Article
Energy & Fuels
Yijie Zhang, Qimeng Xue, Diju Gao, Weifeng Shi, Wanneng Yu
Summary: Compared with ground power systems, the intermittent and random fluctuation of ship load power demand poses challenges to the energy management system of ship power systems. To address this issue, a hybrid energy storage system and a two-level model predictive control strategy are proposed to optimize fuel economy and power distribution.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Javier Tobajas, Felix Garcia-Torres, Pedro Roncero-Sanchez, Javier Vazquez, Ladjel Bellatreche, Emilio Nieto
Summary: This study focuses on the development of a resilience-oriented optimization for microgrids with hybrid Energy Storage System (ESS), validated through numerical simulations. The research aims to improve the autonomy of the microgrid and achieve a rapid transition response.
Article
Engineering, Marine
Cheng Liu, Ting Sun, Qizhi Hu
Summary: This paper presents a novel synchronization controller based on model predictive control (MPC) for dynamic positioning (DP) ships to achieve underway replenishment. The controller ensures synchronization of position, orientation, and velocities, handles control input constraints, improves computational efficiency, and stability by incorporating a terminal cost function from the Lyapunov equation. Extensive simulations demonstrate the effectiveness and advantages of the proposed control design.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Ali Haseltalab, Faisal Wani, Rudy R. Negenborn
Summary: This paper proposes a multi-level approach for hybrid power generation control in the shipping industry, modeling the on-board power system and utilizing Model Predictive Control to consider the impact of DC current on DC voltage control. The results of the study suggest that this approach may improve power generation and stability control for constant power loaded microgrids.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Automation & Control Systems
Xiang Tian, Yingfeng Cai, Xiaodong Sun, Zhen Zhu, Yiqiang Xu
Summary: This study proposes a model predictive control method with an estimation of distribution algorithm to optimize the energy flow of plug-in hybrid electric buses (PHEBs). The short-term velocity prediction is achieved using a Markov chain model with online updates, and the energy-flow control problem is formulated as a discrete-time nonlinear optimization problem. The EDA algorithm is incorporated into the MPC-based control framework to efficiently obtain an optimal solution.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Marine
Antti Ritari, Kirsi Spoof-Tuomi, Janne Huotari, Seppo Niemi, Kari Tammi
Summary: This paper evaluates the impact of large-capacity electrical energy storage on optimal sailing routes, speeds, fuel choice, and emission abatement technology selection. It finds that zero-emission legs powered by batteries are feasible, but slower speeds on these legs may lead to increased greenhouse gas emissions over the entire voyage.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Review
Energy & Fuels
Marcin Kolodziejski, Iwona Michalska-Pozoga
Summary: The shipping industry is undergoing a technology transition to increase the use of carbon-neutral fuels. Vessels are being ordered with alternative fuel propulsion, and the future fuel market will be more diverse. Operating ships with sustainable electrical energy through integrating local renewables and battery energy storage systems is a promising means to meet decarbonisation requirements.
Article
Engineering, Electrical & Electronic
Chao Jia, Junwei Cui, Wei Qiao, Liyan Qu
Summary: This article proposes a new model predictive control (MPC) strategy for the energy management of a battery-supercapacitor (SC) hybrid energy storage system (HESS) for electric vehicle (EV) applications. The linear parameter-varying (LPV) models of the HESS are developed, offering higher modeling and prediction accuracy compared to conventional linear time invariant (LTI) models. The real-time LPV-MPC strategy optimally allocates the load current of the HESS between battery and SC to achieve the goals of minimizing power loss, mitigating battery degradation, and regulating the SOC of the SC.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Review
Energy & Fuels
Xueqin Lu, Siwei Li, XiangHuan He, Chengzhi Xie, Songjie He, Yuzhe Xu, Jian Fang, Min Zhang, Xingwu Yang
Summary: This paper comprehensively summarizes the advantages and applicable scenarios of hybrid electric vehicle energy management strategy based on model predictive control. The specific application and actual performance of this strategy in different systems are analyzed. The research aims to provide guidance and design ideas for researchers and promote the development of energy management strategies.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Kyaw Hein, Yan Xu, Gary Wilson, Amit K. Gupta
Summary: The research focuses on the coordination of AES and HESS for optimal voyage planning and multi-objective energy management to optimize vessel route, operation cost, emission, and ESS degradation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Yongpeng Shen, Yuanfeng Li, Dongqi Liu, Yanfeng Wang, Jianbin Sun, Songnan Sun
Summary: This paper proposes an energy management strategy based on model predictive control to improve the performance of the energy storage system in electric vehicles. The strategy aims to stabilize the DC bus voltage and improve system efficiency as optimization goals. An enumeration algorithm is used to solve the optimization function. Experimental results show that the proposed energy management strategy enhances overall instantaneous power and prevents battery overload. Compared to a single battery storage system, the proposed strategy reduces the maximum amplitude of battery current in the hybrid energy storage system by 40.81% and reduces overall system energy loss by 24.13%.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Xibeng Zhang, Benfei Wang, Don Gamage, Abhisek Ukil
Summary: This paper proposes a hybrid control method utilizing both MPC and ILC for a hybrid energy storage system in an islanded microgrid with PV generation. The method is effective in handling sudden changes in power demands and improving system performance through algorithm enhancements and controller designs.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Yingbing Luo, Sidun Fang, Tao Niu, Ruijin Liao
Summary: This study proposes a two-part dynamic power management method for all-electric ships (AESs), including a novel multi-scenario propulsion power model and a three-layer dynamic allocation strategy based on feedforward control. Three case studies are conducted to verify its effectiveness. The proposed method has three advantages: accounting for power fluctuations brought by floating conditions, better sharing of power demand, and real-time applicability.
IET ELECTRIC POWER APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Omer Berkehan Inal, Jean-Frederic Charpentier, Cengiz Deniz
Summary: Increasing environmental concerns are driving the shipping industry to take strict measures to deal with greenhouse gas emissions. The use of electricity as the main energy vector is one of the ways to improve the shipping propulsion system's efficiency. The study suggests that electrical components and architectural design should be elaborated according to operational and architectural characteristics for different ship types. Furthermore, new regulations on emission mitigation will accelerate the transition to hybrid power, which is an important option for achieving the ultimate goal of zero-carbon shipping.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Maro Jelic, Vedran Mrzljak, Gojmir Radica, Nikola Racic
Summary: The maritime industry is increasingly aware of the global environmental impact of ships and is gradually reducing emissions. However, new concepts like environmental-friendly fuels, hybrid propulsion, and all-electric propulsion have advantages and disadvantages in terms of adjustment time, implementation cost, and energy storage capacity.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2021)
Article
Energy & Fuels
Jun Hou, Ziyou Song
Article
Thermodynamics
Ziyou Song, Jun Hou, Xuefeng Li, Xiaogang Wu, Xiaosong Hu, Heath Hofmann, Jing Sun
Article
Engineering, Electrical & Electronic
Ziyou Song, Hao Wang, Jun Hou, Heath F. Hofmann, Jing Sun
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2020)
Article
Engineering, Electrical & Electronic
Haojie Zhu, Ziyou Song, Jun Hou, Heath F. Hofmann, Jing Sun
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2020)
Article
Automation & Control Systems
Jun Hou, Ziyou Song, Heath F. Hofmann, Jing Sun
Summary: This article investigates a battery/flywheel hybrid energy storage system to mitigate load fluctuations in a shipboard microgrid. Two control strategies are proposed and case studies in various sea conditions demonstrate the superior performance of the new control strategies in power fluctuation mitigation and HESS power-loss reduction. A comparison between the two approaches quantifies their performances, analyzes their advantages and disadvantages, and highlights the most suitable scenarios for each strategy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Bin Xu, Jun Hou, Junzhe Shi, Huayi Li, Dhruvang Rathod, Zhe Wang, Zoran Filipi
Summary: This study aims to reduce the learning iterations of Q-learning in HEV application utilizing warm-start methods, resulting in significant improvements compared to traditional cold-start methods.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Energy & Fuels
Niankai Yang, Ziyou Song, Heath Hofmann, Jing Sun
Summary: This paper investigates the estimation of State of Health (SOH) under partial discharge for lithium-ion batteries. The proposed approach utilizes convolutional neural networks (CNNs) to extract indicators for both SOH and changes in SOH, and the random forest algorithm is used to produce the final SOH estimate. The proposed approach demonstrates improved estimation accuracy and robustness compared to other methods.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Niankai Yang, Ziyou Song, Mohammad Reza Amini, Heath Hofmann
Summary: This paper investigates ISC detection of parallel-connected battery cells by establishing an electro-thermal model and designing a convolutional neural network to estimate ISC resistance, effectively identifying faulty batteries and guiding replacement.
AUTOMOTIVE INNOVATION
(2022)
Article
Thermodynamics
Yue Wu, Zhiwu Huang, Heath Hofmann, Yongjie Liu, Jiahao Huang, Xiaosong Hu, Jun Peng, Ziyou Song
Summary: This paper proposes a hierarchical model predictive control framework for electric vehicles to optimize power demand and energy management, improving energy efficiency and driving safety.
Article
Thermodynamics
Meng Wei, Palani Balaya, Min Ye, Ziyou Song
Summary: This paper investigates the accurate prediction and management of remaining useful life (RUL) for sodium-ion batteries, using incremental capacity analysis to study oxidation process and aging mechanisms, and Gaussian process regression for precise RUL prediction, as well as principal component analysis to obtain a syncretic health indicator.
Article
Thermodynamics
Fei Ju, Nikolce Murgovski, Weichao Zhuang, Xiaosong Hu, Ziyou Song, Liangmo Wang
Summary: This paper addresses the energy management problem of a power-split hybrid electric vehicle (HEV) with planetary gear sets. A mixed-integer global optimal control problem is formulated, and convex modeling is presented to reformulate the problem as a two-step program. The alternating direction method of multipliers (ADMM) algorithm is employed to optimize the engine switching and battery power decisions. Simulation results show significant fuel savings and computational efficiency compared to heuristic and dynamic programming methods. An ADMM-MPC method is also developed for real-time control with promising results.
Article
Engineering, Electrical & Electronic
Yongjun Yan, Nan Li, Jinlong Hong, Bingzhao Gao, Jia Zhang, Hong Chen, Jing Sun, Ziyou Song
Summary: This study proposes an eco-coasting strategy that calculates the optimal timing and duration of coasting maneuvers using road information preview. By evaluating different coasting mechanisms, it is found that the engine start/stop method performs better in terms of fuel consumption and travel time. The online performance of the eco-coasting strategy is evaluated using Mixed Integer Model Predictive Control (MIMPC), and simulation results show that it achieves near-optimal performance and outperforms the rule-based method.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Automation & Control Systems
Niankai Yang, Chao Shen, Ziyou Song, Matthew Johnson-Roberson, Jing Sun
Summary: This work proposes a robust energy-optimal control method for achieving 3-D path following for autonomous underwater vehicles in environments with ocean currents. The method optimizes setpoints considering uncertainty and uses a line-of-sight-based guidance law for calculating yaw angle setpoints. Model predictive controllers are designed for controlling horizontal and vertical vehicle motion, with simulation confirming the performance of the proposed approach.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Ziyou Song, Hyeongjun Park, Fanny Pinto Delgado, Hao Wang, Zhaojian Li, Heath F. Hofmann, Jing Sun, Jun Hou
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2020)
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.
