Detail publikace
Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor
Liu, W.H. Lee, M.Y. Hashim, H. Lim, J.S. Klemeš, J.J. Wan Alwi, S.R. Idris, A.M. Ho, W.S.
Anglický název
Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
en
Originální abstrakt
In order to cater for fluctuating energy demand, power plants are designed either as base power plant or peak power plant. The advantage of base power plant is that due to its constant power generation, the power plant has a higher efficiency. To optimize and design a power plant, many previous study has been conducted. Among the studies, Power Pinch tool named Electric System Cascade Analysis (ESCA) was applied to design an optimal power system. ESCA analysis is conducted by assuming that the power plant generates constant power as it is more efficient. However, further analysis using ESCA shows that with a minimal power plant capacity would result in a trade-off that the energy storage system would be larger and leads to higher energy charging and discharging tendency (result in higher energy lost). Considering the time change of heat rate with the corresponding load factor, this study incorporates new algorithm for flexible power generation into the existing ESCA methodology. To validate the new algorithm, an off-grid distributed energy generation system is mathematically modelled and solved. The result from the new algorithm is compared with that of the mathematical model. The comparison of optimal generator capacity shows a difference of 5.71%. The similarity of the result hence validates that the new algorithm is suitable.
Anglický abstrakt
In order to cater for fluctuating energy demand, power plants are designed either as base power plant or peak power plant. The advantage of base power plant is that due to its constant power generation, the power plant has a higher efficiency. To optimize and design a power plant, many previous study has been conducted. Among the studies, Power Pinch tool named Electric System Cascade Analysis (ESCA) was applied to design an optimal power system. ESCA analysis is conducted by assuming that the power plant generates constant power as it is more efficient. However, further analysis using ESCA shows that with a minimal power plant capacity would result in a trade-off that the energy storage system would be larger and leads to higher energy charging and discharging tendency (result in higher energy lost). Considering the time change of heat rate with the corresponding load factor, this study incorporates new algorithm for flexible power generation into the existing ESCA methodology. To validate the new algorithm, an off-grid distributed energy generation system is mathematically modelled and solved. The result from the new algorithm is compared with that of the mathematical model. The comparison of optimal generator capacity shows a difference of 5.71%. The similarity of the result hence validates that the new algorithm is suitable.
Klíčová slova anglicky
Electric System Cascade Analysis (ESCA); Generation flexibility; Heat rate; Mathematical model; Energy management; Energy resources; Mathematical models; Cascade analysis; Distributed energies; Energy storage systems; Fluctuating energy; Generation flexibilities; Generator capacity; Heat rate; Higher efficiency; Economic and social effects
Vydáno
01.01.2019
Nakladatel
Elsevier Ltd
Místo
ELSEVIER SCIENCE BV, SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
ISSN
1876-6102
Kniha
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS
Číslo
158
Číslo edice
158
Strany od–do
4190–4197
Počet stran
8
BIBTEX
@inproceedings{BUT160784,
author="Jiří {Klemeš},
title="Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor",
booktitle="INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS ",
year="2019",
number="158",
month="January",
pages="4190--4197",
publisher="Elsevier Ltd",
address="ELSEVIER SCIENCE BV, SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS",
issn="1876-6102"
}