Owing to the call for energy efficiency, the need to optimize the energy consumption of commercial buildings-- responsible for over 40% of US energy consumption--has recently gained significant attention. Moreover, the ability to participate in the retail electricity markets through proactive demand-side participation has recently led to development of economic model predictive control (EMPC) for building's Heating, Ventilation, and Air Conditioning (HVAC) system. The objective of this paper is to develop a price-sensitive operational model for building's HVAC systems while considering inflexible loads and other distributed energy resources (DERs) such as photovoltaic (PV) generation and battery storage for the buildings. A Nonlinear Economic Model Predictive Controller (NL-EMPC) is presented to minimize the net cost of energy usage by building's HVAC system while satisfying the comfort-level of building's occupants. The efficiency of the proposed NL-EMPC controller is evaluated using several simulation case studies.
@article{arxiv.1906.00362,
title = {Smart Building Energy Management using Nonlinear Economic Model Predictive Control},
author = {Mohammad Ostadijafari and Anamika Dubey and Yang Liu and Jie Shi and Nanpeng Yu},
journal= {arXiv preprint arXiv:1906.00362},
year = {2019}
}
Comments
arXiv admin note: text overlap with arXiv:1906.00352