Advances in Applied Energy最新文献_第8页

Critical metal requirement for clean energy transition: A quantitative review on the case of transportation electrification 清洁能源转型的关键金属需求:交通电气化案例的定量回顾

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100116

Chunbo Zhang , Jinyue Yan , Fengqi You

{"title":"Critical metal requirement for clean energy transition: A quantitative review on the case of transportation electrification","authors":"Chunbo Zhang , Jinyue Yan , Fengqi You","doi":"10.1016/j.adapen.2022.100116","DOIUrl":"10.1016/j.adapen.2022.100116","url":null,"abstract":"<div><p>The clean energy transition plays an essential role in achieving climate mitigation targets. As for the transportation sector, battery and fuel cell electric vehicles (EVs) have emerged as a key solution to reduce greenhouse gasses from transportation emissions. However, the rapid uptake of EVs has triggered potential supply risks of critical metals (e.g., lithium, nickel, cobalt, platinum group metals (PGMs), etc.) used in the production of lithium-ion batteries and fuel cells. Material flow analysis (MFA) has been widely applied to assess the demand for critical metals used in transportation electrification on various spatiotemporal scales. This paper presents a quantitative review and analysis of 78 MFA research articles on the critical metal requirement of transportation electrification. We analyzed the characteristics of the selected studies regarding their geographical and temporal scopes, transportation sectors, EV categories, battery technologies, materials, and modeling approaches. Based on the global forecasts in those studies, we compared the annual and cumulative global requirements of the four metals that received the most attention: lithium, nickel, cobalt, and PGMs. Although major uncertainties exist, most studies indicate that the annual demand for these four metals will continue to increase and far exceed their production capacities in 2021. Global reserves of these metals may meet their cumulative demand in the short-term (2020–2030) and medium-term (2020–2050) but are insufficient for the long-term (2020–2100) needs. Then, we summarized the proposed policy implications in these studies. Finally, we discuss the main findings from the four aspects: environmental and social implications of deploying electric vehicles, whether or not to electrify heavy-duty vehicles, opportunities and challenges in recycling, and future research direction.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100116"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41370203","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}

引用次数: 11

Energy-efficient AI-based Control of Semi-closed Greenhouses Leveraging Robust Optimization in Deep Reinforcement Learning 基于深度强化学习鲁棒优化的半封闭温室节能人工智能控制

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100119

Akshay Ajagekar , Neil S. Mattson , Fengqi You

{"title":"Energy-efficient AI-based Control of Semi-closed Greenhouses Leveraging Robust Optimization in Deep Reinforcement Learning","authors":"Akshay Ajagekar , Neil S. Mattson , Fengqi You","doi":"10.1016/j.adapen.2022.100119","DOIUrl":"10.1016/j.adapen.2022.100119","url":null,"abstract":"<div><p>As greenhouses are being widely adopted worldwide, it is important to improve the energy efficiency of the control systems while accurately regulating their indoor climate to realize sustainable agricultural practices for food production. In this work, we propose an artificial intelligence (AI)-based control framework that combines deep reinforcement learning techniques to generate insights into greenhouse operation combined with robust optimization to produce energy-efficient controls by hedging against associated uncertainties. The proposed control strategy is capable of learning from historical greenhouse climate trajectories while adapting to current climatic conditions and disturbances like time-varying crop growth and outdoor weather. We evaluate the performance of the proposed AI-based control strategy against state-of-the-art model-based and model-free approaches like certainty-equivalent model predictive control, robust model predictive control (RMPC), and deep deterministic policy gradient. Based on the computational results obtained for the tomato crop's greenhouse climate control case study, the proposed control technique demonstrates a significant reduction in energy consumption of 57% over traditional control techniques. The AI-based control framework also produces robust controls that are not overly conservative, with an improvement in deviation from setpoints of over 26.8% as compared to the baseline control approach RMPC.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100119"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44864813","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}

引用次数: 9

A general model for comprehensive electrical characterization of photovoltaics under partial shaded conditions 部分遮荫条件下光伏综合电学特性的通用模型

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100118

Fuxiang Li , Wentao Dong , Wei Wu

{"title":"A general model for comprehensive electrical characterization of photovoltaics under partial shaded conditions","authors":"Fuxiang Li , Wentao Dong , Wei Wu","doi":"10.1016/j.adapen.2022.100118","DOIUrl":"10.1016/j.adapen.2022.100118","url":null,"abstract":"<div><p>Partial shading condition (PSC) causes underperformance, unreliability, and fire risks in photovoltaic (PV) systems. Accurate estimation of PV behaviors is crucial to fundamental understanding and further mitigation. However, current modeling methods lack full consideration of the physical behaviors, system complexities, and shading pattern diversities, ending in coarse and simple analysis. Herein, an innovative modeling approach with high-performance algorithms is proposed to address these challenges simultaneously. Based on rigorous analysis, physics models considering the reverse-biased behaviors, the system complexities, and shading pattern diversities, are developed at the cell, module, and array levels, respectively. Then, a strict and progressive validation via measurement data is conducted to justify the effectiveness of the developed method. The method is valid for mainstream PV technologies in the market and can predict cell behaviors and module electrical characteristics perfectly. Notably, the proposed method is more computationally efficient than Simulink when simulating the same PV array. Lastly, to demonstrate its exclusive advantages, two case studies are conducted. The localized power dissipation can be quantified. The observed energy loss justifies the necessity of reverse biased behaviors and high-resolution simulation. This method can be coded in any development environment, providing an efficient and comprehensive tool to analyze PV systems.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100118"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43737089","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}

引用次数: 4

Day-ahead probabilistic forecasting at a co-located wind and solar power park in Sweden: Trading and forecast verification 瑞典风能和太阳能发电园区的未来一天概率预测：交易和预测验证

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100120

O. Lindberg , D. Lingfors , J. Arnqvist , D. van der Meer , J. Munkhammar

{"title":"Day-ahead probabilistic forecasting at a co-located wind and solar power park in Sweden: Trading and forecast verification","authors":"O. Lindberg , D. Lingfors , J. Arnqvist , D. van der Meer , J. Munkhammar","doi":"10.1016/j.adapen.2022.100120","DOIUrl":"10.1016/j.adapen.2022.100120","url":null,"abstract":"<div><p>This paper presents a first step in the field of probabilistic forecasting of co-located wind and photovoltaic (PV) parks. The effect of aggregation is analyzed with respect to forecast accuracy and value at a co-located park in Sweden using roughly three years of data. We use a fixed modelling framework where we post-process numerical weather predictions to calibrated probabilistic production forecasts, which is a prerequisite when placing optimal bids in the day-ahead market. The results show that aggregation improves forecast accuracy in terms of continuous ranked probability score, interval score and quantile score when compared to wind or PV power forecasts alone. The optimal aggregation ratio is found to be 50%–60% wind power and the remainder PV power. This is explained by the aggregated time series being smoother, which improves the calibration and produces sharper predictive distributions, especially during periods of high variability in both resources, i.e., most prominently in the summer, spring and fall. Furthermore, the daily variability of wind and PV power generation was found to be anti-correlated which proved to be beneficial when forecasting the aggregated time series. Finally, we show that probabilistic forecasts of co-located production improve trading in the day-ahead market, where the more accurate and sharper forecasts reduce balancing costs. In conclusion, the study indicates that co-locating wind and PV power parks can improve probabilistic forecasts which, furthermore, carry over to electricity market trading. The results from the study should be generally applicable to other co-located parks in similar climates.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100120"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47902255","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}

引用次数: 6

Transfer learning for battery smarter state estimation and ageing prognostics: Recent progress, challenges, and prospects 迁移学习用于电池智能状态估计和老化预测：最新进展、挑战和前景

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100117

Kailong Liu , Qiao Peng , Yunhong Che , Yusheng Zheng , Kang Li , Remus Teodorescu , Dhammika Widanage , Anup Barai

{"title":"Transfer learning for battery smarter state estimation and ageing prognostics: Recent progress, challenges, and prospects","authors":"Kailong Liu , Qiao Peng , Yunhong Che , Yusheng Zheng , Kang Li , Remus Teodorescu , Dhammika Widanage , Anup Barai","doi":"10.1016/j.adapen.2022.100117","DOIUrl":"10.1016/j.adapen.2022.100117","url":null,"abstract":"<div><p>With the advent of sustainable and clean energy transitions, lithium-ion batteries have become one of the most important energy storage sources for many applications. Battery management is of utmost importance for the safe, efficient, and long-lasting operation of lithium-ion batteries. However, the frequently changing load and operating conditions, the different cell chemistries and formats, and the complicated degradation patterns pose challenges for traditional battery management. The data-driven solutions that have emerged in recent years offer great opportunities to uncover the underlying data mapping within a battery system. In particular, transfer learning improves the performance of data-driven strategies by transferring existing knowledge from different but related domains, and if properly applied, would be a promising approach for smarter battery management. To this end, this paper presents a systematic review for the applications of transfer learning in the field of battery management for the first time, with particular focuses on battery state estimation and ageing prognostics. Specifically, the general issues faced by conventional battery management are identified and the applications of transfer learning to these issues are summarized. Then, the specific challenges of each topic are identified and the potential solutions based on transfer learning are explained, followed by a discussion of the state of the art in terms of principles, algorithm frameworks, advantages and disadvantages. Finally, future trends of data-driven battery management with transfer learning are discussed in terms of key challenges and promising opportunities.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100117"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41399701","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}

引用次数: 22

Emerging information and communication technologies for smart energy systems and renewable transition 智能能源系统和可再生能源转型的新兴信息和通信技术

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2023.100125

Ning Zhao , Haoran Zhang , Xiaohu Yang , Jinyue Yan , Fengqi You

引用次数: 24

Floating wind power in deep-sea area: Life cycle assessment of environmental impacts 深海漂浮风力发电：环境影响的生命周期评估

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2023.100122

Weiyu Yuan , Jing-Chun Feng , Si Zhang , Liwei Sun , Yanpeng Cai , Zhifeng Yang , Songwei Sheng

{"title":"Floating wind power in deep-sea area: Life cycle assessment of environmental impacts","authors":"Weiyu Yuan , Jing-Chun Feng , Si Zhang , Liwei Sun , Yanpeng Cai , Zhifeng Yang , Songwei Sheng","doi":"10.1016/j.adapen.2023.100122","DOIUrl":"10.1016/j.adapen.2023.100122","url":null,"abstract":"<div><p>Floating offshore wind power, an emerging technology in the offshore wind industry, has attracted increasing attention for its potential to cooperate with other renewable energies to decarbonize energy systems. The environmental effects of the floating offshore wind farm in deep-sea areas should be considered, and methods to enhance the low-carbon effect should be devised. There have been a few studies assessing the environmental effects of the floating offshore wind farm, but the scales of these studies were relatively small. This study evaluated the environmental impacts of a floating wind farm with 100 wind turbines of 6.7 MW using life cycle assessment (LCA) method, based on the Chinese core life cycle database. Results showed that the carbon footprint of the wind farm was 25.76 g CO<sub>2</sub>-eq/kWh, which was relatively low in terms of global warming potential. Additionally, the floating offshore wind farm contributed most to eutrophication potential. A ± 20% variation in steel resulted in a ±3% to ±15% variation in the indicator score of each environmental category, indicating that the environmental performance of the wind farm was mainly influenced by this parameter. Moreover, scenario analysis showed that electric arc furnace routes can reduce the cumulative greenhouse gas emissions from upstream process of the floating offshore wind farm by 1.75 Mt CO<sub>2</sub>-eq by 2030. Emission reduction of the steel industry will further reduce the carbon footprint of the floating offshore wind farm. In the future, more baseline data need to be collected to improve the reliability of LCA. The effects of the floating offshore wind farm on marine ecology and atmospheric physical characteristics remain to be investigated in depth.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100122"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43980988","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}

引用次数: 3

A reactive power market for the future grid 未来电网的无功电力市场

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100114

Adam Potter , Rabab Haider , Giulio Ferro , Michela Robba , Anuradha M. Annaswamy

{"title":"A reactive power market for the future grid","authors":"Adam Potter , Rabab Haider , Giulio Ferro , Michela Robba , Anuradha M. Annaswamy","doi":"10.1016/j.adapen.2022.100114","DOIUrl":"10.1016/j.adapen.2022.100114","url":null,"abstract":"<div><p>As pressures to decarbonize the electricity grid increase, the grid edge is witnessing a rapid adoption of distributed and renewable generation. As a result, traditional methods for reactive power management and compensation may become ineffective. Current state-of-art for reactive power compensation, which rely primarily on capacity payments, exclude distributed generation (DG). We propose an alternative: a reactive power market at the distribution level designed to meet the needs of decentralized and decarbonized grids. The proposed market uses variable payments to compensate DGs equipped with smart inverters, at an increased spatial and temporal granularity, through a distribution-level Locational Marginal Price (d-LMP). We validate our proposed market with a case study of the US New England grid on a modified IEEE-123 bus, while varying DG penetration from 5% to 160%. Results show that our market can accommodate such a large penetration, with stable reactive power revenue streams. The market can leverage the considerable flexibility afforded by inverter-based resources to meet over 40% of reactive power load when operating in a power factor range of 0.6 to 1.0. DGs participating in the market can earn up to 11% of their total revenue from reactive power payments. Finally, the corresponding daily d-LMPs determined from the proposed market were observed to exhibit limited volatility.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100114"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49459610","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}

引用次数: 10

Multi-zone building control with thermal comfort constraints under disjunctive uncertainty using data-driven robust model predictive control 基于数据驱动鲁棒模型预测控制的不确定性条件下具有热舒适性约束的多区域建筑控制

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2023.100124

Guoqing Hu , Fengqi You

{"title":"Multi-zone building control with thermal comfort constraints under disjunctive uncertainty using data-driven robust model predictive control","authors":"Guoqing Hu , Fengqi You","doi":"10.1016/j.adapen.2023.100124","DOIUrl":"10.1016/j.adapen.2023.100124","url":null,"abstract":"<div><p>This paper proposes a novel data-driven robust model predictive control (MPC) framework for a multi-zone building considering thermal comfort and uncertain weather forecast errors. The control objective is to maintain each zone's temperature and relative humidity within the specified ranges by minimizing the energy usage of the underlying heating system. A state-space model is developed to use a hybrid physics-based and data-driven method for the multi-zone building's temperature and relative humidity. The temperature and humidity RMSEs between the state-space model and the EnergyPlus-based model are less than 0.25 °C and 5.9%, respectively. The uncertainty space is based on historical weather forecast error data, which are clustered by using a k-means clustering algorithm. Machine learning approaches, including principal component analysis and kernel density estimation, are used to construct each basic uncertainty set and reduce the conservatism of resulting robust control action under disturbances. A robust MPC framework is built upon the proposed state-space model and data-driven disjunctive uncertainty set. An affine disturbance feedback rule is employed to obtain a tractable approximation of the robust MPC problem. Besides, the feasibility and stability of the proposed MPC are discussed in detail. A case study of controlling temperature and relative humidity of a multi-zone building in Ithaca, New York, USA, is presented. The results demonstrate that the proposed framework can reduce up to 8.8% of total energy consumption compared to conventional robust MPC approaches. Moreover, the proposed framework can essentially satisfy the thermal constraints that certainty equivalent MPC and robust MPC largely violate.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42219321","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}

引用次数: 7

A distributed robust control strategy for electric vehicles to enhance resilience in urban energy systems 提高城市能源系统弹性的分布式电动汽车鲁棒控制策略

Advances in Applied Energy Pub Date : 2023-02-01 DOI: 10.1016/j.adapen.2022.100115

Zihang Dong , Xi Zhang , Ning Zhang , Chongqing Kang , Goran Strbac

{"title":"A distributed robust control strategy for electric vehicles to enhance resilience in urban energy systems","authors":"Zihang Dong , Xi Zhang , Ning Zhang , Chongqing Kang , Goran Strbac","doi":"10.1016/j.adapen.2022.100115","DOIUrl":"10.1016/j.adapen.2022.100115","url":null,"abstract":"<div><p>Resilient operation of multi-energy microgrid is a critical concept for decarbonization in modern power system. Its goal is to mitigate the low probability and high damaging impacts of electricity interruptions. Electrical vehicles, as a key flexibility provider, can react to unserved demand and autonomously schedule their operation in order to provide resilience. This paper presents a distributed control strategy for a population of electrical vehicles to enhance resilience of an urban energy system experiencing extreme contingency. Specifically, an iterative algorithm is developed to coordinate the charging/discharging schedules of heterogeneous electrical vehicles aiming at reducing the essential load shedding while considering the local constraints and multi-energy microgrid interconnection capacities. Additionally, the gap between electrical vehicle energy and the required energy level at the departure time is also minimised. The effectiveness of the introduced distributed coordinated approach on energy arbitrage and congestion management is tested and demonstrated by a series of case studies.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"9 ","pages":"Article 100115"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44066637","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}

引用次数: 7