Project Description

The residential sector is responsible for ~20% of U.S. carbon pollution and 21% of the energy consumption. Multi-dwelling residential developments represent a significant opportunity to lock-in substantially lower energy demands and environmental pollution loads for the future if such initiatives are supported by meaningful community engagement. Unlike commercial buildings, where supervised control is possible, in residential buildings, the operation of energy-related devices is governed by residents. Therefore, our primary research goals are to 1) Discover new knowledge on how individuals, groups, and residential communities make decisions related to their home energy consumption; 2) Develop feedback mechanisms and smart technology to transform this often-irrational, information-poor process into an information-rich and coordinated energy management activity. The unique advantage of our team is that we have been granted permission to conduct sociotechnical research on four residential communities located in Indiana. In particular, we have access to real-time disaggregated energy-use data and we have the ability to provide visual/audio feedback and/or monetary incentives to the residents. The postdoctoral applicant is encouraged to submit a research proposal that makes use of the available test-beds and defines research objectives related to our two primary research goals. 

Start Date

Within 2019

Postdoc Qualifications

1. PhD in any engineering or science discipline

2. Technical expertise in at least two of the following fields (all three is ideal):
(a) High-performance buildings;
(b) Behavioral economics;
(c) Machine learning.

3. Excellent Python programming skills.

4. Excellent writing skills.

5. Potential to lead a research direction.

6. Ability to mentor a team of PhD students. 

Co-advisors

Panagiota Karava
pkarava@purdue.edu
Lyles School of Civil Engineering
https://engineering.purdue.edu/CE/People/view_person?resource_id=56531

Ilias Bilionis
ibilion@purdue.edu
School of Mechanical Engineering
https://www.predictivesciencelab.org

References

1. Kyle Anderson, SangHyun Lee,
An empirically grounded model for simulating normative energy use feedback interventions,
Applied Energy,
Volume 173,
2016,
Pages 272-282,
ISSN 0306-2619,
https://doi.org/10.1016/j.apenergy.2016.04.063.
(http://www.sciencedirect.com/science/article/pii/S0306261916305116)
Keywords: Agent-based modeling; Normative feedback; Residential energy use; Occupant behavior; Behavior diffusion

2. Florian Skopik,
The social smart grid: Dealing with constrained energy resources through social coordination,
Journal of Systems and Software,
Volume 89,
2014,
Pages 3-18,
ISSN 0164-1212,
https://doi.org/10.1016/j.jss.2013.04.052.
(http://www.sciencedirect.com/science/article/pii/S0164121213001064)
Keywords: Social smart grid; Energy consumption balancing; Community-driven energy sharing

3. Omar Isaac Asensio, Magali A. Delmas,
The dynamics of behavior change: Evidence from energy conservation,
Journal of Economic Behavior & Organization,
Volume 126, Part A,
2016,
Pages 196-212,
ISSN 0167-2681,
https://doi.org/10.1016/j.jebo.2016.03.012.
(http://www.sciencedirect.com/science/article/pii/S0167268116300257)
Keywords: Energy conservation; Decision framing; Repeated behavior; Randomized controlled trials

4. L. J. Ratliff, M. Jin, I. C. Konstantakopoulos, C. Spanos and S. S. Sastry, "Social game for building energy efficiency: Incentive design," 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, 2014, pp. 1011-1018.
doi: 10.1109/ALLERTON.2014.7028565
keywords: {building management systems;energy conservation;game theory;particle swarm optimization;social game;building energy efficiency;incentive design;energy efficient occupants behavior;reversed Stackelberg game;noncooperative game;particle swarm optimization method;Nash equilibrium;leader choice;Games;Lighting;Buildings;Optimization;Nash equilibrium;Estimation;Joints},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7028565&isnumber=7028426