A multi-period optimization model for energy planning with CO2 emission considerations

被引:27
|
作者
Sirikitputtisak, Tule [1 ]
Mirzaesmaeeli, Hamidreza [2 ]
Douglas, Peter L. [2 ]
Croiset, Eric [2 ]
Elkamel, Ali [2 ]
Gupta, Murlidhar [2 ]
机构
[1] Univ Waterloo, Dept Chem Engn, Waterloo, ON N2L 3G1, Canada
[2] Nat Resources Canada, CANMET Energy Technol Ctr, Ottawa, ON K1A 1M1, Canada
来源
关键词
multi-period; fleet-wide; energy planning; optimization model; emission; CO2; capture;
D O I
10.1016/j.egypro.2009.02.247
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
A multi-period optimal energy planning program for Ontario has been developed in mixed-integer non-linear programming using General Algebraic Modeling System, GAMS. The program applies both time-dependent and time-independent constraints. These include, but not limited to, construction time, fluctuation of fuel prices, and CO2 emission reduction target. It also offer flexibility of fuel balancing and fuel switching of the existing boilers and option purchasing of Carbon credit if the reduction target is not achievable. The objective function incorporates all these constraints as well as minimizes over all the cost of electricity and meets the projected electricity demand over a span of 14 years. Originally it was used for only two study cases which are the base case scenario for Ontario where no CO2 emission reduction target is applied and the 6% reduction case to meet the Kyoto Protocol; to reduce its CO2 emission to 6% below that of 1990. This project utilizes the program for various similar study cases and beyond. The Ontario's study cases include different CO2 emission reduction targets ranging from 6% to 75% below 1990 levels by 2012. The overall cost of the electricity for different CO2 emission reduction targets increases linearly with slope of 1.3. Carbon capture and sequestration, retrofitting of the carbon capture and storage, and fuel switching are the main strategy in order to keep the cost of electricity relative low and satisfy the CO2 emission constraints. These results help us better understand the factors affecting the fleet's structure. It may also help plan the energy direction of Ontario and perhaps serve as an example for other provinces, territories, states, and even countries. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4339 / 4346
页数:8
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