In practice, the conductor resistance of elements in power systems is not a constant but
depends on the temperature. The conventional power flow problem considering the
conductor resistance as a constant may lead to not exact results, especially for the power
losses. In this paper, a combined particle swarm optimization and differential evolution
(CPSO-DE) method is proposed to solve the temperature dependent optimal power flow
(TDOPF) problem in power systems. The considered TDOPF problem is a very large
scale and complex problem in power systems due to the consideration of the effect of
temperature on the resistance of transmission lines in the conventional OPF problem. On
the other hand, the proposed CPSO-DE is a powerful method suitable for solving OPF
problems by utilizing the advantages of both PSO and DE algorithms to find the optimal
solution. For implementing the proposed method to the TDOPF problem, the PSO
algorithm with constriction factor guided by a pseudo-gradient method is first used to
explore the global search space of the problem and then the DE algorithm is used to exploit
the local search space of the problem to guarantee that the near optimal solution can be
found. To validate the effectiveness of the proposed method for the considered problem,
the IEEE 30-bus and IEEE 118-bus systems have been used for testing and the results
obtained from the proposed method have been compared to those from other methods for
the both conventional OPF and TDOPF problems. The test results have indicated that the
proposed method can effectively solve these problems compared to other methods for the
considered cases. Therefore, the proposed CPSO-DE method is a very effective method
for solving the large-scale and complex TDOPF problem in power systems.