Article
Energy & Fuels
Hao Su, Donghan Feng, Yun Zhou, Xing Hao, Yin Yi, Kele Li
Summary: In this paper, a novel battery scheduling model is proposed to maximize arbitrage benefits while meeting peak shaving requirements in the presence of uncertain renewable power generation and on-site demand. The model considers uncertainty using a stochastic optimization approach and guarantees a globally optimal solution with computational efficiency. Through case studies and simulations, the convexity and solution stability of the model are verified, and the impact of uncertainty on the optimal battery schedule is demonstrated.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Electrical & Electronic
Jin-Oh Lee, Yun-Su Kim
Summary: This paper proposes a new formulation of battery degradation cost for the optimal scheduling of BESSs, which integrates cycle life curve and auxiliary state of charge to model the degradation cost, resulting in more economical operation of BESSs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Yi Lin, Wei Lin, Wei Wu, Zhenshan Zhu
Summary: This paper proposes a flexibility scheduling method for high-penetration renewable energy power systems that considers flexibility index constraints. The method includes quantifying flexibility resources and demands and developing optimization scheduling strategies for different time scales. Simulation studies show that the proposed strategy enhances system flexibility, reduces operating costs, and decreases wind curtailment rate. It not only considers economic efficiency but also ensures a sufficient margin to cope with the uncertainty of intra-day renewable energy fluctuations.
Article
Green & Sustainable Science & Technology
Jie Ji, Mengxiong Zhou, Renwei Guo, Jiankang Tang, Jiaoyue Su, Hui Huang, Na Sun, Muhammad Shahzad Nazir, Yaodong Wang
Summary: This paper proposes a hybrid energy storage system model adapted to industrial enterprises. The operation of the hybrid system is optimized in different scenarios using a bipolar second-order RC battery model. The model accurately responds to battery characteristics like end voltage, SOC, and ageing mechanism. The system consists of batteries and a supercapacitor, and the paper investigates the system operation cost and battery cycle life. Load prediction technology is used to realize energy scheduling, reducing the frequency of battery charging and discharging. Experimental results show improved accuracy and reduced economic costs.
Article
Energy & Fuels
Oluwaseun Ogunmodede, Kate Anderson, Dylan Cutler, Alexandra Newman
Summary: By utilizing an optimization model, we can minimize costs while recommending an optimal mix of renewable energy, conventional generation, and energy storage technologies, simultaneously optimizing dispatch strategies for cost savings and renewable energy utilization.
Article
Energy & Fuels
Fulin Fan, Ivana Kockar, Han Xu, Jingsi Li
Summary: This paper develops a dynamic optimal power flow (DOPF) scheduling framework to optimize the operation of a grid-scale battery energy storage system (BESS) in order to mitigate limitations on renewable energy generation and balance network demand. The framework integrates all generating units across the network and time horizon, minimizing total generation cost while satisfying constraints and considering the state of charge of the battery.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Marcos Tostado-Veliz, Hany M. Hasanien, Rania A. Turky, Yasser O. Assolami, David Vera, Francisco Jurado
Summary: Energy storage is crucial for decarbonizing the electricity sector, especially in residential installations. Home energy management applications play a vital role in enabling active control of appliances and storage systems to achieve efficient energy utilization. However, the emergence of renewable generators and electric vehicles poses challenges due to uncertainties in residential asset operation. This paper introduces a novel home energy management tool that addresses these uncertainties by using a Lexicographic-Interval formulation and prioritizing the impact of random parameters. A benchmark case study validates the proposed tool and demonstrates its ability to handle different tariffs.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Sajad Karimi, Soongeol Kwon
Summary: This research proposes a mathematical optimization-based approach to comprehensively evaluate and analyze the impact of energy-aware production scheduling, on-site solar power generation, and battery energy storage on energy cost and makespan in manufacturing systems. Numerical experiments show that utilizing all three technologies can significantly reduce energy cost and total cost, with a 36% savings in energy cost and a 15% savings in total cost when considering energy and time-related makespan costs. Sensitivity analysis is also conducted to assess the practical benefits of renewable energy generation and battery energy storage under different capacities.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Nan Yin, Rabeh Abbassi, Houssem Jerbi, Alireza Rezvani, Martin Mueller
Summary: This paper investigates the day-ahead operation of a grid-connected microgrid with distributed generation units and storage systems, and utilizes the theta-modified krill herd approach to provide an efficient solution. The simulation results were validated by comparing with results from well-known optimization algorithms.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Energy & Fuels
Rui Xie, Yilin Wang, Shengqi Zhang, Bin Lin, Qing Chen, Fei Wang, Xiaohe Wang, Yuwei Chen, Bingqing Xia
Summary: This paper proposes a frequency regulation strategy for user-side BESS to address the issue of existing BESS mainly profiting from energy arbitrage strategy rather than frequency regulation strategy. By applying chance-constrained programming, it ensures the profit of BESS from energy arbitrage and fully utilizes the existing BESS to obtain additional profit from frequency regulation. Experimental results demonstrate the advantages of the proposed frequency regulation strategy.
Article
Energy & Fuels
Muhyaddin Rawa, Yusuf Al -Turki, Khaled Sedraoui, Sajjad Dadfar, Mehrdad Khaki
Summary: In order to address worldwide environmental concerns, power system operators and planning entities are seeking new energy sources with lower emissions. Utilities are increasingly choosing renewable energy sources, and microgrids provide an ideal platform for incorporating them. This study presents a seasonal optimization framework for the short-term operation of a microgrid, taking into account energy storage and solar photovoltaic systems, and analyzing the impact of climate factors on resource scheduling.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Green & Sustainable Science & Technology
Zhongjie Guo, Wei Wei, Mohammad Shahidehpour, Laijun Chen, Shengwei Mei
Summary: This paper studies intraday dynamic energy-reserve dispatch following a two-timescale setting, which includes coarse timescale and fine timescale. A stochastic dynamic programming method is proposed to make decisions at the coarse timescale while guaranteeing the robust feasibility of the fast process. The fast-response actions at the fine timescale are updated using a truncated rolling-horizon optimization.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Energy & Fuels
A. Castillejo-Cuberos, J. M. Cardemil, R. Escobar
Summary: The addition of energy storage systems to photovoltaic plants for reliability and flexibility in dispatch is an active research area. Battery degradation is a critical parameter to assess plant performance, and its complexity can introduce uncertainty in assessments. This work explores different plant configurations with batteries and provides insights on simulation time steps, battery degradation rates, and plant design philosophy.
Article
Green & Sustainable Science & Technology
Mengke Lu, Jun Guan, Huahua Wu, Huizhe Chen, Wei Gu, Ye Wu, ChengXiang Ling, Linqiang Zhang
Summary: In this paper, a day-ahead optimal dispatching model for a power system is established by combining wind, photovoltaic, hydropower, thermal, and pumped storage. Various mathematical models and opportunity constraint programming are used to address the output uncertainty of renewable energy sources, improve economic efficiency, reduce start-stop times, and enhance system stability. The model aims to optimize the joint dispatch of different energy sources while considering system economics.
Article
Green & Sustainable Science & Technology
Hunyoung Shin, Ross Baldick
Summary: This paper presents a novel Li-ion battery model based on linear matrix inequalities for optimal control decisions of multiple services in distribution systems. The effectiveness of the model is verified through mathematical analysis and simulations using real-world data.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Multidisciplinary
Adrian Soto, Alberto Berrueta, Ignacio Oficialdegui, Pablo Sanchis, Alfredo Ursua
Summary: This article presents a noninvasive technical analysis of degradation in four lithium-ion batteries used in extreme frigid weather conditions. The batteries were aged during an expedition in the WindSled project, covering over 2500 km on the East Antarctic Plateau using a zero-emission vehicle. The study shows that the batteries experienced a 5% capacity fade and a 30% increase in internal resistance, but no substantial increase in the impedance of the solid electrolyte interface. These results indicate that the batteries can successfully operate at -50 degrees C and can still be used in future expeditions, providing financial and environmental benefits.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Chemistry, Analytical
Diego Hilario Castillo-Martinez, Adolfo Josue Rodriguez-Rodriguez, Adrian Soto, Alberto Berrueta, David Tomas Vargas-Requena, Ignacio R. Matias, Pablo Sanchis, Alfredo Ursua, Wenceslao Eduardo Rodriguez-Rodriguez
Summary: In recent years, there has been an increasing demand for electric vehicles, leading to a rise in the use of rechargeable batteries. Although lithium-ion batteries are commonly used in electric vehicles, once their capacity drops below 80-70%, they can no longer be used in the vehicles but can be repurposed as stationary energy storage systems. This study introduces an embedded system that allows a Nissan LEAF lithium-ion battery to communicate with an Ingecon Sun Storage 1Play inverter for monitoring and control purposes. The feasibility of using automotive lithium-ion battery packs with the inverter without the need for disassembly and rebuilding has been determined through experimental tests. Additionally, this research presents a programming and hardware methodology for developing embedded systems focused on repurposing electric vehicle lithium-ion batteries. A second-life battery pack from a Nissan Leaf, which has been aged under real driving conditions, was successfully integrated into a residential microgrid as an energy storage system.
Article
Energy & Fuels
Adrian Soto, Alberto Berrueta, Miren Mateos, Pablo Sanchis, Alfredo Ursua
Summary: This article experimentally studies the impact of micro-cycles on the loss of performance of lithium-ion batteries. The results show that micro-cycles have a negligible, or even positive effect on battery aging compared to full cycles.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Elisa Braco, Idoia San Martin, Pablo Sanchis, Alfredo Ursua, Daniel-Ioan Stroe
Summary: This article analyzes the importance of 58 health indicators (HIs) for the evaluation of reused Li-ion batteries, and finds the best health indicators and algorithms for accurate estimation of battery life (SOH), based on cycling tests.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Elisa Braco, Idoia San Martin, Pablo Sanchis, Alfredo Ursua
Summary: This study proposes a novel fast characterization method to estimate the capacity and internal resistance of second-life Li-ion batteries during the repurposing stage. The method is validated with satisfactory results and reduces testing time and energy consumption, contributing to the reduction of repurposing procedures and costs.
Article
Automation & Control Systems
David Elizondo, Ernesto L. Barrios, Alfredo Ursua, Pablo Sanchis
Summary: This article proposes an analytical model for accurately estimating the high-frequency winding loss in toroidal inductors, considering the 2-D characteristic of the magnetic field and the geometrical particularities of toroidal windings. The proposed model shows good agreement with finite-element analysis (FEA) and experimental results, while existing analytical methods overestimate the loss by 93% to 226%.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Multidisciplinary
David Elizondo, Ernesto L. Barrios, Inaki Larequi, Alfredo Ursua, Pablo Sanchis
Summary: This paper conducts an exhaustive research on the performance of LLC converter under DCM-ZLS, achieving lossless switching in the primary and secondary sides. By designing a set of parameter boundaries and a comprehensive methodology, the conduction states studied theoretically in the analysis of the LLC converter are verified in the experimental results, and the operation of the test bench under DCM-ZLS is confirmed.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Alberto Berrueta, Javier Sacristan, Jesus Lopez, Jose Luis Rodriguez, Alfredo Ursua, Pablo Sanchis
Summary: This paper investigates the importance of accelerating the transition to renewable energy and proposes a strategy to simulate the inertia response of synchronous generators by connecting a supercapacitor directly to the back-to-back converter DC link, thus replacing conventional power plants. Compared to existing techniques, this strategy allows for a more accurate emulation of synchronous generators.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Alvaro Iribarren, David Elizondo, Ernesto L. Barrios, Harkaitz Ibaiondo, Alain Sanchez-Ruiz, Joseba Arza, Pablo Sanchis, Alfredo Ursua
Summary: This paper presents a dynamic model for simulating pressurized alkaline water electrolyzers, integrating electrochemical, thermodynamic, heat transfer, and gas evolution processes. The model has been validated using experimental data from a commercial alkaline water electrolyzer under real scenarios with power profiles from renewable sources. The results show that the simulated values are consistent with the measured values, indicating the potential of this model in designing efficient green hydrogen production systems.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Alberto Berrueta, Jose J. Astrain, Guillermo Puy, Ismail El Hamzaoui, Alfredo Ursua, Pablo Sanchis, Jesus Villadangos, Francisco Falcone, Antonio Lopez-Martin, Ignacio R. Matias
Summary: This paper introduces the importance of the smart charging station and its monitoring and control system installed at the Public University of Navarre, as well as its crucial role as a key tool in the data infrastructure of a smart city.
PROCEEDINGS OF THE 37TH CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS 2022)
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Idoia San Martin, Elisa Braco, Alvaro Martin, Pablo Sanchis, Alfredo Ursua
Summary: This paper analyzes the technical and economic feasibility of using batteries from electric vehicles for stationary applications. Through experimental validation, the study proves the technical viability of these batteries in applications such as residential microgrids and fast charging stations.
2022 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2022 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Elisa Braco, Idoia San Martin, Pablo Sanchis, Alfredo Ursua
Summary: The reuse of Li-ion batteries from electric vehicles is a promising alternative to recycling, but the technical and economic feasibility of these second-life batteries is still uncertain. This study examines the calendar aging behavior of reused batteries, finding that higher temperatures and state of charge accelerate degradation. The worst case for aging is a combination of 60°C temperature and 66% state of charge. The study also proposes and validates a calendar aging model for these batteries, with high accuracy in predicting capacity fade and resistance increase.
2022 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2022 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)
(2022)
Proceedings Paper
Automation & Control Systems
Alvaro Iribarren, Ernesto L. Barrios, Harkaitz Ibaiondo, Alain Sanchez-Ruiz, Joseba Arza, Pablo Sanchis, Alfredo Ursua
Summary: This paper presents a detailed analysis of a 6-pulse thyristor rectifier for supplying high power electrolyzers, developing a mathematical model and predicting the system's operating point. This model can be used for dimensioning thyristor rectifiers.
2022 IEEE 23RD WORKSHOP ON CONTROL AND MODELING FOR POWER ELECTRONICS (COMPEL 2022)
(2022)
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.