Accurate Allocation of PV-DSTATCOM and Supercapacitors in Distribution Networks Using an Adaptive Learning Strategy to Enhance Operation Indices

A significant portion of electrical energy in power grids is wasted in distribution systems. Distribution systems typically have radially shaped feeders. Today, increased demand resulted in the expansion of distribution systems and their dimensions, which in turn causes greater voltage drop, increased losses, and consequently reduced stability, decreased node voltage, and load imbalance. Nowadays, using modern methods and employing power electronics devices such as flexible alternating current transmission system (FACTS) devices can enhance the quality of electrical power. Additionally, considering the global warming, most power generation companies are inclined towards renewable energies such as photovoltaic panels. One of the suitable FACTS devices used in the PV distribution system is PV-DSTATCOM. These devices are based on reactive power control and use a photovoltaic (PV) system to supply their required energy. Therefore, they should be installed in a way that coordinates with capacitor banks installed in the distribution network and improves power quality parameters, including reduced network losses, improved network performance, deferred investment, increased reliability, and enhanced power quality. In this paper, the problem of locating and sizing of PV-DSTATCOM and shunt supercapacitors is solved based on a simultaneous multi-objective manner, with the objectives focused on power and energy losses, voltage profile, and voltage stability. To solve this multi-objective problem, the Fuzzy-ALPSO algorithm is adopted and implemented on standard IEEE 33- and 69-bus systems.