cases, significant differences emerge in economic viability. The PCM TES system demonstrates the lowest levelized cost of electricity (LCoE) at $14.35/kWh, leveraging its high energy density and reduced material requirements, despite lower efficiency (93 % compared to 99 % in molten salt). Conversely, the concrete TES system, while capable of extended discharge at partial loads, incurs higher parasitic losses and investment costs, resulting in a higher LCoE ($16.16/kWh). The cost analysis further highlights the cost-performance quotient (CPQ) as a valuable metric for assessing TES competitiveness, with PCM exhibiting the most favorable CPQ of $1.04/kWh. These findings underscore the necessity of integrating economic assessments into TES selection for CSP plants. Moreover, the study identifies opportunities for cost reduction in concrete TES through optimized modular designs and improved material formulations. This work provides valuable insights for policymakers, engineers, and industry stakeholders aiming to enhance the financial feasibility of next-generation CSP storage solutions. This study receives funding from the Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación (MCIN/AEI/10.13039/501100011033) through the PCI2020-120695-2 project and the European Union “NextGenerationEU”/PRTR“. CSP-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation Horizon 2020 (Cofund ERA-NET Action, N° 838311). This work was partially funded by the Ministerio de Ciencia e Innovación de España TED2021-132216A-I00 funded by MCIN/AEI/10.13039/501100011033 and the European Union by NextGenerationEU/PRTR. This work was partially funded by the Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación (AEI) (PID2021-123511OB-C31 – MCIN/AEI/10.13039/501100011033/FEDER, UE) and (RED2022-134219-T). This work is partially supported by ICREA under the ICREA Academia programme. The authors from University of Lleida would like to thank the Departament de Recerca i Universitats of the Catalan Government for the quality accreditation given to their research group (2021 SGR 01615). GREiA is certified agent TECNIO in the category of technology developers from the Government of Catalonia.

Thermal energy storage (TES) plays a key role in concentrating solar power (CSP) plants by enhancing dispatchability and improving overall system efficiency. This study presents a comparative techno-economic analysis of three TES configurations integrated into CSP plants: (i) the conventional two-tank molten salt system, (ii) a phase change material (PCM)-based system with a cascade arrangement, and (iii) a concrete-based system. While technical performance simulations indicate similar annual energy production across all cases, significant differences emerge in economic viability. The PCM TES system demonstrates the lowest levelized cost of electricity (LCoE) at $14.35/kWh, leveraging its high energy density and reduced material requirements, despite lower efficiency (93 % compared to 99 % in molten salt). Conversely, the concrete TES system, while capable of extended discharge at partial loads, incurs higher parasitic losses and investment costs, resulting in a higher LCoE ($16.16/kWh). The cost analysis further highlights the cost-performance quotient (CPQ) as a valuable metric for assessing TES competitiveness, with PCM exhibiting the most favorable CPQ of $1.04/kWh. These findings underscore the necessity of integrating economic assessments into TES selection for CSP plants. Moreover, the study identifies opportunities for cost reduction in concrete TES through optimized modular designs and improved material formulations. This work provides valuable insights for policymakers, engineers, and industry stakeholders aiming to enhance the financial feasibility of next-generation CSP storage solutions. This study receives funding from the Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación (MCIN/AEI/10.13039/501100011033) through the PCI2020-120695-2 project and the European Union “NextGenerationEU”/PRTR“. CSP-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation Horizon 2020 (Cofund ERA-NET Action, N° 838311). This work was partially funded by the Ministerio de Ciencia e Innovación de España TED2021-132216A-I00 funded by MCIN/AEI/10.13039/501100011033 and the European Union by NextGenerationEU/PRTR. This work was partially funded by the Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación (AEI) (PID2021-123511OB-C31 – MCIN/AEI/10.13039/501100011033/FEDER, UE) and (RED2022-134219-T). This work is partially supported by ICREA under the ICREA Academia programme. The authors from University of Lleida would like to thank the Departament de Recerca i Universitats of the Catalan Government for the quality accreditation given to their research group (2021 SGR 01615). GREiA is certified agent TECNIO in the category of technology developers from the Government of Catalonia.

Short-term load forecasting (STLF) plays an important role in real-time decision-making and management of the power system while is still a challenging task. Considering that sleep improves brain memories and cognitive processes, this paper explores a approach of integrating biological mechanisms to reduce information loss of networks, and hence proposes a sleep-induced network (SI-Net) by analogy for achieving high-performance STLF. Firstly, through mimicking the sleep process, a multi-level bionic flowchart of the SI-Net is designed to integrate the gated, attention, parallel, cooperative, and asynchronous mechanisms, which not only encode features from coarse to fine but also enhance the fitting capability at the feature layer. Secondly, through imitating the brain memory paths during sleep, the primary and secondary memory paths are designed to update and store information, respectively, and their independence and collaboration avoid information loss in the SI-Net. Thirdly, the loss function constructed by the Gaussian kernel makes nonlinear errors linearly separable in the high-dimensional space, being beneficial to train the SI-Net. The experiments with real-world load datasets are performed and the results show that the SI-Net outperforms 15 baselines and presents high accuracy and stability. Bionically-inspired ideas are promising to design high-performance forecasting networks for energy systems.

Short-term load forecasting (STLF) plays an important role in real-time decision-making and management of the power system while is still a challenging task. Considering that sleep improves brain memories and cognitive processes, this paper explores a approach of integrating biological mechanisms to reduce information loss of networks, and hence proposes a sleep-induced network (SI-Net) by analogy for achieving high-performance STLF. Firstly, through mimicking the sleep process, a multi-level bionic flowchart of the SI-Net is designed to integrate the gated, attention, parallel, cooperative, and asynchronous mechanisms, which not only encode features from coarse to fine but also enhance the fitting capability at the feature layer. Secondly, through imitating the brain memory paths during sleep, the primary and secondary memory paths are designed to update and store information, respectively, and their independence and collaboration avoid information loss in the SI-Net. Thirdly, the loss function constructed by the Gaussian kernel makes nonlinear errors linearly separable in the high-dimensional space, being beneficial to train the SI-Net. The experiments with real-world load datasets are performed and the results show that the SI-Net outperforms 15 baselines and presents high accuracy and stability. Bionically-inspired ideas are promising to design high-performance forecasting networks for energy systems.

Scenario analysis plays a central role in estimating how global changes affect the relationships linking ecosystem conditions and functioning to human needs. This is particularly true for agroecosystems, which are pivotal to ensure sustainable land planning, ecological management and food security strategies. Soils are key providers of multiple ecosystem services (ES) in agroecosystems but they are very sensitive to global drivers such as changes in climate, land use and cover. How agroecosystems should achieve sustainability, through optimizing soil capacity to supply ES while limiting the occurrence of threats, is a priority of EU policy agendas. Nevertheless, there is currently a lack of a comprehensive framework of scenario-based approaches to assess changes in soil ES (SES) and soil threats (ST). As a part of the project SERENA funded by the European Joint Program on Agricultural Soil Management, this study aims to: i) understand how drivers of global change are commonly studied in the scientific literature; ii) identify how some SES and ST are assessed in scenario-based approaches; iii) provide a preliminary discussion on how soil properties are represented in these approaches. Through a systematic review of 230 published articles related to seven SES and ten ST, this study highlights that not all SES and ST are considered with the same frequency and geographic distribution in scenario-based approaches. Despite a great methodological variability in the assessment and mapping of SES and ST, dominant methodological trends can be identified. SES are mapped more frequently than ST and, specific SES appear more disposed to spatially explicit assessments than others. Due to its novelty and complexity, research on this topic is limited to a small subset of ST or SES and projections of the combined impacts of climate, land use and management changes on multiple ST and SES should be a scientific priority to help policy makers.

Scenario analysis plays a central role in estimating how global changes affect the relationships linking ecosystem conditions and functioning to human needs. This is particularly true for agroecosystems, which are pivotal to ensure sustainable land planning, ecological management and food security strategies. Soils are key providers of multiple ecosystem services (ES) in agroecosystems but they are very sensitive to global drivers such as changes in climate, land use and cover. How agroecosystems should achieve sustainability, through optimizing soil capacity to supply ES while limiting the occurrence of threats, is a priority of EU policy agendas. Nevertheless, there is currently a lack of a comprehensive framework of scenario-based approaches to assess changes in soil ES (SES) and soil threats (ST). As a part of the project SERENA funded by the European Joint Program on Agricultural Soil Management, this study aims to: i) understand how drivers of global change are commonly studied in the scientific literature; ii) identify how some SES and ST are assessed in scenario-based approaches; iii) provide a preliminary discussion on how soil properties are represented in these approaches. Through a systematic review of 230 published articles related to seven SES and ten ST, this study highlights that not all SES and ST are considered with the same frequency and geographic distribution in scenario-based approaches. Despite a great methodological variability in the assessment and mapping of SES and ST, dominant methodological trends can be identified. SES are mapped more frequently than ST and, specific SES appear more disposed to spatially explicit assessments than others. Due to its novelty and complexity, research on this topic is limited to a small subset of ST or SES and projections of the combined impacts of climate, land use and management changes on multiple ST and SES should be a scientific priority to help policy makers.