Ahmed Alkhonain

Ahmed Alkhonain, Kiran Kumar Challa, Amarsagar Reddy Ramapuram Matavalam et al.

The rapid growth of inverter-based resources (IBRs) and distributed energy resources (DERs) has fundamentally altered the long-term voltage stability characteristics of modern power systems. This article leverages the advantages of machine learning (ML) for the online estimation of long-term voltage stability margin (VSM) and enhancement of VSM through coordinated transmission system operator-distribution system operator (TSO-DSO) optimization. An explicit analytical VSM expression is derived from offline T&D co-simulation data using a physics-informed ML-trained model under probabilistic loading and generation mix scenarios, while accounting for unbalanced distribution modeling. The resulting closed-form VSM representation is linearized and embedded into the TSO optimization problem, enabling real-time enforcement of minimum VSM constraints. We further enhance operational efficiency by incorporating VSM sensitivities into both transmission and distribution optimization, allowing prioritization of the most influential reactive power resources. Simulation studies conducted on the IEEE 30-bus transmission network integrated with multiple IEEE 37-node distribution feeders validate that the proposed framework successfully achieves the desired VSM enhancement while maintaining high estimation accuracy.

Mohammad Almomani, Ahmed Alkhonain, Venkataramana Ajjarapu

The increasing integration of Distributed Energy Resources (DERs) in distribution networks presents new challenges for voltage regulation and reactive power support. This paper extends a sensitivity-aware reactive power dispatch algorithm tailored to manage smart inverters operating under different control modes, including PQ, PV, and Volt-Var (VV). The proposed approach dynamically optimizes reactive power dispatch and voltage setpoints, enabling effective coordination among distribution systems as a virtual power plant (VPP) to support the transmission network. The algorithm is applied to the IEEE 13-bus and IEEE-123 bus test systems, and its performance is validated by comparing results with OpenDSS simulations across various operating scenarios. Results show that the maximum error in the voltages is less than 0.015 pu.

Mohammad Almomani, Ahmed Alkhonain, Venkataramana Ajjarapu

This paper presents TSO-DSO coordinated reactive power dispatch, with a focus on real-time implementation. A sensitivity-aware, mixed-integer linear programming (MILP) formulation is developed to model the IEEE 1547-compliant droop-based control modes Volt VAR (VV), Volt Watt (VW), and Watt VAR (WV) of smart inverters. The algorithm employs a hierarchical optimization strategy using Special Ordered Sets (SOS1) to enhance computational efficiency and supports limited measurement scenarios through Recursive Least Squares (RLS) estimation. The proposed method is tested on the IEEE 13-bus and 123-bus distribution networks, which are connected to a 9-bus transmission system. Results demonstrate the feasibility and effectiveness of the real-time dispatch framework in improving voltage regulation and minimizing power curtailment.