Operational management of renewable energy systems with storage using an optimisation-based simulation methodology

被引:4
作者
Mallor, F. [1 ]
Azcarate, C. [1 ]
Blanco, R. [1 ]
Mateo, P. [2 ]
机构
[1] Univ Publ Navarra, Pamplona 31006, Spain
[2] Univ Zaragoza, Zaragoza, Spain
关键词
simulation; optimisation; energy system; storage; management; HYDROGEN STORAGE; WIND POWER; TECHNOLOGIES; DESIGN;
D O I
10.1057/jos.2015.16
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
It has been widely recognised that renewable energy, such as wind, provides valuable benefits for the environment, human health, and the economy. Nevertheless, renewable energy has several drawbacks: high variability in its availability, uncertainty in its forecast, and difficulty in matching production to demand. The storage of energy would enable solving of most of these problems. In this paper, we obtain operative management policies for energy storage under two criteria: maximising the profit of selling the energy and maximising the reliability of the system as a provider of committed energy. Decisions take into account data concerning the structure of selling prices and penalties, as well as updated probabilistic wind speed forecasts. We use a sequence of rolling horizon stochastic optimisation problems to determine the parameters of the proposed management strategies. To solve these problems we propose a simulation-based optimisation methodology.
引用
收藏
页码:263 / 278
页数:16
相关论文
共 42 条
[1]   Economical assessment of a wind-hydrogen energy system using WindHyGen® software [J].
Aguado, Monica ;
Ayerbe, Elixabete ;
Azcarate, Cristina ;
Blanco, Rosa ;
Garde, Raquel ;
Mallor, Fermin ;
Rivas, David M. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2009, 34 (07) :2845-2854
[2]   Practical introduction to simulation optimization [J].
April, J ;
Glover, F ;
Kelly, JP ;
Laguna, M .
PROCEEDINGS OF THE 2003 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2003, :71-78
[3]   Peaking strategies for the management of wind-H2 energy systems [J].
Azcarate, Cristina ;
Blanco, Rosa ;
Mallor, Fermin ;
Garde, Raquel ;
Aguado, Monica .
RENEWABLE ENERGY, 2012, 47 :103-111
[4]  
Barton RR, 2006, HBK OPERAT RES MANAG, V13, P535, DOI 10.1016/S0927-0507(06)13018-2
[5]   Energy storage for mitigating the variability of renewable electricity sources: An updated review [J].
Beaudin, Marc ;
Zareipour, Hamidreza ;
Schellenberglabe, Anthony ;
Rosehart, William .
ENERGY FOR SUSTAINABLE DEVELOPMENT, 2010, 14 (04) :302-314
[6]   Efficient design of hybrid renewable energy systems using evolutionary algorithms [J].
Bernal-Agustin, Jose L. ;
Dufo-Lopez, Rodolfo .
ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (03) :479-489
[7]   The effectiveness of storage and relocation options in renewable energy systems [J].
Blarke, M. B. ;
Lund, H. .
RENEWABLE ENERGY, 2008, 33 (07) :1499-1507
[8]   Metaheuristics in combinatorial optimization: Overview and conceptual comparison [J].
Blum, C ;
Roli, A .
ACM COMPUTING SURVEYS, 2003, 35 (03) :268-308
[9]   Particle swarm optimization for AC-coupling stand alone hybrid power systems [J].
Boonbumroong, U. ;
Pratinthong, N. ;
Thepa, S. ;
Jivacate, C. ;
Pridasawas, W. .
SOLAR ENERGY, 2011, 85 (03) :560-569
[10]   Evaluation of a hybrid photovoltaic-wind system with hydrogen storage performance using exergy analysis [J].
Calderon, M. ;
Calderon, A. J. ;
Ramiro, A. ;
Gonzalez, J. F. ;
Gonzalez, I. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2011, 36 (10) :5751-5762