Optimal Generation Expansion Planning Strategy with Carbon Trading

Fossil fuel-firing power plants dominate electric power generation in Taiwan, which are also the major contributor to Green House gases (GHG). CO2 is the most important greenhouse gas that cause global warming. This paper penetrates the relationship between carbon trading for GHG reduction and power generation expansion planning (GEP) problem for the electrical utility. The Particle Swarm Optimization (PSO) Algorithm is presented to deal with the generation expansion planning strategy of the utility with independent power providers (IPPs). The utility has to take both the IPPs’ participation and environment impact into account when a new generation unit is considering expanded from view of supply side. Keywords—Carbon Trading, CO2 Emission, Generation Expansion Planning (GEP), Green House gases (GHG), Particle Swarm Optimization (PSO).

[1]  Jong-Bae Park,et al.  A hybrid genetic algorithm/dynamic programming approach to optimal long-term generation expansion planning , 1998 .

[2]  Yoshikazu Fukuyama,et al.  A PARALLEL GENETIC ALGORITHM F GENERATION EXPANSION PLANNIN , 1996 .

[3]  S. A. Al-Baiyat,et al.  Economic load dispatch multiobjective optimization procedures using linear programming techniques , 1995 .

[4]  Jong-Bae Park,et al.  An improved genetic algorithm for generation expansion planning , 2000 .

[5]  A. M. Leite da Silva,et al.  Efficient loss-of-load cost evaluation by combined pseudo-sequential and state transition simulation , 1997 .

[6]  Mo-Yuen Chow,et al.  A review of emerging techniques on generation expansion planning , 1997 .

[7]  A. A. El-Keib,et al.  Economic dispatch in view of the Clean Air Act of 1990 , 1994 .

[8]  M. Clerc,et al.  The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[9]  Yoshikazu Fukuyama,et al.  Parallel genetic algorithm for generation expansion planning , 1996 .

[10]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[11]  A.A. Abido,et al.  Particle swarm optimization for multimachine power system stabilizer design , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[12]  R. Yokoyama,et al.  An effective DP solution for optimal generation expansion planning under new environment , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[13]  Kit Po Wong,et al.  Combined genetic algorithm/simulated annealing/fuzzy set approach to short-term generation scheduling with take-or-pay fuel contract , 1996 .

[14]  Kit Po Wong,et al.  Power markets analysis using genetic algorithm with population concentration , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[15]  Roy Billinton,et al.  Algorithm for failure frequency and duration assessment of composite power systems , 1998 .

[16]  M. Kitagawa,et al.  Implementation of genetic algorithm for distribution systems loss minimum re-configuration , 1992 .

[17]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[18]  Koji Yamada,et al.  Immune algorithm for n-TSP , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[19]  Naruaki Toma,et al.  Immune algorithm with immune network and MHC for adaptive problem solving , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[20]  G. P. Granelli,et al.  Emission constrained dynamic dispatch , 1992 .

[21]  R. Eberhart,et al.  Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[22]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[23]  Peter J. Angeline,et al.  Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.

[24]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[25]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[26]  Shyh-Jier Huang,et al.  An immune-based optimization method to capacitor placement in a radial distribution system , 2000 .