Economic dispatch (ED) is a calculation to find the operation of power
generators with the lowest cost for a limited set of generators, subject to individual
constraints, and to meet the total generation that can fulfill the load demand and losses.
ED focuses on coordinating the power produced and the costs incurred by all electric
generators operating in the system. Dynamic economic dispatch (DED) extends the ED
problem, where in DED, the load demand constantly changes in each period within a
24-hour range. In this research, ramp-rate limits and prohibited operating zones are
also applied as constraints in the DED simulation. The DED simulation will be
conducted in Matlab using the Constriction Factor Particle Swarm Optimization
(CFPSO) algorithm. The CFPSO algorithm is tested on the IEEE 6-unit thermal system
and the IEEE 15-unit thermal system. The results of the CFPSO algorithm on both
systems are then compared with the results from the Bees Algorithm (BA) testing. The
results show that both algorithms can solve the DED simulation without violating the
applied constraints. From the testing results on both systems, the CFPSO algorithm
yields a total cost of 317,328.2387 Btu/Hr and 770,141.9306 Btu/Hr, while the BA
yields a total cost of 317,500.4784 Btu/Hr and 773,737.8976 Btu/Hr. In terms of
computation time and convergence speed, the CFPSO algorithm completes the
simulation in 8.557 seconds and 9.153 seconds, reaching convergence at the 30th and
55th iterations. On the other hand, the BA completes the simulation in 62.833 seconds
and 68.338 seconds, reaching convergence at the 12th and 11th iterations.