Article
Energy & Fuels
Peng Zheng, Zheng Fang, Hai Li, Yajia Pan, Dabing Luo, Zutao Zhang
Summary: This study proposes a hybrid energy management approach to increase the use of renewable energy in electric chargers for electric vehicles. Wind turbines and solar power generating modules are used to provide energy, and optimization algorithms are employed to determine the optimal energy cost and grid dependence. The results show that the system can balance energy cost and grid dependence, with a majority of the energy coming from renewable sources.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Thermodynamics
Seyed Farhad Zandrazavi, Cindy Paola Guzman, Alejandra Tabares Pozos, Jairo Quiros-Tortos, John Fredy Franco
Summary: A stochastic multi objective optimization model is proposed for grid-connected unbalanced microgrids to minimize total operational cost and voltage deviation. The epsilon-constraint method and fuzzy satisfying approach are used to solve the multi-objective optimization problem, considering uncertainties through the roulette wheel mechanism for scenario generation.
Article
Thermodynamics
Ashfaq Ahmad, Jamil Yusuf Khan
Summary: This article investigates the optimal sizing and real-time control of electrical and thermal distributed energy resources (DERs) in smart buildings. It proposes a comprehensive system architecture and utilizes planning optimization problems and one-slot-look-ahead (OSLA) optimization technique to optimize the sizing and control of DERs. The proposed approach considers various costs and provides customer-oriented modeling, making it practical and applicable in general scenarios. Simulation results show significant cost reduction and accurate load task execution.
Article
Thermodynamics
Yi He, Su Guo, Jianxu Zhou, Guotao Song, Aynur Kurban, Haowei Wang
Summary: This paper proposes a hybrid electrical thermal energy storage system to mitigate the intermittency of renewable energy. The optimal sizing and operation of the system are achieved through a multi-stage framework that considers the minimization of net load and levelized cost of storage. The study shows that the hybrid system is more reliable and cost-effective compared to single thermal energy storage or single battery systems. The multi-stage framework outperforms rule-based operation strategies, and demand response can reduce the investment cost of the system effectively.
Article
Energy & Fuels
Nzube Ntube, Haiyu Li
Summary: This paper highlights the importance of deploying renewable local generation sources at home to reduce emissions in residential homes. In addition, it discusses the increasing adoption of residential PV systems due to the decreasing installation costs. The study formulates a stochastic optimisation problem to determine the optimal size of an energy storage system and investigates the benefits of considering uncertainty in the sizing optimisation problem formulation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Joao Faria, Carlos Marques, Jose Pombo, Silvio Mariano, Maria do Rosario Calado
Summary: This paper proposes a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to determine the optimal sizing of production and storage units within renewable energy communities. The effectiveness of this approach is evaluated through case studies focusing on different energy management strategies, demonstrating its ability to address conflicting objectives and ensure economic viability and flexibility.
Article
Computer Science, Information Systems
Xuezhou Wang, Udai Shipurkar, Ali Haseltalab, Henk Polinder, Frans Claeys, Rudy R. Negenborn
Summary: This paper uses a nested double-layer optimization architecture to study the sizing and energy management optimization of a hybrid offshore support vessel, considering the complexity brought by different power sources and the impact of operational profiles on hybrid design.
Article
Energy & Fuels
Ali Asaad, Abdelfatah Ali, Karar Mahmoud, Mostafa F. F. Shaaban, Matti Lehtonen, Ahmed M. M. Kassem, Mohamed Ebeed
Summary: This paper proposes an optimal planning approach for allocating EV charging stations with controllable charging and hybrid RERs within multi-microgrids. The charging strategy in the proposed planning approach contributes to improving power quality and overall system cost, reducing voltage deviation, energy not supplied, and total cost by 26.03%, 49.57%, and 70.45% respectively.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Ahmet Gullu, Seda Goktepe Korpeoglu, Elif Sila Selek Kilicarslan
Summary: Different mathematical optimization techniques, namely sequential quadratic programming, gradient-based method, and Lagrange multiplier method, are employed to improve the seismic performance and energy dissipative characteristics of energy dissipative steel cushion. Results showed that the gradient-based method requires fewer function evaluations to converge, while the Lagrange multiplier method with a Hessian produces more accurate results. Geometric dimension ratios for the optimal sizing of steel cushions are provided based on optimization studies.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Operations Research & Management Science
Ghimar Merhy, Ahmed Nait-Sidi-Moh, Nazih Moubayed
Summary: This study presents an energy strategy based on a multi-objective optimization algorithm for controlling energy flows between electric vehicles and the electricity grid, focusing on optimizing the charging mode of vehicles.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Energy & Fuels
Md. Arif Hossain, Ashik Ahmed, Shafiqur Rahman Tito, Razzaqul Ahshan, Taiyeb Hasan Sakib, Sarvar Hussain Nengroo
Summary: This study proposes a hybrid optimization method to assess the optimal energy mix of wind, photovoltaic, and battery for a hybrid microgrid system. The method combines Non-dominant Sorting Genetic Algorithm II and Grey Wolf Optimizer to minimize the total energy cost and loss of power supply probability. Comparative analysis shows that the proposed method outperforms other optimization algorithms in terms of convergence speed, reaching global minima, lower mean (for minimization objective), and higher standard deviation. The analysis also reveals that relaxing the loss of power supply probability can lead to an additional cost reduction.
Article
Energy & Fuels
Jing Liu, Hongyu Wang, Yanping Du, Yilan Lu, Zhenghang Wang
Summary: The increase of electric vehicles (EVs) can lead to a reduction in carbon emissions and dependence on fossil energy. However, uncoordinated charging can cause peak load issues and load imbalance, posing challenges to system reliability. This paper proposes a multi-objective optimal peak load shaving strategy that aims to achieve the best peak load shaving effect with minimal electricity cost through coordinated scheduling of EVs and battery energy storage systems (BESS). The strategy considers various factors such as load balance constraint, charging/discharging power limits, EV and BESS capacity limits, vehicles to grid (V2G), time-of-use (TOU) price, and EVs' driving behavior. The results show significant improvements in load fluctuation level and electricity cost reduction.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Mohamed Y. Nassar, Mohamed L. Shaltout, Hesham A. Hegazi
Summary: This study develops multi-objective optimum energy management strategies for pre-and post-transmission parallel hybrid electric vehicles. The strategies aim to improve fuel economy, electric system efficiency, battery performance, and life. Multi-objective genetic algorithm is used to solve the energy management problems and generate optimum control inputs. Vehicle dynamics and drivetrain models are integrated with the strategies in a simulation environment. Results show significant improvement in battery performance and varied effects on fuel consumption. The pre-transmission drivetrain configuration shows better battery performance than the post-transmission configuration.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Energy & Fuels
Saeed Zeynali, Naghi Rostami, Ali Ahmadian, Ali Elkamel
Summary: This study investigates the cooperation between a compressed air energy storage (CAES) and a battery energy storage system (BESS) in energy hubs to optimize residential thermal and electrical systems for cost and emission reduction. The proposed formulation includes various renewable energy units and demand response programs, with uncertainties handled by a computationally effective robust method.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Thermodynamics
Poonam Singh, Manjaree Pandit, Laxmi Srivastava
Summary: In this study, an optimal sizing model is developed for a hybrid micro-grid system (HMGS) that includes solar photovoltaic, wind turbine, diesel generator, and battery. A tri-objective formulation considering techno-socio-economic factors is proposed to find the optimal size and configuration. Dynamic domain search employing a hybrid intelligent computational technique is used to improve the search efficiency. The best solution is identified using a fuzzy attainment module. The optimal sizing is analyzed considering the effect of selected optimization objectives, and multiple choices are offered to the designer based on preferences. The results show that a system with solar PV capacity of 78.44 kW, wind turbine of 95 kW, and a battery of 2 kW is the best option.
Article
Energy & Fuels
Adeniyi Kehinde Onaolapo, Rudiren Pillay Carpanen, David George Dorrell, Evans Eshiemogie Ojo
Summary: The reliability of the power supply depends on the reliability of the grid structure, which is prone to faults due to varying weather events. With the concern of increasing and severe weather events caused by climate change, it is important to explore predictive models for electricity outages caused by weather factors. This study presents a model using artificial neural networks to predict electricity outages caused by severe weather conditions and demonstrates their robustness compared to conventional models.
Article
Engineering, Electrical & Electronic
Da Li, Peng Liu, Zhaosheng Zhang, Lei Zhang, Junjun Deng, Zhenpo Wang, David G. Dorrell, Weihan Li, Dirk Uwe Sauer
Summary: In this article, an AHG-based thermal runaway prognosis model is proposed by combining LSTM and CNN, which accurately predicts battery temperature. Principal component analysis is used to optimize the model input factors and reduce computing time. The verification results show that the proposed model achieves accurate battery temperature prediction and thermal runaway prognosis.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Engineering, Mechanical
Cong Wang, Zhenpo Wang, Lei Zhang, Huilong Yu, Dongpu Cao
Summary: This paper proposes a post-impact motion planning and stability control method for autonomous vehicles to reduce traffic accidents and fatalities.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2022)
Article
Energy & Fuels
Mathew Habyarimana, David George Dorrell, Remmy Musumpuka
Summary: This paper investigates the compensation requirements and application of parallel capacitors in large induction motors during starting. It shows that using parallel capacitors can significantly reduce the starting current and proposes the use of series filters to prevent harmonic current.
Article
Engineering, Electrical & Electronic
Zhenpo Wang, Chunbao Song, Lei Zhang, Yang Zhao, Peng Liu, David G. Dorrell
Summary: In this article, a data-driven method based on massive real-world EV operating data is proposed for diagnosing battery charging capacity abnormalities. By utilizing multiple input parameters and a tree-based prediction model for training, along with a statistical method for abnormality diagnosis, the proposed method demonstrates the highest prediction accuracy.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Automation & Control Systems
Xiaolin Ding, Zhenpo Wang, Lei Zhang
Summary: This article proposes an enabling event-triggered sideslip angle estimator using a low-cost GPS and IMU, which accurately estimates the vehicle sideslip angle and velocity based on kinematic information. The proposed scheme demonstrates better estimation accuracy, reliability, and real-time performance compared to other typical estimators through hardware-in-loop and field tests.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Review
Thermodynamics
Weipeng Zhan, Zhenpo Wang, Lei Zhang, Peng Liu, Dingsong Cui, David G. Dorrell
Summary: This paper provides a comprehensive literature review on the siting, sizing, and operation mechanisms of battery swapping stations, highlighting the synergistic optimization of siting and sizing, collaborative scheduling with microgrids, and routing of EVs. Major challenges and future research directions for BSSs are also pointed out.
Article
Energy & Fuels
Lei Zhang, Lvwei Huang, Zhaosheng Zhang, Zhenpo Wang, David D. Dorrell
Summary: This paper explores the degradation characteristics of lithium-ion battery cells with NCA electrode during cyclic overcharging and proposes non-destructive methods to detect overcharging degradation failure. Experimental results show that battery capacity drops significantly with increasing overcharge depth and number of cycles, especially during the first three cycles and when the charging termination voltage is set to 5V. At the same time, the cell's overcharge tolerance decreases with cyclic overcharging. The combination of electrochemical impedance spectroscopy, incremental capacity analysis, and differential voltage analysis is used to diagnose cell degradation. Three main degradation modes are identified and quantified by analyzing characteristic parameters such as internal resistance and changes in peak, valley, and curve position of incremental capacity curves. It is concluded that loss of lithium inventory and loss of active materials are the dominant degradation modes during cyclic overcharging. Additionally, the sharp increase of the third peak on incremental capacity curves is identified as a unique feature of overcharging degradation, which can be used to diagnose cyclic overcharging-induced degradation in batteries with NCA cathode.
Article
Automation & Control Systems
Anuoluwapo O. Aluko, Remmy Musumpuka, David G. Dorrell
Summary: This article proposes a cyberattack-resilient scheme for secondary frequency control in a stand-alone microgrid system. The scheme accurately estimates the system states and maintains frequency stability under different cyberattack scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Chengqi She, Lei Zhang, Zhenpo Wang, Fengchun Sun, Peng Liu, Chunbao Song
Summary: This article proposes an enabling SOH estimation scheme based on the ICA method for real-world EVs. The effectiveness of the proposed method is verified using the datasets collected from both well-controlled laboratory tests and daily operating EVs. The results show that the proposed method can realize an accurate pack-level SOH estimation both for laboratory battery packs and real-world EVs.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Energy & Fuels
Christopher Hecht, Jan Figgener, Xiaohui Li, Lei Zhang, Dirk Uwe Sauer
Summary: Electric vehicles are becoming dominant in the global automobile market due to their environmental friendliness. This paper creates standard load profiles for different power levels, station sizes, and operating environments based on a large-scale empirical dataset. The study reveals that the average power per charge point increases with rated station power, especially for power above 100 kW, and decreases with the number of charge points per station for AC chargers. It also shows how the shape of the power curve largely depends on the station environment, with urban settings experiencing the highest average power of 0.71 kW on average, resulting in an annual energy sale of 6.2 MWh. These findings suggest that the rated grid capacity can be lower than the sum of the rated power of each charge point.
Article
Automation & Control Systems
Adeniyi K. Onaolapo, Rudiren Pillay Carpanen, David G. Dorrell, Evans E. Ojo
Summary: An increase in weather events can lead to more grid faults and a decrease in electricity supply reliability. This article proposes a multiple-constraints event-driven outage model using the CONN algorithm to develop a better performance model for outage forecasting. The CONN algorithm successfully resolves the challenge of obtaining large complex weather events and outage data.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Green & Sustainable Science & Technology
Ze Zhao, Lei Zhang, Jianyang Wu, Liang Gu, Shaohua Li
Summary: This paper presents a comprehensive study on the coupled vertical-longitudinal effect in suspension-in-wheel-motor systems (SIWMS), and proposes a viable optimization procedure to improve ride comfort and handling performance.
Review
Energy & Fuels
Namhla Mtukushe, Adeniyi K. Onaolapo, Anuoluwapo Aluko, David G. Dorrell
Summary: With the increasing use of cyber-physical systems (CPSs) in different sectors, there is a critical need for robust cybersecurity mechanisms to protect these systems from cyberattacks. Effective detection and mitigation methods in CPSs require a comprehensive security strategy that considers the unique characteristics of CPSs and utilizes techniques such as intrusion detection systems, firewalls, and encryption. By implementing these methods, CPSs can be better protected against cyberattacks, ensuring the safety and reliability of critical infrastructure and other vital systems.
Article
Chemistry, Multidisciplinary
Ze-Yu Chen, Rui Xiong, Bo Zhang, Rui-Xin Yang, Wei-Xiang Shen, Xiao-Guang Yang, Wan-Zhou Sun, Dai-Wei Yu, Feng-Chun Sun
Summary: This study reports the impact of different ESC durations on battery performance and divides the ESC process into four stages. It reveals a transition from benign to malignant when the ESC duration is close to a critical time. The establishment of the critical time surface and the disclosure of center temperatures of the critical time and battery failure pave the way for fault diagnosis and controlled benign ESC.
CELL REPORTS PHYSICAL SCIENCE
(2022)
