Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F20%3A43960459" target="_blank" >RIV/49777513:23220/20:43960459 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S2213138820312546?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2213138820312546?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.seta.2020.100827" target="_blank" >10.1016/j.seta.2020.100827</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran
Popis výsledku v původním jazyce
Although much efforts have been devoted to the optimal design of the energy systems, there is a research gap about the multi-year load growth-based optimal planning of microgrids. This paper tries to fill such a research gap by developing a novel method for the optimal design of the grid-connected microgrids based on the longterm load demand forecasting. The multilayer perceptron artificial neural network is used for time-series load prediction. The impacts of the annual load growth are analyzed under various cases based on the consideration and determination methods of yearly load growth. The proposed method is applied to an actual microgrid in Tehran, Iran, using HOMER (Hybrid Optimization of Multiple Energy Resources) software. The load modeling’s capabilities of HOMER software, as a well-known software for the optimal design of energy systems, are used, which have received less attention. Since most existing research works in Iran focused on the off-grid operating mode, the study of an actual microgrid under grid-connected operating mode is one of the most contributions of this paper. The comparison of the obtained results and other available methods illustrate the impacts of the adequately precise estimation of annual load growth in the design of energy systems.
Název v anglickém jazyce
Multi-year load growth-based optimal planning of grid-connected microgrid considering long-term load demand forecasting: A case study of Tehran, Iran
Popis výsledku anglicky
Although much efforts have been devoted to the optimal design of the energy systems, there is a research gap about the multi-year load growth-based optimal planning of microgrids. This paper tries to fill such a research gap by developing a novel method for the optimal design of the grid-connected microgrids based on the longterm load demand forecasting. The multilayer perceptron artificial neural network is used for time-series load prediction. The impacts of the annual load growth are analyzed under various cases based on the consideration and determination methods of yearly load growth. The proposed method is applied to an actual microgrid in Tehran, Iran, using HOMER (Hybrid Optimization of Multiple Energy Resources) software. The load modeling’s capabilities of HOMER software, as a well-known software for the optimal design of energy systems, are used, which have received less attention. Since most existing research works in Iran focused on the off-grid operating mode, the study of an actual microgrid under grid-connected operating mode is one of the most contributions of this paper. The comparison of the obtained results and other available methods illustrate the impacts of the adequately precise estimation of annual load growth in the design of energy systems.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Sustainable Energy Technologies and Assessments
ISSN
2213-1388
e-ISSN
—
Svazek periodika
42
Číslo periodika v rámci svazku
December 2020
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
19
Strana od-do
1-19
Kód UT WoS článku
000595926700005
EID výsledku v databázi Scopus
2-s2.0-85091339316