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1843. Charge Scheduling with Renewables for Electric Buses Using Stochastic Optimization

Invited abstract in session TB-51: Electric Busses, stream Public Transport Optimization.

Tuesday, 10:30-12:00
Room: M5 (building: 101)

Authors (first author is the speaker)

1. Rito Brata Nath
Civil Engineering, Indian Institute of Science (IISc)
2. Madhusudan Baldua
Civil Engineering, Indian Institute of Science
3. Vivek Vasudeva
CiSTUP, Indian Institute of Science
4. Tarun Rambha
Civil Engineering, Indian Institute of Science

Abstract

While electrification of urban transit systems is underway worldwide, it is essential to integrate it with renewable energy sources to make it fully sustainable. The intermittent nature of renewables poses a challenge in deciding the required solar panels and battery storage capacity at charging locations. To address these challenges, we propose a two-stage stochastic programming model considering uncertainties in solar energy generation and bus energy consumption under dynamic time-of-use electricity prices. Specifically, we formulate the problem as a multi-scenario linear program and employ a Benders’ decomposition approach where the first stage (long-term) master variables determine the contracted power grid capacity, battery storage capacity, and the area of solar panels installed at each charging location. The second stage variables (scenario-specific) associated with each child problem prescribe the energy transferred to buses from the grid or solar-based power systems during layovers. We present a case study on the Arlington bus network, US, for 52 scenarios with 3337 trips, where 145 buses and 26 charging locations are required as per a concurrent scheduler algorithm. The solar energy generation data is collected from the National Renewable Energy Laboratory database. Our results reveal that the Benders’ decomposition is faster compared to the Simplex algorithm, and the scenario-based schedule adapts better to the uncertainties than the average scenario schedule.

Keywords

Status: accepted

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