Article
Energy & Fuels
Kyaw Hein, Yan Xu, Venkataraman Aditya, Amit Kumar Gupta
Summary: This research adopts a risk-averse approach by coordinating investment and operation stages to ensure optimal operation, effectively solving the optimization problem of energy storage systems in ships.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Multidisciplinary
Tianyang Zhao, Jiayu Qiu, Shuli Wen, Miao Zhu
Summary: This article proposes a joint optimization scheme for the sizing and power management of energy storage systems in all-electric ships. The method takes into account the uncertainty of onshore electricity prices and aims to reduce costs, emissions, and navigation time. Numerical simulation results validate the efficiency of the proposed method and the importance of navigation route scheduling.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Energy & Fuels
Siqing Guo, Yubing Wang, Lei Dai, Hao Hu
Summary: The global shipping industry is shifting towards all-electric ships (AESs) due to the serious shipping emission and stringent environmental regulations. Despite operational and managerial challenges, rather than technological limitations, hindering the promotion of AESs, there is a lack of systematic reviews in the literature. This paper provides a comprehensive review of state-of-the-art solutions and research trends in AES operations and management, aiming to improve understanding, encourage further research and applications, and identify future research directions.
Article
Mathematics
Hao Jin, Xinhang Yang
Summary: This paper proposes a bilevel optimal sizing and operation method for fuel cell/battery hybrid all-electric ships (AESs) in order to optimize the size of the AES and consider joint optimal energy management and voyage scheduling. Simulations on a passenger ferry show that the proposed method can achieve a 5.3% fuel saving and 5.2% total cost reduction, improving the ship's energy efficiency. This approach can also enhance the overall performance and sustainability of similar vessels.
Article
Engineering, Marine
Yan Zhang, Lin Sun, Tianyuan Fan, Fan Ma, Yiyong Xiong
Summary: Zero-emission battery-powered ships are considered an ideal solution for emission reduction and energy conservation in inland shipping. However, due to long charging time and limited onboard space, the all-electric ship in battery charging mode may not be suitable for long-distance navigation. This study proposes the all-electric ship in battery-swapping mode and develops a joint optimization method for optimal voyage scheduling and energy management. The effectiveness of this method is verified through a case study on the Yangtze River, demonstrating that it efficiently minimizes operation costs.
Article
Energy & Fuels
Hyun-Keun Ku, Chang-Hwan Park, Jang-Mok Kim
Summary: This paper proposes a full simulation model for the electrical analysis of all-electric ship (AES) based on a medium voltage DC power system. The model includes both mechanical and electrical elements and is developed using MATLAB/Simulink. The consistency of different elements is verified, which can simplify the design of the AES and optimize the control of its electric system.
Article
Green & Sustainable Science & Technology
Yu Liu, Yan Zheng, Yanjing Wang, Pinqiao Ren, Boxue Sun, Feng Gao, Xianzheng Gong
Summary: This study conducted a life cycle assessment to compare the greenhouse gas emissions reduction potential of calcium carbide sludge (CCS) cement clinker with Portland cement clinker. The results showed that CCS cement clinker had approximately 31% lower global warming potential than Portland cement clinker. However, there may be other environmental impacts due to the extra energy used for CCS pretreatment.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Jasper A. Ros, Eirini Skylogianni, Vincent Doedee, Joan T. van den Akker, Alex W. Vredeveldt, Marco J. G. Linders, Earl L. Goetheer, Juliana G. M-S Monteiro
Summary: The International Maritime Organization has set clear objectives for drastically reducing greenhouse gas emissions in the maritime sector in the coming decades. Ship-based carbon capture (SBCC) technology can be a viable solution to significantly reduce CO2 emissions in the maritime sector in the short term.
INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL
(2022)
Article
Energy & Fuels
Wentao Gong, Eryk Remiezowicz, Philip Loldrup Fosbol, Nicolas von Solms
Summary: This study models CO2 conditioning processes for ship-based CCS sequestration using APSEN HYSYS V11, reviewing purification processes and comparing open-cycle and closed-cycle liquefaction approaches. It found that closed-cycle liquefaction requires less energy than open-cycle, and using ammonia as refrigerant is more energy efficient than propane. Liquefaction at 15 bar requires less energy than 7 bar.
Article
Green & Sustainable Science & Technology
Van Can Nguyen, Chi-Tai Wang, Ying-Jiun Hsieh
Summary: The urgency to eliminate greenhouse gas emissions has led to the prioritization of using renewable energy to power electric vehicles. Case studies utilizing mixed-integer programming models can provide insights into the availability of renewable energy and required investments in highway networks.
Article
Engineering, Electrical & Electronic
Qian Xun, Nikolce Murgovski, Yujing Liu
Summary: This paper proposes a cost-effective way to design and operate fuel cell hybrid electric trucks (FCHETs) through sequential convex programming to minimize costs. The results show that the power rating of the electric machine is drastically reduced when the delivered power is satisfied in a probabilistic sense.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Environmental
Mohd Hafiz Abu Hassan, Farooq Sher, Saba Sehar, Tahir Rasheed, Ayesha Zafar, Jasmina Sulejmanovic, Usman Ali, Tazien Rashid
Summary: Gas hydrate formation is considered a new technology to reduce the impact of greenhouse gases, specifically the increasing CO2 concentration in the atmosphere. Experimental studies have shown that different sample preparation procedures, stirring speed, and temperature all play a role in the rate of CO2 hydrate formation. Promoters combination has also been found to increase the conversion of water to hydrate over longer experimental durations.
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
(2021)
Article
Energy & Fuels
Yawer Jafri, Johan M. Ahlstroem, Erik Furusjoe, Simon Harvey, Karin Pettersson, Elin Svensson, Elisabeth Wetterlund
Summary: As fossil-reliant industries shift towards sustainable biomass, the competition for biogenic carbon is expected to increase. This paper demonstrates the benefits of capturing residual CO2 for either permanent storage or biofuel production in various biofuel pathways. However, for these benefits to be fully realized, emerging biofuel technologies based on gasification and hydrotreatment of forest residues need to be commercially deployed.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Engineering, Marine
Hyungwon Shim, Yun Ho Kim, Jang-Pyo Hong, Donghee Hwang, Hee Jin Kang
Summary: As the IMO aims to reduce greenhouse gas emissions from ships by more than 50% by 2050 compared to 2008, the shipbuilding and shipping industries are undergoing a paradigm shift. The use of carbon-free fuels and electric propulsion systems is progressing, and the verification of reliability and safety is crucial. However, maritime demonstration is time-consuming and expensive, thus a more efficient means of demonstrating carbon-neutral technologies in ships is required. This study proposes a ship design for marine demonstration, integrating eco-friendly fuels and electric propulsion systems.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Wenjia Xia, Qihe Shan, Geyang Xiao, Yonggang Tu, Yuan Liang
Summary: This paper proposes an advanced joint seaport-AES microgrid system, aiming to minimize the total operational cost of power production and marketing, and utilizes a parameter projection distributed optimization algorithm to solve the power dispatching problem. The feasibility of this approach is verified through a case study.
Article
Automation & Control Systems
Tianyang Zhao, Haoyuan Yan, Xiaochuan Liu, Zhaohao Ding
Summary: The electrification of vehicles has strengthened the interaction between power systems and transportation systems, resulting in the formation of coupled transportation power systems (CTPSs). A novel optimal traffic power flow (OTPF) problem is proposed to analyze the spatial and temporal congestion propagation on CTPSs. This problem considers congested roads, transmission lines, and charging stations. The spatial and temporal distribution of electric vehicles (EVs) on roads and charging stations, connected by multilayer time-space networks (TSNs), is used to depict the traffic flow. The distribution is obtained by optimizing the charging, discharging, routing, and origin-destination pairing of EV fleets on TSNs, while the power flow is captured using dynamic optimal power flow problems with security constraints. An algorithm combining the alternating direction multiplier method with the convex-concave procedure is proposed to solve OTPFs. The results validate the effectiveness of the proposed scheme for managing congestion on CTPSs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Multidisciplinary
Zhaohao Ding, Yu Zhang, Wenrui Tan, Xuyang Pan, Henglin Tang
Summary: The paper proposes a charging price-setting scheme for highway charging station operation, taking into account distributed renewable energy generators near the stations. The proposed bi-level approach optimizes charging price and routes considering conflicting objectives between the charging station operator and electric vehicles. The column-and-constraint generation algorithm is adopted to solve the model and the proposed scheme is evaluated through numerical case studies.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Nan Zhou, Bei Han, Yan Xu, Lingen Luo, Gehao Sheng, Xiuchen Jiang
Summary: A novel method for fault locating and severity assessment in power distribution systems is proposed based on elasticity network mapping. By comparing the normalized distribution rate values, the fault location and severity can be accurately evaluated.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Yimeng Sun, Zhaohao Ding, Zechun Hu, Wei-Jen Lee
Summary: With the development of mobility on-demand and transportation electrification technologies, electric vehicle (EV)-based ride-hailing fleets are playing an increasingly important role in the urban ground transportation system. Due to the stochastic nature of order request arrival and electricity price, there exists decision-making risks for ride-hailing EVs operated in order grabbing mode. It is important to investigate their risk-aware operation and model their impact on fleet charging demand and trajectory.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Green & Sustainable Science & Technology
Hongxu Huang, Zhengmao Li, Lahanda Purage Mohasha Isuru Sampath, Jiawei Yang, Hung D. D. Nguyen, Hoay Beng Gooi, Rui Liang, Dunwei Gong
Summary: In this paper, a blockchain-enabled distributed market framework is proposed for the bi-level carbon and energy trading between coal mine integrated energy systems (CMIESs) and a virtual power plant (VPP) with network constraints. The bi-level trading problem is formulated as a Stackelberg game, considering integrating the energy market and the cap-and-trade carbon market mechanism, in order to maximize the profits of these two entities and describe their complicated interactions in the market. The proposed method effectively reduces the system operation cost and regional carbon emission, while protecting the privacy of each participant.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Ruoxuan Leng, Zhengmao Li, Yan Xu
Summary: This paper proposes a stochastic programming method for coordinated operation of distributed energy resources in the unbalanced active distribution network with diverse correlated uncertainties. The method models the three-phase branch flow to characterize the unbalanced nature, schedules DER for three phases, and derives a realistic DER allocation. It co-optimizes active and reactive power resources for voltage regulation and power loss reduction. The proposed method effectively reduces the system cost and co-optimizes the active and reactive power.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Energy & Fuels
Zhengmao Li, Yan Xu, Peng Wang, Gaoxi Xiao
Summary: This paper proposes a coordinated restoration method for the renewable energy-integrated multi-energy distribution system (MDS) to address the threats of low-probability but high-impact extreme events, such as floods, earthquakes, and hurricanes, to the security of the energy system. The method comprehensively models the MDS restoration with coupled power and thermal network constraints, utilizing thermal inertia and smart buildings' thermal demand response as buffers to reduce post-disaster energy supply cost. Preparation and load recovery stage measures are employed for efficient and reliable system restoration. Multiple uncertainties are dealt with through a risk-averse two-stage stochastic programming approach. Simulation results validate the effectiveness and superiority of the method.
Article
Energy & Fuels
Yesen Yang, Zhengmao Li, Pradeep V. Mandapaka, Edmond Y. M. Lo
Summary: This paper proposes a coordinated restoration framework for a coupled power and water system, considering physical networks and mechanisms. The framework minimizes the aggregate service loss with respect to different consumer loads and time periods by network reconfiguration, energy/water dispatching, load curtailment, and operation management of components. A two-stage risk-averse stochastic programming is applied for reliable restoration and manage risks.
Article
Energy & Fuels
Hongxu Huang, Zhengmao Li, Hoay Beng Gooi, Haifeng Qiu, Xiaotong Zhang, Chaoxian Lv, Rui Liang, Dunwei Gong
Summary: In this paper, a coordinated operation approach is proposed for scheduling the energy-transportation coupled coal mine integrated energy system (CMIES) under diverse uncertainties. The belt conveyors in the coal transportation network (CTN) and the CMIES are used to coordinate coal delivery scheduling and energy management. A novel energy-transportation coordinated model is proposed, which consists of the radial CTN and second-order cone programming (SOCP) relaxed CMIES. The aim is to overcome the challenges of robust optimization and stochastic programming by applying the distributionally robust optimization (DRO) method.
Article
Engineering, Electrical & Electronic
Yihong Zhou, Zhaohao Ding, Qingsong Wen, Yi Wang
Summary: In this study, a Bayesian training method is proposed to enhance the robustness of deep learning-based load forecasting models against adversarial attacks. The experimental results demonstrate that this method maintains good prediction performance under no attack and achieves higher robustness compared to four other benchmark methods.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Lin Xue, Tao Niu, Sidun Fang, Tianen Huang, Fan Li
Summary: Efficient voltage/VAR feasible boundary (VVFB) assessments for large-scale wind farms can help reduce cascading trip risks. This paper proposes an adaptive parameter aggregation dimensionality reduction equivalence (APA-DRE) method to efficiently and accurately solve the VVFB problem. The proposed approach reduces the computation scale of the VVFB and improves the computation efficiency of the original model by approximately three times while ensuring accuracy.
IET RENEWABLE POWER GENERATION
(2023)
Article
Computer Science, Information Systems
Yuan Huang, Zhaohao Ding, Wei-Jen Lee
Summary: With the advancement of transportation electrification and IoT, cloud-based shared on-demand logistic fleet management platforms are becoming increasingly popular. In this setting, the scheduling platform needs to dispatch vehicles while dealing with the charging demands and logistic requests. Using IoT technology, the platform coordinates fleet management decisions to optimize operational profit. To solve the fleet management problem, we propose a deep reinforcement learning-based method that adapts to the stochastic arriving of logistic requests and explores different charging pricing schemes. Simulation results demonstrate its effectiveness in optimizing decisions and maintaining delivery service quality.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Annie Lin, Shuli Wen, Miao Zhu, Zhaohao Ding, Tao Ding
Summary: Marine power systems are more vulnerable than land-based power systems, posing a crucial challenge to shipboard power systems. This study proposes a two-stage optimization framework considering navigation, demonstrating the effectiveness of the scheme in economic and resilient operation.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Tao Niu, Fan Li, Sidun Fang
Summary: A coordinated dispatch framework between power system and energy-intensive enterprises (EIEs) under the intrinsic time of use (TOU) prices is designed in this paper, which requires only several local information for interaction. The proposed method can effectively improve the regional consumption level of renewable energy and ensure interests of all sides.
IET RENEWABLE POWER GENERATION
(2023)
Editorial Material
Energy & Fuels
Zhengmao Li, Josep M. Guerrero, Mohammad Shahidehpour, Edmond Y. M. Lo, Shunbo Lei
FRONTIERS IN ENERGY RESEARCH
(2023)
