Dynamic arithmetic optimization algorithm control of distributed generations for demand balancing and enhancing power...

Area of Science:

• Electrical Engineering
• Power Systems Analysis
• Optimization Techniques

Background:

• Unbalanced power systems lead to equipment overheating, increased energy losses, and protective device malfunction.
• Maintaining power quality and system stability is crucial for reliable electricity distribution.
• Distributed generators (DG) offer a solution for power system balancing and quality improvement.

Purpose of the Study:

• To develop and evaluate an optimization-based control technique for DG to mitigate imbalances in distribution systems.
• To improve voltage, power, and current quality factors (VUF, PUF, CUF) in imbalanced power grids.
• To minimize power losses and enhance the voltage profile in distribution networks.

Main Methods:

• Utilized Particle Swarm Optimization (PSO) and Dynamic Arithmetic Optimization Algorithm (DAOA) for DG placement, sizing, and power factor determination.
• Applied optimization algorithms to three imbalanced distribution systems (10, 13, and 37 nodes) under full load and daily operating conditions.
• Assessed voltage, power, and current imbalance factors (VUF, PUF, CUF) against ANSI and IEEE standards.

Main Results:

• Optimization techniques successfully reduced voltage imbalance factors (VUF) below standard criteria across all systems.
• Achieved significant reductions in power imbalance factors (PUF) from initial values (116%, 28%, 17%) to near zero.
• Demonstrated substantial improvements in current imbalance factors (CUF), alongside power loss reductions of 80%, 51%, and 52% for the respective systems.
• Enhanced voltage profiles and reduced voltage variance were observed in all studied systems.

Conclusions:

• The proposed optimization-based DG control effectively balances imbalanced power systems, enhancing overall power quality.
• PSO and DAOA are viable algorithms for determining optimal DG parameters to address system imbalances and reduce losses.
• The implemented strategy significantly improves system reliability and operational efficiency by mitigating voltage, current, and power quality issues.