Grid-connected solar power generation, either dispersed or centralized, has developed and grown at the margin of a core of dispatchable and baseload conventional generation. Its economics and management have required ever more versatile and precise historical and operational solar resource information with increasing penetration. Operational solar forecasts have become central to both TSO/RTO and distribution operations in regions with significant solar penetration, for e.g., energy markets, ramp and power quality management.

This article proposes that optimally deployed solutions to the intermittency introduced by high penetration solar - e. g., electrical storage, optimized curtailment and demand response - could affordably transform solar power generation into the firm power delivery system modern energy economies require, thereby enabling very high solar penetration and the displacement of conventional power generation. The optimal deployment of these high-penetration-enabling solutions imply the existence of a healthy power grid, and therefore imply a central role for utilities and grid operators.This article also proposes that a value-based electricity compensation mechanism (based on e.g., Value of Solar (VOS) and load shaping tariffs), recognizing the multi-facetted, penetration-dependent value and cost of solar energy, and capable of shaping consumption patterns to optimally match resource and demand, could be an effective vehicle to enable high solar penetration and deliver affordable firm power generation. (C) 2016 Elsevier Ltd. All rights reserved.

Validation and operational improvements to the existing SUNY satellite-to-solar irradiance model through incorporation of four of the geostationary satellite infrared (IR) channels are presented herein. The SUNY model is the gridded data set used by NREL in the National Solar Radiation Database (NSRDB) and is available commercially through the Clean Power Research software, SolarAnywhere® Data. This improved model addresses the present model's limitations when representing the irradiance conditions in circumstances of snow cover, high ground reflectance and persistent cloud cover. Improvements in the satellite-to-solar irradiance model have been realized using the IR channels to detect snow conditions and modulate the model background to more accurately reflect irradiance conditions.

This article presents a set of empirical models capable of extracting metrics quantifying the short-term variability of the solar resource based upon site/time specific satellite-derived hourly irradiance data. The model is derived from over 92,000 experimental hourly data points at twenty-four sites in the United States. The model returns four metrics characterizing intra-hourly variability, including the standard deviation of the global irradiance clear sky index, and the mean index change from one time interval to the next, as well as the maximum and standard deviation of the latter. The variability time scales addressed in this paper are 20s, one-minute, 5min and 15min. The trends underlying the models are robust and show little site dependency.

This paper describes an ongoing effort to reach consensus on the notion of capacity credit for solar power electrical generation. The paper presents different methodologies quantifying capacity credit and reports on their intercomparison through experimental case studies for three diverse electric utility companies. Satellite-derived solar resource data are used to simulate the site/time specific PV output injected in the selected power grids. The paper concludes by reporting the initial results of a consensus-building effort involving the utility industry, the solar industry, and government.

Payback is often used as a measure of profitability by prospective PV owners. Contrasting this measure with another financial gauge––life-cycle cash flow––the paper discusses why payback may not be the most appropriate measure for residential PV applications and why it may hide sound financial opportunities for those deciding to invest in a PV system.

We present an evaluation of a new version of the web-based clean power estimator (CPE) capable of evaluating the effectiveness and value of solar load control (SLC) for commercial applications in the US. Three experimental building case studies are used as a validation benchmark. The selected buildings include a large office building near New York City, a department store in Long Island, and another department store in Hawaii. The results of the CPE calculations are compared against results obtained using actual building load and colocated hourly actual solar radiation data.

Rapid market growth for customer-sited photovoltaics (CSPV) is the direct result of new policy, program and tariff related incentives developed by a variety of energy industry stakeholders. In previous publications (1,2), the authors investigated the geographical distribution of the economic feasibility of customer-owned commercial photovoltaic (PV) systems in the U. S. to assess the commercial market value. The market value is presented as a breakeven turn-key cost (BTC) by analyzing the installed and operating costs relative to incentives, energy savings and externality values over the life of the PV system. This paper provides an updated snapshot of the commercial BTC values for the US. Included in the paper are:

As the energy industry seeks new definition, either within