Thesis: M.S., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1980 / Bibliography: leaves 85-87. / by Frances Annette Habib. / M.S. / M.S. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

Indiana University-Purdue University Indianapolis (IUPUI) / The interconnection of distributed resources requires specific voltage regulation, monitoring, protective relaying, power quality, and islanding detection. For this reason IEEE established standard IEEE 1547 that ensures the compliance with such requirements and it will help formulate technical specifications for grid interconnection with Distributed Generator (DG) resources. In search of meeting the IEEE 1547 standard requirement of detecting unintentional islanded operation, there has been ongoing research to develop anti-islanding methods that can detect the different changes that can occur when the grid is disconnected. A team of Electrical Engineering faculty at Indiana University Purdue University Indianapolis has worked previously on testing a DG unintentional Islanding Detection Scheme. This scheme uses an active anti-islanding method in which a small 1 Hz perturbation signal is added into the DG system and it helps detect when the grid is disconnected. The scheme uses the premise that a frequency deviation caused by perturbation to the system is smaller when the grid is connected than when it is in an island. In an initial dynamic simulation model for the islanding detection scheme, a two-machine microgrid system is used to explore frequency and voltage responses when the grid is disconnected. In this thesis, the two-machine microgrid is expanded to a ten-machine system so it can be shown that the frequency deviation caused by a perturbation signal is much smaller when the grid is connected even for a larger DG network. The 1 Hz component of the DG electrical frequency in a multiple machine microgrid system is also calculated in this thesis. This project was conducted in different stages. First, it was necessary to calculate the steady state power flow and electric power of a three-machine system and update the two-machine MATLAB program with the necessary changes. After making the changes, it was necessary to simulate the system and adjust the inertia of the machine that represents the grid to ensure that the simulation output was close in magnitude to previous testing results. When the three-machine system was successfully generated, a brand new program was created so a multiple machine system could be simulated. Then the multiple machine program was used to simulate and experiment with up to a ten-machine system. Finally a program to calculate the 1 Hz component of the DG electrical frequency was generated and used to show that the magnitude squared of the 1 Hz component is inversely proportional to the number of machines connected to the system. These last findings will later help set the threshold for islanding detection appropriately for different numbers of DG.

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Residential demand is a large and important factor of the utility load during the system peak period. And the control of residential demand can make a significant change to the system load of the utility. This research is designed to study the residential end-use appliances under various direct load control schemes. These appliances are water heaters, air conditioners, and space heaters which are the major electrical demand of the residential load. The study will apply the LOADSIM, an Electrical Power Research Institute (EPRI) load simulation program, to conduct load control strategies of these residential appliances. The LOADSIM program can be applied both for cycling and shedding control strategies during a specified control period. In this study, the cycling control is done on an air conditioner and space heater. The water heating control is performed under shedding strategy. The research has studied the appliance use of four house types under the same weather and control conditions. A total of 100,000 houses have been used in the study. These houses have the same dwelling and appliance characteristics but their house insulations are different. Diversity in house insulations gives different results in terms of load reduction and temperature change due to the load control. For example, a better-insulated house demands less electricity for its appliance than a low-insulated house. This study also uses the EPRl-LOADSIM program to estimate the load reduction and temperature change of each house type under the load control. / Master of Science

by Tang Yee On. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 56-60). / ABSTRACT --- p.ii / TABLE OF CONTENTS --- p.iii / ACKNOWLEDGMENTS --- p.v / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Thesis --- p.3 / Background --- p.4 / Thailand Economy and State-Owned Enterprises --- p.5 / Privatization Program of State-Owned Enterprises --- p.6 / Chapter II. --- THE PRIVATE PARTICIPATION PROGRAM OF THAI ELECTRICITY GENERATING INDUSTRY --- p.8 / The Four-Step Plan of Restructuring the Thai Electricity Power Sector --- p.9 / Electricity Generating Authority of Thailand --- p.10 / Electricity Generating Public Company Limited --- p.11 / Rayong Electricity Generating Company Limited --- p.11 / Khanom Electricity Generating Company Limited --- p.12 / Chapter III. --- PRIVATIZATION PROJECT OF KHANOM --- p.13 / Power Purchase Agreement (PPA) --- p.13 / Financing Plan --- p.16 / Equity Financing --- p.17 / Debt Financing --- p.18 / The Deal of Khanom --- p.18 / Chapter IV. --- THE IMPACT OF ASIAN FINANCIAL CRISIS ON THE INFRASTRUCTURE PROJECTS IN THAILAND --- p.20 / The Financial Crisis in Thailand --- p.20 / Thai Government Reaction --- p.22 / The Electricity Industry --- p.23 / Electricity Generating Authority of Thailand (EGAT) --- p.24 / Small Power Providers (SPP) --- p.27 / Independent Power Providers (IPP) --- p.27 / Other Electricity Projects --- p.28 / Other Infrastructure Projects: Hopewell BERTS --- p.29 / Chapter V. --- ANALYSIS --- p.34 / Benefits of the Private Participation Program --- p.34 / Importance of Project Finance in Infrastructure Projects --- p.36 / Impact of Financial Crisis on the Projects --- p.37 / Tariff Structure of KEGCO --- p.38 / Government Reaction After the Financial Crisis --- p.40 / Market Responses --- p.41 / Future Developments --- p.42 / Privatization Experience in the United Kingdom --- p.45 / Chapter VI. --- "SUMMARY, CONCLUSIONS AND RECOMMENDATIONS" --- p.46 / APPENDICES --- p.48 / BIBLIOGRAPHY --- p.56

"This work was supported by the Center for Energy Policy Research and the Electric Power Systems Engineering Laboratory of the Massachusetts Institute of Technology."

Electricity prices in competitive markets are extremely volatile with salient features such as mean-reversion and jumps and spikes. Modeling electricity spot prices is essential for asset and project valuation as well as risk management. I introduce the mean-reversion feature into a classical variance gamma model to model the electricity price dynamics as a mean-reverting variance gamma (MRVG) process. Derivative pricing formulae are derived through transform analysis and model parameters are estimated by the generalized method of moments and the Markov Chain Monte Carlo method. A real option approach is proposed to value a tolling contract incorporating operational characteristics of the generation asset and contractual constraints. Two simulation-based methods are proposed to solve the valuation problem. The effects of different electricity price assumptions on the valuation of tolling contracts are examined. Based on the valuation model, I also propose a heuristic scheme for hedging tolling contracts and demonstrate the validity of the hedging scheme through numerical examples. Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized ARCH (GARCH) models are widely used to model price volatility in financial markets. Considering a GARCH model with heavy-tailed innovations for electricity price, I characterize the limiting distribution of a Value-at-Risk (VaR) estimator of the conditional electricity price distribution, which corresponds to the extremal quantile of the conditional distribution of the GARCH price process. I propose two methods, the normal approximation method and the data tilting method, for constructing confidence intervals for the conditional VaR estimator and assess their accuracies by simulation studies. The proposed approach is applied to electricity spot price data taken from the Pennsylvania-New Jersey-Maryland market to obtain confidence intervals of the empirically estimated Value-at-Risk of electricity prices. Several directions that deserve further investigation are pointed out for future research.

Thesis (M. Phil.)--University of Hong Kong, 1980.