The Costs of Privacy in Local Energy Markets
The Costs of Privacy in Local Energy Markets
复制标题
当地能源市场的隐私成本
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Klemens Böhm
中科院分区：
文献类型：
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作者：
Erik Buchmann;Stephan Kessler;P. Jochem;Klemens Böhm
许多可再生能源发电是分布式的，本质上不稳定，效率低下，难以与传统输电路径协调。作为从化石燃料向可再生能源过渡的一部分，地方能源市场使当地能源能够有效地分配和分配给附近的家庭。当使用离散时间双向拍卖模型时，此类市场中的出价反映了能源的供应和需求。然而，由于家庭的能源需求包含个人信息，这种市场不符合隐私立法。在本文中，我们研究了匿名化方法对当地能源市场的影响。特别是，我们匿名化订单簿的出价，并将此分配的市场参与者的二氧化碳排放量和费用与非匿名者进行比较。我们为当地的能源拍卖平台建立了个人数据流模型，并为一个小镇在不久的将来的电力供应和需求开发了一个模型。我们的实验表明，使用基本的匿名化方法，匿名化对成本和二氧化碳排放量的影响很小。
Many renewable sources for electricity generation are distributed and volatile by nature, and become inefficient and difficult to coordinate with traditional power transmission paths. As a part of the transition from fossil fuel to renewable sources, local energy markets allow an efficient allocation and distribution of energy from local sources to nearby households. When using a discrete time double auction model, bids in such markets reflect the supply and demand of energy. However, since the energy demand of a household contains personal information, such markets are not in line with privacy legislation. In this paper, we investigate the influence of anonymization methods on local energy markets. In particular, we anonymize the bids of the order book, and we compare the CO2 emissions and the expenses of market participants of this allocation with a non-anonymous one. We have modeled the flows of personal data for a local energy auction platform, and we have developed a model for the supply and demand of electricity of a small town in the near future. Our experiments show that with elementary anonymization methods, the impact of anonymization on the costs and on the CO2 emissions is small.