Mixed-integer Second-Order Cone Programming for Multi-period Scheduling of Flexible AC Transmission System Devices

TL;DR

This paper presents a mixed-integer second-order cone programming model for multi-period scheduling of FACTS devices in power systems, aiming to reduce losses while ensuring operational constraints are met.

Contribution

It introduces a novel MISOCP model that integrates multiple FACTS devices with device-specific constraints and a multi-period framework for efficient grid operation.

Findings

Model reduces active power losses in test systems.

Demonstrates effectiveness of multi-period scheduling for FACTS devices.

Applicable to larger power grids with similar benefits.

Abstract

With the increasing energy demand and the growing integration of renewable sources of energy, power systems face operational challenges such as overloads, losses, and stability concerns, particularly as networks operate near their capacity limits. Flexible alternating current transmission system (FACTS) devices are essential to ensure reliable grid operations and enable the efficient integration of renewable energy. This work introduces a mixed-integer second-order cone programming (MISOCP) model for the multi-period scheduling of key FACTS devices in electric transmission systems. The proposed model integrates four key control mechanisms: (i) on-load tap changers (OLTCs) for voltage regulation via discrete taps; (ii) static synchronous compensators (STATCOMs) and (iii) shunt reactors for reactive power compensation; and (iv) thyristor-controlled series capacitors (TCSCs) for adjustable impedance and flow control. The objective is to minimize active power losses using a limited number of control actions while meeting physical and operational constraints at all times throughout the defined time horizon. To ensure tractability, the model employs a second-order cone relaxation of the power flow. Device-specific constraints are handled via binary expansion and linearization: OLTCs and shunt reactors are modelled with discrete variables, STATCOMs through reactive power bounds, and TCSCs using a reformulation-linearization technique (RLT). A multi-period formulation captures the sequential nature of decision making, ensuring consistency across time steps. The model is evaluated on the IEEE 9-bus, 30-bus, and RTS96 test systems, demonstrating its ability to reduce losses, with potential applicability to larger-scale grids.