Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system...

Area of Science:

• Electrical Engineering
• Power Systems
• Optimization Algorithms

Background:

• Distributed generation (DG) integration is crucial for enhancing electricity distribution network (EDN) performance, power quality, and reliability.
• Optimal placement and sizing of DG units are essential for maximizing benefits and mitigating potential issues like voltage instability and protection system challenges.
• Existing optimization methods may face limitations in handling complex, multimodal problems and avoiding local optima in DG integration studies.

Purpose of the Study:

• To develop and evaluate a hybrid technique integrating a modified grey wolf optimization (MGWO) algorithm with ETAP software for optimal DG placement and sizing.
• To minimize active and reactive power losses (APL and RPL) and improve voltage stability (VS) in EDNs.
• To analyze the impact of DG integration on fault current variations and ensure protection system adaptability.

Main Methods:

• A modified grey wolf optimization (MGWO) algorithm, featuring adaptive weights and dynamic circling, was developed to improve exploration and exploitation balance.
• The MGWO algorithm was integrated with MATLAB and the Electrical Transient Analysis Program (ETAP) for security analysis and optimal DG placement/sizing.
• Simulations were conducted on IEEE 33-bus and 114-bus distribution networks, with load flow analysis performed using the Newton-Raphson method.

Main Results:

• The proposed MGWO-ETAP approach achieved significant reductions in power losses (up to 69.7% in the 33-bus system, 65.2% APL in the 114-bus system) and enhanced voltage stability (7.3% in the 33-bus system, 6.5% in the 114-bus system).
• DG integration led to considerable fault current variations, with maximum fault current (I_max) increasing by up to 21.5%, necessitating adjustments in protection strategies.
• The MGWO-ETAP technique outperformed traditional and advanced metaheuristic algorithms in power loss minimization and maintaining system stability.

Conclusions:

• The hybrid MGWO-ETAP technique provides an effective global solution for optimizing DG placement and sizing while ensuring adaptive protection controls.
• This approach ensures reliable and efficient DG integration into complex power systems, addressing challenges related to power loss, voltage stability, and fault current.
• The study highlights the importance of considering protection system adaptability when integrating DG units to maintain overall network security and performance.