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ID:
116937
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| Publication |
2012.
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| Summary/Abstract |
We develop a metric to quantify the sub-hourly variability cost of individual wind plants and show its use in valuing reductions in wind power variability. Our method partitions wind energy into hourly and sub-hourly components and uses corresponding market prices to determine variability costs. We use publically available 15-min ERCOT data, although the method developed can be applied to higher time resolution data if available. We do not estimate uncertainty costs though our metric can separate integration costs into variability and uncertainty components. The mean variability costs arising from 15-min to 1-h variations (termed load following) for 20 ERCOT wind plants was $8.73±$1.26 per MWh in 2008 and $3.90±$0.52 per MWh in 2009. Load following variability costs decrease as capacity factors increase, indicating wind plants sited in locations with good wind resources cost a system less to integrate. Twenty interconnected wind plants had a variability cost of $4.35 per MWh in 2008. The marginal benefit of interconnecting another wind plant diminishes rapidly: it is less than $3.43 per MWh for systems with 2 wind plants already interconnected, less than $0.7 per MWh for 4-7 wind plants, and less than $0.2 per MWh for 8 or more wind plants.
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| 2 |
ID:
096627
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| Publication |
2010.
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| Summary/Abstract |
Geographic diversification of wind farms can smooth out the fluctuations in wind power generation and reduce the associated system balancing and reliability costs. The paper uses historical wind production data from five European countries (Austria, Denmark, France, Germany, and Spain) and applies the Mean-Variance Portfolio theory to identify cross-country portfolios that minimise the total variance of wind production for a given level of production. Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios. The methodology is then elaborated to derive optimal constrained portfolios taking into account national wind resource potential and transmission constraints and compare them with the projected portfolios for 2020. Such constraints limit the theoretical potential efficiency gains from geographical diversification, but there is still considerable room to improve performance from actual or projected portfolios. These results highlight the need for more cross-border interconnection capacity, for greater coordination of European renewable support policies, and for renewable support mechanisms and electricity market designs providing locational incentives. Under these conditions, a mechanism for renewables credits trading could help aligning wind power portfolios with the theoretically efficient geographic dispersion.
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| 3 |
ID:
097466
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| Publication |
2010.
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| Summary/Abstract |
Geographic diversification of wind farms can smooth out the fluctuations in wind power generation and reduce the associated system balancing and reliability costs. The paper uses historical wind production data from five European countries (Austria, Denmark, France, Germany, and Spain) and applies the Mean-Variance Portfolio theory to identify cross-country portfolios that minimise the total variance of wind production for a given level of production. Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios. The methodology is then elaborated to derive optimal constrained portfolios taking into account national wind resource potential and transmission constraints and compare them with the projected portfolios for 2020. Such constraints limit the theoretical potential efficiency gains from geographical diversification, but there is still considerable room to improve performance from actual or projected portfolios. These results highlight the need for more cross-border interconnection capacity, for greater coordination of European renewable support policies, and for renewable support mechanisms and electricity market designs providing locational incentives. Under these conditions, a mechanism for renewables credits trading could help aligning wind power portfolios with the theoretically efficient geographic dispersion.
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