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Article
Chemistry, Multidisciplinary
Fayez Alanazi
Summary: The primary issues facing transportation today are rising oil costs and carbon emissions. Electric vehicles (EVs) are becoming popular due to their independence from oil and lack of greenhouse gas emissions. However, there are operational challenges that need to be addressed for widespread adoption, such as infrastructure costs, limited charging stations, range anxiety, and battery performance. Solutions include improving charging infrastructure, increasing charging station availability, using battery swapping techniques, and enhancing battery technology. Governments can incentivize EV adoption through tax credits or subsidies, while industry stakeholders can collaborate to promote EVs and reduce carbon emissions and air pollution.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Qinghua Tang et al.
Summary: With the growing popularity of AEVs, optimizing path-planning and charging strategy is crucial. This paper proposes a joint push-pull communication mode to obtain real-time traffic conditions and charging infrastructure information. Dynamic optimization algorithms are used to minimize travel and charging costs.
APPLIED SCIENCES-BASEL
(2023)
Article
Energy & Fuels
Klemen Dezelak et al.
Summary: The widespread adoption of electric vehicles presents challenges to the distribution grid, which needs to handle the increased demand without overloading and additional losses. A methodology was developed to assess the electricity consumption of battery electric vehicles in Slovenia, considering factors such as the number of electric cars, average consumption, distance traveled, and system efficiency. The modelling results of an integrated distribution grid model showed how power losses can be managed and an optimal outcome obtained through the application of a particle swarm optimization-based strategy to minimize reliance on the grid system.
Article
Energy & Fuels
Khalil Bachiri et al.
Summary: Electric vehicles (EVs) are a sustainable transportation solution, but finding appropriate charging stations in cities with limited infrastructure and dynamic charging demands is a challenge. To address this issue, we propose a multi-agent deep deterministic policy gradient (MADDPG) method that considers real-time traffic conditions to recommend optimal EV charging stations. Our approach aims to minimize travel time in a stochastic environment for efficient smart transportation management. Simulation experiments demonstrate MADDPG's superiority over other methods, highlighting its value for sustainable urban mobility and efficient EV charging station scheduling.
Article
Automation & Control Systems
Zhaoyuan Wu et al.
Summary: In this article, a marginal pricing mechanism for frequency response service provision considering the participation of P2H is proposed to enhance grid resilience. Case studies based on the IEEE RTS-24 system and a realistic Northwest power grid of China show that P2H can significantly improve the frequency response ability, especially reduce the startup of conventional units, so as to reduce carbon emissions. This effect is extremely appealing in the renewable-dominated cases.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Green & Sustainable Science & Technology
Xin Chang et al.
Summary: China is promoting the construction of national electricity market and carbon market to accelerate the low-carbon transition in the energy sector. The coupling effect of carbon emission trading and tradable green certificates under electricity marketization in China is examined. Simulation results show that coordination of the two can alleviate the pressure of fiscal deficit and promote low-carbon transition.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Computer Science, Artificial Intelligence
Yusef Ahsini et al.
Summary: This article explores the optimization of electric delivery vehicle routes in urban areas. By combining city graphs with topographic and traffic information and training an artificial neural network model using synthetic data, we transform the problem into a conventional Traveling Salesman Problem and propose an optimization algorithm based on a Nearest Neighbor initialization. Compared to distance-based optimization approaches, our algorithm achieves a reduction of 17.34% in energy consumption for tested instances of the problem.
Article
Engineering, Electrical & Electronic
Zhaoyuan Wu et al.
Summary: With the increasing electrification of end-use sectors, flexible resources on the demand side have great potential for system operation. However, challenges such as the randomness of power consumption behavior and low utilization rate of flexible resources need to be addressed. The concept of the sharing economy has gained popularity in local energy markets, and this paper provides an overview of potential market design and reviews related research on local energy sharing, enabling technologies, and potential practices. This paper can serve as a useful reference and offer insights for activating demand-side flexibility potential and integrating the sharing economy in local energy markets.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Zhaoyuan Wu et al.
Summary: In this paper, an incentive mechanism is designed to facilitate flexible resource sharing under balancing market integration (BMI). The paper analyzes the sources of benefits and compares the influence of different market regulation approaches. Based on the Coase theorem, an incentive profit-sharing mechanism is designed to optimize resource allocation, reduce welfare transfers, and enhance integration acceptance.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Chemistry, Multidisciplinary
Gianmatteo Cannavacciuolo et al.
Summary: This research focuses on the estimation of electric vehicle range, finding that factors such as battery health, pack temperature, power consumption, and battery pre-heating can significantly impact the driving range of electric vehicles.
APPLIED SCIENCES-BASEL
(2021)
Article
Energy & Fuels
Qiang Xing et al.
Article
Chemistry, Multidisciplinary
Hanif Tayarani et al.
APPLIED SCIENCES-BASEL
(2019)
Review
Green & Sustainable Science & Technology
Zhenya Ji et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2018)
Article
Thermodynamics
Yugong Luo et al.
Article
Engineering, Electrical & Electronic
Difei Tang et al.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2016)
Article
Energy & Fuels
Yunfei Mu et al.
