7 papers
Online Smoothed Demand Management
Adam Lechowicz, Nicolas Christianson, Mohammad Hajiesmaili +2
We introduce and study a class of online problems called online smoothed demand management , motivated by paradigm shifts in grid integration and energy storage fo…
Degradation-Aware Frequency Regulation of a Heterogeneous Battery Fleet via Reinforcement Learning
Tanay Raghunandan Srinivasa, Vivek Deulkar, Jia Bhargava +2
Battery energy storage systems are increasingly deployed as fast-responding resources for grid balancing services such as frequency regulation and for mitigating renewable generati…
Quantifying the Carbon Reduction of DAG Workloads: A Job Shop Scheduling Perspective
Roozbeh Bostandoost, Adam Lechowicz, Walid A. Hanafy +2
Carbon-aware schedulers aim to reduce the operational carbon footprint of data centers by running flexible workloads during periods of low carbon intensity. Most schedulers treat w…
LEAD: Towards Learning-Based Equity-Aware Decarbonization in Ridesharing Platforms
Mahsa Sahebdel, Ali Zeynali, Noman Bashir +2
Ridesharing platforms such as Uber, Lyft, and DiDi have grown in popularity due to their on-demand availability, ease of use, and commute cost reductions, among other benefits. How…
Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints
Adam Lechowicz, Nicolas Christianson, Bo Sun +4
We introduce and study spatiotemporal online allocation with deadline constraints (), a new online problem motivated by emerging challenges in sustainability and ene…
Dynamic Incentive Allocation for City-scale Deep Decarbonization
Anupama Sitaraman, Adam Lechowicz, Noman Bashir +3
Greenhouse gas emissions from the residential sector represent a significant fraction of global emissions. Governments and utilities have designed incentives to stimulate the adopt…