Article
Economics
Alejandro Pena-Bello, Robin Junod, Christophe Ballif, Nicolas Wyrsch
Summary: This study investigates the impact of five electricity tariffs on distributed photovoltaics and finds that capacity-based tariffs can promote the adoption of PV and storage while allowing distribution system operators to recover grid costs.
Article
Construction & Building Technology
Benjamin Hauck, Weimin Wang, Yibing Xue
Summary: This paper investigates the impact of model granularity and temporal resolution on simulated energy flow items, self-sufficiency and self-consumption of grid-connected residential PV-battery systems. The results show that temporal resolutions have negligible impact on self-consumption and self-sufficiency, but cause noticeable differences in power profiles observed in the PV-battery system. The impact of model granularity on self-consumption and self-sufficiency is also discussed.
DEVELOPMENTS IN THE BUILT ENVIRONMENT
(2021)
Article
Energy & Fuels
Yuchen Hao, Dawei Su, Zhen Lei
Summary: A bi-level control strategy is proposed in this paper to maintain power stability of PV plants by identifying and mitigating PV power fluctuations, aiming at minimizing the operation cost of BES. By coordinating the PV power fluctuations identification block and the mitigation block, promising results are obtained to regulate the operation of battery sub-modules for PV-BES systems.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Kandil M. Kandil, Ibrahim M. Kadad, Adel A. Ghoneim, Reem S. Altawash
Summary: This study proposes a high concentrated photovoltaic system integrated with a battery storage system for energy production in hot harsh weather conditions of Kuwait. The integrated system shows higher energy density and lower system cost compared to individual component systems. It also effectively reduces the temperature of the battery and converters.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Energy & Fuels
Wenya Xu, Yanxue Li, Guanjie He, Yang Xu, Weijun Gao
Summary: This study proposes a model-based reinforcement learning approach to optimize the operation of zero-energy houses, considering PV generation consumption and energy costs. The proposed RL agents achieve fast convergence and demonstrate cost-effectiveness in scheduling operations of the hybrid energy system. The DDPG algorithm performs the best, outperforming rule-based operation by 7.2% in energy cost.
Article
Green & Sustainable Science & Technology
Pietro Lubello, Francesco Papi, Alessandro Bianchini, Carlo Carcasci
Summary: The research shows that using aging models for analysis of residential energy systems can better predict their economic viability and avoid incorrect predictions. When using aging algorithms, the breakeven price for introducing batteries into residential energy systems is lower, and higher optimal capacities are obtained for lower battery prices.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Chemistry, Physical
Rachid Dabou, Ahmed Bouraiou, Abderrezzaq Ziane, Ammar Necaibia, Nordine Sahouane, Mohamed Blal, Seyfallah Khelifi, Abdelkrim Rouabhia
Summary: This study aims to improve the monitoring systems for two grid-connected PV stations of URERMS ADRAR by developing monitoring software that visualizes real-time data and evaluates performance, allowing for a better understanding of the dynamic behavior of PV system components.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Electrochemistry
Shiqi Liu, Junhua Wang, Haolu Liu, Qisheng Liu, Jia Tang, Zhongxiang Li
Summary: This paper proposes a novel battery lifetime estimator based on multiple health indicators, utilizing six different characteristics to train a neural network model in order to improve accuracy and robustness of battery lifetime estimation. Additionally, an empirical degradation model for low-capacity batteries considering different usage factors is introduced, which is significant for the optimized design of BESS.
ELECTROCHIMICA ACTA
(2021)
Article
Energy & Fuels
Nicolas T. D. Fernandes, Anderson Rocha, Danilo Brandao, Braz C. Filho
Summary: Despite extensive coverage in the literature on the development of battery chargers control strategies, there remains a gap in comparing these strategies. This work categorizes charger control strategies into Adapted SoC strategies, related to overstress management, and SoH strategies, related to wear-out management. The methodology involves comparing battery lifetime, charger, and photovoltaic plant models, with simulations using real measure data from a solar power plant and a battery model provided by MathWorks(R).
Article
Computer Science, Information Systems
Emon Chatterji, Kate Anderson, Morgan D. Bazilian
Summary: Resilience of power systems is a key issue globally, with a need to consider resilience at both bulk supply and customer levels. The study demonstrates how a conceptual framework can be utilized to balance system costs and resilience dimensions, such as the duration, depth, and frequency of service outages. By developing a planning model, the study shows how a comprehensive resilience metric can be optimized at a household level.
Article
Energy & Fuels
Pablo Duran Gomez, Fernando Echevarria Camarero, Ana Ogando-Martinez, Pablo Carrasco Ortega
Summary: The decreasing costs of solar photovoltaic (PV) technology have led to an exponential growth in the use of PV self-consumption systems. This development has encouraged the consideration of battery energy storage systems (BESS) as a potential means of achieving even more independence from the fluctuating grid electricity prices. As PV technology and energy storage costs continue to decline, both technologies will likely play an increasingly important role in the renewable energy sector.
Article
Thermodynamics
Joao Graca Gomes, Juan Jiang, Cheng Tung Chong, Joao Telhada, Xu Zhang, Sergio Sammarchi, Shuyang Wang, Yu Lin, Jialong Li
Summary: The coupling of electrical batteries with variable renewable power generation can increase the production flexibility and revenue of power plant operators. This study focuses on developing an optimization model to manage the operational revenue of a renewable power unit comprising a wind farm, solar photovoltaic (PV) power plant, and electrical battery. The study analyzes various scenarios and case studies to assess the value of storage for revenue maximization.
Article
Energy & Fuels
Abdelrahman O. Ali, Ahmed M. Hamed, Mohamed M. Abdelsalam, Mohamed Nabil Sabry, Mohamed R. Elmarghany
Summary: The study investigates a grid-connected hybrid power system with an optimal EMS algorithm, which effectively manages energy production, storage, and reduces grid consumption.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Construction & Building Technology
Altti Merilainen, Jan-Henri Montonen, Antti Kosonen, Tuomo Lindh, Jero Ahola
Summary: This study investigates the conversion of an oil-heated townhouse into a carbon-neutral one and analyzes five different energy efficiency alternatives. It aims to cover the electricity demand of these alternatives cost-effectively using solar photovoltaics and a battery energy storage system. The results show that a partially dimensioned ground source heat pump along with a solar PV system provides the lowest life cycle cost, and the battery energy storage system becomes profitable at 2022 electricity prices.
ENERGY AND BUILDINGS
(2023)
Article
Energy & Fuels
Anisa Emrani, Asmae Berrada, Ameur Arechkik, Mohamed Bakhouya
Summary: This study investigates the optimal design and operation of a new energy storage system called gravity energy storage (GES) integrated with large-scale renewable energy plants. The results show that the hybrid PV-wind-GES system is the best option in terms of reliability and economic benefits.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Fabian Meishner, Cem Unlubayir, Dirk Uwe Sauer
Summary: Wayside energy recovery systems (WERS) can increase energy efficiency in DC railway grids. Our work presents a novel concept for a direct grid-coupled, uncontrolled WERS based on a commercial lithium-ion-titanate-oxide (LTO) cell. Field measurements on two vehicles support the investigations.
Article
Energy & Fuels
Felix Hildenbrand, Dominik Ditscheid, Elias Barbers, Dirk Uwe Sauer
Summary: The anode overhang has a significant influence on the ageing trajectory of lithium-ion batteries. It affects the cell balancing by transferring active lithium between the anode overhang and the active anode. This study demonstrates that the anode overhang also influences the open-circuit voltage, leading to a persistent rise.
Article
Chemistry, Physical
Hendrik Pegel, Dominik Wycisk, Alexander Scheible, Luca Tendera, Arnulf Latz, Dirk Uwe Sauer
Summary: Various automobile manufacturers are using large-format cylindrical lithium-ion cells with innovative tab design for future vehicles. This study focuses on a cylindrical lithium-ion cell with a novel full-tab design and advanced cathode and anode materials for automotive high-performance applications. The internal heat path of the enhanced tab design is accurately modeled and validated, and the spatially-resolved physico-chemical model is extensively validated with experimental data. The validated model is used to investigate optimal fast-charging times and thermal management strategies for large-format cylindrical cells.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Alexander Reiter, Susanne Lehner, Oliver Bohlen, Dirk Uwe Sauer
Summary: In recent years, digital twins for large-scale and investment-intensive Li-ion battery systems in marine and stationary applications have gained increasing interest. Considering electrical cell-to-cell variations (CtCVs) within the battery model of such a digital twin offers advantages in model-based optimization and predictive maintenance. However, existing approaches for the characterization and modeling of CtCVs are not suitable for large-scale systems. This paper presents a holistic tool chain consisting of a non-destructive method for in-situ determination of resistance and capacity distributions, parameterization of a multi-cell battery model, and simplification through multivariate statistical analysis.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Lucas Koltermann, Karl Konstantin Drenker, Mauricio Eduardo Celi Cortes, Kevin Jacque, Jan Figgener, Sebastian Zurmuehlen, Dirk Uwe Sauer
Summary: Large-scale battery energy storage systems (BESS) are already important in ancillary service markets worldwide, with batteries being suitable for applications with fast response times. However, the overall system response time of current BESS for future grid services has not been extensively studied. Measurements of a 6 MW BESS's inverters show that the response times can meet current standards even with older hardware, but hardware upgrades may be necessary for even faster future grid services.
JOURNAL OF ENERGY STORAGE
(2023)
Correction
Chemistry, Physical
Logan Ward, Susan Barbinec, Eric J. Dufek, David A. Howey, Venkatasubramanian Viswanathan, Muratahan Aykol, David A. C. Beck, Benjamin Blaiszik, Bor-Rong Chen, George Crabtree, Simon Clark, Valerio De Angelis, Philipp Dechent, Matthieu Dubarry, Erica E. Eggleton, Donal P. Finegan, Ian Foster, Chirranjeevi Balaji Gopal, Patrick K. Herring, Victor W. Hu, Noah H. Paulson, Yuliya Preger, Dirk Uwe-Sauer, Kandler Smith, Seth W. Snyder, Shashank Sripad, Tanvir R. Tanim, Linnette Teo
Article
Chemistry, Physical
Zhongbao Wei, Xiaofeng Yang, Yang Li, Hongwen He, Weihan Li, Dirk Uwe Sauer
Summary: This paper proposes a machine learning-based fast charging strategy for lithium-ion batteries. By using a reduced-order electrochemical-thermal model in the cloud, the soft actor-critic deep reinforcement learning algorithm is exploited to train the strategy. Hardware-in-Loop tests and experiments show that the proposed strategy effectively mitigates risks and improves the safety and longevity of batteries during fast charging. Compared to the commonly-used empirical protocol, the proposed approach extends the battery cycle life by about 75%.
ENERGY STORAGE MATERIALS
(2023)
Article
Energy & Fuels
Hubert Maximilian Sistig, Dirk Uwe Sauer
Summary: Driven by global and local environmental concerns, public transport operators are transitioning to battery-powered electric buses. The total cost of ownership is the most crucial factor in choosing the electric bus concept. This paper analyzes the relationship between electrification and operational planning, focusing on vehicle scheduling and crew scheduling.
Article
Energy & Fuels
Alexander Epp, Sunny Rai, Finn van Ginneken, Andreas Varchmin, Juergen Koehler, Dirk Uwe Sauer
Summary: This article proposes a methodology for optimizing cooling plate topologies in the concept phase of battery system development, using a lumped-mass modeling approach and parameter preselection. It enables quick and efficient evaluation of different liquid cooling plate designs.
Article
Energy & Fuels
Philipp Dechent, Elias Barbers, Alexander Epp, Dominik Joest, Weihan Li, Dirk Uwe Sauer, Susanne Lehner
Summary: This paper presents a detailed correlation index of health indicators for lithium-ion batteries, which is important for cell selection and reducing cell-to-cell spread. The health indicators considered include impedance measurements at different pulse lengths, capacity values at different discharge procedures and checkups, weight, and initial voltage. The study is based on four different aging datasets, including variations in cell chemistry (NMC, LFP, NCA), cell type (round, prismatic), as well as size and designated application (consumer, automotive). A publicly available dataset is included for easy replication of the results.
Article
Electrochemistry
Katharina Lilith Quade, Dominik Joest, Dirk Uwe Sauer, Weihan Li
Summary: An accurate estimation of the residual energy, State of Energy (SoE), is crucial for battery diagnostics in electric vehicles. Existing literature lacks in-depth analysis and comparison of SoE estimation methods. This work provides a comprehensive understanding of SoE by discussing various definitions and estimation approaches. Two physically feasible definitions are proposed, and the practical challenges of SoE estimation are critically analyzed. Experimental evaluation highlights the underestimation of residual energy by the State of Charge, emphasizing the importance of accurate SoE estimation.
BATTERIES & SUPERCAPS
(2023)
Article
Energy & Fuels
Valentin Steininger, Peter Huesson, Katharina Rumpf, Dirk Uwe Sauer
Summary: This study aims to generate virtual customer driving data of mild-hybrid electric vehicles using automotive simulation models and stochastic customer driving profiles, in order to establish a simulation database for model training purposes and conduct lifetime simulations for new vehicles in the market. Mapping algorithms ensure a realistic representation of individual customer driving behavior. The results show significant differences in aging implications due to individual driving behavior and environmental conditions, with Asian customers exhibiting about 33% higher aging rate per driven kilometer compared to European customers during a 10-year simulation.
Article
Energy & Fuels
Sebastian Klick, Gereon Stahl, Dirk Uwe Sauer
Summary: This paper investigates the influence of electrolyte volume on the degradation of lithium-ion batteries and finds that cells with higher amounts of electrolyte degrade substantially slower. Based on electrical tests, a theory explaining the volume-dependent rise of resistance and capacity decay is proposed.
Article
Electrochemistry
Lucas Koltermann, Kevin Jacque, Jan Figgener, Sebastian Zurmuehlen, Dirk Uwe Sauer
Summary: Large-scale battery storage systems have become popular for grid services, leading to increased competition in the market. An intelligent energy management system (EMS) is necessary for these systems, including a power distribution algorithm (SPDA) to control battery units. Field tests on a 6 MW/7.5 MWh system validated the SPDA's ability to exploit individual technological strengths and reduce cyclic aging by shifting energy throughput.
BATTERIES & SUPERCAPS
(2023)
Article
Electrochemistry
Hendrik Pegel, Stefan Schaeffler, Andreas Jossen, Dirk Uwe Sauer
Summary: This study extensively characterizes the thermal runaway and thermal propagation characteristics of large-format tabless cylindrical cells with aluminum housing and laser welded endcaps. The results provide insights into the challenges and safety measures associated with the use of aluminum housing in these cells.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
