The Optimal Division of the Energy Market into Zones: Comparison of Two Methodologies under Variable Wind Conditions

TL;DR

This paper compares two methodologies for dividing energy markets into zones under variable wind conditions, aiming to maximize social welfare by analyzing congestion and locational prices.

Contribution

It introduces a comparative analysis of clustering and congestion-based methods for optimal market zoning under wind variability.

Findings

Consensus clustering effectively identifies zones with higher welfare gains.

Congestion contribution method provides a different zoning approach under variable wind scenarios.

Both methods improve social welfare compared to uniform market division.

Abstract

We compare two competing methodologies of market zones identification under the criterion of social welfare maximization: (i) consensus clustering of Locational Marginal Prices over different wind scenarios and (ii) congestion contribution identification with congested lines identified across variable wind generation outputs. We test the division of market into zones based on each of the two methodologies using a welfare criterion, i.e., comparing the cost of supplying energy on uniform market (including readjustments made on a balancing market to overcome the congestion) with cost on k-zone market. A division which maximizes the welfare is considered as the optimum.