Optimal Control of DERs in ADN under Spatial and Temporal Correlated Uncertainties

TL;DR

This paper introduces an Ito process-based moment optimization approach for controlling distributed energy resources in active distribution networks, effectively handling complex spatial-temporal uncertainties with improved efficiency and performance.

Contribution

It proposes a unified Ito process model and a moment optimization method that significantly reduces computational complexity while managing correlated uncertainties in DER control.

Findings

Outperforms existing methods in accuracy and efficiency.

Reduces computational load comparable to deterministic problems.

Effective in large-scale distribution network applications.

Abstract

The control schemes of distributed energy resources (DERs) in active distribution networks (ADNs) are largely influenced by uncertainties. The uncertainties of DERs are complicated, containing spatial and temporal correlation, which makes it challenging to design proper control schemes, especially when there exist temporal-correlated units such as energy units (EUs). This paper provides an Ito process model to describe the characteristics of stochastic resources and EUs in a unified way, which makes it easy to evaluate the impacts of stochastic resources on temporal-correlated units. Based the moment form of the Ito process model, a moment optimization (MO) approach is provided to transform the stochastic control (SC) problem into an optimization problem with respect to the first-order and second-order moments of the system variables. The scale of MO is comparable to that of the corresponding deterministic control problem, which means that the computational efficiency of MO is much smaller than that of traditional approaches. Case studies also show that the proposed approach outperforms existing approaches in both the performance and computational efficiency, which means that the proposed approach has attractive potential for use in large-scale applications.