Abstract:
This paper presents a new approach to solve the
multi area unit commitment problem (MAUCP) using an
evolutionary programming-based tabu search (EPTS)
method. The objective of this paper is to determine the
optimal or a near optimal commitment schedule for
generating units located in multiple areas that are
interconnected via tie- lines. The evolutionary
programming-based tabu search method is used to solve
multi area unit commitment problem, allocated generation
for each area and find the operating cost of generation for
each hour. Joint operation of generation resources can
result in significant operational cost savings. Power
transfer between the areas through the tie- lines depends
upon the operating cost of generation at each hour and tieline
transfer limits. The tie -line transfer limits were
considered as a set of constraints during optimization
process to ensure the system security and reliability. The
overall algorithm can be implemented on an IBM PC, which
can process a fairly large system in a reasonable period of
time. Case study of four areas with different load pattern
each containing 26 units connected via tie- lines has been
taken for analysis. Numerical results showed comparing the
operating cost using evolutionary programming-based tabu
search method with conventional dynamic programming
(DP), evolutionary programming (EP), Partical Swarm
Optimization (PSO), Simulated Annealing (SA),
Evolutionary Programming based Partical Swarm
Optimization (EPPSO), Evolutionary Programming based
Simulated Annealing (EPSA)) method. Experimental results
shows that the application of this evolutionary
programming-based tabu search method have the potential
to solve multi area unit commitment problem with lesser
computation time.
