A Model Predictive Control based Peak Shaving Application for a Grid Connected Household with Photovoltaic and Battery Storage

Deepranjan Dongol, Thomas Feldmann, Elmar Bollin

2018

Abstract

The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.

Paper Citation

in Harvard Style

Dongol D., Feldmann T. and Bollin E. (2018). A Model Predictive Control based Peak Shaving Application for a Grid Connected Household with Photovoltaic and Battery Storage.In Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-292-9, pages 54-63. DOI: 10.5220/0006685300540063

in Bibtex Style

@conference{smartgreens18,
author={Deepranjan Dongol and Thomas Feldmann and Elmar Bollin},
title={A Model Predictive Control based Peak Shaving Application for a Grid Connected Household with Photovoltaic and Battery Storage},
booktitle={Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2018},
pages={54-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006685300540063},
isbn={978-989-758-292-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - A Model Predictive Control based Peak Shaving Application for a Grid Connected Household with Photovoltaic and Battery Storage
SN - 978-989-758-292-9
AU - Dongol D.
AU - Feldmann T.
AU - Bollin E.
PY - 2018
SP - 54
EP - 63
DO - 10.5220/0006685300540063