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This paperpresents an application of acondition-monitoring system (CMS) based on a polynomial regression model (PRM)to study the influence of heat loss on a wind generator’s temperatures.Monitoring the wind generator temperatures is a significant for efficientoperation, and plays a key role in an effective CMS. Many techniques, includingprediction models can be utilized to reliably forecast a wind generator’stemperature during operation and avoid the occurrence of a failure. PRMs arewidely used in situations when therelationship between the response and the independent variables are curve-linear.Thesetechniques can be used to construct a normal behavior model of an electricalgenerator’s temperatures based on recorded data. Many independent variables affect agenerator’s temperature; however, the degree of influence of each independent variable on the response is dissimilar. In manysituations, adding a new independent variableto the model may cause unsatisfactory results; therefore,the selection of the variables should be veryaccurate. A generator’s heatloss can be considered a significant independent variable that greatlyinfluences the wind generator with respect to the other variables. A generator’s heat loss can be estimated in intervals by analyzing theexchange in the heat between the hot and cold fluid throughthe heat exchangers of wind generators. Acase study built on data collected from actual measurements demonstrates theadequacy of the proposed model.

Phasor-based interdependencies of multiple harmonic sources, especially Distributed Energy Resources, on distribution networks are analyzed in this paper. A new index, Phasor Harmonic Index (IPH), is proposed by the authors. IPH considers both harmonic source magnitude and phase angle for different harmonic orders. Other commonly used harmonic indices are based solely on magnitude of waveforms. A very detailed model of a distribution network is used in the harmonic assessment. With the help of the detailed distribution network model, the phase couplings and the phase balancing impacts on harmonic propagation between three phases are investigated. Moreover, effects of harmonic source phase angle deviations are analyzed at both the customer side and the substation side. This paper investigates the importance of phase angles in harmonic assessment and how distribution network characteristics can be analyzed appropriately with phasor-based harmonic studies. In addition to device level harmonics, system level harmonic propagation need to be considered.

Presented paper – COMPENG 2010: Complexity in Engineering

Developed and conducted a demonstration of two real-time software tools to provide a grid operator a display of information and alarms from a network of phasor monitoring units and analysis of voltage security. Performed a scoping study that examined and prioritized options for data collection to improve the load and generator models used by CAISO and its control member utilities.

California is striving to achieve 33% renewable penetration by 2020 in accordance with the state’s Renewable Portfolio Standard (RPS). The behavior of renewable resources and electric vehicles in distribution systems is creating constraints on the penetration of these resources into the distribution system. One such constraint is the ability of present-­‐‑day voltage management methodologies to maintain proper distribution system voltage profiles in the face of higher penetrations of PV and electric vehicle technologies. This white paper describes the research gaps that have been identified in current Volt/VAR Optimization and Control (VVOC) technologies, the emerging technologies which are becoming available for use in VVOC, and the research gaps which exist and must be overcome in order to realize the full promise of these emerging technologies.

A presentation for the i4Energy Seminar Series for Spring 2011, February 4, 2011, UC Berkeley, Berkeley, California

Dynamic models of wind farms for power system studies are at present not a standard feature of many software tools, but are being developed by research institutes, universities and commercial entities. Accurate dynamic wind farm models are critical; hence model validation is a key issue and taken up by IEA Wind R&D Annex 21. This international working group includes participants from nine countries, and has since start-up in 2002 developed a systematic approach for model benchmark testing. This paper present this methodology, including example benchmark test results, but also gives an overview of the various wind farm models now being available from both Annex partners and external entities.