Advances in Applied Energy最新文献

{"title":"Conditions for profitable operation of P2X energy hubs to meet local demand under energy market access","authors":"Y. Wan, T. Kober, T. Schildhauer, T. Schmidt, R. McKenna, M. Densing","doi":"10.1016/j.adapen.2023.100127","DOIUrl":"https://doi.org/10.1016/j.adapen.2023.100127","url":null,"abstract":"","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46085933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of battery energy storage technologies and renewable integration on the energy transition in the New York State","authors":"Wei-Chieh Huang ,&nbsp;Qianzhi Zhang ,&nbsp;Fengqi You","doi":"10.1016/j.adapen.2023.100126","DOIUrl":"10.1016/j.adapen.2023.100126","url":null,"abstract":"<div><p>In light of current energy policies responding to rapid climate change, much attention has been directed to developing feasible approaches for transitioning energy production from fossil-based resources to renewable energy. Although existing studies analyze regional dispatch of renewable energy sources and capacity planning, they do not fully explore the impacts of the energy storage system technology's technical and economic characteristics on renewable energy integration and energy transition, and the importance of energy storage systems to the energy transition is currently ignored. To fill this gap, we propose an integrated optimal power flow and multi-criteria decision-making model to minimize system cost under operational constraints and evaluate the operational performance of renewable energy technologies with multidimensional criteria. The proposed method can identify the most critical features of energy storage system technologies to enhance renewable energy integration and achieve New York State's climate goals from 2025 to 2040. We discover that lead-acid battery requires an additional 38.66 GW capacity of renewable energy sources than lithium-ion battery to achieve the zero carbon dioxide emissions condition. Based on the cross-sensitivity analysis in the multidimensional evaluation, the vanadium redox flow battery performs the best, and the nickel-cadmium battery performs the worst when reaching the zero carbon dioxide emissions target in 2040. The results of the proposed model can also be conveniently generalized to select ESS technology based on the criteria preferences from RE integration and energy transition studies and serve as a reference for ESS configurations in future energy and power system planning.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45052151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable machine learning for building energy management: A state-of-the-art review","authors":"Zhe Chen ,&nbsp;Fu Xiao ,&nbsp;Fangzhou Guo ,&nbsp;Jinyue Yan","doi":"10.1016/j.adapen.2023.100123","DOIUrl":"10.1016/j.adapen.2023.100123","url":null,"abstract":"<div><p>Machine learning has been widely adopted for improving building energy efficiency and flexibility in the past decade owing to the ever-increasing availability of massive building operational data. However, it is challenging for end-users to understand and trust machine learning models because of their black-box nature. To this end, the interpretability of machine learning models has attracted increasing attention in recent studies because it helps users understand the decisions made by these models. This article reviews previous studies that adopted interpretable machine learning techniques for building energy management to analyze how model interpretability is improved. First, the studies are categorized according to the application stages of interpretable machine learning techniques: ante-hoc and post-hoc approaches. Then, the studies are analyzed in detail according to specific techniques with critical comparisons. Through the review, we find that the broad application of interpretable machine learning in building energy management faces the following significant challenges: (1) different terminologies are used to describe model interpretability which could cause confusion, (2) performance of interpretable ML in different tasks is difficult to compare, and (3) current prevalent techniques such as SHAP and LIME can only provide limited interpretability. Finally, we discuss the future R&amp;D needs for improving the interpretability of black-box models that could be significant to accelerate the application of machine learning for building energy management.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49644477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operation of a circular economy, energy, environmental system at a wastewater treatment plant","authors":"Davis Rusmanis ,&nbsp;Yan Yang ,&nbsp;Richen Lin ,&nbsp;David M. Wall ,&nbsp;Jerry D. Murphy","doi":"10.1016/j.adapen.2022.100109","DOIUrl":"10.1016/j.adapen.2022.100109","url":null,"abstract":"<div><p>Decarbonising economies and improving environment can be enhanced through circular economy, energy, and environmental systems integrating electricity, water, and gas utilities. Hydrogen production can facilitate intermittent renewable electricity through reduced curtailment of electricity in periods of over production. Positioning an electrolyser at a wastewater treatment plant with existing sludge digesters offers significant advantages over stand-alone facilities. This paper proposes co-locating electrolysis and biological methanation technologies at a wastewater treatment plant. Electrolysis can produce oxygen for use in pure or enhanced oxygen aeration, offering a 40% reduction in emissions and power demand at the treatment facility. The hydrogen may be used in a novel biological methanation system, upgrading carbon dioxide (CO₂) in biogas from sludge digestion, yielding a 54% increase in biomethane production. A 10 MW electrolyser operating at 80% capacity would be capable of supplying the oxygen demand for a 426,400 population equivalent wastewater treatment plant, producing 8,500 tonnes dry solids per annum (tDS/a) of sludge. Digesting the sludge could generate 1,409,000 m³CH₄/a and 776,000 m³CO₂/a. Upgrading the CO₂ to methane would consume 22.2% of the electrolyser generated hydrogen and capture 1.534 ktCO_2e/a. Hydrogen and methane are viable advanced transport fuels that can be utilised in decarbonising heavy transport. In the proposed circular economy, energy, and environment system, sufficient fuel would be generated annually for 94 compressed biomethane gas (CBG) heavy goods vehicles (HGV) and 296 compressed hydrogen gas fuel cell (CHG) HGVs. Replacement of the equivalent number of diesel HGVs would offset approximately 16.1 ktCO_2e/a.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100109"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000270/pdfft?md5=bd6c288cceea896cac852038398af646&pid=1-s2.0-S2666792422000270-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42728155","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":"A semantic ontology for representing and quantifying energy flexibility of buildings","authors":"Han Li,&nbsp;Tianzhen Hong","doi":"10.1016/j.adapen.2022.100113","DOIUrl":"10.1016/j.adapen.2022.100113","url":null,"abstract":"<div><p>Energy flexibility of buildings can be an essential resource for a sustainable and reliable power grid with the growing variable renewable energy shares and the trend to electrify and decarbonize buildings. Traditional demand-side management technologies, advanced building controls, and emerging distributed energy resources (including electric vehicle, energy storage, and on-site power generation) enable the transition of the building stock to grid-interactive efficient buildings (GEBs) that operate efficiently to meet service needs and are responsive to grid pricing or carbon signals to achieve energy and carbon neutrality. Although energy flexibility has received growing attention from industry and the research community, there remains a lack of common ground for energy flexibility terminologies, characterization, and quantification methods. This paper presents a semantic ontology—EFOnt (Energy Flexibility Ontology)—that extends existing terminologies, ontologies, and schemas for building energy flexibility applications. EFOnt aims to serve as a standardized tool for knowledge co-development and streamlining energy flexibility related applications. We demonstrate potential use cases of EFOnt via two examples: <span>(1)</span> energy flexibility analytics with measured data from a residential smart thermostat dataset and a commercial building, and <span>(2)</span> modeling and simulation to evaluate energy flexibility of buildings. The compatibility of EFOnt with existing ontologies and the outlook of EFOnt's role in the building energy data tool ecosystem are discussed.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100113"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000312/pdfft?md5=d6ee4042b42668183aa3d8d3f1775244&pid=1-s2.0-S2666792422000312-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47102915","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":"Using crowdsourced data to estimate the carbon footprints of global cities","authors":"Xinlu Sun ,&nbsp;Zhifu Mi ,&nbsp;Andrew Sudmant ,&nbsp;D'Maris Coffman ,&nbsp;Pu Yang ,&nbsp;Richard Wood","doi":"10.1016/j.adapen.2022.100111","DOIUrl":"10.1016/j.adapen.2022.100111","url":null,"abstract":"<div><p>Cities are at the forefront of the battle against climate change. However, intercity comparisons and responsibility allocations among cities are hindered because cost- and time-effective methods to calculate the carbon footprints of global cities have yet to be developed. Here, we establish a hybrid method integrating top-down input–output analysis and bottom-up crowdsourced data to estimate the carbon footprints of global cities. Using city purchasing power as the main predictor of the carbon footprint, we estimate the carbon footprints of 465 global cities in 2020. Those cities comprise 10% of the global population but account for 18% of the global carbon emissions showing a significant concentration of carbon emissions. The Gini coefficients are applied to show that global carbon inequality is less than income inequality. In addition, the increased carbon emissions that come from high consumption lifestyles offset the carbon reduction by efficiency gains that could result from compact city design and large city scale. Large climate benefits could be obtained by achieving a low-carbon transition in a small number of global cities, emphasizing the need for leadership from globally important urban centres.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100111"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000294/pdfft?md5=abe7a1fb37b7734178f9d84ad708bdfe&pid=1-s2.0-S2666792422000294-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47054328","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":"Moving toward the low-carbon hydrogen economy: Experiences and key learnings from national case studies","authors":"Gunhild A. Reigstad ,&nbsp;Simon Roussanaly ,&nbsp;Julian Straus ,&nbsp;Rahul Anantharaman ,&nbsp;Robert de Kler ,&nbsp;Maxine Akhurst ,&nbsp;Nixon Sunny ,&nbsp;Ward Goldthorpe ,&nbsp;Lionel Avignon ,&nbsp;Jonathan Pearce ,&nbsp;Stefan Flamme ,&nbsp;Gianfranco Guidati ,&nbsp;Evangelos Panos ,&nbsp;Christian Bauer","doi":"10.1016/j.adapen.2022.100108","DOIUrl":"10.1016/j.adapen.2022.100108","url":null,"abstract":"<div><p>The urgency to achieve net-zero carbon dioxide (CO₂) emissions by 2050, as first presented by the IPCC special report on 1.5 °C Global Warming, has spurred renewed interest in hydrogen, to complement electrification, for widespread decarbonization of the economy. We present reflections on estimates of future hydrogen demand, optimization of infrastructure for hydrogen production, transport and storage, development of viable business cases, and environmental impact evaluations using life cycle assessments. We highlight challenges and opportunities that are common across studies of the business cases for hydrogen in Germany, the UK, the Netherlands, Switzerland and Norway. The use of hydrogen in the industrial sector is an important driver and could incentivise large-scale hydrogen value chains. In the long-term hydrogen becomes important also for the transport sector. Hydrogen production from natural gas with capture and permanent storage of the produced CO₂ (CCS) enables large-scale hydrogen production in the intermediate future and is complementary to hydrogen from renewable power. Furthermore, timely establishment of hydrogen and CO₂ infrastructures serves as an anchor to support the deployment of carbon dioxide removal technologies, such as direct air carbon capture and storage (DACCS) and biohydrogen production with CCS. Significant public support is needed to ensure coordinated planning, governance, and the establishment of supportive regulatory frameworks which foster the growth of hydrogen markets.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100108"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000269/pdfft?md5=ff03db60650f0d6118f190e61c044a43&pid=1-s2.0-S2666792422000269-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"53939134","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":"Why we must move beyond LCOE for renewable energy design","authors":"Eric Loth ,&nbsp;Chris Qin ,&nbsp;Juliet G. Simpson ,&nbsp;Katherine Dykes","doi":"10.1016/j.adapen.2022.100112","DOIUrl":"10.1016/j.adapen.2022.100112","url":null,"abstract":"<div><p>The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design since LCOE neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified with examples of two large grids with high renewable shares using three approaches to model hourly price: (1) residual demand, (2) wind and solar generation, and (3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. This is because COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100112"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000300/pdfft?md5=e6a6b7b159c443be41621352048b710e&pid=1-s2.0-S2666792422000300-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45644196","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":"Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings","authors":"Jingjing Liu ,&nbsp;Rongxin Yin ,&nbsp;Lili Yu ,&nbsp;Mary Ann Piette ,&nbsp;Marco Pritoni ,&nbsp;Armando Casillas ,&nbsp;Jiarong Xie ,&nbsp;Tianzhen Hong ,&nbsp;Monica Neukomm ,&nbsp;Peter Schwartz","doi":"10.1016/j.adapen.2022.100107","DOIUrl":"10.1016/j.adapen.2022.100107","url":null,"abstract":"<div><p>Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., <em>benchmarking DF</em>). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. These examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100107"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000257/pdfft?md5=efdc41be29d1b7740934ef7e862dd497&pid=1-s2.0-S2666792422000257-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47883229","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":"Batteries, fuel cells, or engines? A probabilistic economic and environmental assessment of electricity and electrofuels for heavy goods vehicles","authors":"Nathan Gray ,&nbsp;Richard O'Shea ,&nbsp;David Wall ,&nbsp;Beatrice Smyth ,&nbsp;Piet N.L. Lens ,&nbsp;Jerry D. Murphy","doi":"10.1016/j.adapen.2022.100110","DOIUrl":"10.1016/j.adapen.2022.100110","url":null,"abstract":"<div><p>Uncertainty surrounding the total cost of ownership, system costs, and life cycle environmental impacts means that stakeholders may lack the required information to evaluate the risks of transitioning to low-carbon fuels and powertrains. This paper assesses the life cycle costs and well-to-wheel environmental impacts of using electricity and electrofuels in Heavy Good Vehicles (HGVs) whilst considering input parameter uncertainty. The complex relationship between electricity cost, electrolyser capacity factor, CO₂ capture cost and electricity emissions intensity is assessed within a Monte Carlo based framework to identify scenarios where use of electricity or electrofuels in heavy goods vehicles makes economic and environmental sense. For vehicles with a range of less than 450 km, battery electric vehicles achieve the lowest total cost of ownership for an electricity cost less than 100 €/MWh. For vehicles that require a range of up to 900 km, hydrogen fuel cell vehicles represent the lowest long-term cost of abatement. Power-to-methane and power-to-liquid scenarios become economically competitive when low-cost electricity is available at high-capacity factors and CO₂ capture costs for fuel synthesis are below 100 €/tCO₂; these fuels may be more applicable to decarbonise shipping and aviation. Battery electric HGVs reduce greenhouse gas emissions by 50% compared to the diesel baseline with electricity emissions of 350 gCO₂e/kWh. Electricity emissions less than 35 gCO₂e/kWh are required for the power-to-methane and power-to-liquid scenarios to meet EU emissions savings criteria. High vehicle capital costs and a lack of widespread refuelling infrastructure may hinder initial uptake of low-carbon fuels and powertrains for HGVs.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100110"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000282/pdfft?md5=0e5a4bea2374cbfe9d19f320f1298293&pid=1-s2.0-S2666792422000282-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43492822","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}