Optimal Wind Bidding Strategies in Day-Ahead Markets

被引：1

作者：

Gomes, Isaias L. R. ^{[2
]}

Pousinho, Hugo M. I. ^{[1
]}

Melicio, Rui ^{[1
,2
]}

Mendes, Victor M. F. ^{[2
,3
]}

机构：

[1] Univ Lisbon, Inst Super Tecn, IDMEC LAETA, Lisbon, Portugal

[2] Univ Evora, Escola Ciencias & Tecnol, Dept Fis, Evora, Portugal

[3] Inst Super Engn Lisboa, Lisbon, Portugal

来源：

TECHNOLOGICAL INNOVATION FOR CYBER-PHYSICAL SYSTEMS | 2016年 / 470卷

关键词：

Bidding strategies; Wind power system; Stochastic linear programming; Day-ahead market; SHORT-TERM ENERGY; ELECTRICITY MARKET; RENEWABLE ENERGY; POWER-SYSTEM; GENERATION; STORAGE;

D O I：

10.1007/978-3-319-31165-4_44

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a computer application (CoA) for wind energy (WEn) bidding strategies (BStr) in a pool-based electricity market (EMar) to better accommodate the variability of the renewable energy (ReEn) source. The CoA is based in a stochastic linear mathematical programming (SLPr) problem. The goal is to obtain the optimal wind bidding strategy (OWBS) so as to maximize the revenue (MRev). Electricity prices (EPr) and financial penalties (FiPen) for shortfall or surplus energy deliver are modeled. Finally, conclusions are addressed from a case study, using data from the pool-based EMar of the Iberian Peninsula.

引用

页码：475 / 484

页数：10

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