Load estimation data using direct search method based on pattern search.

Area of Science:

• Electrical Engineering
• Computational Methods

Background:

• Accurate electric load estimation is crucial for efficient power system operations.
• Key applications include distribution planning, asset management, power flow, loss calculations, and distributed energy resource integration.

Purpose of the Study:

• To generate a comprehensive dataset for electric load estimation.
• To evaluate the effectiveness of the pattern search method for load estimation.

Main Methods:

• Simulations performed using Matlab and OpenDSS on IEEE 13, 37, and 123-bus distribution feeders.
• Load estimation utilized a pattern search direct search method.
• Dataset comprises 96 scenarios with individual consumer demand profiles (residential, commercial, industrial).

Main Results:

• A dataset with 96 distinct scenarios for load estimation was generated.
• The pattern search method was applied to estimate loads on three typical feeders.
• Load estimation quality was assessed using author-proposed indices.

Conclusions:

• The developed dataset and method provide a valuable resource for load estimation studies.
• The data facilitates comparison with future load estimation techniques.
• The findings support improved power system planning and management.