可验证计算技术在能源区块链系统中的分析与应用

Andreas Zeiselmair, Bernd Steinkopf, Ulrich Gallersdörfer, A. Bogensperger, F. Matthes
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引用次数: 4

摘要

能源系统正变得越来越分散。这种发展需要在一个复杂的系统中整合和协调越来越多的参与者和小单位。区块链可以为新工具和平台提供基础设施,这些工具和平台可以在各个方面解决这些任务——从调度优化或动态负载适应到(本地)市场机制。其中许多应用程序目前正在开发中,并受到研究项目的影响。特别是在分散的能源市场中,能源产品的优化配置需要复杂的计算。由于存储和计算资源有限,将这些与分布式账本技术相结合会导致隐私要求和性能方面的瓶颈和挑战。可验证计算技术有望解决这些问题。本文概述了可验证计算技术,包括可信预言机、zksnark和多方计算。我们进一步分析了它们在区块链环境中的应用,重点是与能源相关的应用。应用于可再生能源证书的一个独特的优化问题,我们评估了这些解决方案的方法,并最后演示了一个简单优化的实现,使用zkSNARKs作为案例研究。最后,我们评估了所描述的可验证计算技术的适用性,并解决了大规模部署的局限性,然后展望了当前的发展趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Application of Verifiable Computation Techniques in Blockchain Systems for the Energy Sector
The energy system is becoming increasingly decentralized. This development requires integrating and coordinating a rising number of actors and small units in a complex system. Blockchain could provide a base infrastructure for new tools and platforms that address these tasks in various aspects—ranging from dispatch optimization or dynamic load adaption to (local) market mechanisms. Many of these applications are currently in development and subject to research projects. In decentralized energy markets especially, the optimized allocation of energy products demands complex computation. Combining these with distributed ledger technologies leads to bottlenecks and challenges regarding privacy requirements and performance due to limited storage and computational resources. Verifiable computation techniques promise a solution to these issues. This paper presents an overview of verifiable computation technologies, including trusted oracles, zkSNARKs, and multi-party computation. We further analyze their application in blockchain environments with a focus on energy-related applications. Applied to a distinct optimization problem of renewable energy certificates, we have evaluated these solution approaches and finally demonstrate an implementation of a Simplex-Optimization using zkSNARKs as a case study. We conclude with an assessment of the applicability of the described verifiable computation techniques and address limitations for large-scale deployment, followed by an outlook on current development trends.
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