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710 IEEE Transactions on Power Systems, Vol. 13, No. 2, May 1998 ower in New England: Modeling and Analysis of Non-Dispatchable Renewable Energy Technologies Judith B. Cardell Laboratory for Electromagnetic and Electronic Systems Massachusetts Institute of Technology Cambridge, MA 02139 Abstract: Non-dispatchable renewable energy technologies have beneficial environmental, financial and planning characteristics, yet are not readily included in resource planning anairis for two main reasons: the lack of amiliarity m t e power sector with their behavior, and the lack of a propriate analysis tools. This paper presents a methodoi)ogy, to be used in conjunction with a standard production-costing model, for anal zing non-dispatchable systems operation. Our analysis of 1500 MWP of windpower in New En land shows that this capacity can capture the same amount opener y as the re ion's utility s onsored DSM programs, and &at the win$ resource in Jew England is comparable, on an energy basis, to that in Califomia. Keywords: Renewable energ , wind power,, resource renewable energy technologies (R l Ts) as part of power I planning, renewable resource mo Ly eling INTRODUCTION Renewable energy technologies differ from more conventional thermal generators in that their resource, such as solar insolation or wind, is intermittent and cannot be controlled. Such non- dispatchable power generators cannot be modeled or analyzed in the same manner as conventional power plants, thus an alternative methodology must be employed for determining their usefulness and overall effect on the power system, in terms of system reliability and environmental and economic impacts. The Analysis Group for Regional Electricity Alternatives (AGREA), in the MIT Energy Lab, works with New England electric utilities, environmental groups, regulators and industry, to obtain mutually acceptable, long-range strategies for meeting the region's future electricity demand. In response to the increasing interest in renewable energy technologies (RETs), some of these technologies have been included in AGREA's analysis. Off-the-shelf data and analysis tools required to analyze the potential value and contribution of RETs are not currently available. PE-888-PWRS-2-06-1997 A paper recommended and approved by the IEEE Power System Planning and implementation Committee of the IEEE Power Engineering Society for publication in the IEEE Transactions on Power Systems. Manuscript submitted December 31, 1996; made available for printing June 9: 1997. Stephen R. Connors, Member, IEEE Electric Utility Program, Energy Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 Thus the AGREA team has developed the necessary analytic tools to both build the required databases, and to analyze this data to quantify the impacts of RETs on power system operation. This paper applies the methodology developed to an analysis of two hypothetical wind farms, totaling 1500 MWp, in New England. This paper discusses both stages of this windpower analysis, the hourly windspeed data preparation and the calculation of the potential impacts of windpower electricity generation in New England. WINDSPEED DATA PREPARATION The basic properties of wind are speed, direction, and fluctuations in this speed and direction. Although intermittent in nature, a wind resource can be well understood and predicted through use of winds peed and direction measurements, and probabilistic models. We use the probabilistic nature of a wind regime, along with hourly data, in developing the required databases. This process is described below. Obtaininr Hourly Data Annual and monthly average windspeeds are widely available, and useful for broad classifications of the wind resource at any site. However, power generation from wind turbines is determined by the windspeed and direction at each moment. Thus, in order to accurately model the power generation from the turbines and their impact on a power system, data on the windspeed and direction at each moment is required. A common method to acquire this data is to take measurements every ten to fifteen minutes and then average these to an hourly value. Using data from multiple years is also important for any analysis so that long-term weather patterns and other variations are fully represented. For this analysis, multi-year, hourly windspeed data for two different sites in New England, one in Maine and the other in Massachusetts, was used. The absence of directional data is acceptable since turbines in general have yaw control to allow them to constantly point into the wind. A small loss factor is included to account for the inaccuracy. 0885-8950/98/$10.00 0 1997 IEEE711 wind direction. A standard lower boundary for "a" is 1/7 [5,7,9,10]; an upper boundary for the New England study was calculated for Stratton Mt. VT at a value of 0.426. A conservative value of 0.250, between these two extremes, was used in this analysis. The National Climatic Data Center (NCDC) in Ashville, North Carolina has the only publicly available, multi-year, hourly windspeed data for the Northeast. However, the NCDC hourly windspeed data was inappropriate for direct use in our analysis since it contains numerous gaps and is most often recorded at airports where the wind resource differs significantly from that at a likely wind farm site due to the difference in terrain. The methodology for preparing the data for our analysis, which includes repairing the gaps in the NCDC data, shifting it to the appropriate altitude and wind turbine height, and then adjusting it to reflect the resource at a potential wind farm site, is described below. The data for the Massachusetts site was recorded on Mt. Tom in Western Massachusetts, and thus needed little preparation to be appropriate for use in our analysis. The Maine data however, was recorded at an airport, and thus required significant adjustment to represent the wind resource of a mountain ridge. The Massachusetts data provides a good baseline for comparing the adjusted Maine data. We also benchmarked our resultant data with proprietary data from two New England utilities, to ensure that it was representative of potential windpower sites in the region. EfpairinE: All


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