As the technology behind renewable energy sources becomes more advanced and cost-effective, these sources have become an ever-increasing portion of the generation portfolios of power systems across the country. While the shift away from non-renewable resources is generally considered beneficial, the fact remains that intermittent renewable sources present special challenges associated with their unique operating characteristics. Because of the high variability of intermittent renewables, the frequency performance of the system to which they are connected can degrade. Generators assigned to regulate frequency, keeping it close to the desired 60 Hz, are forced to ramp up and down quickly in order to offset the rise and fall of the variable resources (in addition to the rise and fall of load), causing transient frequency deviations, power swings, major interface transfer variations and other significant issues. This research measures the impact of intermittent renewable resource penetration level on power system frequency performance, and offers methods for managing that performance. Currently, the generally accepted amount of regulation (rapidly-dispatchable reserve, used as a supplement to base generation on a short time scale to avoid performance issues) is 1% of peak load. Because of the high variability associated with intermittent renewables, including wind generation (the focus of this thesis), it is expected that this amount of regulation must increase in order to maintain adequate system frequency performance. Thus, the primary objective of this thesis is to quantify the amount of regulation necessary to maintain adequate frequency performance as a function of the penetration level of wind generation. Presently, balancing resource requirements are computed, in both industry and in the research literature, using static models, which rely entirely on statistical manipulation of net load, failing to capture the intricacies of dynamic system and generator interactions. Using a dynamic model with high temporal resolution data, instead of these statistical models, this thesis confirms the need for additional regulation as wind generation penetration increases. But beyond that, our research demonstrates an exponentially increasing relationship between necessary regulation and wind generation percentage, indicating that, without further technological breakthroughs, there is a practical limit to the amount of wind generation that a typical system can accommodate. Furthermore, we compare our dynamic model results with those of the statistical models, and show that the majority of current statistical models substantially under-predict the necessary amount of regulation to accommodate significant amounts of wind generation. Finally, we verify that the ramping capability of the regulating generators impacts the amount of necessary regulation, although it is generally ignored in current analysis and related literature.

When wind power and other intermittent renewable energy (IRE) sources begin to supply a significant part of the load, concerns are often raised about the inherent intermittency and unpredictability of these sources. In order to study the impact from higher IRE penetration levels on the power system, integration studies are regularly performed. The model package presented and evaluated in Papers I–IV provides a comprehensive methodology for simulating realistic time series of wind generation and forecasts for such studies. The most important conclusion from these papers is that models based on coarse meteorological datasets give very accurate results, especially in combination with statistical post-processing. Advantages with our approach include a physical coupling to the weather and wind farm characteristics, over 30 year long, 5-minute resolution time series, freely and globally available input data and computational times in the order of minutes. In this thesis, I make the argument that our approach is generally preferable to using purely statistical models or linear scaling of historical measurements. In the variability studies in Papers V–VII, several IRE sources were considered. An important conclusion is that these sources and the load have very different variability characteristics in different frequency bands. Depending on the magnitudes and correlations of these fluctuation, different time scales will become more or less challenging to balance. With a suitable mix of renewables, there will be little or no increase in the needs for balancing on the seasonal and diurnal timescales, even for a fully renewable Nordic power system. Fluctuations with periods between a few days and a few months are dominant for wind power and net load fluctuations of this type will increase strongly for high penetrations of IRE, no matter how the sources are combined. According to our studies, higher capacity factors, more offshore wind power and overproduction/curtailment would be beneficial for the power system.