This paper proposes an improved moth flame optimization (IMFO) algorithm to effectively solve the optimal power flow (OPF) problems. The concept of moth flame optimization (MFO) is inspired from the movement of moth towards the moon direction. IMFO is mainly based on the concept of MFO with modifying the path of moths in new spirals around the flame. Standard IEEE 30‐bus, IEEE 57‐bus and IEEE 118‐bus test systems are used to validate and prove the efficiency and robustness of IMFO algorithm. The validation of the proposed algorithm is based on 15 case studies in terms of different single and multi‐objective functions: fuel cost minimization, gas emission reduction, active power loss minimization, voltage profile improvement, and voltage stability enhancement. The simulation results of the proposed algorithm are compared with those obtained by other well‐known optimization techniques. The obtained results demonstrate the capability and robustness of IMFO algorithm to solve OPF problems. The results reveal that IMFO algorithm is capable of finding precise and better OPF solutions compared with the other techniques. A comparison among the convergence characteristics of IMFO technique and the other techniques proves the prevalence of IMFO to attain the optimal power flow solution with fast convergence.

Optimal planning of integration the Photovoltage Distributed Generation (PV-DG) and DSTATCOM is a crucial task due to the stochastic variations of PV output power and the load demand which are related to solar irradiance variations and the activities of the customers, respectively. In this article, the optimal planning problem of the PV-DG and DSTATCOM system is solved. The proposed model considers the uncertainties of the solar irradiance and the load demand for a multi-objective function, including the cost reduction, the voltage profile, and stability index improvement. Modified Ant Lion Optimizer (MALO) is proposed to enhance the basic ALO searching ability using two strategies. The first strategy is based on Levy Flight Distribution (LFD) to strengthen the exploration of the algorithm and avoid the premature of the basic ALO. In contrast, the second strategy is based on updating the solutions in a spiral orientation to improve the exploitation of the algorithm. The IEEE 69-bus and 118-bus radial distribution systems are used to demonstrate the effectiveness of the proposed method, and the yielded simulations are compared with the basic ALO and other well-known optimization techniques for power loss minimization under deterministic conditions. The simulation results demonstrate that the techno-economic benefits can be increased considerably by optimal inclusion of two PV-DGs and DSTATCOMs compared with a single system.