Text

Sustainable Energy Management for Electric Bus Fleets: Dynamic Route Assignment and Optimal Charging Scheduling with Solar and Energy Storage

About this Digital Document

This thesis presents mathematical models to optimize the depot charging of a transit electric bus fleet given route schedules. The total cost of electricity drawn from the power grid is minimized in the presence of solar (PV) generation and an energy storage system (ESS). A mixed-integer linear program (MILP) is proposed that allows for static bus-route pairs as well as more flexible and dynamic assignments of buses to routes. The models are tested on data from a transit agency in Santa Clara County, California, including time-of-use (TOU) grid prices, vehicle specifications, and solar generation capabilities. Results show both models achieve full solar utilization and consume less power during peak hours. Dynamic route assignment achieves an 11% reduction in operational costs and performs well over a range of parameters based on sensitivity analysis. Furthermore, the results demonstrate the effect of weather on operational costs and other operational strategies.

Full Title
Sustainable Energy Management for Electric Bus Fleets: Dynamic Route Assignment and Optimal Charging Scheduling with Solar and Energy Storage
Member of
Theses and Dissertations
Contributor(s)
Creator: Masri, Nicholas E.
Thesis advisor: Snyder, Lawrence V.
Publisher
Lehigh University
Date Issued
2023-05-01
Type
Text
Genre
theses
Form
electronic documents
Department name
Industrial and Systems Engineering
Digital Format
electronic documents
Media type
application/pdf
Creator role
Graduate Student
Subject (LCSH)
Transportation--Mathematics--Translation studies
Keywords
Data Science
electric buses
electric vehicles
integer programming
Optimization ;

Citation


        
      

              

        
@mastersthesis{masri2023,
  title = {Sustainable Energy Management for Electric Bus Fleets: Dynamic Route Assignment and Optimal Charging Scheduling with Solar and Energy Storage},
  author = {Masri, Nicholas},
  year = {2023},
  month = may,
  publisher = {Lehigh University},
  keywords = {Data Science, electric buses, electric vehicles, integer programming, Optimization ;},
  abstract = {This thesis presents mathematical models to optimize the depot charging of a transit electric bus fleet given route schedules. The total cost of electricity drawn from the power grid is minimized in the presence of solar (PV) generation and an energy storage system (ESS). A mixed-integer linear program (MILP) is proposed that allows for static bus-route pairs as well as more flexible and dynamic assignments of buses to routes. The models are tested on data from a transit agency in Santa Clara County, California, including time-of-use (TOU) grid prices, vehicle specifications, and solar generation capabilities. Results show both models achieve full solar utilization and consume less power during peak hours. Dynamic route assignment achieves an 11\% reduction in operational costs and performs well over a range of parameters based on sensitivity analysis. Furthermore, the results demonstrate the effect of weather on operational costs and other operational strategies.},
}