Nonlinear Model-Based Predictive Control of Electric Water Heaters in Individual Dwellings
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{laguili:2024:CEC,
-
author = "Oumaima Laguili and Julien Eynard and Stephane Grieu",
-
title = "Nonlinear Model-Based Predictive Control of Electric
Water Heaters in Individual Dwellings",
-
booktitle = "2024 IEEE Congress on Evolutionary Computation (CEC)",
-
year = "2024",
-
editor = "Bing Xue",
-
address = "Yokohama, Japan",
-
month = "30 " # jun # " - 5 " # jul,
-
publisher = "IEEE",
-
keywords = "genetic algorithms, genetic programming, Water
heating, Predictive models, Prediction algorithms,
Solar panels, Solar heating, Greenhouse gases,
Optimization, Domestic hot water, electric water
heater, genetic algorithm, model-based predictive
control, nonlinear optimization, rule-based control,
solar photovoltaics",
-
isbn13 = "979-8-3503-0837-2",
-
DOI = "doi:10.1109/CEC60901.2024.10611874",
-
abstract = "The increasing use of photovoltaics (PV) in the
residential sector aims at contributing to reducing
greenhouse gas (GHG) emissions. However, one issue that
slows down the adoption of the technology is the duck
curve issue. A promising solution for addressing this
issue is to use electric water heaters (EWHs) as a
means of storing the PV power generation surplus - in
buildings equipped with PV solar panels, a big part of
the electricity produced is often not consumed locally
- while preserving users' comfort. The primary goal of
this research work encompass the development of EWH
control strategies, including a model-based predictive
control (MPC) strategy - the optimisation problem is
solved using a genetic algorithm (GA) -, with the aim
of improving both the PV power generation
self-consumption (SC) rate and the economic gain. The
MPC strategy outperforms the rule-based (RB)
strategies.",
-
notes = "also known as \cite{10611874}
WCCI 2024",
- }
Genetic Programming entries for
Oumaima Laguili
Julien Eynard
Stephane Grieu
Citations