Sustainable Energy and Artificial Intelligence

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

Document Type : Original Article

Authors

Mahyar Abasi 1
Arash Zeinalzadeh 2
Mohammad Amin Bahramian 1
Javad Ebrahimi 3

1 Department of Electrical Engineering, Faculty of Engineering, Arak university, Arak 38156-8-8349, Iran.

2 North Khorasan Electric distribution company (NKEDC)

3 Research Institute of Renewable Energy, Arak University, Arak 38156-8-8349, Iran.

https://doi.org/10.61186/seai.2409-1010
Abstract
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. 

Highlights

  • Dealing with the critical issue of energy losses in distribution systems,
  • Simultaneous optimization of the location and sizing of PV-DSTATCOMs and shunt supercapacitors,
  • Using the "Fuzzy-ALPSO" algorithm to solve the problem of optimal design of the distribution network,
  • Implementation of the proposed method on a multi-objective function

Keywords

Parallel Supercapacitors
PV-DSTATCOM
Power Loss
Voltage Stability
FUZZY-ALPSO Algorithm

Subjects

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Sustainable Energy and Artificial Intelligence
Volume 1, Issue 2
Spring 2025
Pages 77-90

  • Receive Date 28 September 2024
  • Revise Date 03 November 2024
  • Accept Date 09 November 2024
  • First Publish Date 10 November 2024

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