For decades, researchers have sought to make the North American power system as reliable as possible with many security measures in place to include redundancy. Yet the increasing number of blackouts and failures have highlighted the areas that require improvement. Meeting the increasing demand for energy and the growing complexity of the loads are two of the main challenges faced by the power grid. In order to prepare for contingencies and maintain a secure state, power engineers must perform simulations using steady state and dynamic models of the system. The results from the contingency studies are only as accurate as the models of the grid components. The load components are generally the most difficult to model since they are controlled by the consumer. This study focuses on developing static and dynamic load models using advanced mathematical approximation algorithms and wide area measurement devices, which will improve the accuracy of the system analysis and hopefully decrease the frequency of blackouts. The increasing integration of phasor measurement units (PMUs) into the power system allows us to take advantage of synchronized measurements at a high data rate. These devices are capable of changing the way we manage online security within the Energy Management System (EMS) and can enhance our offline tools. This type of data helps us redevelop the measurement-based approach to load modeling. The static ZIP load model composition is estimated using a variation of the method of least squares, called bounded-variable least squares. The bound on the ZIP load parameters allows the measurement matrix to be slightly correlated. The ZIP model can be determined within a small range of error that won't affect the contingency studies. Machine learning is used to design the dynamic load model. Neural network training is applied to fault data obtained near the load bus and the derived network model can estimate the load parameters. The neural network is trained using simulated data and then applied to real PMU measurements. A PMU algorithm was developed to transform the simulated measurements into a realistic representation of phasor data. These new algorithms will allow us to estimate the load models that are used in contingency studies. / Ph. D.

The objective of this thesis is to examine the effect of dynamic induction machine modeling and polynomial static load modeling on the stability of electric power systems and to compare the results with those obtained using constant impedance or constant current load models. A least-squares curve fit algorithm is developed and used in modeling static and quasi-static loads as a function of the bus voltage. A dynamic model for the induction machine which accounts for rotor electrical and mechanical transients is incorporated into the solution algorithm. A test system is analyzed under a variety of loading conditions. The effect of the induction motor .load inertia constants on the system stability are also examined. Plots of load bus voltages during the transient stability period are included. / Master of Science

Load models have evolved from simple ZIP model to composite model that incorporates the transient dynamics of motor loads. This research utilizes the latest trend on Machine Learning and builds reliable and accurate composite load model. A composite load model is a combination of static (ZIP) model paralleled with a dynamic model. The dynamic model, recommended by Western Electricity Coordinating Council (WECC), is an induction motor representation. In this research, a dual cage induction motor with 20 parameters pertaining to its dynamic behavior, starting behavior, and per unit calculations is used as a dynamic model. For machine learning algorithms, a large amount of data is required. The required PMU field data and the corresponding system models are considered Critical Energy Infrastructure Information (CEII) and its access is limited. The next best option for the required amount of data is from a simulating environment like PSSE. The IEEE 118 bus system is used as a test setup in PSSE and dynamic simulations generate the required data samples. Each of the samples contains data on Bus Voltage, Bus Current, and Bus Frequency with corresponding induction motor parameters as target variables. It was determined that the Artificial Neural Network (ANN) with multivariate input to single parameter output approach worked best. Recurrent Neural Network (RNN) is also experimented side by side to see if an additional set of information of timestamps would help the model prediction. Moreover, a different definition of a dynamic model with a transfer function-based load is also studied. Here, the dynamic model is defined as a mathematical representation of the relation between bus voltage, bus frequency, and active/reactive power flowing in the bus. With this form of load representation, Long-Short Term Memory (LSTM), a variation of RNN, performed better than the concurrent algorithms like Support Vector Regression (SVR). The result of this study is a load model consisting of parameters defining the load at load bus whose predictions are compared against simulated parameters to examine their validity for use in contingency analysis. / Master of Science / Independent system Operators (ISO) and Distribution system operators (DSO) have a responsibility to provide uninterrupted power supply to consumers. That along with the longing to keep operating cost minimum, engineers and planners study the system beforehand and seek to find the optimum capacity for each of the power system elements like generators, transformers, transmission lines, etc. Then they test the overall system using power system models, which are mathematical representation of the real components, to verify the stability and strength of the system. However, the verification is only as good as the system models that are used. As most of the power systems components are controlled by the operators themselves, it is easy to develop a model from their perspective. The load is the only component controlled by consumers. Hence, the necessity of better load models. Several studies have been made on static load modeling and the performance is on par with real behavior. But dynamic loading, which is a load behavior dependent on time, is rather difficult to model. Some attempts on dynamic load modeling can be found already. Physical component-based and mathematical transfer function based dynamic models are quite widely used for the study. These load structures are largely accepted as a good representation of the systems dynamic behavior. With a load structure in hand, the next task is estimating their parameters. In this research, we tested out some new machine learning methods to accurately estimate the parameters. Thousands of simulated data are used to train machine learning models. After training, we validated the models on some other unseen data. This study finally goes on to recommend better methods to load modeling.

Thesis (MScEng)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Energy efficiency and the move to renewable energy resources are of vital importance in growing profitable and sustainable economies. In recent years, greater emphasis has been placed on institutions, companies and individuals to reduce their electrical energy demand through energy management. In an attempt to reduce the demand, the electrical power utility in South Africa, Eskom, has introduced Demand Side Management programs and substantial increases in electricity tariffs. In addition to these, tax incentives have been offered to help off-set the capital costs associated with the investments made in replacing old electrical equipment with new electrically efficient equipment. Thus the need for accurate Measurement and Verification of electrical energy demand reduction, to substantiate fiscal claims, has become imperative. The main purpose of Measurement and Verification is to investigate the actual monetary performance of an energy savings project. Energy savings assessments, based on purely deterministic baseline demand, do not adequately represent the statistical nature of the savings impacts of many practical load systems, as disclosed in a reporting period. This thesis presents the development of a generic probabilistic methodology to determine the demand profiles of preand post-Energy Conservation Measures (ECMs) for practical load systems. The difference between the simulated demand of the pre- and post-ECMs for a particular set of variables represent the electrical demand impact. The electrical demand of the pre- and post-ECMs is defined in terms of Probability Density Functions, and derived using a multivariate kernel density estimation algorithm. The approach is tested using a simulation model of a waterheating geyser implemented in MATLAB. Three different ECMs are simulated using the geyser model and demand density estimation. The results of the demand impacts of the ECMs are presented and evaluated. With regards to possible future research this methodology could be applied to the evaluation of the demand impacts of heat pump technologies and solar water heaters. / AFRIKAANSE OPSOMMING: en die skuif na hernubare energiebronne is van deurslaggewende belang vir die ontwikkeling van winsgewende en volhoubare ekonomieë. Onlangs is meer klem geplaas op instansies, maatskappye en individue om hul aanvraag na energie te verminder met behulp van energiebestuur. In ‘n poging om die aanvraag te verlaag, het Eskom, Suid-Afrika se elektrisiteitsverskaffer, aansienlike elektrisiteitstariefverhogings ingelyf en Aanvraagbestuursprogramme van stapel gestuur. Bykomend hiertoe is belastingaansporings ook aangebied, waarteen kapitale kostes, geassosieer met die vervanging van ou elektriese toerusting met nuwe elektries doeltreffende toerusting, afgeset kan word. Derhalwe het die behoefte aan akkurate Meting en Verifikasie van elektriese energie aanvraagvermindering, om finansiële eise te staaf, noodsaaklik geword. Die hoofdoel van Meting en Verifikasie is om die werklike finansiële prestasie van energiebesparingsprojek te ondersoek soos bekend gemaak word tydens ’n verslagdoeningstydperk. Energiebesparingassesserings wat slegs gebaseer word op die suiwer deterministiese basislyn aanvraag na elektrisiteit, verteenwoordig nie die werklike statistiese aard van die besparingsimpakte van baie praktiese lasstelsels nie. Hierdie tesis stel die ontwikkeling van generiese waarskynlikheids-metodologie voor, om die voor- en na- Energiebesparings-maatreëls se aanvraagprofiele vir sulke praktiese lasstelsels, vas te stel. Die verskil tussen die gesimuleerde aanvraag van die voor- en na- Energiebesparings-maatreëls vir spesifieke stel veranderlikes verteenwoordig die elektriese aanvraag impak. Die voor- en na- Energiebesparings-maatreëls van die energieverbruik profieldata word gedefinieer in terme van Waarskynlikheidsdigtheidsfunksies en afgelei deur gebruik te maak van meerveranderlike kerndigtheidafskattingsalgoritme. Die benadering is getoets deur gebruik te maak van simuleringsmodel van warmwaterstelsel geïmplimenteer in MATLAB. Drie verskillende voor- en na- Energiebesparings-maatreëls is gesimuleer met behulp van die warmwaterstelselmodel en aanvraag digtheidafskatting. Die resultate van die elektriese aanvraag impakte van die voor- en na- Energiebesparings-maatreëls word vervolgens bespreek en geëvalueer. Met betrekking tot moontlike toekomstige navorsing kan hierdie metodologie toegepas word om die aanvraag impakte van hittepomp- en sonwaterverwarmingstegnologieë te evalueer.

Master of Science / Department of Electrical Engineering / Shelli K. Starrett / Modern power systems are integrated, complex, dynamic systems. Due to the complexity, power system operation and control need to be analyzed using numerical simulation. The load model is one of the least known models among the many components in the power system operation. The two different load models are the static and dynamic models. The ZIP load model has been extensively studied. This has widely applied to composite load models that could maintain constant impedance, constant current, and/or constant power. In this work, various Neural Networks algorithms and fuzzy logic have been used to obtain these ZIP load model coefficients for determining the percentage of constant impedance, current, or power for the various load buses. The inputs are a combination of voltage, voltage change, and power change, or voltage and power, and the outputs consist of the ZIP load model coefficients for determining the type and the percentage of load at the bus. The trained model is used to predict the type and percentage of constant load at other buses using simulated transient data from the 16-generator system. A small study was also done using a dynamic induction machine model in addition to the ZIP load model. As expected, the results show that the dynamic model is more difficult to determine than the static model.

abstract: The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics 1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies 2. A systematic approach to n-1-1 analysis for power system security as-sessment To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work. Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

abstract: This thesis presents a new technique to develop an air-conditioner (A/C) compressor single phase induction motor model for use in an electro-magnetic transient program (EMTP) simulation tool. The method developed also has the capability to represent multiple units of the component in a specific three-phase distribution feeder and investigate the phenomenon of fault-induced delayed voltage recovery (FIDVR) and the cause of motor stalling. The system of differential equations representing the single phase induction motor model is developed and formulated. Implicit backward Euler method is applied to numerically integrate the stator currents that are to be drawn from the electric network. The angular position dependency of the rotor shaft is retained in the inductance matrix associated with the model to accurately capture the dynamics of the motor loads. The equivalent circuit of the new model is interfaced with the electric network in the EMTP. The dynamic response of the motor when subjected to faults at different points on voltage waveform has been studied using the EMTP simulator. The mechanism and the impacts of motor stalling need to be explored with multiple units of the detailed model connected to a realistic three-phase distribution system. The model developed can be utilized to assess and improve the product design of compressor motors by air-conditioner manufacturers. Another critical application of the model would be to examine the impacts of asymmetric transmission faults on distribution systems to investigate and develop mitigation measures for the FIDVR problem. / Dissertation/Thesis / M.S. Electrical Engineering 2012

A tendência crescente na geração de harmônicos nos sistemas elétricos de potência tem ganhado atenção especial no planejamento das redes de transporte de energia elétrica, uma vez que os crescimentos observados acontecem em regiões que antes não representavam qualquer tipo de preocupação. Um dos principais fatores que contribuíram para esse novo contexto é a característica distribuída da geração de harmônicos. Devido a essa nova realidade, métodos mais aprimorados para avaliação de desempenho e modelos mais precisos para a representação de equipamentos tornaram-se necessários. Sendo assim, a pesquisa realizada para a elaboração da presente tese fundamentou a sua investigação em três tópicos com o intuído de fornecer contribuições que permitissem uma avaliação mais precisa das redes elétricas, proporcionando, assim, resultados mais aderentes com a realidade existente: Modelagem Agregada de Carga; Equivalentes de Redes; Estimação de Estados das Distorções Harmônicas. Através das contribuições feitas nesses tópicos, torna-se possível a consideração de aspectos que antes eram ignorados na avaliação harmônica das redes de transporte de energia elétrica e, assim, permite-se uma verificação precisa dos impactos da característica distribuída da geração de harmônicos nos sistemas elétricos de potência. / The growing rate of harmonic generation present in the electric power systems has gained special attention in the planning process of power networks. The major factor that contributed for this new context is the increasing harmonic generation observed in regions that did not use to represent any concern in the past. One of the main causes for this new trend is the distributed characteristic of the harmonic generation. In this new environment, sophisticated methods and models have become necessary, in order to precisely represent the electric elements behaviour and to accurately evaluate the systems performance. As a result, the research work presented in this thesis focused in three different topics, in order to provide contributions that would lead to a more accurate performance evaluation of the power networks and that would provide results closer to the values found in the field: Aggregate Load Modeling; Network Equivalents; Harmonic State Estimation. These contributions would allow the consideration of aspects that normally are ignored in the harmonic assessment of power systems. Consequently, the evaluation of the impacts caused by the distributed generation of harmonics becomes more accurate.

Orientador: Prof. Dr. Carlos Eduardo Capovilla / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia Elétrica, 2014. / Este trabalho academico apresenta a modelagem eletrica de um ambiente residencial e a disponibiliza como infraestrutura necess'aria para pesquisas futuras na 'area de redes inteligentes dom'esticas (Home Smart Grids). Tais modelos são disponbilizados em um formato de arquivo de biblioteca do ambiente de simulação MatLab/Simulink. Para atingir este objetivo, é realizada a modelagem te'orica e experimental de diversos aparelhos domésticos e cabos elétricos. Dois modelos de medidores de energia inteligentes são desenvolvidos, que podem ser conectados a qualquer ponto da instalação el'etrica residencial. Um modelo de resid¿encia com seu respectivo diagrama unifilar da simulação el'etrica 'e apresentado, permitindo execução de simulações de seu funcionamento completo. / This academic work presents the electric modeling of a residential wiring and makes it available as a necessary infrastructure for future researches about Home Smart Grids. The models are available in a MatLab/Simulink simulation environment library format. In order to achieve this objective, both theoretical and experimental modeling is performed for many electric loads (home appliances) and cables. Two kinds of electric smart meters are also developed, which can be connected at any point of the residential wiring. A residence model with its wiring diagram is presented, allowing the simulation execution of a full residence operation.

A tendência crescente na geração de harmônicos nos sistemas elétricos de potência tem ganhado atenção especial no planejamento das redes de transporte de energia elétrica, uma vez que os crescimentos observados acontecem em regiões que antes não representavam qualquer tipo de preocupação. Um dos principais fatores que contribuíram para esse novo contexto é a característica distribuída da geração de harmônicos. Devido a essa nova realidade, métodos mais aprimorados para avaliação de desempenho e modelos mais precisos para a representação de equipamentos tornaram-se necessários. Sendo assim, a pesquisa realizada para a elaboração da presente tese fundamentou a sua investigação em três tópicos com o intuído de fornecer contribuições que permitissem uma avaliação mais precisa das redes elétricas, proporcionando, assim, resultados mais aderentes com a realidade existente: Modelagem Agregada de Carga; Equivalentes de Redes; Estimação de Estados das Distorções Harmônicas. Através das contribuições feitas nesses tópicos, torna-se possível a consideração de aspectos que antes eram ignorados na avaliação harmônica das redes de transporte de energia elétrica e, assim, permite-se uma verificação precisa dos impactos da característica distribuída da geração de harmônicos nos sistemas elétricos de potência. / The growing rate of harmonic generation present in the electric power systems has gained special attention in the planning process of power networks. The major factor that contributed for this new context is the increasing harmonic generation observed in regions that did not use to represent any concern in the past. One of the main causes for this new trend is the distributed characteristic of the harmonic generation. In this new environment, sophisticated methods and models have become necessary, in order to precisely represent the electric elements behaviour and to accurately evaluate the systems performance. As a result, the research work presented in this thesis focused in three different topics, in order to provide contributions that would lead to a more accurate performance evaluation of the power networks and that would provide results closer to the values found in the field: Aggregate Load Modeling; Network Equivalents; Harmonic State Estimation. These contributions would allow the consideration of aspects that normally are ignored in the harmonic assessment of power systems. Consequently, the evaluation of the impacts caused by the distributed generation of harmonics becomes more accurate.