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Hamidreza Nazaripouya received the B.S. degree in electrical engineering from the University of Tehran, Iran, the M.Sc. degree in power electronics from the Sharif University of Technology, Tehran, Iran, and the M.Sc. degree in power systems from Louisiana State University, LA, USA. He obtained his Ph.D. degree from the University of California, Los Angeles (UCLA). He is currently an Assistant Professor at Oklahoma State University, OK, USA and an Assistant Adjunct Professor at the University of California, Riverside (UCR), CA, USA. His research interests include control and optimization in power systems, distributed energy resources modeling, control and integration, power system dynamics, and power system resilience. He holds U.S. patents in control of energy storage systems. His patented technology won the NSF Grant Award with him as the Entrepreneurial Lead. He also received IEEE SFV Section Rookie of the Year Award, IEEE IAS and PES Presentation awards, and the UC Dissertation-Year Fellowship Award.
An intrinsically stable microgrid, operated by inverter-interfaced distributed energy resources (I-DERs) is introduced in this paper. The microgrid is built upon a systematic design method, which is adapted from the operation of the synchronous machine (SM). The proposed method analogizes the dynamics of the dc-link in I-DERs to the rotor dynamics in synchronous generators (SGs) and utilizes the capacitor as energy storage. Thus, the proposed mechanism relaxes battery usage for frequency control, and by using the capacitive stored energy, provides a high fault ride-through capability, which is suitable for both on-grid and off-grid applications. Based on stability analysis of the SG and the dynamic state matrix eigenvalues for multimachine power system, the dc-link capacitor of I-DERs is characterized in the context of microgrid. The dc-link capacitor stores kinetic energy similar to the rotor of the SG and provides inertia in transients without the need of battery storage. The inverter angle responds to the change of the dc link voltage (energy). The dc-link voltage is then controlled similar to the field control pertaining to the SG. Finally, a governor-like mechanism is applied to maintain dc-link voltage stability. Simulation and experimental results are provided to show the effectiveness of the proposed design mechanisms.
Hossein Saberi; Hamidreza Nazaripouya; Shahab Mehraeen. Implementation of a Stable Solar-Powered Microgrid Testbed for Remote Applications. Sustainability 2021, 13, 2707 .
AMA StyleHossein Saberi, Hamidreza Nazaripouya, Shahab Mehraeen. Implementation of a Stable Solar-Powered Microgrid Testbed for Remote Applications. Sustainability. 2021; 13 (5):2707.
Chicago/Turabian StyleHossein Saberi; Hamidreza Nazaripouya; Shahab Mehraeen. 2021. "Implementation of a Stable Solar-Powered Microgrid Testbed for Remote Applications." Sustainability 13, no. 5: 2707.
This paper proposes an algorithm that finds the optimal sets of phasor measurement units (PMUs) to achieve a fault observable system, while it addresses the multi‐estimation issue. The optimal PMU placement (OPP) problem here is to find a set of PMU locations with minimum number of members that enables fault observability in a system and satisfies a defined minimum sensitivity requirement in measurements. The proposed algorithm generalizes the impedance method in fault analysis and optimizes PMU utilization to maintain a required minimum sensitivity in each set of measurements, given the required fault detection accuracy. Also, the set of measurements is unique and distinctive for each fault scenario, preventing multi‐estimation. A fault is referred to as a set of affected faulty line, fault location, and fault impedance. A sensitivity analysis is performed and sensitivity indices are derived to evaluate measurements quality to detect changes in fault line, location, or resistance. The algorithm is executed on IEEE 7‐bus, 14‐bus, and 30‐bus test systems. Subsequently, artificial neural networks (ANN) are employed to build fault locators through offline training. ANN use an optimal PMU set obtained by the proposed algorithm to uniquely map between the corresponding measurements set and the faults.
Pooria Mohammadi; Shahab Mehraeen; Hamidreza Nazaripouya. Sensitivity analysis‐based optimal PMU placement for fault observability. IET Generation, Transmission & Distribution 2020, 15, 737 -750.
AMA StylePooria Mohammadi, Shahab Mehraeen, Hamidreza Nazaripouya. Sensitivity analysis‐based optimal PMU placement for fault observability. IET Generation, Transmission & Distribution. 2020; 15 (4):737-750.
Chicago/Turabian StylePooria Mohammadi; Shahab Mehraeen; Hamidreza Nazaripouya. 2020. "Sensitivity analysis‐based optimal PMU placement for fault observability." IET Generation, Transmission & Distribution 15, no. 4: 737-750.
The recent advent of distribution-level phasor measurement units (D-PMUs), a.k.a., micro-PMUs, has introduced a wide range of new applications in power distribution systems. A sub-class of such emerging applications are called event-based methods. These methods focus on the analysis of events in the stream of micro-PMU measurements to achieve situational awareness, enhance load modeling, integrate distributed energy resources, etc. In this paper, we explore a scenario, where a cyberattack compromises the micro-PMU measurements during an event. Such a targeted attack could be limited in scope but result in a major impact on the operation of the power grid by highly deviating the outcome of the event-based methods. First, we investigate and model two types of such attacks, event-unsynchronized (basic) attacks and event-synchronized (advanced) attacks. We then conduct a geometric analysis to understand each attack type, in a setting where the events are represented in the phasor domain in a differential mode. Next, we introduce a novel method to detect the presence of the attack and then identify which micro-PMUs are compromised so as to discard the compromised measurements as a defense mechanism. The proposed approach makes critical use of magnitude as well as phase angle measurements from micro-PMUs. The method is tested on the IEEE 33-bus power distribution test system.
Mohasinina Kamal; Mohammad Farajollahi; Hamidreza Nazaripouya; Hamed Mohsenian-Rad. Cyberattacks Against Event-Based Analysis in Micro-PMUs: Attack Models and Counter Measures. IEEE Transactions on Smart Grid 2020, 12, 1577 -1588.
AMA StyleMohasinina Kamal, Mohammad Farajollahi, Hamidreza Nazaripouya, Hamed Mohsenian-Rad. Cyberattacks Against Event-Based Analysis in Micro-PMUs: Attack Models and Counter Measures. IEEE Transactions on Smart Grid. 2020; 12 (2):1577-1588.
Chicago/Turabian StyleMohasinina Kamal; Mohammad Farajollahi; Hamidreza Nazaripouya; Hamed Mohsenian-Rad. 2020. "Cyberattacks Against Event-Based Analysis in Micro-PMUs: Attack Models and Counter Measures." IEEE Transactions on Smart Grid 12, no. 2: 1577-1588.
This paper proposes and implements a model-free optimal strategy to regulate the voltage in distribution systems by effective control of Inverter-interfaced Distributed Energy Resources (I-DERs) output power. In distribution systems, where the ratio of R/X is considerable, reactive power control is not always an optimum solution for voltage regulation. With the aim of improving voltage regulation, this paper proposes an alternative method to optimally coordinate active and reactive power of I-DERs in the grid. The proposed method does not need to have a system model and phase measurement, which are barriers in control and operation of behind-the-meter assets. The paper formulates the problem of voltage regulation in form of equilibrium-map-with-optimum, without any restriction on system configuration, amount of reverse power flow and losses. Using the extremum seeking control technique and without an explicit model of distribution circuit, the ratio of active and reactive power is coordinated in real time. The amount of exchanged apparent power is also adjusted simultaneously. Simulation results for a typical distribution circuit verify the effectiveness of the proposed approach in improving the voltage regulation performance. The experimental results also show a 20 percent reduction in use of system capacity to provide the desired voltage regulation performance.
Hamidreza Nazaripouya; Hemanshu Roy Pota; Chi-Cheng Chu; Rajit Gadh. Real-Time Model-Free Coordination of Active and Reactive Powers of Distributed Energy Resources to Improve Voltage Regulation in Distribution Systems. IEEE Transactions on Sustainable Energy 2019, 11, 1483 -1494.
AMA StyleHamidreza Nazaripouya, Hemanshu Roy Pota, Chi-Cheng Chu, Rajit Gadh. Real-Time Model-Free Coordination of Active and Reactive Powers of Distributed Energy Resources to Improve Voltage Regulation in Distribution Systems. IEEE Transactions on Sustainable Energy. 2019; 11 (3):1483-1494.
Chicago/Turabian StyleHamidreza Nazaripouya; Hemanshu Roy Pota; Chi-Cheng Chu; Rajit Gadh. 2019. "Real-Time Model-Free Coordination of Active and Reactive Powers of Distributed Energy Resources to Improve Voltage Regulation in Distribution Systems." IEEE Transactions on Sustainable Energy 11, no. 3: 1483-1494.
In this paper, super-short-term prediction of solar power generation for applications in dynamic control of energy system has been investigated. In order to follow and satisfy the dynamics of the controller, the deployed prediction method should have a fast response time. To this end, this paper proposes fast prediction methods to provide the control system with one step ahead of solar power generation. The proposed methods are based on univariate time series prediction. That is, instead of using external data such as the weather forecast as the input of prediction algorithms, they solely rely on past values of solar power data, hence lowering the volume and acquisition time of input data. In addition, the selected algorithms are able to generate the forecast output in less than a second. The proposed methods in this paper are grounded on four well-known prediction algorithms including Autoregressive Integrated Moving Average (ARIMA), K-Nearest Neighbors (kNN), Support Vector Regression (SVR), and Random Forest (RF). The speed and accuracy of the proposed algorithms have been compared based on two different error measures, Mean Absolute Error (MAE) and Symmetric Mean Absolute Percentage Error (SMAPE). Real world data collected from the PV installation at the University of California, Riverside (UCR) are used for prediction purposes. The results show that kNN and RF have better predicting performance with respect to SMAPE and MAE criteria.
Mostafa Majidpour; Hamidreza Nazaripouya; Peter Chu; Hemanshu R. Pota; Rajit Gadh. Fast Univariate Time Series Prediction of Solar Power for Real-Time Control of Energy Storage System. Forecasting 2018, 1, 107 -120.
AMA StyleMostafa Majidpour, Hamidreza Nazaripouya, Peter Chu, Hemanshu R. Pota, Rajit Gadh. Fast Univariate Time Series Prediction of Solar Power for Real-Time Control of Energy Storage System. Forecasting. 2018; 1 (1):107-120.
Chicago/Turabian StyleMostafa Majidpour; Hamidreza Nazaripouya; Peter Chu; Hemanshu R. Pota; Rajit Gadh. 2018. "Fast Univariate Time Series Prediction of Solar Power for Real-Time Control of Energy Storage System." Forecasting 1, no. 1: 107-120.
This paper introduces a scalable framework to coordinate the net load scheduling, sharing, and matching in a neighborhood of residential prosumers connected to the grid. As the prosumers are equipped with smart appliances, photovoltaic panels, and battery energy storage systems, they take advantage of their consumption, generation, and storage flexibilities to exchange energy with neighboring prosumers through negotiating on the amount of energy and its price with an aggregator. The proposed framework comprises two separate multi-objective mixed integer nonlinear programming optimization models for prosumers and the aggregator. Prosumers' objective is to maximize the comfort level and minimize the electricity cost at each instant of time, while aggregator intends to maximize its profit and minimize the grid burden by matching prosumers' supply and demand. The evolutionary Non-dominated Sorting Genetic Algorithm-III (NSGA-III) is employed to generate a set of feasible non-dominated solutions to the optimization problem of each individual prosumer and the aggregator. As a bilateral negotiation between each prosumer and the aggregator results in significant computational and communication overhead, a virtual power plant is introduced as an intermediator on behalf of all prosumers to proceed the negotiation with the aggregator in a privacy-preserving non-cooperative environment, where no private information is shared. Hence, an automated negotiation approach is embedded in the framework, which enables the negotiators to reactively negotiate on concurrent power and price using private utility functions and preferences. To converge to an acceptable agreement, the negotiation approach follows an alternating-offer production protocol and a reactive utility value concession strategy. The effectiveness of the framework is evaluated by several economic and environmental assessment metrics through a variety of numerical simulations.
Armin Ghasem Azar; Hamidreza Nazaripouya; Behnam Khaki; Chi-Cheng Chu; Rajit Gadh; Rune Hylsberg Jacobsen. A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers. IEEE Transactions on Industrial Informatics 2018, 15, 2523 -2534.
AMA StyleArmin Ghasem Azar, Hamidreza Nazaripouya, Behnam Khaki, Chi-Cheng Chu, Rajit Gadh, Rune Hylsberg Jacobsen. A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers. IEEE Transactions on Industrial Informatics. 2018; 15 (5):2523-2534.
Chicago/Turabian StyleArmin Ghasem Azar; Hamidreza Nazaripouya; Behnam Khaki; Chi-Cheng Chu; Rajit Gadh; Rune Hylsberg Jacobsen. 2018. "A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers." IEEE Transactions on Industrial Informatics 15, no. 5: 2523-2534.
A new method for the control of a battery energy storage system and its implementation on a solar system to compensate power intermittency and improve distribution grid power quality is presented in this paper. The novelty of the proposed method is to provide a systematic way to optimize the size of the battery capacity for the desired level of solar power smoothing. This goal is achieved by designing a two-stage filter solution. The first stage is a fast response digital finite impulse response (FIR) filter that makes a trade-off between smoothing of the solar output and battery capacity. This paper proposes an optimal design of minimum-length-minimum-group-delay FIR filter by employing convex optimization, discrete signal processing, and polynomial stabilization techniques. The new strategy proposed in this paper formulates the design of a length-N minimum-group-delay FIR filter as a convex second-order cone programming (SOCP) which guarantees that all the filter zeros are inside the unit circle (minimum-phase). A quasi-convex optimization problem is formulated to minimize the length of minimum-group-delay FIR filter. The second stage filter is designed to level the battery charging load. The effectiveness and performance of the proposed approach is demonstrated by simulation results and over a real case implementation.
Hamidreza Nazaripouya; Chi-Cheng Chu; Hemanshu Pota; Rajit Gadh. Battery Energy Storage System Control for Intermittency Smoothing Using an Optimized Two-Stage Filter. IEEE Transactions on Sustainable Energy 2017, 9, 664 -675.
AMA StyleHamidreza Nazaripouya, Chi-Cheng Chu, Hemanshu Pota, Rajit Gadh. Battery Energy Storage System Control for Intermittency Smoothing Using an Optimized Two-Stage Filter. IEEE Transactions on Sustainable Energy. 2017; 9 (2):664-675.
Chicago/Turabian StyleHamidreza Nazaripouya; Chi-Cheng Chu; Hemanshu Pota; Rajit Gadh. 2017. "Battery Energy Storage System Control for Intermittency Smoothing Using an Optimized Two-Stage Filter." IEEE Transactions on Sustainable Energy 9, no. 2: 664-675.