An Efficient Primal-Dual Approach to Chance-Constrained Economic Dispatch

TL;DR

This paper proposes an efficient primal-dual method for solving chance-constrained economic dispatch problems in microgrids, effectively managing renewable energy variability and ensuring reliable operation.

Contribution

It introduces a novel primal-dual approach that bypasses complex distribution modeling to efficiently solve joint chance constraints in microgrid energy scheduling.

Findings

The method achieves reliable microgrid dispatch with reduced computational complexity.

Numerical results demonstrate the approach's effectiveness in handling renewable variability.

The approach provides a practical solution for risk-aware energy management in microgrids.

Abstract

To effectively enhance the integration of distributed and renewable energy sources in future smart microgrids, economical energy management accounting for the principal challenge of the variable and non-dispatchable renewables is indispensable and of significant importance. Day-ahead economic generation dispatch with demand-side management for a microgrid in islanded mode is considered in this paper. With the goal of limiting the risk of the loss-of-load probability, a joint chance constrained optimization problem is formulated for the optimal multi-period energy scheduling with multiple wind farms. Bypassing the intractable spatio-temporal joint distribution of the wind power generation, a primal-dual approach is used to obtain a suboptimal solution efficiently. The method is based on first-order optimality conditions and successive approximation of the probabilistic constraint by generation of p-efficient points. Numerical results are reported to corroborate the merits of this approach.