相关论文: Evaluation of Rail Decarbonization Alternatives: F…
This paper focuses on what we call Reaction Network Cardon Dioxide Removal (RNDCR) framework to analyze several proposed negative emissions technologies (NETs) so as to determine when present-day Earth carbon cycle system would exhibit…
We study carbon-aware smart charging in a fossil-dominated grid by coupling a simplified hydro-thermal-renewable dispatch model with a tractable linear charging scheduler. The case study is informed by Vietnam's regional data. Thermal units…
Accurate prediction of lithium-ion battery lifespan is vital for ensuring operational reliability and reducing maintenance costs in applications like electric vehicles and smart grids. This study presents a hybrid learning framework for…
Electric vehicles (EVs) are considered as sustainable alternatives to conventional vehicles, as they reduce emission and fossil fuel dependency. A recent study has proposed a charging infrastructure planning tool to support intercity trips…
A comprehensive analysis of energy requirements and emissions associated with electric vehicles, ranging from mining and making the rare-earth magnets required in electric motor to assembling the Li-ion battery, including charging and…
Cities all around the world struggle with urban air quality due to transportation related emissions. In public transport networks, replacing internal combustion engine buses by electric buses provides an opportunity to improve air quality.…
Recent advances in distributed learning raise environmental concerns due to the large energy needed to train and move data to/from data centers. Novel paradigms, such as federated learning (FL), are suitable for decentralized model training…
Accurate day-ahead individual residential load forecasting is of great importance to various applications of smart grid on day-ahead market. Deep learning, as a powerful machine learning technology, has shown great advantages and promising…
We propose the REORIENT (REnewable resOuRce Investment for the ENergy Transition) model for energy systems planning with the following novelties: (1) integrating capacity expansion, retrofit and abandonment planning, and (2) using…
In high renewables-integrated power systems, irrespective to their sizes, energy storage is commonly included and utilized to mitigate fluctuations from both the load and renewable power generation, ensuring system reliability, among which…
To alleviate energy shortages and environmental impacts caused by transportation, this study introduces EcoFollower, a novel eco-car-following model developed using reinforcement learning (RL) to optimize fuel consumption in car-following…
While the transition to electric vehicles (EVs) is essential for decarbonizing the transportation system, the production and distribution of EVs entail substantial carbon costs. To ensure these emissions are accurately accounted for and…
Hydrogen-electrical microgrids are increasingly assuming an important role on the pathway toward decarbonization of energy and transportation systems. This paper studies networked hydrogen-electrical microgrids planning (NHEMP), considering…
The goal of this project is to determine the feasibility of calculating a travel route for an electric vehicle (EV) that will require the least amount of energy for the trip, and thus extending the range of the EV. To achieve this goal, the…
California has committed to ambitious decarbonization targets across multiple sectors, including decarbonizing the electrical grid by 2045. In addition, the medium- and heavy-duty truck fleets are expected to see rapid electrification over…
Decentralized Federated Learning (DFL) is an emerging paradigm that enables collaborative model training without centralized data and model aggregation, enhancing privacy and resilience. However, its sustainability remains underexplored, as…
With electric power infrastructure posing an increasing risk of igniting wildfires under continuing climate change, utilities are frequently de-energizing power lines to mitigate wildfire ignition risk, which can cause load shedding. Recent…
In this paper, we propose a novel energy-efficient framework for an electric vehicle (EV) network using a contract theoretic-based economic model to maximize the profits of charging stations (CSs) and improve the social welfare of the…
Cement production is among the largest contributors to industrial air pollution, emitting ~3 Mt NOx/year. The industry-standard mitigation approach, selective non-catalytic reduction (SNCR), exhibits low NH3 utilization efficiency,…
Range-extended electric vehicles combine the higher efficiency and environmental benefits of battery-powered electric motors with the longer mileage and autonomy of conventional internal combustion engines. This combination is particularly…