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

## TL;DR

This paper introduces a dataset for load estimation in electric distribution systems using a pattern search method, tested on three standard distribution feeders.

## Contribution

A novel dataset and optimization method for load estimation using pattern search on IEEE distribution feeders.

## Key findings

- The dataset includes 96 scenarios with residential, commercial, and industrial demand profiles.
- Load estimation quality was evaluated using newly proposed indices for three distribution feeders.
- The dataset can be used for benchmarking future load estimation methods.

## Abstract

Accurately estimating load is essential for effective electric distribution planning, assets management, precise power flow predictions, accurate power losses calculations, and efficient integration of distributed energy resources. This work describes a dataset that was generated using Matlab and OpenDSS to produce several simulations in which load estimation is performed using a direct search method called pattern search. These simulations were conducted on three typical distribution feeders (IEEE 13-bus, 37-bus, and 123-bus) that support studies in distribution planning, assets management, power flow predictions, power losses calculations, and distributed resource integration. The dataset includes individual demand profiles of residential, commercial, and industrial consumers specified for the three distribution feeders, comprising 96 distinct scenarios. An optimization method was developed to obtain the dataset, which employs the pattern search technique to estimate loads through the optimization of objective functions and specified constraints. The load estimation quality was assessed for all three feeders, utilizing estimation quality indices proposed by the authors. These indices evaluated both the initial and proposed load estimation methods across the developed scenarios. Furthermore, the data provided in this article can be utilized for comparison with future load estimation studies, particularly regarding the quality of the method's results.