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ID:
122711
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2013.
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| Summary/Abstract |
In electricity markets that use a merit order dispatch system, generation capacity is ranked by the price that it is bid into the market. Demand is then met by dispatching electricity according to this rank, from the lowest to the highest bid. The last capacity dispatched sets the price received by all generation, ensuring the lowest cost provision of electricity. A consequence of this system is that significant deployments of low marginal cost electricity generators, including renewables, can reduce the spot price of electricity. In Australia, this prospect has been recognized in concern expressed by some coal-fired generators that delivering too much renewable generation would reduce wholesale electricity prices. In this analysis we calculate the likely reduction of wholesale prices through this merit order effect on the Australian National Electricity Market. We calculate that for 5 GW of capacity, comparable to the present per capita installation of photovoltaics in Germany, the reduction in wholesale prices would have been worth in excess of A$1.8 billion over 2009 and 2010, all other factors being equal. We explore the implications of our findings for feed-in tariff policies, and find that they could deliver savings to consumers, contrary to prevailing criticisms that they are a regressive form of taxation.
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| 2 |
ID:
109661
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2011.
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| Summary/Abstract |
With increased focus on renewable energy in our modern era, it is increasingly important to understand the impact of policies on the performance and reliability of regional energy systems. This research develops a model to understand how geographic dispersion of PV installations impacts the reliability of electricity generated from the total PV network, measured by the variance of the distribution of generated electricity. Using NREL data, beta probability distributions of sunlight (kWh/m2/day) in various regions of Virginia are estimated using a fitting method that minimizes the Kolmogorov-Smirnov test statistic. A Monte Carlo simulation model is developed to measure PV electricity generation from multiple centralized and dispersed configurations over 100,000 days of probabilistic sunlight.
There is a calculable tradeoff between average generation and generation variability, and increased geographic dispersion of PV installations can decrease this variability. Controlling variable generation through policies that promote efficient PV siting can help provide reliable power, minimizing the need for load-balancing peaking power infrastructure and costly electricity purchases from the grid. Using a tradeoff framework of generation and costs, this paper shows that geographically dispersed generation can mitigate the risk of unreliable solar generation that can significantly impact the end-user costs and make PV infrastructure unattractive.
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