Title
Optimal Management of Energy Consumption and Comfort for Smart Buildings Operating in a Microgrid
Date Issued
01 May 2019
Access level
metadata only access
Resource Type
journal article
Author(s)
Pinzon J.A.
Vergara Pedro
Da Silva L.C.P.
University of Campinas
University of Campinas
Abstract
This paper presents a mixed integer non-linear programming model to optimize, in a centralized fashion, the operation of multiple buildings in a microgrid. The proposed model aims to minimize the total cost of the energy imported from the main grid at the interconnection point, managing the power demand and generation of buildings, while operational constraints of the electrical grid are guaranteed. This approach considers the management of heating, ventilation, and air conditioning units, lighting appliances, photovoltaic generation and energy storage system of each building. Comfortable indoor conditions for the occupants are kept by a set of mathematical constraints. Additionally, a strategy that simplifies the original model is presented, based on a set of linearization techniques and equivalent representations, obtained through a pre-processing stage executed in EnergyPlus software. This strategy allows approximating the proposed model into a mixed integer linear programming formulation that can be solved using commercial solvers. The proposed model was tested in a 13-bus microgrid for different deterministic cases of study with non-manageable loads and smart buildings. A large-size test case is also considered. Finally, a rolling horizon strategy is proposed with the aim of addressing the uncertainty of the data, as well as reducing the amount of forecasting data required.
Start page
3236
End page
3247
Volume
10
Issue
3
Language
English
OCDE Knowledge area
Ingeniería eléctrica, Ingeniería electrónica
Scopus EID
2-s2.0-85062305006
Source
IEEE Transactions on Smart Grid
Resource of which it is part
IEEE Transactions on Smart Grid
ISSN of the container
19493053
Sponsor(s)
Manuscript received November 10, 2017; revised February 21, 2018; accepted March 28, 2018. Date of publication April 3, 2018; date of current version April 19, 2019. This work was supported in part by the Sao Paulo Research Foundation (FAPESP) under Grant 2015/18145-0 and Grant 2015/09136-8, and in part by the Companhia Paulista de Força e Luz (CPFL) under Grant PD ANEEL-00063-3032/2017. Paper no. TSG-01641-2017. (Corresponding author: Jerson A. Pinzon.) The authors are with the Department of Systems and Energy, University of Campinas, Campinas 13083-852, Brazil (e-mail: jpinzon@ dsee.fee.unicamp.br; pedropa@dsee.fee.unicamp.br; lui@dsee.fee.unicamp.br; mjrider@dsee.fee.unicamp.br).
Sources of information: Directorio de Producción Científica Scopus