Extended Electric System Cascade Analysis (ESCA) for optimal power system targeting considering generation flexibility and heat rate factor

被引:4
|
作者
Liu, Wen Hui [1 ]
Lee, Ming Yang [1 ]
Hashim, Haslenda [1 ]
Lim, Jeng Shiun [1 ]
Klemes, Jiri J. [2 ]
Alwi, Sharifah Rafidah Wan [1 ]
Idris, Ahmad Muzammil [1 ]
Ho, Wai Shin [1 ]
机构
[1] Univ Teknol Malaysia, Proc Syst Engn Ctr PROSPECT Res, RISE, Utm Johor Bahru 81310, Johor, Malaysia
[2] Brno Univ Technol, Fac Mech Engn, NETME Ctr, SPIL, Tech 2896-2, Brno 61600, Czech Republic
来源
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS | 2019年 / 158卷
关键词
Electric System Cascade Analysis (ESCA); mathematical model; generation flexibility; heat rate; PROCESS INTEGRATION; DESIGN;
D O I
10.1016/j.egypro.2019.01.810
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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. (C) 2019 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:4190 / 4197
页数:8
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