Controlled Evolution-Based Day-Ahead Robust Dispatch Considering Frequency Security with Frequency Regulation Loads and Curtailable Loads

TL;DR

The paper tackles the non-convex maximum frequency deviation constraint and causality gaps in day-ahead dispatch under high renewable penetration.It introduces a convex relaxation framework that converts the max-frequency deviation into a set of hyperplane constraints, enabling tractable optimization.A two-layer evolution-based robust dispatch framework is proposed: a day-ahead decision layer with a min–max–min objective and an evolution layer that tests intraday feasibility under adverse renewable scenarios, using corrective cuts to refine decisions.A controlled-evolution algorithm employing gradient-based cuts and a correction set improves day-ahead decisions, with case studies on a modified IEEE-14 bus system showing enhanced frequency security and reliability.

Abstract

With the extensive integration of volatile and uncertain renewable energy, power systems face significant challenges in primary frequency regulation due to instantaneous power fluctuations. However, the maximum frequency deviation constraint is inherently non-convex, and commonly used two-stage dispatch methods overlook causality, potentially resulting in infeasible day-ahead decisions. This paper presents a controlled evolution-based day-ahead robust dispatch method to address these issues. First, we suggest the convex relaxation technique to transform the maximum frequency deviation constraint to facilitate optimization. Then, an evolution-based robust dispatch framework is introduced to align day-ahead decisions with intraday strategies, ensuring both frequency security and power supply reliability. Additionally, a novel controlled evolution-based algorithm is developed to solve this framework efficiently. Case studies on a modified IEEE 14-bus system demonstrate the superiority of the proposed method in enhancing frequency security and system reliability.

Figures (7)

• Figure 1: The evolution-based robust dispatch framework.
• Figure 2: The dispatch algorithm for the framework.
• Figure 3: Renewable power range and total load demand curve.
• Figure 4: Imbalance power before and after controlled evolution.
• Figure 5: UC before and after the controlled evolution.