Genetic algorithm optimized impact assessment of optimally placed DGs and FACTS controller with different load models from minimum total real power loss viewpoint

Abstract This paper presents the impact assessment of optimally placed different distributed generations (DGs) with different load models (DLMs) (such as DG-1, DG-2, DG-3 and DG-4) and flexible alternating current transmission system (FACTS) controller like static VAR compensator (SVC) by employing genetic algorithm (GA) in a distribution power systems (DPSs) from minimum total real power loss viewpoint. Different DPS performance indices such as minimization of real power loss, minimization of the reactive power loss, improvement of the voltage profile, reduction of the short circuit current or MVA line capacity and reduction of the environmental greenhouse gases like carbon dioxide (CO2), sulphur dioxide (SO2), nitrogen oxide (NOx) and particulate matters in an emergency e.g. under fault, sudden change in field excitation of alternators or load increase in DPSs are considered. A comparison among different DGs with DLMs (such as DG-1, DG-2, DG-3 and DG-4) and FACTS controller like SVC is presented in this paper by employing GA. The effectiveness of the proposed methodology is tested on IEEE 37-bus distribution test system (38-node system). This paper clarifies the fact that, among the four types of DGs considered, DG-2 and DG-4 types of DGs at different operating power factors and FACTS controller like SVC offer better DPS performance indices when power factors varies from 0.80 to 0.99 leading and lagging, respectively. It is revealed that DG-2 type DG and SVC gives better DPS performance indices as compared to DG-1, DG-3 and DG-4 types DGs with DLMs and SVC. It is observed that DG-2 with SVC is more reliable and efficient as compared to the rest types of DG like DG-1, DG-3and DG-4 with SVC.