The Costs of Privacy in Local Energy Markets

Abstract

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.

Day-ahead micro-market design for distributed energy resources

“…This proposal, similary to Buchmann et al [20], includes the role of the micromarket operator (MMO). Additionally, [19] explores the cost structure of market participants.…”

Privacy Violations in Constrained Micro-Grids: Adversarial Cases

“…The ETO is interested in making some profit, so its primary concern is not consumer interest. A distributed case is an open market where renewable energy producer and consumers participate in the local markets and trade energy over short time intervals [25], [26] i.e. energy producer auctioning and consumer bidding for electricity.…”

Forecasting in Blockchain-Based Local Energy Markets

“…Mainly driven by the widespread adoption of smart meters and Internet-connected home appliances, recent work on LEMs focuses on use cases in developed and highly technologized energy grid systems [19]. While substantial work regarding LEMs in general has been done (e.g., [7,8,15]), there are only few examples of blockchain-based LEM designs in the existing literature. Mengelkamp et al [10] derived seven principles for microgrid energy markets and evaluated the Brooklyn Microgrid according to those principles.…”

“…LEMs enable interconnected energy consumers, producers, and prosumers to trade energy in near real-time on a market platform with a specific pricing mechanism [6]. A common pricing mechanism used for this purpose are discrete double auctions [7][8][9]. Blockchain-based LEMs utilize a blockchain as underlying information and communication technology and a smart contract to match future supply and demand and to settle transactions [10].…”

“…However, research on blockchain-based LEM mostly employ market mechanisms that require accurate forecasts of household energy consumption/production making the aspect of forecasting especially relevant here. Despite this, it is frequently assumed in existing research on (blockchain-based) LEMs that such accurate forecasts are readily available (see, e.g., [6][7][8]16,17]). However, forecasting the consumption/production of single households is difficult due to the inherently high degree of uncertainty, which cannot be reduced by the aggregation of households [18].…”