Solar Today November December 2012 : Page 31

SOLAR TODAY NOVEMBER/DECEMBER 2012 VOL. 26, NO. 7 ® What is the best match to U.S. loads that could be achieved with wind power and PV? NREL’s load-matching model calculates the answer. B y V ICTOR DIAKO V Vict or Di a k o v (victor.diakov@nrel.gov), senior engi-neer at the National Renewable Energy Laboratory, is a member of the Energy Forecasting and Modeling Group in NREL’s Strategic Energy Analysis Center. For Diakov, the road to renewable energy has taken him from trading stocks for an agrochemical company to designing chemical reactors, testing clean coal power plants at Air Liquide, integrating vehicular hydrogen infrastructure models and now, to electric power modeling at NREL. A PPRO A CH Our model (Short and Diakov, 2012) answers the following question: What is the best match to U.S. loads that could be achieved with wind power and photovoltaics? (Specifi-cally, we examined the wind, solar resources and loads in the United States as a whole and in the area of the WECC. Our primary decision variables are where and how much resource W i (wind and/or photovoltaic) should be built at each wind and PV site i . Over all 8,760 hours in a year, the model minimizes the sum of the squared difference between loads (l t ) and the generation from the selected wind and solar sites: Minimize ∑ t Δ t 2 Δ t = l t –∑ i W i *w it for all t forall i 0 < W i <1 (1) with the following constraints (2) (3) w it are inputs; thus we assume a perfect forecast throughout the year. The sum of all the positive ∆ t is the total amount of generation required from dispatch-able generators. Similarly, the sum of the nega-tive ∆ t is the total amount of all energy curtailed or sent to storage. The wind and solar generation are traded off solely on the basis of how well they meet load, not their relative economics. INPUT D A T A For the wind resource, we are using NREL data developed for the Western Wind and Solar Integration Study (WWSIS) (Potter et al . 2008) and the Eastern Wind Integration and Transmission Study (EnerNex 2011). The data include three years of generation information, 2004–2006, for 32,000 potential wind sites in the western United States and about 6,000 potential wind sites in the eastern United States. w it is the generation that could be produced at hour t by the wind or PV resource at site i ; F IGURE 1. Using data from the Western Wind and Solar Integration Study (WWSIS) and the Eastern Wind Integration and Transmission Study (EWITS) databases, the author’s load-matching model gen-erates a 3-D projection of the electric load (green vertical line), wind (blue, green and black dots to the right of the load) and PV (red, blue, green and black dots to the left from the load line) variable generation profiles. The goal of renewable load matching is to combine the PV and wind dots so that the aggregated wind and PV generation is closest to the load. For demonstration purposes, all generation sites on the figure are scaled up or down to have equal 30-MW nominal capacity. Linear programming models are usually more practical because they require significantly less computation time. The quadratic version, though, allows for a more transparent geometric interpretation of the model results and is used here. 2 Flexible (dispatchable) generators are those that can be used when needed. They would include the standard set of conven-tional plants (e.g. gas, hydro, biomass). They would exclude wind and photovoltaics, which are not fully dispatchable due to their variable resources. 3 The geographic diversity of solar resources effectively reduces short-term (mostly sub-hourly) variability of solar generation (Perez and Hoff, 2012). Here, we only consider hourly variations, although on a larger geographic scale. Copyright © 2012 by the American Solar Energy Society Inc. All rights reserved. 1 solartoday.org SOLAR TODAY November/December 2012 31

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