Optimal energy management of residential PV/HESS using evolutionary fuzzy control

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238698" target="_blank" >RIV/61989100:27240/17:10238698 - isvavai.cz</a>

Result on the web

<a href="http://ieeexplore.ieee.org/document/7969558/" target="_blank" >http://ieeexplore.ieee.org/document/7969558/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CEC.2017.7969558" target="_blank" >10.1109/CEC.2017.7969558</a>

Result language

angličtina

Original language name

Optimal energy management of residential PV/HESS using evolutionary fuzzy control

Original language description

The adoption of residential photovoltaic power generators combined with energy storage system can reduce the energy dependency of individual households while alleviating the impact of intermittent solar energy on the electric power grid. However, to maximize the benefits, energy in such systems must be carefully managed. The first step towards development of such energy management system, described in our previous work, is determination of the optimal power flows that reflects the current and future solar energy availability and household load, as well as the state of the energy storage system. This paper builds on the optimal power flows to develop an advanced energy management system in form of a fuzzy rule base system. The time series of the optimal flows, determined using linear programming, are used to determine the parameters of a Takagi-Sugeno fuzzy controller through differential evolution. The resulting system can be implemented to control power flows in other systems composed of photovoltaic generation and energy storage. The results confirm the operational and economic benefits of using the optimal operational strategy, while allowing its in-depth analysis through the evolved fuzzy rule base. © 2017 IEEE.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Multi-paradigm data mining algorithms based on information retrieval, fuzzy, and bio-inspired methods</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

ISBN

978-1-5090-4601-0

ISSN

—

e-ISSN

neuvedeno

Number of pages

8

Pages from-to

2094-2101

Publisher name

IEEE

Place of publication

Piscataway

Event location

San Sebastián

Event date

Jun 5, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000426929700271