Big-Data Mechanisms and Energy-Policy Design
Abstract
A confluence of technical, economic and political forces are revolutionizing the energy sector. Policy-makers, who decide on incentives and penalties for possible courses of actions, play a critical role in determining which outcomes arise. However, designing appropriate energy policies is a complex and challenging task. Our vision is to provide tools and methodologies for policy makers so that they can leverage the power of big data to make evidence-based decisions. In this paper we present an approach we call big-data mechanism design which combines a mechanism design framework with stakeholder surveys and data to allow policy-makers to gauge the costs and benefits of potential policy decisions.We illustrate the effectiveness of this approach in a concrete application domain: the peaksaver PLUS program in Ontario, Canada.
Cite
Text
Pat et al. "Big-Data Mechanisms and Energy-Policy Design." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9910Markdown
[Pat et al. "Big-Data Mechanisms and Energy-Policy Design." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/pat2016aaai-big/) doi:10.1609/AAAI.V30I1.9910BibTeX
@inproceedings{pat2016aaai-big,
title = {{Big-Data Mechanisms and Energy-Policy Design}},
author = {Pat, Ankit and Larson, Kate and Keshav, Srinivasen},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {3887-3893},
doi = {10.1609/AAAI.V30I1.9910},
url = {https://mlanthology.org/aaai/2016/pat2016aaai-big/}
}