Open AccessChaotic sine–cosine algorithm for chance‐constrained economic emission dispatch problem including wind energy
Author(s) -
Guesmi Tawfik,
Farah Anouar,
Marouani Ismail,
Alshammari Badr,
Abdallah Hsan Hadj
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2019.1081
Subject(s) - wind power , mathematical optimization , sine , trigonometric functions , renewable energy , schedule , electric power system , chaotic , computer science , economic dispatch , algorithm , power (physics) , engineering , mathematics , electrical engineering , artificial intelligence , physics , geometry , quantum mechanics , operating system
One of the most effective approaches to reduce carbon emissions is the integration of renewable energy sources into electrical power networks. Currently, wind turbines are the fastest growing among all renewable sources. With the integration of wind farms into electrical grids, the economic emission dispatch (EED) problem is becoming more complicated due to the stochastic availability of wind energy. In this study, a new approach is proposed to solve the EED problem incorporating wind farms. The problem is formulated as a chance‐constrained problem to deal with the stochastic characteristic of wind power. A novel chaotic sine–cosine algorithm (CSCA) is proposed to provide the optimal generation schedule to minimise simultaneously the generation cost and emission. Some weakness has been encountered in exploitation and exploration capabilities in standard sine cosine algorithm (SCA). Hence, the chaos is integrated into the original SCA to improve its performance. In addition, a new mutation strategy is added to the SCA. In this study, the new algorithm is based on three mutually exclusive equations. The new technique is applied on the 69‐bus ten‐unit and 40‐unit test systems with and without wind energy. The results performed by CSCA are compared with those generated by other recent techniques.