Santiago Grijalva

Santiago Grijalva
Georgia Institute of Technology | GT · School of Electrical & Computer Engineering

About

194
Publications
41,373
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3,080
Citations

Publications

Publications (194)
Conference Paper
Full-text available
Frequent changes in penetration levels of distributed energy resources (DERs) and grid control objectives have caused the maintenance of accurate and reliable grid models for behind-the-meter (BTM) photovoltaic (PV) system impact studies to become an increasingly challenging task. At the same time, high adoption rates of advanced metering infrastru...
Preprint
This paper addresses the conditions for estimation of sensitivities of voltage magnitudes with respect to complex (active and reactive) electric power injections based on sensor measurements. These sensitivities represent submatrices of the inverse power flow Jacobian. We extend previous results to show that the sensitivities of a bus voltage magni...
Conference Paper
Full-text available
Incorrect modeling of control characteristics for inverter-based resources (IBRs) can affect the accuracy of electric power system studies. In many distribution system contexts, the control settings for behind-the-meter (BTM) IBRs are unknown. This paper presents an efficient method for selecting a small number of time series samples from net load...
Conference Paper
Full-text available
Identifying the location of faults in a fast and accurate manner is critical for effective protection and restoration of distribution networks. This paper describes an efficient method for detecting, localizing, and classifying faults using advanced signal processing and machine learning tools. The method uses an Isolation Forest technique to detec...
Technical Report
Full-text available
This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring...
Conference Paper
Full-text available
Advanced solar PV inverter control settings may not be reported to utilities, or may be changed without notice. This paper develops an estimation method for determining a fixed power factor control setting of a behind-the-meter (BTM) solar PV smart inverter. The estimation is achieved using linear regression methods with historical net load advance...
Presentation
Full-text available
This presentation summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to...
Article
This article proposes a supervised learning approach for centralized localization of faults in microgrids with radial configuration that can operate in grid-connected or islanded mode. The key concept is to identify faults by learning and analyzing the features of voltage and current disturbances detected by a microgrid central protection unit. Two...
Technical Report
Expectations for the future role of energy storage resources in the electric sector have increased in recent years, as technological developments have been accompanied by policy support. However, energy storage technologies have complex cost, value, and performance characteristics that make them challenging to model. This analysis aims to determin...
Conference Paper
Full-text available
High penetration of solar photovoltaics can have a significant impact on the power flows and voltages in distribution systems. In order to support distribution grid planning, control and optimization, it is imperative for utilities to maintain an accurate database of the locations and sizes of PV systems. This paper extends previous work on methods...
Article
Full-text available
This paper presents a new method for the estimation of the injection state and power factor of distributed energy resources (DERs) using voltage magnitude measurements only. A physics-based linear model is used to develop estimation heuristics for net injections of real and reactive power at a set of buses under study, allowing a distribution engin...
Article
Full-text available
The progression of cyber-attacks on the cyber-physical system is analyzed by the Probabilistic, Learning Attacker, and Dynamic Defender (PLADD) model. Although our research does apply to all cyber-physical systems, we focus on power grid infrastructure. The PLADD model evaluates the effectiveness of moving target defense (MTD) techniques. We consid...
Conference Paper
Full-text available
This paper describes an efficient method to determine the location of solar PV systems in distribution circuits, based on voltage magnitude measurement streams. The method leverages the impact of solar injection variations on the circuit voltages. The estimation model enables recovering the most likely location of PV system based on the distributio...
Technical Report
Full-text available
The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the...
Conference Paper
Networked protection systems use information, communication and computation technologies to collect and process sensor data from spatially distributed sensors, and launch protective and control actions by sending commands to local devices. Such protection systems are also capable of supporting specialized tasks including asset control and backup pr...
Article
This paper is the second part of a two-part paper on communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. Part I of this paper proposed the distributed architecture and algorithmic development, while this Part II provides the corresponding algorithmic impl...
Article
There is an ever-growing number of photovoltaic (PV) installations in the US and worldwide. Many utilities do not have complete or up-to-date information of the PVs present within their grids. This research presents a deep neural network approach for estimating PV size, tilt, and azimuth using only behind-the-meter data. It is found that the propos...
Conference Paper
Full-text available
This paper presents an optimization approach to maximize the value of behind-the-meter energy storage that is owned and operated by customers. The objective of the optimization problem is to minimize the customer's electricity bill under various utility tariff rates. Each rate structure results in different options for the formulation of the optimi...
Article
Distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electricity grid. Distributed algorithms rely on the communication network for exchanging information. Failures in the communication network c...
Article
The area of building energy management has received a significant amount of interest in recent years. This area is concerned with combining advancements in sensor technologies, communications and advanced control algorithms to optimize energy utilization. Reinforcement learning is one of the most prominent machine learning algorithms used for contr...
Conference Paper
Full-text available
Significant changes in the regulatory environment, coupled with economic viability, has led various electric utilities to consider distributed photovoltaic (PV) systems as an alternative to traditional circuit upgrades. Increased penetration of distributed PV can result in the overload of the distribution system infrastructure, which can lead to pr...
Preprint
The area of building energy management has received a significant amount of interest in recent years. This area is concerned with combining advancements in sensor technologies, communications and advanced control algorithms to optimize energy utilization. Reinforcement learning is one of the most prominent machine learning algorithms used for contr...
Preprint
Full-text available
Collecting, analyzing and gaining insight from large volumes of data is now the norm in an ever increasing number of industries. Data analytics techniques, such as machine learning, are powerful tools used to analyze these large volumes of data. Synthetic data sets are routinely relied upon to train and develop such data analytics methods for sever...
Preprint
Full-text available
The area of building energy management has received a significant amount of interest in recent years. This area is concerned with combining advancements in sensor technologies, communications and advanced control algorithms to optimize energy utilization. Reinforcement learning is one of the most prominent machine learning algorithms used for contr...
Article
The Smart Grid (SG) is vulnerable to cyber-attacks due to its integration with a variety of information, communication and control technologies. If undetected by deployed security systems, cyber-attacks could damage critical power system infrastructure and disrupt service to a very large number of energy customers. In particular, cyber-attackers co...
Conference Paper
Full-text available
Quasi-static time-series (QSTS) simulation provides an accurate method to determine the impact that new PV interconnections including control strategies would have on a distribution feeder. However, the QSTS computational time currently makes it impractical for use by the industry. A vector quantization approach [1-2] leverages similarities in powe...
Conference Paper
Distributed energy resource (DER) hosting capacity of distribution feeders is commonly analyzed with scenario-based methods assuming specific load conditions. For feeders with existing DER, additional processing is necessary to capture conditions of these DERs, that can impact hosting capacity indicators. Only modeling min/max scenarios for the loa...
Conference Paper
Full-text available
Fast deployment of renewable energy resources in distribution networks, especially solar photovoltaic (PV) systems, have motivated the need for inverter-based voltage regulation. Integration studies are often necessary to fully understand the potential impacts of PV inverter settings on the various elements of the distribution system, including vol...
Article
Full-text available
Understanding the impact of distributed photovoltaic (PV) resources on various elements of the distribution feeder is imperative for their cost effective integration. A year-long Quasi-Static Time Series (QSTS) simulation at 1-second granularity is often necessary to fully study these impacts. However, the significant computational burden associate...
Article
The output power of distributed energy resources (DERs) may experience irregular fluctuations due to variations of renewable sources, which need to be monitored in order to reliably control the grid. This paper proposes a novel approach for centralized detection of such irregularities based on the time-series analysis of the data reported by phasor...
Article
The rapidly growing penetration levels of distributed photovoltaic (PV) systems requires more comprehensive studies to understand their impact on distribution feeders. IEEE P.1547 highlights the need for Quasi-Static Time Series (QSTS) simulation in conducting distribution impact studies for distributed resource interconnection. Unlike conventional...
Chapter
Integration of large amounts of renewable energy in electric power networks must address emerging behavior at new spatial and temporal scales. It must also address factors or dimensions, associated with resource availability, economic viability, social management, grid aspects, and regional objectives. This chapter starts by reviewing the relevant...
Conference Paper
Full-text available
It has now become critical and important to understanding the nature of cyber-attacks and their impact on the physical operation of emerging smart electricity grids. Modeling and simulation provide a cost-effective means to develop frameworks and algorithms that address cyber-physical security challenges facing the smart grid. Existing simulation t...
Article
Full-text available
In this paper, we propose a multi-agent based distributed algorithm for enhanced frequency response in large scale multi-area power systems. Control nodes associated with these areas preemptively agree on their relative contributions in supporting the frequency response, in a completely distributed manner. Consequently, in case of system contingenc...
Article
In this work, we develop a mathematical model and framework to represent rolling-horizon unit commitment (UC) processes with multiple periodicities. In control center operations, UC is solved repeatedly to adjust device commands based on new information about load, generation availability, renewable energy production, and other aspects of system st...
Article
Deploying microgrids with the capability of islanding and self-supply can considerably enhance power system resilience in coping with weather events. To this end, practical methods are needed in order to operationally position and manage the microgrid to optimally control its resources and minimize the risk in the face of such disturbances. This pa...
Conference Paper
Energy storage systems (ESS) have gained interest due to the benefits they can offer by increasing the flexibility of the grid. However, the economics behind them is very complex and uncertain. Storage technologies can act as a player to coordinate production and demand, hence changing the just-in-time balancing requirements. As energy policies und...
Conference Paper
Full-text available
Yearlong quasi-static time series (QSTS) simulations at second-level granularity are required to accurately model controller devices and determine the impact of PV resources on distribution systems. However, the computational time for running such simulations takes 10 to 120 hours for a realistic-sized distribution feeder. This long simulation time...
Conference Paper
Full-text available
Quasi-static time-series (QSTS) provides the necessary simulation fidelity on the impact that new energy resources would have on a specific distribution system feeder. However, this simulation can often take 10-120 hours for a single study, on traditional computers. The vector quantization approach proposed in [1] demonstrated very attractive compu...
Conference Paper
Full-text available
The industry has recognized the risk of cyber-attacks targeting to the advanced metering infrastructure (AMI). A potential adversary can modify or inject malicious data, and can perform security attacks over an insecure network. Also, the network operators at intermediate devices can reveal private information, such as the identity of the individua...
Technical Report
Full-text available
The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and th...