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arXiv · 1906.00362

Smart Building Energy Management using Nonlinear Economic Model Predictive Control

Mohammad Ostadijafari·Anamika Dubey·Yang Liu·Jie Shi·Nanpeng Yu
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Abstract

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.

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Mohammad Ostadijafari, Anamika Dubey, Yang Liu, Jie Shi, Nanpeng Yu. 2019-06-02. Smart Building Energy Management using Nonlinear Economic Model Predictive Control. https://arxiv.org/abs/1906.00362

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