Energy Conversion and Management-X最新文献

{"title":"Technologies and strategies fostering the sustainable development of energy, water and environment systems","authors":"Davide Astiaso Garcia ,&nbsp;Predrag Raskovic ,&nbsp;Neven Duić ,&nbsp;Moh’d Ahmad Al-Nimr","doi":"10.1016/j.ecmx.2024.100736","DOIUrl":"10.1016/j.ecmx.2024.100736","url":null,"abstract":"<div><div>Holistic strategies in energy, water, and environmental systems can enhance climate change mitigation efforts. Recent scientific innovations have opened up numerous pathways toward comprehensive human development. This editorial explores the 18th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES), highlighting eight key topics from eight research articles that showcase the latest scientific advancements. The articles that addressed energy saving, energy efficiency, and clean energy, include (1) Bioethanol burner operating parameters optimization: Effects of burner opening area modulation on heat output and flue gas composition, (2) Integration of photovoltaic panels and biomass-fuelled CHP in an Italian renewable energy community, (3) AI-Driven Innovations in Greenhouse Agriculture: Reanalysis of Sustainability and Energy Efficiency Impacts, and (4) Methodology to assess the impact of urban vegetation on the energy consumption of residential buildings. A case study in a Mediterranean city. One article discussed infrastructure planning: (5) Dynamic Reduction of Network Flow Optimization Problem: Case of Waste-to-Energy Infrastructure Planning in Czech Republic. One article reviewed the effects of national policies on renewable energy communities: (6) How do national policies influence energy community development across Europe? A review on societal, technical, and economical factors. Additionally, other two articles discussed the method for projections of wind power: (7) A copula post-processing method for wind power projections under climate change, and comparative analysis on open/closed loop with thermal load in an elastocaloric device: (8) 2D thermo-fluidynamic rotary model of an elastocaloric cooling device: The energy performances.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100736"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Decision-Making for Flexible Natural Gas Allocation Under Uncertainties: An Agent-Based Modelling Approach","authors":"Noor Yusuf,&nbsp;Ahmed AlNouss,&nbsp;Roberto Baldacci,&nbsp;Tareq Al-Ansari","doi":"10.1016/j.ecmx.2024.100734","DOIUrl":"10.1016/j.ecmx.2024.100734","url":null,"abstract":"<div><div>Despite the anticipated growth in the global demand for energy commodities, the frequently changing market dynamics imposed by environmental regulations and political sanctions create end-user demand uncertainties. This imposes the need for prompt quantitative decision-making approaches to understand how various market structures affect the planning of current natural gas projects. Agent-based modelling (ABM) emerges as a powerful approach to facilitate expedited and well-informed decisions amidst limited timeframes. This study deploys agent-based modelling to investigate natural gas allocation across various utilisation routes under diverse economic and environmental scenarios. Results from four main cases and two sub-scenarios imply that the allocation strategy is driven by utilisation routes considered in each case, followed by the allocation target (i.e., economic or environmental) and the operational bounds. The results reveal that cases prioritising natural gas monetisation for export outperform those meeting power requirements in average annual profitability. In case 4, considering a full network with power, the average annual profitability in the economic scenario reduces by approximately 47% compared to case 3, representing the optimal network configuration with $5.22 billion in average annual profitability. However, the economic scenario of case 3 demonstrates the second-highest rate of emissions (0.66 CO₂-eq t/y), following the hydrogen-rich process routes in case 2. Overall, this study presents an innovative data-driven framework for enhancing strategic resource allocation in dynamic business environments. By integrating empirical evidence and technical data with an advanced technical tool (i.e., ABM), the framework provides decision-makers and policymakers with valuable insights for managing uncertainties and shifts in market structures, particularly in existing natural gas projects.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100734"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142437803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soybean oil-based green diesel production via catalytic deoxygenation (CDO) technology using low-cost modified dolomite and commercial zeolite-based catalyst","authors":"R.S.R.M. Hafriz ,&nbsp;S.H. Habib ,&nbsp;N.A. Raof ,&nbsp;M.Y. Ong ,&nbsp;C.C. Seah ,&nbsp;S.Z. Razali ,&nbsp;R. Yunus ,&nbsp;N.M. Razali ,&nbsp;A. Salmiaton","doi":"10.1016/j.ecmx.2024.100749","DOIUrl":"10.1016/j.ecmx.2024.100749","url":null,"abstract":"<div><div>Green diesel derived from sustainable biomass is an alternative and potential energy source to petroleum fossil fuel replacement in response to reducing carbon footprint and achieving a circular economy, which has sparked public interest and concern in advancing renewable energy development. Catalytic deoxygenation (CDO) is a promising method because it can process a wide variety of feedstocks and produce a diverse range of fuels. The CDO of soybean oil (SO) was executed using a modified low-cost dolomite catalyst denoted as NiO-CD catalyst and its performance has been compared with commercial zeolite heterogeneous-based catalysts such as ZSM-5, HY-zeolite and FCC. The NiO-CD catalyst exhibited exceptional deoxygenation ability, attaining an 88.6 % removal efficiency of oxygenated compounds, markedly surpassing all commercially available zeolite catalysts. The highest degree of CDO of SO via decarboxylation/decarbonylation (deCOx) reaction was achieved due to improvement in particle size, mesoporous structure and the presence of the synergistic effect of modified bi-functional acid-base properties of NiO-CaO/MgO catalyst. To investigate the effect of NiO-CD catalyst loading ranging from 1 to 7 wt%, a One Factor At a Time (OFAT) optimisation study was performed. The current study found that an optimised NiO-CD catalyst loading of 5 wt% yielded the highest green diesel (50.5 wt%) with an 88.63 % hydrocarbon composition. The influence of catalyst loading on deoxygenation activity is significant in green diesel production using NiO-CD catalyst.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100749"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication and evaluation of a CMOS-based energy harvesting chip integrating photovoltaic and thermoelectric energy harvesters","authors":"Zhi-Xuan Dai ,&nbsp;Chun-Yu Chen","doi":"10.1016/j.ecmx.2024.100748","DOIUrl":"10.1016/j.ecmx.2024.100748","url":null,"abstract":"<div><div>This study explores the development of an energy harvesting chip (EHC) using a complementary metal oxide semiconductor (CMOS) process, addressing the need for efficient micro-scale energy harvesters in modern electronics. The EHC integrates a thermoelectric energy harvester (TEH) and a photovoltaic energy harvester (PEH) to maximize energy conversion efficiency. A key challenge in TEH design is enhancing power output, which is addressed by suspending the cold ends of 41 thermocouples within the TEH structure through post-processing. Experimental methods were employed to assess the performance of the TEH, revealing an output voltage of 21.4 mV and a maximum output power of 9.32 nW under a 3 K temperature difference. The TEH demonstrated a voltage factor of 8.9 mV/(mm²·K) and a power factor of 1.3 nW/(mm²·K²). The PEH was designed with novel patterned p-n junctions, integrating lightly doped n-type regions with interdigitated p-type doping to increase junction density, resulting in high conversion efficiency. The experimental results confirm the effectiveness of the EHC design, showcasing its potential in energy harvesting applications.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100748"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Achieving net zero energy penalty in post-combustion carbon capture through solar Energy: Parabolic trough and photovoltaic technologies","authors":"Farzin Hosseinifard ,&nbsp;Milad Hosseinpour ,&nbsp;Mohsen Salimi ,&nbsp;Majid Amidpour","doi":"10.1016/j.ecmx.2024.100757","DOIUrl":"10.1016/j.ecmx.2024.100757","url":null,"abstract":"<div><div>The adoption of carbon capture systems presents a pivotal strategy for mitigating greenhouse gas emissions, notably carbon dioxide. Nevertheless, the substantial surge in energy consumption associated with such systems remains a significant challenge. Addressing this challenge necessitates the integration of renewable energy sources. This study is dedicated to optimizing the conventional post-combustion carbon capture configuration, focusing on energy, exergy, and exergoeconomic considerations. The optimized configuration showcases a noteworthy 10 % reduction in overall energy penalties compared to its conventional counterpart, primarily attributed to diminished energy utilization in the reboiler. To achieve absolute sustainability and eliminate energy penalties in the optimized configuration, integration of a parabolic trough collector for steam provision to the reboiler and photovoltaic solar collectors for powering the plant’s equipment was undertaken. Furthermore, the incorporation of solar thermal storage tanks and batteries enables the storage of excess heat and electricity, ensuring operational continuity for up to 13 h in the absence of sunlight, such as during nighttime. The final optimized configuration manifests a commendable 14 % enhancement in exergoeconomic performance relative to the conventional configuration, thereby realizing zero energy penalties. This achievement renders the optimized configuration a compelling and viable choice for carbon capture units.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100757"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One techno-economic analysis to rule them all: Instant prediction of hydrothermal liquefaction economic performance with a machine learned analytic equation","authors":"Muntasir Shahabuddin,&nbsp;Nikolaos Kazantzis,&nbsp;Andrew R Teixeira,&nbsp;Michael T. Timko","doi":"10.1016/j.ecmx.2024.100756","DOIUrl":"10.1016/j.ecmx.2024.100756","url":null,"abstract":"<div><div>Hydrothermal liquefaction (HTL) has remarkable potential for efficient conversion of abundant, decentralized organic wastes into renewable fuels. Because waste is a highly distributed resource with context-dependent economic viability, selection of optimal deployment sites is slowed by the need to develop detailed techno-economic analyses (TEA) for the thousands of potential deployment locations, each with their own unique combinates of scale, proximity to infrastructure/markets, and feedstock properties. An economic modeling framework that requires only easily obtainable inputs for assessing economic performance would therefore allow multiplexed analysis of many thousands of cases, whereas traditional TEA would not be possible for more than a handful of cases. Within such a context, the present study uses machine learning to guide development of a TEA and modeling framework which provides accurate cost predictions using three key inputs – feedstock cost, biocrude yield, and process scale – to estimate the minimum fuel selling price (MFSP) that an HTL process can achieve. The structure of the proposed framework is informed and based on empirical observations of cost projections made by a detailed TEA over a wide range of feedstock costs, biocrude yields, and process scales. A machine learning guided process was used to identify, train, and test a series of models using auto-generated data for training and independently reported data for testing. The most accurate model consists of three terms and requires 6 adjustable parameters to predict independently published values of MFSP (<em>N</em> = 28) to within an average value of ± 20.4%. It is demonstrated that the reduced-order model’s predictions fall within 40% of the corresponding published values 95% of the time, and in the worst case, the associated discrepancy is 45.9%, suggesting that the accuracy of the machine learned model is indeed comparable to the TEAs that were used to build it. Moreover, the terms in the model are physically interpretable, conferring greater reliability to the use of its predictions. The model can be used to predict the dependence of MSFP on biocrude yield, scale, and feedstock cost; interestingly, MFSP is insensitive to biocrude yield and/or scale under many situations of interest and identifying the critical value for a given application is crucial to optimizing economic performance. The proposed model can be also extended to evaluate economic performance of newly developed HTL-based processes, including catalytic HTL, and the methodological framework used in this study is deemed appropriate for the development of machine learned TEA models in cases of other similar waste-to-energy technologies.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100756"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy and exergy analysis of a multipass macro-encapsulated phase change material/expanded graphite composite thermal energy storage for domestic hot water applications","authors":"Ajay Muraleedharan Nair ,&nbsp;Christopher Wilson ,&nbsp;Babak Kamkari ,&nbsp;Simon Hodge ,&nbsp;Ming Jun Huang ,&nbsp;Philip Griffiths ,&nbsp;Neil J Hewitt","doi":"10.1016/j.ecmx.2024.100788","DOIUrl":"10.1016/j.ecmx.2024.100788","url":null,"abstract":"<div><div>This study presents the development and performance evaluation of an innovative thermal energy storage (TES) system utilizing a commercially available bioderived organic phase change material (PCM) for domestic hot water production. The primary objective of this research is to enhance the efficiency and effectiveness of thermal energy storage solutions by macro-encapsulating the PCM-expanded graphite (EG) compressed modules in a multi-pass tube arrangement. A comprehensive experimental setup was employed to investigate the thermal performance of the proposed TES unit, focusing on charging and discharging cycles. Key findings reveal that conduction is the dominant mode of heat transfer, with the system achieving a significant maximum average charging power of 1440 W and a discharging power of 1990 W. The thermal energy storage capacity reached an impressive 12.6 MJ, enabling the discharge of 90 % of stored energy within 90 min. Furthermore, the exergy analysis indicated high exergy efficiencies, with charging efficiencies reaching 98 % and overall exergy efficiency at 18 %.</div><div>The implications of this research are significant, demonstrating the feasibility of using bioderived organic PCM for sustainable energy applications. It highlights the potential of the modular structure of the system to integrate with heat pump and solar energy systems, thereby enhancing efficiency and sustainability in domestic hot water applications. This work significantly contributes to the advancement of sustainable thermal energy storage technologies and establishes a solid foundation for future studies aimed at optimizing TES systems for domestic hot water production.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100788"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dispatch of decentralized energy systems using artificial neural networks: A comparative analysis with emphasis on training methods","authors":"Lukas Koenemann ,&nbsp;Astrid Bensmann ,&nbsp;Johannes Gerster ,&nbsp;Richard Hanke-Rauschenbach","doi":"10.1016/j.ecmx.2024.100730","DOIUrl":"10.1016/j.ecmx.2024.100730","url":null,"abstract":"<div><div>Due to the availability of flexibility, Decentralized Energy Systems (DES) play a central role in integrating renewable energies. To efficiently utilize renewable energy, dispatchable components must be operated to bridge the time gap between inflexible supply and energy demand. Due to the large number of energy converters, energy storage systems, and flexible consumers, there are many ways to achieve this. Conventional rule-based dispatch strategies often reach their limits here, and optimized dispatch strategies (e.g., model predictive control or the optimal dispatch) are usually based on very good forecasts. Reinforcement learning, particularly the application of Artificial Neural Networks (ANN), offers the possibility to learn complex decision-making processes. Since long training times are required for this, an efficient training framework is needed. The present paper proposes different training methods to learn an ANN-based dispatch strategy. In Method I, the ANN attempts to learn the solution to the corresponding optimal dispatch problem. In method II, the energy system model is simulated during the training to compute the observation state and operating costs resulting from the ANN-based dispatch. Method III uses the fast executable Method I solution as a warm-up solution for the computationally expensive training with Method II. In the present paper, a model-based analysis compares the different ANN-based dispatch strategies with rule-based dispatch strategies, model predictive dispatch (MPC), and optimal dispatch regarding their computational efficiency and the resulting operating costs. The dispatch strategies are compared based on three case studies with different system topologies for which training and test data are applied.</div><div>Training method I proved to be non-competitive. However, training methods II and III significantly outperformed rule-based dispatch strategies across all case studies for both training and test data sets. Notably, methods II and III also surpassed MPC-based dispatch strategies under high and medium uncertainty forecasts for the training data in the first two case studies. In contrast, MPC-based dispatch was superior in the third case study, likely due to the higher system’s complexity and in the test data set due to the methodological advantage of being optimized for each specific data set. The effectiveness of training method III depends on the performance of the warm-up training with method I: warm-up is beneficial only if this results in an already promising dispatch (as seen in case study two). Otherwise, training method II proves more effective, as observed in case studies one and three.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100730"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142437804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable reuse of oil and gas wells for geothermal energy production: Numerical analysis of deep closed loop solutions in Italy","authors":"Marina Facci ,&nbsp;Eloisa di Sipio ,&nbsp;Gianluca Gola ,&nbsp;Giordano Montegrossi ,&nbsp;Antonio Galgaro","doi":"10.1016/j.ecmx.2024.100743","DOIUrl":"10.1016/j.ecmx.2024.100743","url":null,"abstract":"<div><div>This study assesses the feasibility of repurposing abandoned oil and gas wells in Italy for geothermal energy production employing a geothermal closed-loop system. A systematic methodology was developed, beginning with raw data collection and progressing to numerical simulations using COMSOL Multiphysics to model a U-shaped deep closed-loop geothermal heat exchanger. The analysis relied on a public database of wells drilled in Italy since the mid-20th century. The Horner plot correction method was applied to measured temperature data to obtain accurate geothermal gradients across Italy, which were then used as input parameters for a numerical sensitivity analysis. The results highlight the critical role of the geothermal gradient and heat carrier fluid flow rate in determining system performance. Regions in Italy with geothermal gradients exceeding 40 °C/km, particularly in the Tyrrhenian area, were identified as having high potential for this technology. A preliminary analysis of a virtual Organic Rankine Cycle (ORC) system estimated power production of 73 kW, with an efficiency of 11.66 % after 25 years of operation under optimal conditions (5 l/s flow rate, 60 °C/km geothermal gradient, and 70 °C evaporation temperature).</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100743"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decarbonized district energy systems: Past review and future projections","authors":"Juliet G. Simpson,&nbsp;Nicholas Long,&nbsp;Guangdong Zhu","doi":"10.1016/j.ecmx.2024.100726","DOIUrl":"10.1016/j.ecmx.2024.100726","url":null,"abstract":"<div><div>A significant portion of building energy usage globally goes toward space heating and cooling, and whether using individual building systems or district systems, those loads are often met with carbon-based sources. As we shift to decarbonize the electrical grid, we must also consider how to best decarbonize our heating and cooling loads in a way that aligns well with a renewable electrical grid. District energy systems (DES) distribute thermal energy to buildings in a community using shared resources and infrastructure. Unlike other decarbonized solutions, DES has the potential to reduce strain on the electrical grid and integrate renewable thermal sources and waste heat. This review will focus on current technology for decarbonizing DES and will discuss important design considerations as well as a qualitative comparison to individual systems.</div><div>A DES consists primarily of energy sources and storage, a distribution network, heat conversion, and user loads (such as buildings). We classify heating and cooling sources as constant, variable, or dispatchable, and review carbon-free options. The design of a DES depends on multiple factors including the nature of the energy sources, the loads to meet, central or distributed plant design, and the potential need for redundancy and resilience. We review design decisions including what sources and loads to connect, what distribution network design to implement, and the modeling and control of DES, and consider how to best integrate with a fully renewable electrical grid. Currently, DES designs are unique for each installation and require tailoring for each site. Due to the large number of distributed components, controls are important for DES, both at a component and system level. Future trends to consider include rising cooling demand loads, winter electrical peak load, conversion of traditional DES to state-of-the-art decarbonized systems, and the changing costs and economics of DES.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100726"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}