A Spatial multi-period long-term energy planning model: A case study of the Greek power system

被引:128
作者
Koltsaklis, Nikolaos E. [1 ]
Dagoumas, Athanasios S. [2 ,3 ]
Kopanos, Georgios M. [4 ]
Pistikopoulos, Efstratios N. [4 ]
Georgiadis, Michael C. [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Chem Engn, Thessaloniki 54124, Greece
[2] Elect Market Operator SA, Piraeus 18545, Greece
[3] Univ Piraeus, Dept Int & European Studies, Piraeus 18534, Greece
[4] Univ London Imperial Coll Sci Technol & Med, Dept Chem Engn, Ctr Proc Syst Engn, London SW7 2AZ, England
关键词
Mixed integer linear programming; Energy systems engineering; Generation expansion planning; Power sector; Carbon emissions; ELECTRICITY-GENERATION; OPTIMIZATION MODEL; EXPANSION; MITIGATION; ALGORITHM; EMISSION; UNCERTAINTY; REDUCTION; SECTOR;
D O I
10.1016/j.apenergy.2013.10.042
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
080707 [能源环境工程]; 082001 [油气井工程];
摘要
This paper presents a mixed-integer linear programming (MILP) model for the optimal long-term energy planning of a (national) power generation system. In order to capture more accurately the spatial and technical characteristics of the problem, the underlying geographical area (country) is divided into a number of individual networks that interact with each other. The proposed model determines the optimal planning of the power generation system, the selection of the power generation technologies, the type of fuels and the plant locations so as to meet the expected electricity demand, while satisfying environmental constraints in terms of CO2 emissions. Furthermore, the suggested model determines the electricity imports from neighbouring countries, the electricity transmission as well as the transportation of primary energy resources between domestic networks. A real case study concerning the Greek energy planning problem demonstrates the applicability of the proposed approach, which can provide policy makers with a systematic computer-aided tool to analyse various scenarios and technology options. Finally, a sensitivity analysis was conducted in order to capture the influence of some key parameters such as electricity demand, natural gas and CO2 emission price as well as wind power investment cost. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:456 / 482
页数:27
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