Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines
Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines
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DOI：
10.1016/j.eneco.2013.07.004
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发表时间：
2013-11
期刊：
影响因子：
12.8
通讯作者：
Johannes Schmidt;Georg V. Lehecka;V. Gass;E. Schmid
中科院分区：
文献类型：
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作者：
Johannes Schmidt;Georg V. Lehecka;V. Gass;E. Schmid
上网电价(FIT)是促进可再生电力生产的最重要政策工具之一。固定价格FIT(FFIT)和基于溢价的FIT(PFIT)在欧盟普遍实施，FFIT保证每单位生产的电力有固定的价格，PFIT在市场价格之上支付溢价。FFIT平衡间歇性发电量的成本可能比PFIT高得多，当边际生产成本较高时，FFIT不会提供任何生产电力的激励。相比之下，PFIT确实提供了强大的激励措施，以更好地将可再生电力产出与系统中的边际生产成本相匹配。本文的目的是评估这两种收费方案对风力发电机组位置选择的影响。在一个分析模型中，我们表明，在PFIT方案中，风电供需之间的协方差以及不同风电位置之间的协方差对投资者都是重要的。与其他间歇性生产商的高度协方差导致市场价格下降，从而导致风电投资者的收入下降。因此，他们受到激励，使风力涡轮机的位置多样化，以减少不同风力发电地点之间的协方差。在一个经验优化模型中，我们在奥地利的一个政策实验中分析了这两种不同方案的效果。数值结果表明，在PFIT方案下，(1)空间多样化得到激励；(2)风电发电量与边际发电成本的协方差增大；(3)当风电配置达到全国总用电量的10%时，风电发电量和剩余负荷的方差减小。
Feed-in tariffs (FIT) are among the most important policy instruments to promote renewable electricity production. The fixed-price FIT (FFIT), which guarantee a fixed price for every unit of produced electricity and the premium based FIT (PFIT), which pay a premium on top of the market price are commonly implemented in the EU. Costs for balancing intermittent electricity production may be significantly higher with FFIT than with PFIT, and FFIT do not provide any incentive to produce electricity when marginal production costs are high. In contrast, PFIT do provide strong incentives to better match renewable power output with marginal production costs in the system. The purpose of this article is to assess the effects of the two tariff schemes on the choice of wind turbine locations. In an analytical model, we show that both the covariance between wind power supply and demand as well as between the different wind power locations matter for investors in a PFIT scheme. High covariance with other intermittent producers causes a decrease in market prices and consequently in revenues for wind power investors. They are therefore incentivized to diversify the locations of wind turbines to decrease the covariance between different wind power production locations. In an empirical optimization model, we analyze the effects of these two different schemes in a policy experiment for Austria. The numerical results show that under a PFIT scheme, (1) spatial diversification is incentivized, (2) the covariance of wind power production with marginal electricity production costs increases, and (3) the variances of the wind power output and of residual load decrease if wind power deployment attains 10% of total national electricity consumption.