Multi-objective short-term scheduling of thermoelectric power systems using a novel multi-objective θ-improved cuckoo optimisation algorithm

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 a...

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Veröffentlicht in:IET generation, transmission & distribution Jg. 8; H. 5; S. 873 - 894
Hauptverfasser: Azizipanah-Abarghooee, Rasoul, Niknam, Taher, Zare, Mohsen, Gharibzadeh, Masihallah
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Stevenage The Institution of Engineering and Technology 01.05.2014
Institution of Engineering and Technology
Schlagworte:
Applied sciences
dynamic scheduling
economical objectives
Electrical engineering. Electrical power engineering
Electrical power engineering
environmental objectives
Exact sciences and technology
fuzzy set theory
fuzzy‐based clustering
Miscellaneous
multiobjective optimal static scheduling
multiobjective short‐term scheduling
multiobjective θ‐improved cuckoo optimisation algorithm
niching method
optimisation
polar coordinates
population diversity
Power networks and lines
prohibited operating zones
real‐time power system operation
scheduling
spinning reserve constraints
thermal power stations
thermoelectric power
thermoelectric power systems
transmission lines power flow limits
valve‐point effects
thermal power stations
multiobjective optimal static scheduling
valve-point effects
transmission lines power flow limits
fuzzy set theory
multiobjective θ-improved cuckoo optimisation algorithm
economical objectives
prohibited operating zones
dynamic scheduling
niching method
thermoelectric power
multiobjective short-term scheduling
optimisation
polar coordinates
spinning reserve constraints
population diversity
fuzzy-based clustering
scheduling
environmental objectives
thermoelectric power systems
real-time power system operation
Short term
Performance evaluation
Set point
Automatic classification
Spinning reserve
Polar coordinate
Optimization method
Multiobjective programming
Scheduling
Algorithm
Real time system
Optimization
Convergence speed
Electrical network
Thermoelectric power
Convergence rate
Valve
Planning
Comparative study
ISSN:1751-8687, 1751-8695
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Beschreibung
Zusammenfassung: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.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2013.0354