Smart Building Energy Management using Nonlinear Economic Model Predictive Control

Mohammad Ostadijafari; Anamika Dubey; Yang Liu; Jie Shi; Nanpeng Yu

doi:10.1109/PESGM40551.2019.8973669

Smart Building Energy Management using Nonlinear Economic Model Predictive Control

Mohammad Ostadijafari
, Anamika Dubey
, Yang Liu
, Jie Shi
, Nanpeng Yu

Washington State University
University of California at Riverside

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

26 Scopus citations

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.

Original language	English
Title of host publication	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Publisher	IEEE Computer Society
ISBN (Electronic)	9781728119816
DOIs	https://doi.org/10.1109/PESGM40551.2019.8973669
State	Published - Aug 2019
Externally published	Yes
Event	2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States Duration: 4 Aug 2019 → 8 Aug 2019

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2019-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Country/Territory	United States
City	Atlanta
Period	4/08/19 → 8/08/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Building thermal model
Demand response
HVAC
Nonlinear economic model predictive control
PV
battery

Access to Document

10.1109/PESGM40551.2019.8973669

Cite this

@inproceedings{d0a418c92913468db228939bc5a46c53,

title = "Smart Building Energy Management using Nonlinear Economic Model Predictive Control",

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.",

keywords = "Building thermal model, Demand response, HVAC, Nonlinear economic model predictive control, PV, battery",

author = "Mohammad Ostadijafari and Anamika Dubey and Yang Liu and Jie Shi and Nanpeng Yu",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Power and Energy Society General Meeting, PESGM 2019 ; Conference date: 04-08-2019 Through 08-08-2019",

year = "2019",

month = aug,

doi = "10.1109/PESGM40551.2019.8973669",

language = "英语",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2019 IEEE Power and Energy Society General Meeting, PESGM 2019",

}

Ostadijafari, M, Dubey, A, Liu, Y, Shi, J & Yu, N 2019, Smart Building Energy Management using Nonlinear Economic Model Predictive Control. in 2019 IEEE Power and Energy Society General Meeting, PESGM 2019., 8973669, IEEE Power and Energy Society General Meeting, vol. 2019-August, IEEE Computer Society, 2019 IEEE Power and Energy Society General Meeting, PESGM 2019, Atlanta, United States, 4/08/19. https://doi.org/10.1109/PESGM40551.2019.8973669

Smart Building Energy Management using Nonlinear Economic Model Predictive Control. / Ostadijafari, Mohammad; Dubey, Anamika; Liu, Yang et al.
2019 IEEE Power and Energy Society General Meeting, PESGM 2019. IEEE Computer Society, 2019. 8973669 (IEEE Power and Energy Society General Meeting; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Smart Building Energy Management using Nonlinear Economic Model Predictive Control

AU - Ostadijafari, Mohammad

AU - Dubey, Anamika

AU - Liu, Yang

AU - Shi, Jie

AU - Yu, Nanpeng

PY - 2019/8

Y1 - 2019/8

N2 - 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.

AB - 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.

KW - Building thermal model

KW - Demand response

KW - HVAC

KW - Nonlinear economic model predictive control

KW - PV

KW - battery

UR - https://www.scopus.com/pages/publications/85079067595

U2 - 10.1109/PESGM40551.2019.8973669

DO - 10.1109/PESGM40551.2019.8973669

M3 - 会议稿件

AN - SCOPUS:85079067595

T3 - IEEE Power and Energy Society General Meeting

BT - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

PB - IEEE Computer Society

T2 - 2019 IEEE Power and Energy Society General Meeting, PESGM 2019

Y2 - 4 August 2019 through 8 August 2019

ER -

Smart Building Energy Management using Nonlinear Economic Model Predictive Control

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this