English

Unlocking Energy Flexibility From Thermal Inertia of Buildings: A Robust Optimization Approach

Systems and Control 2023-12-11 v1 Systems and Control

Abstract

Towards integrating renewable electricity generation sources into the grid, an important facilitator is the energy flexibility provided by buildings' thermal inertia. Most of the existing research follows a single-step price- or incentive-based scheme for unlocking the flexibility potential of buildings. In contrast, this paper proposes a novel two-step design approach for better harnessing buildings' energy flexibility. In a first step, a robust optimization model is formulated for assessing the energy flexibility of buildings in the presence of uncertain predictions of external conditions, such as ambient temperature, solar irradiation, etc. In a second step, energy flexibility is activated in response to a feasible demand response (DR) request from grid operators without violating indoor temperature constraints, even in the presence of uncertain external conditions. The proposed approach is tested on a high-fidelity Modelica simulator to evaluate its effectiveness. Simulation results show that, compared with price-based demand-side management, the proposed approach achieves greater energy reduction during peak hours.

Keywords

Cite

@article{arxiv.2312.05108,
  title  = {Unlocking Energy Flexibility From Thermal Inertia of Buildings: A Robust Optimization Approach},
  author = {Yun Li and Neil Yorke-Smith and Tamas Keviczky},
  journal= {arXiv preprint arXiv:2312.05108},
  year   = {2023}
}

Comments

8 pages, accepted to the 62nd IEEE Conference on Decision and Control (CDC 2023)