Optimal scheduling of interconnected power systems

被引:24
作者
Koltsaklis, Nikolaos E. [1 ]
Gioulekas, Ioannis [1 ,2 ]
Georgiadis, Michael C. [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Chem Engn, Thessaloniki 54124, Greece
[2] UCL, Dept Chem Engn, London, England
关键词
Energy scheduling; Electricity interconnections; Unit commitment; Electricity trade; Day-ahead market; UNIT COMMITMENT PROBLEM; ENERGY PLANNING-MODEL; DEMAND RESPONSE; OFFERING STRATEGIES; COMBINED HEAT; ELECTRICITY; OPTIMIZATION; MULTIPERIOD; GENERATION; MARKET;
D O I
10.1016/j.compchemeng.2018.01.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents an optimization-based approach to address the problem of the optimal daily energy scheduling of interconnected power systems in electricity markets. More specifically, a Mixed Integer Linear Programming model (MILP) has been developed to address the specific challenges of the underlying problem. The main focus of the proposed framework is to examine the importance and the impacts of electricity interconnections and cross-border electricity trade on the scheduling of power systems, both at a technical and economic level. The applicability of the proposed approach has been tested on an illustrative case study including five power systems which can be interconnected (with a certain interconnection structure) or not. The proposed model determines in a detailed and analytical way the optimal power generation mix, the electricity trade among the systems, the electricity flows (in case of interconnection options), the marginal price of each system, as well as it investigates through a sensitivity analysis the effects of the available interconnection capacity on the resulting power production mix. The work demonstrates that the proposed optimization approach is able to provide important insights into the appropriate energy strategies followed by the market participants, as well as on the strategic long-term decisions to be implemented by investors and/or policy makers at a national and/or regional level, underlining potential risks and providing appropriate price signals on critical energy infrastructure projects under real market operating conditions. (c) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:164 / 182
页数:19
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