Improved PSO for the best compromise of power systems

This paper develops an improved particle swarm optimization (IPSO) based multi-objective approach for the optimal economic emission dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The IPSO equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the e-constraint technique is employed to manage the multi-objective problem. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test EED problem of the HPS. The proposed approach integrates the IPSO, the MU and the e-constraint technique, revealing that the proposed approach has the following merits - 1) ease of implementation; 2) applicability to non-smooth fuel cost and emission level functions; 3) better effectiveness than the previous method; 4) better efficiency than Particle Swarm Optimization with the MU (PSO-MU), and 5) the requirement for only a small population in applying the optimal EED problem of the HPS.