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Photovoltaic (PV) technologies have shown remarkable progress recently in terms of annual production capacity and life cycle environmental performances, which necessitate timely updates of environmental indicators. Based on PV production data of 2004–2006, this study presents the life-cycle greenhouse gas emissions, criteria pollutant emissions, and heavy metal emissions from four types of major commercial PV systems: multicrystalline silicon, monocrystalline silicon, ribbon silicon, and thin-film cadmium telluride. Life-cycle emissions were determined by employing average electricity mixtures in Europe and the United States during the materials and module production for each PV system. Among the current vintage of PV technologies, thin-film cadmium telluride (CdTe) PV emits the least amount of harmful air emissions as it requires the least amount of energy during the module production. However, the differences in the emissions between different PV technologies are very small in comparison to the emissions from conventional energy technologies that PV could displace. As a part of prospective analysis, the effect of PV breeder was investigated. Overall, all PV technologies generate far less life-cycle air emissions per GWh than conventional fossil-fuel-based electricity generation technologies. At least 89% of air emissions associated with electricity generation could be prevented if electricity from photovoltaics displaces electricity from the grid.

The price of delivered electricity will rise if generators have to pay for carbon dioxide emissions through an implicit or explicit mechanism. There are two main effects that a substantial price on CO2 emissions would have in the short run (before the generation fleet changes significantly). First, consumers would react to increased price by buying less, described by their price elasticity of demand. Second, a price on CO2 emissions would change the order in which existing generators are economically dispatched, depending on their carbon dioxide emissions and marginal fuel prices. Both the price increase and dispatch changes depend on the mix of generation technologies and fuels in the region available for dispatch, although the consumer response to higher prices is the dominant effect. We estimate that the instantaneous imposition of a price of $35 per metric ton on CO2 emissions would lead to a 10% reduction in CO2 emissions in PJM and MISO at a price elasticity of -0.1. Reductions in ERCOT would be about one-third as large. Thus, a price on CO2 emissions that has been shown in earlier work to stimulate investment in new generation technology also provides significant CO2 reductions before new technology is deployed at large scale.

The wind is an increasingly significant source of energy with the rising price of non-renewable fuels. The purpose of this project is to determine the specific intensity and frequency of wind speed required to sustain a large-scale wind farm with power output on the order of hundreds of megawatts. To this end, a non-deterministic methodology will be developed to analyze the viability of wind energy systems. A deterministic analysis method considers the majority of design parameters to be known or fixed and may only perform trade studies on a few parameters at a time to optimize performance. In the case of the energy market though, this is not an advantageous strategy since several factors related to economic viability such as energy prices, interest rates, government incentives, acquisition costs and maintenance are highly variable and cannot be assumed to be known. A non-deterministic, statistical approach to wind turbine design has the advantage of predicting with corresponding levels of certainty the power output and economic viability of an energy system. The primary goal of this project is to define the envelope of operating conditions for a large-scale wind project while considering variables of both engineering and economic significance. The National Renewable Energy Laboratory’s (NREL) Hybrid Optimization Model for Electric Renewables (HOMER) will be incorporated into the previous analysis using YawDyn and PROPID to determine the economic returns on investment in hypothetical financing cases. Cost factors will now be assigned a mean value along with a probability distribution. Monte Carlo simulations will be run for a large number of variations in the assumed economic and engineering variables to develop an accurate estimate of the price per kilowatt-hour of energy produced from the simulated wind project for a variety of site conditions with the goal of finding the most suitable environment for sustainable wind development.

According to a new report, "Renewables Portfolio Standards in the United States: A Status Report with Data through 2007," released by the Lawrence Berkeley National Laboratory, a growing number of states are supporting renewable electricity through the creation of renewable portfolio standards (RPS). The report provides a comprehensive overview of early experience with these state-level RPS policies.

This paper proposes a simple method of determining the distance to voltage collapse using some local information such as bus voltage magnitude and load current magnitude. First the voltage and current information are carefully processed to establish a voltage stability index (VSI) that varies almost linearly with load. The VSI is then used to estimate the distance to voltage collapse using linear extrapolation. The effects of generator reactive power limits, line tripping, non-uniform increase in load and additional shunt reactive power sources on the VSI are also investigated. The effectiveness of the proposed method of determining the distance to voltage collapse is then tested on the IEEE 30-bus system. The results obtained by the proposed method are also compared with the corresponding actual values found through repetitive power flow simulations and are observed to be in very good agreement.