Envisioning security control in renewable dominated power systems through stochastic multi-period AC security constrained optimal power flow

TL;DR

This paper introduces a novel stochastic multi-period AC security constrained optimal power flow model to enhance N-1 security in renewable-dominated power systems, incorporating RES uncertainty, flexible loads, and energy storage.

Contribution

It extends existing deterministic models to a stochastic, multi-period framework, capturing RES variability and flexibility resources for improved security control.

Findings

Model effectively manages congestion and voltage in test systems.

Incorporates RES stochasticity and flexibility resources.

Pushes problem size to solver limits demonstrating model complexity.

Abstract

The accelerated penetration rate of renewable energy sources (RES) brings environmental benefits at the expense of increasing operation cost and undermining the satisfaction of the N-1 security criterion. To address the latter issue, this paper envisions N-1 security control in RES dominated power systems through stochastic multi-period AC security constrained optimal power flow (SCOPF). The paper extends the state-of-the-art, i.e. deterministic and single time period AC SCOPF, to capture two new dimensions, RES stochasticity and multiple time periods, as well as emerging sources of flexibility such as flexible loads (FL) and energy storage systems (ESS). Accordingly, the paper proposes and solves for the first time a new problem formulation in the form of stochastic multi-period AC SCOPF (S-MP-SCOPF). The S-MP-SCOPF is formulated as a non-linear programming (NLP) problem. It computes optimal setpoints of flexibility resources and other conventional control means for congestion management and voltage control in day-ahead operation. Another salient feature of this paper is the comprehensive and accurate modelling, using: AC power flow model for both pre-contingency and post-contingency states, inter-temporal constraints for resources such as FL and ESS in a 24-hours time horizon and RES uncertainties. The importance and performances of the proposed model through a direct approach, pushing the problem size up to the solver limit, are illustrated on two test systems of 5 nodes and 60 nodes, respectively, while future work will develop a tractable algorithm.