Premium
Vector ordinal optimization theory based large‐scale multi‐objective unit commitment considering stochastic wind power
Author(s) -
Xie Min,
Yan Yuanyuan,
Ke Shaojia,
Liu Mingbo
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22589
Subject(s) - wind power , mathematical optimization , stochastic optimization , computer science , power (physics) , hydropower , power system simulation , scale (ratio) , thermal power station , electric power system , operations research , mathematics , engineering , electrical engineering , physics , quantum mechanics
The unit commitment problem of a large power system with the popularity of large‐scale wind power is complex and difficult to solve. Vector ordinal optimization (VOO) is a new method to solve multi‐objective optimization problems with complex calculation burdens which can obtain a satisfactory solution at a high enough probability. Our objective is to develop a new technique for optimal design with stochastic wind power. In this paper, we select coal consumption, power purchase costs and SO 2 emissions as the objective functions. Based on the scenario method, the stochastic wind power generation is taken into account. A real provincial power system with a large‐scale wind farm is taken as a numerical example, in which hydropower, nuclear power, biomass energy, gas turbines, thermal power and other complex power structures are considered. The results show that the VOO based method proposed in this paper is effective in solving large‐scale multi‐objective unit commitment problems considering stochastic wind power. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.