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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Mnohoparadigmatické algoritmy dolování z dat založené na vyhledávání, fuzzy technologiích a bio-inspirovaných výpočtech</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

ISBN

978-1-5090-4601-0

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

8

Strana od-do

2094-2101

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

San Sebastián

Datum konání akce

5. 6. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000426929700271