Multi‐objective short‐term scheduling of thermoelectric power systems using a novel multi‐objective θ ‐improved cuckoo optimisation algorithm
Rasoul Azizipanah‐Abarghooee, Taher Niknam, Mohsen Zare, Masihallah Gharibzadeh · IET Generation Transmission & Distribution · 2014
This study proposes a multi‐objective optimal static and dynamic scheduling of thermoelectric power systems considering the conflicting environmental and economical objectives. Meantime, some restrictions such as valve‐point effects, prohibited operating zones, multi‐fuel options, line flow limits as well as spinning reserve should be taken into account in order to ensure secure real‐time power system operation. A novel multi‐objective θ ‐improved cuckoo optimisation algorithm is projected to solve the optimisation problems by defining a set of nondominated points as the solutions. The suggested method moves forward the particles to the problem search space in the polar coordinates as a substitute of the Cartesian one. In addition, in order to achieve better performance and higher‐convergence speed, several improvement strategies are utilised. This algorithm is equipped with a novel powerful mutation strategy in order to increase the population diversity and to amend the convergence criteria. Furthermore, a fuzzy‐based clustering is used to control the size of the repository and a niching method is utilised to choose the best solution during the optimisation process and to ensure diversity among non‐dominated solutions. Performance of the proposed algorithm is tested on 6‐, 10‐, 14‐, 40‐ and 100‐unit test systems and compared with those of other well‐known methods.