Multi-Area Interchange Scheduling under Uncertainty

TL;DR

This paper introduces a stochastic optimization method for multi-area interchange scheduling that effectively manages uncertainty in renewable energy and load, ensuring optimality and convergence.

Contribution

It proposes a novel iterative scheduling algorithm for multi-proxy bus systems that guarantees optimality and convergence under uncertainty.

Findings

Algorithm converges under both synchronous and asynchronous updates.

Effectively captures renewable generation and load uncertainties.

Provides a robust scheduling framework for multi-area systems.

Abstract

The problem of multi-area interchange scheduling under system uncertainty is considered. A new scheduling technique is proposed for a multi-proxy bus system based on stochastic optimization that captures uncertainty in renewable generation and stochastic load. In particular, the proposed algorithm iteratively optimizes the interface flows using a multidimensional demand and supply functions. Optimality and convergence are guaranteed for both synchronous and asynchronous scheduling under nominal assumptions.