Optimized placement and sizing of solar photovoltaic distributed generation using jellyfish search algorithm for...

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Optimization Algorithms

Background:

• Distributed generation (DG) integration is crucial for modern power systems.
• Optimizing DG placement impacts network efficiency and stability.
• Existing methods face challenges with complex network constraints.

Purpose of the Study:

• To develop and validate an advanced metaheuristic framework for optimal DG placement and sizing.
• To minimize real power loss (RPL), reduce voltage deviation index (VDI), and enhance voltage stability index (VSI).
• To employ the Jellyfish Search Algorithm (JSA) for multi-objective optimization in distribution power networks (DPNs).

Main Methods:

• Formulation of a multi-objective function using a weighted sum approach (WSA).
• Application of the Jellyfish Search Algorithm (JSA) for optimal placement and sizing of solar photovoltaic (PV) DG units.
• Validation on the IEEE 33-bus radial DPN with single, double, and triple PV system deployments.

Main Results:

• Significant reduction in Real Power Loss (RPL): from 210.98 kW to as low as 69.59 kW.
• Substantial decrease in Voltage Deviation Index (VDI): from 1.8047 p.u. to 0.3293 p.u.
• Marked improvement in Voltage Stability Index (VSI): minimum VSI increased from 0.6671 to 0.8916.

Conclusions:

• The JSA demonstrates superior performance compared to other metaheuristic algorithms.
• The proposed framework effectively enhances DPN efficiency, voltage profiles, and stability.
• JSA offers a robust solution for complex DG integration challenges.