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20202023
most citedInterpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations

3 citations · 6 across the 9 of their papers we have counts for

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eess.SY2023

Physics Informed Neural Networks for Phase Locked Loop Transient Stability Assessment

Rahul Nellikkath, Andreas Venzke, Mohammad Kazem Bakhshizadeh +2

A significant increase in renewable energy production is necessary to achieve the UN's net-zero emission targets for 2050. Using power-electronic controllers, such as Phase Locked…

eess.SY2022★ 1 cited

Optimal Design of Volt/VAR Control Rules for Inverter-Interfaced Distributed Energy Resources

Ilgiz Murzakhanov, Sarthak Gupta, Spyros Chatzivasileiadis +1

The IEEE 1547 Standard for the interconnection of distributed energy resources (DERs) to distribution grids provisions that smart inverters could be implementing Volt/VAR control r…

eess.SY2022★ 3 cited

Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations

Robert I. Hamilton, Jochen Stiasny, Tabia Ahmad +5

Interpretable Machine Learning (IML) is expected to remove significant barriers for the application of Machine Learning (ML) algorithms in power systems. This letter first seeks to…

eess.SY2022

A Novel Decentralized Inverter Control Algorithm for Loss Minimization and LVRT Improvement

Ilgiz Murzakhanov, Gururaj Mirle Vishwanath, Vemalaiah Kasi +3

Algorithms that adjust the reactive power injection of converter-connected RES to minimize losses may compromise the converters' fault-ride-through capability. This can become cruc…

eess.SY2021

Priority Lists for Power System Investments: Locating Phasor Measurement Units

Ilgiz Murzakhanov, David Pozo

Power systems incrementally and continuously upgrade their components, such as transmission lines, reactive capacitors, or generating units. Decision-making tools often support the…

eess.SY2020★ 1 cited

Decentralized Model-free Loss Minimization in Distribution Grids with the Use of Inverters

Ilgiz Murzakhanov, Spyros Chatzivasileiadis

Distribution grids are experiencing a massive penetration of fluctuating distributed energy resources (DERs). As a result, the real-time efficient and secure operation of distribut…

eess.SY2020

Extended Mathematical Derivations: Decentralized Model-free Loss Minimization in Distribution Grids with the Use of Inverters

Ilgiz Murzakhanov, Spyros Chatzivasileiadis

This document contains extended mathematical derivations for the communication-free and model-free algorithms that can actively control converter-connected devices, and can operate…