Article
Environmental Studies
Stefano Mingolla, Zhongming Lu
Summary: The study found that FCEVs fueled with hydrogen from renewables and EVs with battery swap stations have lower abatement costs. The choice between the two options depends on the reduction of electricity carbon intensity and the ability to secure an economic and reliable import of hydrogen from renewables. Taxi miles traveled impact the vehicle technology abatement cost ranking. Overall, the study provides insight into sustainable urban taxi transition.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Environmental Sciences
Minxi Wang, Yajie Wang, Lu Chen, Yunqi Yang, Xin Li
Summary: The study shows that the carbon emissions of electric vehicles only account for 37.05% of traditional fuel vehicles, and the rapid growth of electric vehicles has brought significant impact on grid load. Studying the changes in CO2 emissions from energy substitution is significant for formulating the development strategy of the automobile industry and adjusting energy structure policies.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Chemistry, Physical
Olusola Bamisile, Sandra Obiora, Qi Huang, Nasser Yimen, Idriss Abdelkhalikh Idriss, Dongsheng Cai, Mustafa Dagbasi
Summary: This paper provides a detailed analysis of the causes, trends, and solutions to carbon emissions in Africa, investigating the impact of economic development on carbon emissions trends and developing neural network models to predict future CO2 emissions. The use of renewable energy sources and electric vehicles is proposed as viable solutions for reducing carbon emissions on the continent.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Energy & Fuels
Ruchi Gupta, Alejandro Pena-Bello, Kai Nino Streicher, Cattia Roduner, Yamshid Farhat, David Thoni, Martin Kumar Patel, David Parra
Summary: The study highlights the importance of rapid deployment of solar photovoltaics, electric heat pumps, and electric vehicles for decarbonizing the economy. It also emphasizes the challenges faced by the distribution grid infrastructure in integrating these technologies and the need for grid reinforcement to enable decarbonization strategies. The research findings show the varying impact of PV, HP, and EV on the distribution grid network, with different costs for grid reinforcement depending on the urban setting, and the potential for batteries to defer grid reinforcement costs in specific scenarios.
Article
Energy & Fuels
Agata Oltarzewska, Dorota Anna Krawczyk
Summary: Heat pumps are considered an environmentally friendly technology that can contribute to sustainable energy in the future. Research has shown that heat pumps are more beneficial for HVAC systems in Mediterranean-type subtropical climates, with Rome being the most advantageous city in terms of economic and environmental aspects for using heat pumps.
Article
Energy & Fuels
Leo Strobel, Jonas Schlund, Marco Pruckner
Summary: In recent years, electric vehicles have become the primary tool for decarbonization in the transport sector. However, the widespread adoption of electric vehicles also presents new opportunities and challenges for regional and national power systems. This study finds that optimizing the charging of electric vehicles can help avoid national peak loads and integrate more renewable energy, but it may increase peak loads at transmission grid substations.
Review
Green & Sustainable Science & Technology
Pouya Ifaei, Atefeh Tamaskani Esfehankalateh, Fatemeh Ghobadi, Behnam Mohammadi-Ivatloo, ChangKyoo Yoo
Summary: In recent decades, extensive research has been conducted to optimize sustainable energy, focusing on technical performance, economic profitability, and social acceptance. However, there has been limited systematic review of the most popular heuristic algorithms in this field. This study developed a Boolean logic-based program to investigate the applications of heuristic solvers in sustainable energy and explore the factors contributing to their success.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Energy & Fuels
Matthias Kuehnbach, Judith Stute, Anna-Lena Klingler
Summary: Electric vehicles (EVs) offer significant potential for demand response (DR) and the integration of renewable electricity sources in the future energy system. However, DR may lead to unwanted avalanche effects, particularly beyond 2030. By using a dynamically updated DR signal, these negative impacts can be mitigated, reducing peak load and variance and facilitating renewable integration.
ENERGY STRATEGY REVIEWS
(2021)
Article
Energy & Fuels
Ulrich Fretzen, Mohammad Ansarin, Tobias Brandt
Summary: The research introduces a simple coordination strategy to minimize the impact on EV availability for drivers while maximizing the absorption of PV electricity generation by EV batteries. Results show that this coordination can provide 71%-92% of EV charging load from solar panels in the summer and 13%-76% in the winter, offering benefits compared to uncoordinated charging patterns. The gains are generally highest in winter and vary based on PV and EV integration levels, with minimal impact on EV availability for drivers.
Article
Green & Sustainable Science & Technology
F. Liu, A. Schellart, W. Shepherd, J. Boxall, M. Mayfield, S. Tait
Summary: This study investigates spatial and temporal conflicts in meeting domestic heat demand through renewable electrical energy supply and low-grade decentralised heat recovery from the urban drainage network in a UK case study area. The findings suggest that adopting an optimised and integrated water-energy system would lead to a 60% reduction in current carbon emissions.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Construction & Building Technology
Shihao Dong, Hengyi Zhao, Yuanbo Zheng, Long Ni
Summary: Electric heat pumps contribute significantly to carbon reduction and align with the trend of electrification in achieving carbon neutrality. The application of electric heat pumps in medium-low temperature heating in China can potentially reduce carbon emissions by 2.506 billion tons in 2060, with electric heat pumps accounting for 1.453 billion tons, equivalent to 14.7% of China's total current carbon emissions. Compared to direct electric heating, electric heat pumps can significantly reduce national electricity loads and consumption by 67.6% and 64.9% respectively in 2060. Additionally, electric heat pumps can be utilized for peak regulation in the electricity grid, but measures should be taken to restrict refrigerant leakage.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Green & Sustainable Science & Technology
Zhiwei Guo, Tao Li, Bowen Shi, Hongchao Zhang
Summary: The rapid expansion of China's vehicle fleet puts pressure on efforts to reduce carbon emissions. However, concerns have been raised about the environmental impact of electric vehicles (EVs) during the production phase. A study using a computational model found that the increase in EV sales has a negligible impact on the overall economy and the difference in CO2 emissions between EVs and internal combustion engine vehicles is marginal. Therefore, large-scale adoption of EVs will not hinder the sustainable development of the automotive industry.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Engineering, Chemical
Yuanyuan Li, Xin Chen, Yan Xu, Yuming Zhuo, Gui Lu
Summary: This paper reviews the use of renewable energy resources and waste heat for desalination, focusing on energy efficiency and cost analysis. Cost-effective roadmaps are presented, integrating energy storage, heat pumps, and an integrated energy system. Evaluation of heat pump systems and developments in multi-source energy utilization systems are also discussed.
Article
Thermodynamics
Yanxia Wang, Shaojun Gan, Kang Li, Yanyan Chen
Summary: A flexible-possibilist chanced constraints programming (FCCP) model is developed for planning low-carbon energy-transportation systems at the metropolitan scale, showing that the mass roll-out of EVs in Beijing will reduce carbon emissions, but the need for battery supply facilities will incur costs.
Article
Energy & Fuels
Alya AlHammadi, Nasser Al-Saif, Ameena Saad Al-Sumaiti, Mousa Marzband, Tareefa Alsumaiti, Ehsan Heydarian-Forushani
Summary: The United Arab Emirates is moving towards the use of renewable energy to address high energy consumption, unstable oil prices, and increasing carbon dioxide emissions. The study found that the optimal electric vehicle charging model comprising solar photovoltaics, wind turbines, batteries and a distribution grid was superior to other configurations from technical, economic, and environmental perspectives.
Article
Automation & Control Systems
Pudong Ge, Boli Chen, Fei Teng
Summary: This article presents an event-triggered distributed model predictive control strategy for managing the voltage magnitude of distributed generators in a microgrid to achieve a balance between control performance and communication and computation burdens. Additionally, an adaptive nonasymptotic observer is used to estimate internal and output signals of generators, cooperating with the DMPC-based voltage regulator to optimize control performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Electrical & Electronic
Pudong Ge, Yue Zhu, Tim C. Green, Fei Teng
Summary: This paper presents a distributed secondary voltage control method based on extended state Kalman-Bucy filter and fast terminal sliding mode control for improving the stability and performance of inverter-based distributed generation systems in islanded microgrids. By utilizing a unified modeling framework and accurate state estimation, a fast terminal sliding mode surface is designed to accelerate system convergence and consensus tracking.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Hao Li, Ying Qiao, Zongxiang Lu, Baosen Zhang, Fei Teng
Summary: This paper presents a frequency-constrained stochastic planning method for high renewable energy share systems, considering frequency response support from wind farms for the first time and addressing non-linear frequency constraints using novel linear constraints and an adaptive piecewise linearization method.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Jin Zhao, Qiuwei Wu, Nikos D. Hatziargyriou, Fangxing Li, Fei Teng
Summary: This paper introduces a new decentralized data-driven load restoration scheme for transmission and distribution systems with high wind power penetration. The proposed scheme handles uncertainties robustly, provides adjustable robustness, protects information privacy, and demonstrates effectiveness in both small-scale and large-scale systems.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Pengfei Zhao, Chenghong Gu, Zhidong Cao, Da Xie, Fei Teng, Jianwei Li, Xinlei Chen, Chenye Wu, Dongmin Yu, Xu Xu, Shuangqi Li
Summary: This paper proposes a two-stage risk-averse mitigation strategy for water-energy systems, integrating power, natural gas, and water systems to defend against false data injection attacks. An innovative risk-averse distributionally robust optimization method is used, incorporating Conditional Value-at-Risk as a coherent risk measure. Case studies demonstrate the effectiveness of the method in mitigating risks from FDIA and renewable uncertainties.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Zhongda Chu, Fei Teng
Summary: This paper proposes a Unit Commitment model with short circuit current constraint in high inverter based generator penetrated systems to balance system operation cost and short circuit current level. The influence of the short circuit current constraint on system operation and its interaction with frequency regulation are demonstrated through simulations.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Automation & Control Systems
Pengfei Zhao, Chenghong Gu, Zhidong Cao, Yichen Shen, Fei Teng, Xinlei Chen, Chenye Wu, Da Huo, Xu Xu, Shuangqi Li
Summary: This article proposes a new optimal two-stage optimization method to enhance the reliability of integrated energy system planning and operation against seismic attacks. By investing in hardening measures and minimizing emergency response operation costs, the survivability of IES can be improved, outperforming other optimization models in terms of economic losses.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Luis Badesa, Fei Teng, Goran Strbac
Summary: This paper discusses the distinct regional frequencies observed in certain power systems, proposing a reduced-order mathematical model and stability conditions for maintaining frequency stability. The proposed conditions can be implemented in optimization routines for co-optimization of ancillary services to support frequency, making this framework the first of its kind with explicit conditions for frequency stability in systems with inter-area frequency oscillations.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Luis Badesa, Fei Teng, Goran Strbac
Summary: This paper introduced closed-form conditions for ensuring regional frequency stability in a power system and proposed a methodology to represent these conditions in the form of linear constraints. It demonstrated their applicability in a generation-scheduling model for optimizing energy production and ancillary services, particularly in the context of the Great Britain system with non-uniform distribution of inertia. Through case studies, it was shown that location of inertia and frequency response in specific regions is crucial for stability, and proposed constraints allowed for finding the optimal volume of ancillary services in each region.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Andrea Tosatto, Georgios S. Misyris, Adria Junyent-Ferre, Fei Teng, Spyros Chatzivasileiadis
Summary: This paper studies the benefits of exchanging primary frequency reserves between asynchronous areas using the Supplementary Power Control (SPC) functionality of High-Voltage Direct-Current (HVDC) lines. The results suggest that the exchange of primary reserves through HVDC can reduce up to 10% the cost of reserve procurement while maintaining the system N-1 secure.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Zhongda Chu, Ning Zhang, Fei Teng
Summary: This paper proposes a novel microgrid scheduling approach that incorporates system frequency dynamics and uncertainty associated with renewable energy resources and load. The approach includes Synthetic Inertia control, explicit modeling of uncertainty with noncritical load shedding, and frequency constraints reformulated into Second-Order Cone form. By constructing a mixed-integer SOC Programming, optimal frequency services provision from the microgrid perspective is achieved.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Green & Sustainable Science & Technology
Marko Aunedi, Maria Yliruka, Shahab Dehghan, Antonio Marco Pantaleo, Nilay Shah, Goran Strbac
Summary: This paper aims to assess cost-efficient heat decarbonisation pathways for the UK by soft-linking two advanced energy system models. The results demonstrate that using a mix of electricity and hydrogen technologies is a cost-effective option for delivering zero-carbon heat.
Article
Engineering, Electrical & Electronic
Cormac O'Malley, Luis Badesa, Fei Teng, Goran Strbac
Summary: The reduced inertia levels in low-carbon power grids require explicit constraints to limit the frequency's lowest value and rate of change. This paper introduces a novel constraint derived from the swing equation to control the frequency's lowest value using fast frequency response, dynamically reduced largest loss, and under frequency load shedding. Case studies demonstrate that under frequency load shedding can reduce operational costs and its sensitivity to various factors is explored.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Proceedings Paper
Green & Sustainable Science & Technology
Peng Li, Boli Chen, Zhongda Chu, Aiguo Wu, Fei Teng
Summary: A hierarchical estimation scheme is designed to track the frequency and its rate of change of non-stationary power signals in this paper. The proposed estimator achieves fast convergence speed and robustness against noise thanks to the deployed Volterra integral operator and suitably designed kernel-functions. The effectiveness and robustness of the method are verified by numerical experiments and compared with a highly-concerned quadrature phase-locked-loop (QPLL) method.
2021 IEEE MADRID POWERTECH
(2021)
Proceedings Paper
Energy & Fuels
Martin Higgins, Jiawei Zhang, Ning Zhang, Fei Teng
Summary: This study develops a topology-learning-aided False Data Injection (FDI) attack method, enabling covert attacks on power system state estimation without prior knowledge of system information. The attack combines topology learning technique and attacker-side pseudo-residual assessment, achieving attacks with high confidence.
2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM)
(2021)
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.
