An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed...

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Optimization Theory

Background:

• The optimal power flow (OPF) problem is crucial for efficient power system operation.
• Incorporating distributed generation (DG) and multiple objectives complicates traditional OPF.
• Existing methods may struggle with simultaneous optimization of diverse objectives like power loss and voltage stability.

Purpose of the Study:

• To develop a novel formulation for the multi-objective optimal power flow (MOOPF) problem in meshed power networks.
• To address the impact of distributed generation (DG) on MOOPF.
• To propose an effective algorithm for solving the MOOPF problem with simultaneous optimization of power loss, voltage stability, and shunt capacitor MVAR reserve.

Main Methods:

• A multi-objective fuzzy linear programming (MFLP) optimization algorithm was developed.
• Fuzzy membership functions were designed with extreme targets, and inequality constraints were treated as hard constraints.
• The MOOPF formulation was converted to a crisp OPF within a successive linear programming (SLP) framework and solved using an interior point method (IPM).

Main Results:

• Simulations on IEEE 30-bus and IEEE 118-bus test systems validated the MFLP algorithm's efficacy.
• The MFLP approach achieved a unique solution with high satisfaction for defined targets.
• The method demonstrated effectiveness in solution optimality and rapid convergence compared to existing literature.

Conclusions:

• The proposed MFLP technique is effective for solving the multi-objective optimal power flow problem, especially with distributed generation.
• Optimal DG placement, when combined with the MFLP algorithm, yields the highest quality solutions.
• The approach offers a robust and efficient method for enhancing power system operation and stability.