Masood Parvania

University of Utah | UOU · Department of Electrical and Computer Engineering

This paper proposes a model for optimizing the energy flexibility of water distribution systems (WDSs) in day-ahead power systems operation. The water distribution system operators (W-DSOs) are considered as energy-conscious entities, who run the proposed WDS operation model to optimize the operation of pumps and tanks for minimizing the operation...

This paper defines flexibility reserve trajectory as a single reserve product that not only supplies the energy imbalance in real-time operation but also the resulting ramping requirements by embedding the flexible ramping trajectories as time derivative of the reserve trajectories. Further, a stochastic optimization model is proposed for multi-fid...

Automating the process of restoring service to customers after a large-scale outage event have significant impacts on the agility and speed of recovery in distribution systems. This paper develops a set of probabilistic metrics to assess the impact of automation in enhancing the resilience of power distributions systems. The proposed metrics captur...

The paradigm shift in adopting electrified public transportation enabled by long-range battery electric buses (BEBs) and associated charging infrastructure inflict operational challenges to both power distribution and transit systems. This paper takes an opportunistic look at the paradigm shift and develops a model for optimally scheduling the spat...

The cyberphysical power system resilience testbed implements, tests, verifies, and evaluates cyberphysical resilience solutions for power systems integrated with a communication infrastructure. It offers a platform for real-time simulation of power systems in concert with real-world monitoring, control, and protection.

The high adoption of electric vehicles (EVs) and the rising need for charging power in recent years calls for advancing charging service infrastructures and assessing the readiness of the power system to cope with such infrastructures. This paper proposes a novel model for the integrated operation of dynamic wireless charging (DWC) and power distri...

Research around equity AND justice in power systems started after the oil embargo in the 1970s, motivated by the social impact of the unprecedented rise in energy prices in the Western world. During the following two decades, a body of scientific literature focused on different aspects of energy affordability and its social implications, in particu...

The increased frequency, duration, and intensity of extreme weather events happening around the globe are an immediate threat to the ability of power grids to provide reliable power to customers. In September 2017, Hurricane Maria swept across the Caribbean, causing massive destruction in Puerto Rico, leading to more than 4,000 deaths and more than...

Extreme heat events are increasingly impacting the operation of power distribution systems, causing overloads due to excessive use of air conditioning systems, forcing power utilities to take measures to avoid large-scale blackouts in a bulk transmission system, including rotating outages. However, these power outages expose communities to overheat...

The interdependent nature of power and water distribution systems (WDSs), which magnifies the impact of power outages caused by extreme weather, offers an opportunity to coordinate recovery actions towards enhancing their resilience after a major outage event. The authors develop an approach for the coordinated recovery of interdependent power and...

The adoption of autonomous electric vehicles (AEVs) offers an opportunity to decarbonize the transportation sector while eliminating the human errors in driving accidents. However, adopting AEVs may impose challenges to the operation of power distribution systems to ensure the availability of power for charging a growing number of AEVs at different...

Energy and water systems are deeply interdependent yet organized and managed into separate sectors. Although technological innovations emerge at the intersection of energy and water, these sectors largely operate independently, despite their mutual importance. This persistent challenge is structural, as the sectors are organized and managed as sepa...

This paper proposes a novel real-time hierarchical energy flexibility management model for integrated hybrid resources (IHRs) in power distribution systems. In the proposed model, each IHR is a combination of different distributed energy resources (DERs) and electric vehicle (EV) chargers that are controlled and dispatched as a single resource in p...

The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interru...

Identifying the locations of cyber attacks in power distribution systems is critical to take immediate and effective mitigation actions. This paper introduces a novel real-time attack localization strategy for power distribution systems utilizing a Digital Twin (DT) as a cyber-physical real-time reference model that mimics the cyber-physical dynami...

The authors propose a continuous‐time two‐stage stochastic optimisation model for the integration of centralised and distributed energy storage (ES) systems into power systems with high levels of volatile renewable generation. In the proposed model, centralised and distributed ES systems, respectively, controlled by the independent system operator...

Integration of self-driving functions in electric vehicles is radically changing the transportation systems, and representing an opportunity for power utilities to develop innovative solutions for harnessing the spatio-temporal charging flexibility of autonomous electric vehicles (AEVs). This paper develops a multi-agent reinforcement learning mode...

This paper proposes a model for hierarchical combination of deep reinforcement learning (DRL) with quadratic programming for distribution system restoration after major outages. In the proposed model, optimal power dispatch of a collection of distributed energy resources, called integrated hybrid resources (IHRs), is determined by a DRL-trained con...

Deep reinforcement learning (DRL) has scored unprecedented success in finding near-optimal solutions in high-dimensional stochastic problems, leading to its extensive use in operational research, including the operation of power systems. However, in practice, it has been adopted with extreme caution because the standard DRL does not guarantee the s...

This paper proposes a two-level hierarchical matching framework for Integrated Hybrid Resources (IHRs) with grid constraints. An IHR is a collection of Renewable Energy Sources (RES) and flexible customers within a certain power system zone, endowed with an agent to match. The key idea is to pick the IHR zones so that the power loss effects within...

This paper proposes a real-time anomaly location and classification framework for power distribution systems to simultaneously determine the type of anomaly (i.e., short-circuit fault, cyber attack, DER switching) and its location. The proposed framework employs the data aggregation module to collect the measurement data from multiple field devices...

The occurrence of large-scale outages in power distribution systems (PDSs) caused, for instance, by extreme weather events has raised concerns on the cascading impact of the power outages on the resilience of other critical infrastructures, including water distribution systems (WDSs), whose healthy operation highly relies on the availability of pow...

Small pumped-storage hydropower (PSH) units have gained popularity as distributed energy storage options that can provide flexibility to the operation of power distribution systems. Optimal operation of small PSH units is not only dependent on the energy storage provided to power distribution system, but also on the inflow and outflow of water from...

This paper proposes and implements an asynchronous distributed IoT-enabled customer characterization framework to classify customers’ load consumption behaviors in electric distribution networks. More specifically, the proposed framework enables robust distributed clustering of customers’ electricity consumption habits in a highly scalable and inte...

This paper proposes a stochastic continuous-time optimization model for coordinating the operation of flexibility reserve in a hybrid hydro-thermal-wind power system. The proposed continuous-time model captures the sub-hourly uncertainty and variations of wind power and load, and accurately models and schedules the ramping flexibility of the hydrot...

This paper proposes the Decentralized Moving Target Defense via Data Replication (DMTDR) framework, which increases the security of microgrids by adding two layers of uncertainty that limit the success of false-data injection attacks. The DMTDR framework exploits the scalability and low cost of IoT devices to replicate relevant sensory and control...

This article proposes a novel moving target defense (MTD) strategy that leverages the versatility of the Internet of Things (IoT) networks to enhance the security of cyber–physical systems (CPSs) by replicating relevant sensory and control signals. The replicated data are randomly selected and transmitted to create two layers of uncertainties that...

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation. This paper proposes a defense methodology for the...

Wildfires are natural or man‐made disasters that continuously threaten portions of the transmission and distribution grid, and thus the stability of the electric grid. This paper presents a two‐stage framework for assessing power system‐wildfire risk using a data‐driven wildfire prediction model. The first stage of the framework estimates the spati...

Resiliency has been studied in the power and water systems separately. Often the resiliency study is not so comprehensive as to understand interdependent, integrated water and power systems. This research outlines the relevant factors necessary to understand and advance quantification of such integrated systems. It also presents a review of integra...

Handling the variability and uncertainty associated with integrating large capacities of renewable energy sources (RES) into the power grid is a challenge that is increasingly influencing the power systems operation. At the same time, the growing need for desalinated water in arid areas increases the importance of suitable energy sources for sustai...

High penetration of distributed energy storage systems (ESS) offers an unparalleled opportunity to reinforce the distribution grid at the local level against upstream disruptions; however, their mass operation under uncertainty of load and renewable generation is computationally expensive. While deep reinforcement learning (DRL) has been suggested...

Improving the cyber security of critical protection devices is of paramount importance for reducing the impact of cyber attacks on power distribution system. This paper proposes a game-theoretic approach to identify the optimal defensive strategy and scheme to minimize the impact of relay setting attack on power distribution systems. To this end, t...

This paper proposes a graph-based model for interdependent cyber-physical risk analysis of power distribution networks. The proposed methodology evaluates device criticality in the interdependent cyber and physical networks that comprise modern power distribution networks. A network traversal algorithm is developed to identify latent interdependent...

This paper develops a novel intrusion detection system for power distribution systems that utilizes a cyber-physical real-time reference model to accurately replicate the complex behavior of power distribution components for attack detection. The proposed intrusion detection system analyzes the consistency of the physical data from sensor readings...

The proliferation of distributed renewable generation poses many challenges to power distribution networks (DN), such as network congestion and voltage violations. Recent advances in battery technologies have made battery energy storage systems (BESS) more economically viable than ever before, which makes them suitable for many grid-scale applicati...

Cyber-physical systems (CPS) incorporate the complex and large-scale engineered systems behind critical infrastructure operations, such as water distribution networks, energy delivery systems, healthcare services, manufacturing systems, and transportation networks. Industrial CPS in particular need to simultaneously satisfy requirements of availabl...

This paper utilizes deep reinforcement learning (DRL) to develop an intelligent resilience controller (IRC) that devises fast real-time operation decisions to strategically dispatch distributed generation and energy storage units for restoring power to customers after sudden outages. The proposed IRC learns the failure development pattern of uncert...

Existing methods for wireless-sensor network (WSN) topology optimization employ simplifying assumptions of a fixed communication radius between network nodes, which is ill-suited for IoT networks deployed in complex terrain. This article proposes a data-driven approach to WSN topology optimization, employing a Bayesian link classifier trained on LI...

Traditional bulk load flexibility options, such as load shifting and load curtailment, for managing uncertainty in power markets limit the diversity of options and ignore the preferences of the individual loads, thus reducing efficiency and welfare. This paper proposes an alternative to bulk load flexibility options for managing uncertainty in powe...

Identifying the anomaly location and type (fault or attack) is of paramount importance for enhancing cyber-physical situational awareness, and taking informed and effective mitigation actions in power distribution systems with increasing number of attack points in distributed and renewable energy sources (RES). This paper proposes the Fault and Att...

This paper proposes a novel adversarial scheme for learning from data under harsh learning conditions of partially labelled samples and skewed class distributions. This novel scheme integrates the generative ability of the state-of-the-art conditional generative adversarial network with the semi-supervised deep ladder network and semi-supervised de...

Forecasting the available flexible load provided by electric vehicles would enable electric utilities to make informed decision in utilizing these loads for enhancing the operational efficiency of distribution systems. To overcome the lack of historical loads data at newly-installed EV charging stations, this paper proposes a clustered multi-node l...

The threat of high impact low probability (HILP) events on power distribution system is substantial but quite unpredictable. Enhancing the resilience of power distribution grids against such events requires solving combinatorial planning and operational problems in stochastic spaces, as well as classifying system conditions based on high-dimensiona...

This paper proposes a modeling approach for characterizing the probability of wildfire ignition caused by faults on power distribution systems. The proposed model serves as a starting point in research literature to illustrate, from an analytical perspective, the many factors that influence wildfire ignitions in power distribution systems. This pap...

The increasing capacity of distributed flexibility resources (DFRs) in power distribution systems provides an unprecedented opportunity for distribution system operators (DSOs) to offer the available distributed flexibility as services in electricity markets. This paper proposes a novel model to define and co-optimize the deliverable energy flexibi...

Continuous-time optimization models have successfully been used to capture the impact of ramping limitations in power systems. In this paper, the continuous-time framework is adapted to model flexible hydropower resources interacting with slow-ramping thermal generators to minimize the hydrothermal system cost of operation. To accurately represent...

The high penetration of transportation electrification and its associated charging requirements magnify the interdependency of the transportation and power distribution systems. The emergent interdependency requires that system operators fully understand the status of both systems. To this end, a visualization tool is presented to illustrate the in...

The COVID-19 pandemic has depressed overall mobility across the country. The changes seen reflect responses to new COVID-19 cases, local health guidelines, and seasonality, making the relationship between mobility and COVID-19 unique from region to region. This paper presents a data-driven case study of electric vehicle (EV) charging and mobility i...

Multienergy systems (MESs), as coupling of various energy sectors, can offer appropriate solutions to the operation of energy systems. The flexibility introduced by energy diversity can leverage the operation of MESs in supplying different energy demands, e.g., electricity, heat, etc. This article presents a continuous-time optimization framework f...

Modern electric vehicle (EV) charging infrastructure represents an application of an Internet of Things (IoT) framework in power systems where communication networks are the basis to transmit, monitor, and control a network of EV charging stations. This paper takes advantage of the high-resolution EV charging data made available by IoT-enabled char...

In addition to the functional and technical requirements for interconnecting distributed energy resources (DER) to the power system, IEEE standard 1547-2018 recommends DERs to have an interface capable of exchanging information that supports the functionalities in the standard. In this paper, a publish-subscribe data-centric communication scheme wi...

This paper proposes a stochastic optimization model for preparatory operation of distributed resources for enhancing the resilience of power delivery to critical loads against extreme weather events. Adopting hurricanes as a use case, a spatio-temporal hurricane impact analysis model is first developed to enhance the situational awareness of automa...

Managing the risk of wildfires has been arguably the biggest recent challenge of electric utilities with infrastructure located in the wildland-urban interface. Utilities are deploying solutions for wildfire risk mitigation, such as public safety power shutoffs, which are counter-intuitive from a reliability-centric operation paradigm. This article...

This article proposes a continuous-time modeling approach to calculate the spatio-temporal value of energy storage (ES) devices in power transmission networks. More specifically, this article formulates the dynamic operation of ES devices in power transmission networks as a continuous-time optimal control problem, where the Lagrange multiplier traj...

The proliferation of electric vehicle (EV) adoption introduces a suite of opportunities and risks to power system operation which have the potential to significantly increase loading, reduce equipment lifespan, impact rate design and offer energy flexibility. The uncertainty in space, time, power and energy presented by EV charging demand creates a...

This paper proposes two computationally efficient mixed integer optimization models, in quadratic-constrained (QC) and linear forms, for optimal real-time fault isolation and service restoration (FISR) in distribution systems. The proposed models integrate an efficient integer programming formulation to model the automated switching operation, whic...

Pumped-storage hydropower (PSH) is a proven energy storage technology that can provide large capacity support to the bulk power system. PSH is also a promising technology to increase energy storage capabilities of water distribution systems (WDSs), because these systems have most components necessary for supporting PSH, including a water supply, co...

This article proposes a novel continuous-time look-ahead optimization model for scheduling balancing energy and regulation capacity provided by energy storage (ES) devices and generating units in real-time markets. The proposed model implements the receding horizon control approach, where at each time, the operation of ES devices and generating uni...

This paper proposes online algorithms for dynamic matching markets in power distribution systems. These algorithms address the problem of matching flexible loads with renewable generation, with the objective of maximizing social welfare of the exchange in the system. More specifically, two online matching algorithms are proposed for two generation-...

In this work, we aim to minimize the cost of generation in a power system while meeting demand in near-to real time. The proposed architecture is composed of two sub-problems: continuous-time economic dispatch (CTED) and optimal automatic generation control (OAGC). In its original form, the CTED problem incorporates generator aggregate-frequency dy...

This paper proposes a new stochastic day-ahead residential charging model for a vehicle to grid (V2G)-capable plug-in electric vehicle (PEV). The aim is to minimize expected customer’s charging cost, including energy cost and battery aging cost, while satisfying the customer service quality constraints. The proposed model integrates a detailed PEV...

With the rising electricity demand for freshwater production, power and water sectors are becoming increasingly interdependent. This vital link could create new opportunities for power and water distribution system operators to coordinate the operation of their systems and achieve operational cost and energy efficiency benefits. This paper proposes...

This paper aims at implementing an optimization technique in smart manufacturing applications for co-optimizing the operation of multiple production lines to supply the desired demand for multiple products. The proposed model, which is formulated as a mixed-integer linear programming (MILP) problem, minimizes the total manufacturing cost by co-opti...

Increasing electric vehicle (EV) charging demand and residential solar photovoltaic (PV) generation greatly alter traditional distribution system operation and have the potential to overload and otherwise threaten the operating life of legacy infrastructure. The rate and location of adoption of these technologies on residential distribution systems...

In this paper we address the problem of designing online algorithms for dynamic matching markets in distribution systems whose objective is to maximize social welfare while being effective in integrating renewable energy by leveraging load flexibility. With the intuition that the performance of any online algorithm would worsen with increasing rand...

This paper develops a novel continuous-time look-ahead optimization model for co-optimizing balancing energy and flexible ramp products in real-time power systems operation. In addition, a continuous-time day-ahead operation model is developed to commit and schedule an adequate subset of generating units for providing balancing energy and ramping r...

As the global demand for freshwater resources continues to grow at a fast pace, energy costs associated with treating and distributing water in urban areas are projected to increase. A promising solution to enhance the efficiency and reduce these costs is to coordinate the operation of water systems with power distribution systems operation. In thi...

With increasing levels of drought across the world together with the rising demand of freshwater and energy consumption, the interdependence between power and water sectors is becoming increasingly important. However, as power and water system operators have traditionally operated their systems in isolation, there is a lack of understanding of the...