Title :
A review of emerging techniques on generation expansion planning
Author :
Zhu, Jinxiang ; Chow, Mo-Yuen
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fDate :
11/1/1997 12:00:00 AM
Abstract :
Power system generation expansion planning is a challenging problem due to the large-scale, long-term, nonlinear and discrete nature of generation unit size. Since the computation revolution, several emerging techniques have been proposed to solve large scale optimization problems. Many of these techniques have been reported as used in generation expansion planning. This paper describes these emerging optimization techniques (including expert systems, fuzzy logic, neural networks, analytic hierarchy process, network flow, decomposition method, simulated annealing and genetic algorithms) and their potential usage in solving the challenging generation expansion planning in future competitive environments in the power industry. This paper provides useful information and resources for future generation expansion planning
Keywords :
electric power generation; expert systems; fuzzy logic; genetic algorithms; neural nets; power system CAD; power system planning; simulated annealing; analytic hierarchy process; competitive environments; decomposition method; emerging optimization techniques; expert systems; fuzzy logic; genetic algorithms; network flow; neural networks; power industry; power system generation expansion planning; simulated annealing; Algorithm design and analysis; Computational modeling; Expert systems; Fuzzy logic; Large-scale systems; Neural networks; Optimization methods; Power generation; Power system analysis computing; Power system planning;
Journal_Title :
Power Systems, IEEE Transactions on