Reaching Positive Energy Neighborhoods by Optimizing Occupant Behaviors: A Decision-Support Tool Approach

The project focuses on analyzing occupant behaviors at the household and neighborhood levels to achieve Positive Energy Neighborhoods (PENs). The behaviors include behavior adjustments and investment behaviors.

We utilize Design Builder and Repast with Python (dealing with a multi-agent system) to simulate energy consumption at the household and neighborhood levels, respectively. Optimization strategies are implemented at both levels to ensure occupant comfort while reducing the energy gap towards PENs.

This involves investing in neighborhood projects to offset the energy gap, allocated based on households' financial status for energy justice.

Additionally, we incorporate multi-objective optimization, aiming to minimize investment and CO2 emissions.
The successful implementation and replication of PENs in existing regions would significantly contribute to the sustainability of cities.

Keywords: PEDs/PENs, occupant behaviors, multi-agent system, multi-objective optimization, energy consumption.

Project information

  • Category Energy transition
  • Author Bei Wang
  • Project date 2022 -