This paper presents, a Particle Swarm-Optimization (PSO) using Teaching Learning-Based Optimization (TLBO), and Antlion Optimization (ALO), for tuning PI controllers of the voltage regulator and current regulator for the control circuit of Static Synchronous Compensator (STATCOM). The type of STATCOM used is a 48-pulse Neutral Point Clamped (NPC) gate-turn-off thyristor (GTO)-based Voltage Source Converters (VSC). STATCOM is compensating power of up to ±10 MVAR. STATCOM control is provided based on a decoupled current strategy (d-q) using the current direct and quadrature components. Also, STATCOM fed on the dc-link side on the VSC by the renewable energy photovoltaic cells (PV) and battery, to provide the power of compensation. The strategy of enhancing power quality in the face of system fluctuations using STATCOM with multi-supply sources Photo-voltaic cells (PV) and the battery system on the capacitor channel of VSC converters, to provide the required power of compensation. The dc to dc boost converter has been used to regulator the power of PV cells, and the dc-dc buck-boost converter circuit has been used to regulator the power of battery energy storage. Happenings of energy quality during network perturbation or disturbance, like feeder, tripping and reclosing, and load switching were analyzed with the participation of STATCOM, so the multi-source (PV and battery) system with STATCOM suppresses these problems. A modified IEEE 12 bus test feeder with STATCOM has been used for the case study. The design and analysis have been carried out using m-file and SIMULINK for MATLAB 2015b