Transmission Augmentation With Mathematical Modeling of Market Power and Strategic Generation Expansion-Part II

• Published in: IEEE transactions on power systems 2011-11, Vol.26 (4), p.2049-2057
• Main Authors: Hesamzadeh, M. R., Biggar, D. R., Hosseinzadeh, N., Wolfs, P. J.
• Format: Article
• Language: English
• Subjects: A-stability; Augmentation; Biology; Communication pattern; Computer software selection and evaluation; Decision variables; Distributed memory; Electric power generation; Electric power transmission; Electricity market; Generation expansion; Genes; Genetic algorithms; Heuristic optimization technique; Heuristic optimization techniques; High performance computing; high performance computing techniques; Island parallel genetic algorithms; Islands; Isolated evolution; Isolated islands; Limited communication; Market Power; Markets; Mathematical analysis; Mathematical model; Mathematical modeling; Mathematical models; Mathematical operators; Mathematical structure; Memory architecture; Modules; Mutation process; Network architecture; Numerical analysis; Numerical approaches; Numerical solution; Optimization; Search spaces; Shared memories; Stability criteria; Standard genetic algorithm; Studies; Topology; transmission system augmentation; Transmission systems
• ISSN: 0885-8950; 1558-0679; 1558-0679
• DOI: 10.1109/TPWRS.2011.2145009

This paper describes a numerical approach to solving the mathematical structure proposed in the first part of this paper. The numerical approach employs a standard genetic algorithm (GA) embedded with an island parallel genetic algorithm (IPGA). The GA handles the decision variables of the transmission network service provider, (TNSP) while the IPGA module finds the equilibrium of the electricity market. The IPGA module uses the concept of parallel islands with limited communication. The islands evolve in parallel and communicate with each other at a specific rate and frequency. The communication pattern helps the IPGA module to spread the best-found genes across all isolated islands. The isolated evolution removes the fitness pressure of the already-found optima from the chromosomes in other islands. A stability operator has been developed which detects stabilized islands and through a strong mutation process re-employs them in exploring the search space. To improve the efficiency of the proposed numerical solution, two high performance computing (HPC) techniques are used - shared-memory architecture and distributed-memory architecture. The application of the proposed approach to the assessment of transmission augmentation is illustrated using an IEEE 14-bus example system.