@inproceedings{9c8c7d208bce430b86d5eb7bd15d9330,
title = "Benders Decomposition for stochastic programming-based PV/Battery/HVAC planning",
abstract = "In this article, a general Benders Decomposition is applied to solve a stochastic mixed integer programming formulation (SMIP) to obtain the optimal sizing of a photovoltaic system (PV) and battery energy storage system (BESS) to power a Residential Heating Ventilation and Air- Conditioning System (HVAC). The uncertainty of PV-output is stochastically modeled using different scenarios with the probability of their occurring. The total cost of the HVAC energy consumption and installing PVs and BESS is to be minimized cosidering the system is grid-connected and electricity price is varying. A simplified model of a space cooling is used while considering the thermal energy constraints. The optimization problem extends to find the optimal HVAC on/off states, and BESS charging- discharging states for a multi-horizon period.",
keywords = "Bender Decomposition, HVACs, SMIP",
author = "Mohemmed Alhaider and Lingling Fan and Zhixin Miao",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",
year = "2016",
month = nov,
day = "10",
doi = "10.1109/PESGM.2016.7741775",
language = "English",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE Computer Society",
booktitle = "2016 IEEE Power and Energy Society General Meeting, PESGM 2016",
address = "United States",
}
