# Guido CavraroNational Renewable Energy Laboratory | NREL

Guido Cavraro

Phd

## About

66

Publications

6,295

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1,574

Citations

Introduction

Additional affiliations

August 2018 - present

October 2016 - March 2018

February 2015 - January 2017

## Publications

Publications (66)

We investigate the stability and robustness properties of a power transmission system under persistent deceiving attacks on inverter-interfaced energy resources. The attacks can corrupt the damping coefficients in the inverters controllers and measurements of the frequency at the points of coupling. Leveraging tools from hybrid dynamical systems th...

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal ob...

Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met. Nevertheless, unexpected or prolonged abnormal events could undermine the grids functioning. During contingencies, customers could contribute effectively to sustaining the network by providing se...

We propose an operating envelopes (OEs) aware energy community market mechanism that dynamically charges/rewards its members based on two-part pricing. The OEs are imposed exogenously by a regulated distribution system operator (DSO) on the energy community's revenue meter and is subject to a generalized net energy metering (NEM) tariff design. By...

We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power setpoints that approximate optimal power flow (OPF) solutions. We propose an incremental control algorithm an...

This paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The
first
stage involves learnin...

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distributio...

We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power setpoints that approximate optimal power flow (OPF) solutions. We propose an incremental control algorithm an...

This paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution networks (DNs). Aiming to improve DN operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learni...

State estimation is a fundamental task in power systems. Although distribution systems are increasingly equipped with sensing devices and smart meters, measurements are typically reported at different rates and asynchronously; these aspects pose severe strains on workhorse state estimation algorithms, which are designed to process batches of data c...

This paper considers the problem of voltage regulation in distribution networks. The primary motivation is to keep voltages within preassigned operating limits by commanding the reactive power output of distributed energy resources (DERs) deployed in the grid. We develop a framework for developing local Volt/Var control that comprises two main step...

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distributio...

In this paper, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking o...

In this paper, we study the monitoring and control of long-term voltage stability considering load tap changer (LTC) dynamics. We show that under generic conditions, the LTC dynamics admit a unique stable equilibrium. For the stable equilibrium, we characterize an explicit inner approximation of its largest region of attraction (ROA). Compared to e...

This paper proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requ...

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficien...

This paper proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions which combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination req...

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events. Purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven...

Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this...

In this paper, we study the monitoring and control of long-term voltage stability considering load tap-changer (LTC) dynamics. We show that under generic conditions, the LTC dynamics always admit a unique stable equilibrium. For the stable equilibrium, we characterize an explicit inner approximation of its region of attraction (ROA). Compared to ex...

Deep learning for distribution grid optimization can be advocated as a promising solution for near-optimal yet timely inverter dispatch. The principle is to train a deep neural network (DNN) to predict the solutions of an optimal power flow (OPF), thus shifting the computational effort from real-time to offline. Nonetheless, before training this DN...

The paper investigates the problem of estimating the state of a network from heterogeneous sensors with different sampling and reporting rates. In lieu of a batch linear least-squares (LS) approach, well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix, the paper proposes a...

Recovering the distribution grid topology is essential to perform several distribution system operator functions. Many algorithms that address the topology recovery problem have already been proposed in the literature. Most are based on a priori information regarding which buses are fed by which substation; however, this information might not be av...

Although knowing the feeder topology and line impedances is a prerequisite for solving any grid optimization task, utilities oftentimes have limited or outdated information on their electric network assets. Given the rampant integration of smart inverters, we have previously advocated perturbing their power injections to unveil the underlying grid...

We address the problem of multi-agent partition-based convex optimization which arises, for example, in robot localization problems and in regional state estimation in smart grids. More specifically, the global cost function is the sum of locally coupled cost functions that depend only on each agent variables and their neighbors’ variables. Inspire...

This paper proposes a technique to control distributed energy resources in low-voltage microgrids aiming at (i) allowing power flow control at the point of connection with the upstream grid, (ii) keeping voltage profiles within the operational limits. The first feature is crucial in smart low-voltage power systems. In fact, it enables both demand-r...

Recovering the distribution grid topology in real time is essential to perform several distribution system operator (DSO) functions. DSOs often do not have any direct monitoring of switch statuses to track reconfiguration. At the same time, installing real-time meters at a large number of buses is challenging due to the cost of endowing every meter...

We consider the problem of regulating the voltage profile of a power distribution grid by controlling the reactive power injection of distributed microgenerators. We define a very general class of purely local feedback controllers in which reactive power injection is adjusted based on the local voltage measurements. This class includes most of the...

Although knowing the feeder topology and line impedances is a prerequisite for solving any grid optimization task, utilities oftentimes have limited or outdated information on their electric network assets. Given the rampant integration of smart inverters, we have previously advocated perturbing their power injections to unveil the underlying grid...

To perform any meaningful optimization task, power distribution operators need to know the topology and line impedances of their electric networks. Nevertheless, distribution grids currently lack a comprehensive metering infrastructure. Although smart inverters are widely used for control purposes, they have been recently advocated as the means for...

Knowing the connectivity and line parameters of the underlying electric distribution network is a prerequisite for solving any grid optimization task. Although distribution grids lack observability and comprehensive metering, inverters with advanced cyber capabilities currently interface solar panels and energy storage devices to the grid. Smart in...

This paper proposes a novel method for topology detection in distribution networks called the Time-Series Signature Verification Method for Topology Detection (TSV-Top). The TSV-Top analyzes data from phasor measurement units (PMU or μPMU) installed on power distribution feeders. The TSVTop relies on the fact that measurement data time series from...

We address the problem of distributed convex unconstrained optimization over networks characterized by asynchronous and possibly lossy communications. We analyze the case where the global cost function is the sum of locally coupled local strictly convex cost functions. As discussed in detail in a motivating example, this class of optimization objec...

In this paper we consider a voltage control problem in power distribution grids. The specific goal is that of keeping the voltages within pre-assigned operating limits by commanding the reactive power output of the micro-generators connected to the grid. We propose three strategies. The first two strategies are purely local, meaning that each micro...

Distribution grids constitute complex networks of lines often times reconfigured to minimize losses, balance loads, alleviate faults, or for maintenance purposes. Topology monitoring becomes a critical task for optimal grid scheduling. While synchrophasor installations are limited in low-voltage grids, utilities have an abundance of smart meter dat...

We consider the problem of exploiting the micro-generators connected to the power distribution grid to provide distributed reactive power compensation for voltage support. We review some of the state-of-the-art control strategies, compare and analyze their performance. Furthermore, we propose a novel control strategy that, exploiting communications...

We address the problem distributed quadratic programming under lossy communications where the global cost function is the sum of coupled local cost functions, typical in localization problems and partition-based state estimation. We propose a novel solution based on a generalized gradient descent strategy, namely a Block-Jacobi descent algorithm, w...

This paper proposes a novel approach for detecting the topology of
distribution networks based on the analysis of time series measurements. The
time-based analysis approach draws on data from high-precision phasor
measurement units (PMUs or synchrophasors) for distribution systems. A key fact
is that time-series data taken from a dynamic system sho...

This paper proposes a data-driven approach to detect the switching actions
and topology transitions in distribution networks. It is based on the real time
analysis of time-series voltages measurements. The analysis approach draws on
data from high-precision phasor measurement units ($\mu$PMUs or synchrophasors)
for distribution networks. The key fa...

This paper proposes a novel approach to detectingthe topology of distribution networks based on the analysisof time series measurements. The analysis approach draws ondata from high-precision phasor measurement units (PMUs orsynchrophasors) for distribution systems. A key fact is that time-series data taken from a dynamic system show speciﬁc patter...

We consider the problem of minimizing the power generation cost by exploiting the distributed renewable energy sources (DRES) located in the power distribution network. The proposed strategy requires that the intelligent agents, located at the microgenerator buses, measure their voltage and then adjust the amount of injected power, according to a f...

Network topology in distribution networks is often unknown, because most
switches are not equipped with measurement devices and communication links.
However, knowledge about the actual topology is critical for safe and reliable
grid operation. This paper proposes a voting-based topology detection method
based on micro-synchrophasor measurements. Th...

We consider the problem of exploiting the microgenerators connected to the power distribution network to provide distributed reactive power compensation for power losses minimization and voltage support. The proposed strategy relies on the fact that all the intelligent agents, located at the microgenerator buses, can measure their voltage, communic...

Smart grids are a novel paradigm for energy distribution, where instead of the traditional directed flow from a producer to the consumers, several micro-generators are spread throughout the network. We focus on the problem of coordinating the injection of active power into the grid by the micro-generators. Each of them aims at injecting the maximum...

We consider the problem of exploiting the microgenerators dispersed in the
power distribution network in order to provide distributed reactive power
compensation for power losses minimization and voltage regulation. In the
proposed strategy, microgenerators are smart agents that can measure their
phasorial voltage, share these data with the other a...

We consider the problem of exploiting the microgenerators dispersed in
the power distribution network in order to provide distributed reactive
power compensation for power losses minimization and voltage support.
The proposed strategy requires that all the intelligent agents, located
at the microgenerator buses, measure their voltage and share thes...

We consider the problem of exploiting the microgenerators dispersed in the power distribution network in order to provide distributed reactive power compensation for power losses minimization. The proposed strategy requires that all the intelligent agents, located at the microgenerator buses, measure their voltage and share these data with the othe...

We consider the problem of exploiting the microgenerators connected to the low voltage or medium voltage grid in order to provide distributed reactive power compensation in the power distribution network, solving the optimal reactive power flow problem for the minimization of power distribution losses subject to voltage constraints. The proposed st...

We consider the problem of dynamic reactive power compensation in power distribution networks populated by a large number of microgeneration devices. We model the power losses minimization problem in the case of stochastic, time-varying reactive power demands. For this control problem, we propose a randomized iterative optimization algorithm, and w...

We consider the scenario of a low voltage microgrid populated by a number of distributed microgenerators. We focus on the problem of obtaining a dynamic model that describes the input-output relation between complex power commands sent to the microgenerator inverters and the voltage measurements across the network. Such a model is intended as a nec...