Advances in Applied Energy最新文献

{"title":"Life cycle assessment of ammonia co-firing power plants: A comprehensive review and analysis from a whole industrial chain perspective","authors":"Hui Kong ,&nbsp;Yueqiao Sun ,&nbsp;Hongsheng Wang ,&nbsp;Jian Wang ,&nbsp;Liping Sun ,&nbsp;Jun Shen","doi":"10.1016/j.adapen.2024.100178","DOIUrl":"10.1016/j.adapen.2024.100178","url":null,"abstract":"<div><p>Ammonia, a reliable low-carbon alternative fuel with energy storage capabilities, has garnered increasing attention for its application of co-firing in coal-fired power plants as a strategy to mitigate direct carbon emissions. However, various types of ammonia production technologies result in diverse economic feasibility and emission intensities. Simultaneously, each stage, spanning from upstream processes such as raw material extraction to downstream applications, contributes to carbon emissions, which cannot be ignored. It is crucial to select the appropriate assessment method to determine the transformation pathways for co-firing systems. To this end, this review presents a comprehensive life cycle assessment of ammonia co-firing systems from a whole industrial chain perspective, encompassing the entire gamut of processes from fuel production and transportation to co-firing. Studies of the industrial chain perspective and of life cycle assessment methodology that are uniquely tailored for co-firing systems are presented. A nuanced exploration of distinct technologies across the spectrum of system processes ensues, including the advantages, limitations, and trends in advancement, based on carbon emissions and economic criteria. Considering the diverse fuel production, especially ammonia, typologies and intricate processes have undergone comprehensive review. The combustion characteristics, emissions, and economic factors associated with the co-firing process are systematically summarized, drawing upon aspects such as dynamics, experiments, simulations, and demonstration projects. This study illuminates the progression and technology selection of co-firing systems across multiple stages of the whole industry chain, thereby furnishing insights relevant to the low-carbon transformation of ammonia co-firing with coal in power plants.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100178"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000167/pdfft?md5=2eee1ae8953fb0299668fa2c01a83efe&pid=1-s2.0-S2666792424000167-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141138685","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":"Assessing the feasibility of CO2 removal strategies in achieving climate-neutral power systems: Insights from biomass, CO2 capture, and direct air capture in Europe","authors":"Rebeka Béres ,&nbsp;Martin Junginger ,&nbsp;Machteld van den Broek","doi":"10.1016/j.adapen.2024.100166","DOIUrl":"10.1016/j.adapen.2024.100166","url":null,"abstract":"<div><p>To achieve the European Union's goal of climate neutrality by 2050, negative emissions may be required to compensate for emissions exceeding allocated carbon budgets. Therefore, carbon removal technologies such as bioenergy with carbon capture (BECCS) and direct air capture (DAC) may need to play a pivotal role in the power system. To design carbon removal strategies, more insights are needed into the impact of sustainable biomass availability and the feasibility of carbon capture and storage (CCS), including the expensive and energy-intensive DAC on achieving net-zero and net-negative targets. Therefore, in this study the European power system in 2050 is modelled at an hourly resolution in the cost-minimization PLEXOS modelling platform. Three climate-neutral scenarios with targets of 0, -1, and -3.9 Mt CO₂/year (which agree with varying levels of climate justice) are assessed for different biomass levels, and CCS availability. Findings under baseline assumptions reveal that in a climate-neutral power system with biomass and CCS options, it is cost-effective to complement variable renewable energy with a mix of combined cycle natural gas turbines (CCNGT) for flexibility and BECCS as base load to compensate for the CO₂ emissions from natural gas and additional carbon removal in the net-negative scenarios. The role of these technologies becomes more prominent, with -3.9 GtCO₂/year target. Limited biomass availability necessitates additional 0.4–4 GtCO₂/year DAC, 10–50 GW CCNGT with CCS, and 10–50 GW nuclear. Excluding biomass doubles system costs and increases reliance on nuclear energy up to 300 TWh/year. The absence of CCS increases costs by 78%, emphasizing significant investments in bioenergy, nuclear power, hydrogen storage, and biogas. Sensitivity analysis and limitations of the study are fully discussed.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100166"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000040/pdfft?md5=72bf980ea63b5e718607059bb7fb346f&pid=1-s2.0-S2666792424000040-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966492","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":"Demand flexibility and cost-saving potentials via smart building energy management: Opportunities in residential space heating across the US","authors":"Shiyu Yang ,&nbsp;H. Oliver Gao ,&nbsp;Fengqi You","doi":"10.1016/j.adapen.2024.100171","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100171","url":null,"abstract":"<div><p>Leveraging demand-side flexibility resources (e.g., buildings) is a crucial and cost-effective strategy for addressing the operational and infrastructure-related challenges in power grids pursuing deep decarbonization with high renewable energy penetration. However, the demand flexibility opportunities and financial benefits for residential space heating, which are sizeable demand-side flexibility resources, through emerging building energy management solutions (i.e., smart control and phased change material (PCM) thermal storage) across the US are not fully understood. In this paper, we systematically assess the demand flexibility and cost-saving/revenue potentials in residential space heating through detailed building-level simulations for five consecutive years at a 5-min temporal resolution in 20 metro areas across the high-heating-demand regions of the US. The results show a high degree of synergy between PCM thermal storage and smart control, which enables substantial demand flexibility potential, reaching 98.5% of peak load shifting, and electricity cost-saving/revenue potential, reaching 338.3% of electricity cost reductions, for residential space heating in the US. By achieving such performance, adopting smart control and PCM thermal storage is financially viable in 50% of the tested metro areas. The results reveal that the demand flexibility and cost-saving/revenue potentials of residential space heating in the US are further enhanced by higher volatilities in electricity prices. Active PCM thermal storage has lower energy efficiency but much higher energy flexibility than passive PCM thermal storage. Based on the findings, recommendations for integrating PCM thermal storage and smart control systems within residential space heating are provided.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100171"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266679242400009X/pdfft?md5=105ccca94a62a76764cbdc21aaff3ff0&pid=1-s2.0-S266679242400009X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140069500","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 energy management of virtual power plants: A review","authors":"Guangchun Ruan ,&nbsp;Dawei Qiu ,&nbsp;S. Sivaranjani ,&nbsp;Ahmed S.A. Awad ,&nbsp;Goran Strbac","doi":"10.1016/j.adapen.2024.100170","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100170","url":null,"abstract":"<div><p>A virtual power plant (VPP) refers to an active aggregator of heterogeneous distributed energy resources (DERs), which creates a promising pathway to expand renewable energy and demand-side electrification for deep decarbonization. The VPP market is projected to have a significant growth potential, with the global investment surging from $6.47 billion in 2022 to $16.90 billion by 2030. Up to now, VPPs still face technical challenges in dealing with the inherent uncertainty of DERs, and data emerge as a promising and essential resource to handle this issue. This paper makes the first effort to review the development of VPP technologies from a data-centric perspective, and then analyze the major role of data within every decision phase of VPPs. We examine the VPP energy management through a data lifecycle lens, and extensively survey the progress in data creation, data communication, data-driven decision support, data sharing and privacy, as well as technical solutions stemming from reinforcement learning, peer-to-peer sharing, blockchain, and market participation. In addition, we offer a unique overview of open data and recent real-world projects around the world to showcase the latest VPP practices. We finally discuss the major challenges and future opportunities in detail, with a focus on topics such as public benchmarks, internet of things, 5G, explainable artificial intelligence, and federated learning. We highlight the need for technical advances in data management and support systems for the growing scale of future VPP systems, and suggest VPPs delivering more ancillary grid services in the future.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100170"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000088/pdfft?md5=f52f61ef82375f66628906042ebd8a79&pid=1-s2.0-S2666792424000088-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140067424","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":"Assessing the conditions for economic viability of dynamic electricity retail tariffs for households","authors":"Judith Stute ,&nbsp;Sabine Pelka ,&nbsp;Matthias Kühnbach ,&nbsp;Marian Klobasa","doi":"10.1016/j.adapen.2024.100174","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100174","url":null,"abstract":"<div><p>The success of the energy transition relies on effectively utilizing flexibility in the power system. Dynamic tariffs are a highly discussed and promising innovation for incentivizing the use of residential flexibility. However, their full potential can only be realized if households achieve significant benefits. This paper specifically addresses this topic. We examine the leverage of household flexibility and the financial benefits of using dynamic tariffs, considering household heterogeneity, the costs of home energy management systems and smart meters, the impact of higher electricity prices and price spreads and the differences between types of prosumers. To comprehensively address this topic, we use the EVaTar-building model, a simulation framework that includes embedded optimization designed to simulate household electricity consumption patterns under the influence of a home energy management system or in response to dynamic tariffs. The study's main finding is that households can achieve significant cost savings and increase flexibility utilization by using a home energy management system and dynamic electricity tariffs, provided that electricity prices and price spreads reach higher levels. When comparing price levels in a low and high electricity price scenario, with an increase of the average electricity price by 15.2 €ct/kWh (67 % higher than the average for the year 2019) and an increase of the price spread by 8.9 €ct/kWh (494 % higher), the percentage of households achieving cost savings increases from 3.9 % to 62.5 %. Households with both an electric vehicle and a heat pump observed the highest cost benefits. Sufficiently high price incentives or sufficiently low costs for home energy management systems and metering point operation are required to enable households to mitigate rising electricity costs and ensure residential flexibility for the energy system through electric vehicles and heat pumps.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100174"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266679242400012X/pdfft?md5=0189c869809c5ea6aa382102696e1ea8&pid=1-s2.0-S266679242400012X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140644365","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":"Probabilistic load forecasting for integrated energy systems using attentive quantile regression temporal convolutional network","authors":"Han Guo,&nbsp;Bin Huang,&nbsp;Jianhui Wang","doi":"10.1016/j.adapen.2024.100165","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100165","url":null,"abstract":"<div><p>The burgeoning proliferation of integrated energy systems has fostered an unprecedented degree of coupling among various energy streams, thereby elevating the necessity for unified multi-energy forecasting (MEF). Prior approaches predominantly relied on independent predictions for heterogeneous load demands, overlooking the synergy embedded within the dataset. The two principal challenges in MEF are extracting the intricate coupling correlations among diverse loads and accurately capturing the inherent uncertainties associated with each type of load. This study proposes an attentive quantile regression temporal convolutional network (QTCN) as a probabilistic framework for MEF, featuring an end-to-end predictor for the probabilistic intervals of electrical, thermal, and cooling loads. This study leverages an attention layer to extract correlations between diverse loads. Subsequently, a QTCN is implemented to retain the temporal characteristics of load data and gauge the uncertainties and temporal correlations of each load type. The multi-task learning framework is deployed to facilitate simultaneous regression of various quantiles, thereby expediting the training progression of the forecasting model. The proposed model is validated using realistic load data and meteorological data from the Arizona State University metabolic system and National Oceanic and Atmospheric Administration respectively, and the results indicate superior performance and greater economic benefits compared to the baselines in existing literature.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000039/pdfft?md5=b54e77f93d7199836be85cd37c0a9d2f&pid=1-s2.0-S2666792424000039-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139986098","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":"Current challenges in the utilization of hydrogen energy-a focused review on the issue of hydrogen-induced damage and embrittlement","authors":"Binhan Sun ,&nbsp;Huan Zhao ,&nbsp;Xizhen Dong ,&nbsp;Chaoyi Teng ,&nbsp;Aochen Zhang ,&nbsp;Shuai Kong ,&nbsp;Jingjing Zhou ,&nbsp;Xian-Cheng Zhang ,&nbsp;Shan-Tung Tu","doi":"10.1016/j.adapen.2024.100168","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100168","url":null,"abstract":"<div><p>The development of reliable and longevous infrastructures and structural components is the key for the implementation of a hydrogen economy that is currently enjoying unprecedented political and research momentum due to the globally strong demand for clean energy. This is, however, strongly impeded by the risk and concerns of hydrogen embrittlement (or hydrogen-induced degradation in mechanical properties) that generally exists in almost all metallic materials. Structural components and materials operated in the hydrogen production-transport-storage-usage chain can be subjected to a very wide range of temperature, environmental and loading scenarios, which will essentially trigger different hydrogen embrittlement responses and even different embrittling mechanisms. It is thus important to have a systematic assessment and discussion of hydrogen embrittlement behavior of different materials at different testing conditions, which is the focus of the presented review. Here we cover the typical materials (mainly metallic materials) that have been used or planned to be used in the fields of hydrogen energy. We first briefly summarize the current understanding of fundamental hydrogen embrittlement mechanisms in metallic materials and the research progress in recent years. Then we analyze and discuss the hydrogen -induced damage phenomenon in typical materials used in the field of high-pressure hydrogen transport and storage. In addition to room-temperature hydrogen embrittlement behavior, the hydrogen embrittlement phenomenon of some alloys at elevated and cryogenic temperatures is also reviewed, with the aim to provide some guidelines of material selection and design in developing fields such as hydrogen gas turbines and long-flight-duration hydrogen powered aircraft. Finally, the current challenges in the study of hydrogen embrittlement are identified and discussed to guide future research efforts.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000064/pdfft?md5=0e3b45de17bdeb4463f22c807f1691b0&pid=1-s2.0-S2666792424000064-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160136","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":"SkyGPT: Probabilistic ultra-short-term solar forecasting using synthetic sky images from physics-constrained VideoGPT","authors":"Yuhao Nie ,&nbsp;Eric Zelikman ,&nbsp;Andea Scott ,&nbsp;Quentin Paletta ,&nbsp;Adam Brandt","doi":"10.1016/j.adapen.2024.100172","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100172","url":null,"abstract":"<div><p>The variability of solar photovoltaic (PV) power output, driven by rapidly changing cloud dynamics, hinders the transition to reliable renewable energy systems. Information on future sky conditions, especially cloud coverage, holds the promise for improving PV output forecasting. Leveraging recent advances in generative artificial intelligence (AI), we introduce <em>SkyGPT</em>, a physics-constrained stochastic video prediction model, which predicts plausible future images of the sky using historical sky images. We show that <em>SkyGPT</em> can accurately capture cloud dynamics, producing highly realistic and diverse future sky images. We further demonstrate its efficacy in 15-minute-ahead probabilistic PV output forecasting using real-world power generation data from a 30-kW rooftop PV system. By coupling <em>SkyGPT</em> with a U-Net-based PV power prediction model, we observe superior prediction reliability and sharpness compared with several benchmark methods. The propose approach achieves a continuous ranked probability score (CRPS) of 2.81 kW, outperforming a classic convolutional neural network (CNN) baseline by 13% and the smart persistence model by 23%. The findings of this research could aid efficient and resilient management of solar electricity generation, particularly as we transition to renewable-heavy grids. The study also provides valuable insights into stochastic cloud modeling for a broad research community, encompassing fields such as solar energy meteorology and atmospheric sciences.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100172"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000106/pdfft?md5=9fe829b2f1a0245854798ffc7c7f513a&pid=1-s2.0-S2666792424000106-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140555380","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":"Reconfigurable supply-based feedback control for enhanced energy flexibility of air-conditioning systems facilitating grid-interactive buildings","authors":"Mingkun Dai ,&nbsp;Hangxin Li ,&nbsp;Xiuming Li ,&nbsp;Shengwei Wang","doi":"10.1016/j.adapen.2024.100176","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100176","url":null,"abstract":"<div><p>Air-conditioning systems have great potential to provide energy flexibility services to the power grids of high-renewable penetration, due to their high power consumption and inherent energy flexibilities. Direct load control by switching off some operating chillers is the simplest and effective means for air-conditioning systems in buildings to respond to urgent power reduction requests of power grids. However, the implementation of this approach in today's buildings, which widely adopt demand-based feedback controls, would result in serious problems including disordered cooling distribution and likely extra energy consumption. This study, therefore, proposes a reconfigurable control strategy to address these problems. This strategy consists of supply-based feedback control, incorporated with the conventional demand-based feedback control, a control loop reconfiguration scheme and a setpoint reset scheme, facilitating effective control under limited cooling supply and smooth transition between supply-based and demand-based feedback control modes. The proposed control strategy is deployed in a commonly-used digital controller to conduct hardware-in-the-loop control tests on an air-conditioning system involving six AHUs. Test results show that the reconfigurable control achieves commendable control performance. Proper chilled water distribution enables even thermal comfort control among the building zones during demand response and rebound periods. Temperature deviation of the building zones is controlled below 0.2 K most of the time. 11.6 % and 27 % of power demand reductions are achieved during demand response and rebound periods respectively, using the proposed reconfigurable control compared with that using conventional controls.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100176"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000143/pdfft?md5=5d7aa405b6962d8965ddb55dd055d25f&pid=1-s2.0-S2666792424000143-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140638188","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":"Variational quantum circuit learning-enabled robust optimization for AI data center energy control and decarbonization","authors":"Akshay Ajagekar ,&nbsp;Fengqi You","doi":"10.1016/j.adapen.2024.100179","DOIUrl":"https://doi.org/10.1016/j.adapen.2024.100179","url":null,"abstract":"<div><p>As the demand for artificial intelligence (AI) models and applications continues to grow, data centers that handle AI workloads are experiencing a rise in energy consumption and associated carbon footprint. This work proposes a variational quantum computing-based robust optimization (VQC-RO) framework for control and energy management in large-scale data centers to address the computational challenges and overcome limitations of conventional model-based and model-free strategies. The VQC-RO framework integrates variational quantum circuits (VQCs) with classical optimization to enable efficient and uncertainty-aware control of energy systems in AI data centers. Quantum algorithms executed on noisy intermediate-scale quantum (NISQ) devices are used for value function estimation trained with Q-learning, leading to the formulation of a robust optimization problem with uncertain coefficients. The quantum computing-based robust control strategy is designed to address uncertainties associated with weather conditions and renewable energy generation while optimizing energy consumption in AI data centers. This work also outlines the computational experiments conducted at various AI data center locations in the United States to analyze the reduction in power consumption and carbon emission levels associated with the proposed quantum computing-based robust control framework. This work contributes a novel approach to energy-efficient and sustainable data center operation, promising to reduce carbon emissions and energy consumption in large-scale data centers handling AI workloads by 9.8 % and 12.5 %, respectively.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"14 ","pages":"Article 100179"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792424000179/pdfft?md5=21c93fc476ac75038664b923e8d0dd02&pid=1-s2.0-S2666792424000179-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140948357","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}