On the Environmental and Economic Impact of Utility-Scale Renewable Energy Deployment

As per the U.S Energy Information Administration’s latest inventory of electricity generators, renewable energy, most notably solar and wind, will account for roughly 70% of nearly 40 gigawatts of new electricity generating capacity to start commercial operation in 2021. The year 2021 will also set a record in the deployment of utility-scale solar capacity by adding 15.4 gigawatts of capacity to the grid, which surpasses the 12 gigawatts increase in 2020. The rapid increase of renewable energy is expected to significantly decrease emissions of greenhouse gases and change the load profile in the power grid by suppressing production from conventional generators. This paper aims to propose a framework to study the impact of utility-scale solar PV deployment on the generation resource allocation and investigate the economics and policy of electricity generation and carbon emissions. The investigation is carried on the generation resource pool of the southeast region of the U.S augmented by a substantial amount of utility-scale solar generation

On Accelerated Aging of Mechanical Assets in Distribution Systems with Renewable Generation

The integration challenges associated with the widespread adoption of the photovoltaic generation can be divided into operational and the maintenance issues. Work done in recent years has addressed issues like voltage rise and unbalance. Less attention was directed to the maintenance challenges like accelerated aging of mechanically controlled voltage support assets under rapidly changing conditions. In particular, there is need for analysis on the mechanism of accelerated wear and tear of devices such as on-load tap changers and capacitor banks exposed to rapid voltage fluctuations. Such an analysis relies on development of lifetime models of switching devices to study the impact of increased stress, whether electrical or mechanical, on operational life. This article focuses on developing such models and proposes the framework to study the impact of non-scheduled distributed generation on aging of mechanically-switched devices commonly used in distribution feeders

Capacity usage determination of a Capacitor-less D-STATCOM considering Power System Uncertainties

The increasing adoption of distributed energy resources (DERs), particularly solar generation and the use of unconventional loads such as plug-in electric vehicles (PHEVs), has a profound impact on the planning and operation of electric distribution systems. In particular, PHEV charging introduces stochastic peaks in energy consumption, while solar generation is fraught with variability during intermittent clouds. The stochastic nature of such DERs renders the operation of mechanical assets such as on-load tap changers and switched capacitor banks ineffective. A possible solution to mitigate the undesirable effects of DERs is using solid-state-based devices such as a distribution static synchronous compensator (D-STATCOM). This paper examines the capacity usage of a capacitor-less D-STATCOM in distribution systems while considering the uncertainties associated with using the aforementioned DERs. We propose a Monte Carlo simulation to study the capacity usage problem with DER inputs sampled from the proposed underlying distributions

PyProD: A Machine Learning-Friendly Platform for Protection Analytics in Distribution Systems

This paper introduces PyProD, a Python-based machine learning (ML)-compatible test-bed for evaluating the efficacy of protection schemes in electric distribution grids. This testbed is designed to bridge the gap between conventional power distribution grid analysis and growing capability of ML-based decision making algorithms, in particular in the context of protection system design and configuration. PyProD is shown to be capable of facilitating efficient design and evaluation of ML-based decision making algorithms for protection devices in the future electric distribution grid, in which many distributed energy resources and pro-sumers permeate the system

Impact of Short-Term Variations in the Generation Output of Geographically Dispersed PV Systems

When viewed in hourly intervals, a solar photovoltaic (PV) system appears to have a more stable output than usual. However, there are short-term rapid variations in its generation output that result from transient cloudiness and weather disturbances in the atmosphere. By using Monte Carlo simulations applied to a Markov model, this study demonstrates the short-term intermittency of the transient weather conditions and estimates the generation of geographically dispersed PV systems with a capacity of ten percent of peak demand of a statewide grid in one-minute intervals. This study found that geographically distributed PV systems evaluated in one-minute intervals could cope with peaks of a statewide power grid because of the smoothing effect caused by the geographical spread. The purpose of the exercise is to create a framework for integration and optimization of multiple generation sources in order to meet the uncertainty of the fast changing PV output under certain weather conditions.

Enhancing Microgrid Protection: Wavelet Response Analysis for Islanded and Grid-Connected Modes

Research Conference Paper.Copyright ©2023 by IEEE.Microgrid systems have emerged as a viable solution to address the challenges associated with conventional power grids, such as reliability, resiliency, and sustainability. The protection of microgrids plays a crucial role in ensuring their safe and efficient operation. This paper presents a novel approach to enhance microgrid protection by applying wavelet response analysis for current measurements. The proposed technique utilizes a differential technique for fault identification in both islanded and grid-connected modes. The proposed enhanced microgrid protection scheme provides an innovative and robust solution for ensuring the reliable fault detection of microgrids in both islanded and grid-connected modes of operation. Simulation results highlight the application of wavelet response analysis offering a comprehensive and efficient approach to detect and mitigate power system abnormalities, contributing to microgrid systems’ overall stability and resilience. The proposed technique can effectively identify abnormal conditions by implementing wavelet transform to analyze current waveforms through differential relaying techniques distinguishing between short circuit faults, external disturbances, and tap loads. Simulation studies were conducted on a representative 4-Bus benchmark microgrid model to evaluate the performance of the protection scheme. Results demonstrate the effectiveness and superiority of the proposed scheme in accurately identifying symmetrical and asymmetrical faults, effectively segregating tap loads, and contributing to the reliability and resilience of microgrid systems.This collaborative work was supported jointly by the Department of Energy under Award Number DE-IA0000025 and the Indo-US Science and Technology Foundation in partnership with the Department of Science and Technology, Government of India, under grant no. IUSSTF/JCERDC-Smart Grids and Energy Storage/2017

Voltage-Based Frequency Synchronization for Phasor Measurements in Microgrid Protection

Accepted Conference Paper, will be presented in November 2023 in Power Africa, Marrakesh, Morocco.Copyright ©2023 by IEEE.The accurate measurement of current phasors is crucial for the reliable and effective protection of microgrids. However, the presence of harmonics and variations in the fundamental frequency due to the integration of inverter-based resources (IBRs), can lead to errors in current phasor measurements in islanded microgrids. In this work, we propose a novel approach to current phasor measurement in microgrid protection that utilizes voltage-based fundamental frequency stabilization. The proposed method is based on the use of voltage measurements to synchronize a set of variable frequencies, and three-phase signals to track changes in the fundamental frequency and adjust the current phasor measurements accordingly. Simulation results demonstrate that the proposed method is effective in reducing errors in current phasor measurements caused by variations in the fundamental frequency, at the same time it can segregate between a fault and a tap load. The proposed method has the potential to enhance the performance of microgrid protection systems and ensure the reliable operation of microgrids.This collaborative work was supported jointly by the Department of Energy under Award Number DE-IA0000025 and the Indo-US Science and Technology Foundation in partnership with Department of Science and Technology, Government of India, under grant no. IUSSTF/JCERDC-Smart Grids and Energy Storage/2017

On Estimation of Equipment Failures in Electric Distribution Systems Using Bayesian Inference

This paper presents a new statistical parametric model to predict the times-to-failure of broad classes of identical devices such as on-load tap changers, switched capacitors, breakers, etc. A two-parameter Weibull distribution with scale parameter given by the inverse power law is employed to model the survivor functions and hazard rates of on-load tap changers. The resulting three-parameter distribution, referred to as IPL-Weibull, is flexible enough to assume right, left, and even symmetrical modal distribution. In this work, we propose an inferential method based on Bayes’ rule to derive the point estimates of model parameters from the past right-censored failure data. Using the Monte Carlo integration technique, it is possible to obtain such parameter estimates with high accuracy