On the optimized design of next-generation wind farms

被引:11
作者
Fischetti, Martina [1 ]
机构
[1] Vattenfall BA Wind, Havneholmen 29, DK-1561 Copenhagen, Denmark
关键词
Combinatorial optimization; OR in energy; OR in environment and climate change; Wind farm design; Mixed Integer Linear Programming;
D O I
10.1016/j.ejor.2020.10.048
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
A transformation from fossil fuels to renewable energy has been ongoing in recent years, driven by growing environmental and sustainability demands from customers and society. An increased use of renewable sources can, in particular, help during climate change, which is a very sensitive topic right now. Because demand for green energy is increasing, while competition is also growing, innovation and optimization are of key importance in this business. In particular, because the offshore wind energy market is based on an auction system: the company that can construct and operate the farm with the lowest subsidies will win the auction and capitalize on its investment. It is therefore extremely important to both minimize costs and increase profits at the design phase of new farms. In this paper we will illustrate how Operational Research techniques can help companies be more competitive on the market. To be specific, we address two of the main design challenges arising in the design of new offshore wind farms, the optimal allocation of wind turbines (to minimize interference between them and position-related costs) and their electrical interconnection. We show that a synergic use of mixed integer programming models and heuristic methods in the so-called matheuristic framework can be used to solve both problems efficiently. The optimization tools that we will describe have been used also for the design of Hollande Kust Zuid, the first offshore wind farm in the world to be constructed subsidy-free. We report results on a number of real instances, showing the impact of these techniques in decreasing costs and increasing profitability, with average gains of more than (sic) 10 M for each wind farm. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:862 / 870
页数:9
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