基于区块链的框架,用于太阳能基站和电网之间的能源交易

Vikas Hassija, Vatsal Gupta, V. Chamola, Salil Kanhare
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引用次数: 3

摘要

全球快速增长的移动通信流量激增了蜂窝基站的部署,这反过来又导致了电信行业的电力消耗和碳足迹的增加。近年来,太阳能基站(SPBSs)因其使运营更具可持续性的能力而在电信行业广受欢迎。然而,SPBSs所带来的一些潜在能源效益尚未实现。在基站部署密集或移动通信量低的地区,SPBSs存储多余的能量,在大多数情况下,由于电池的电荷存储能力有限,这些能量会丢失。为了限制能源的浪费,可以采用适当的机制,利用这些基站产生的多余能源。为此,我们建立了基站到电网(BS2G)网络模型,其中电网可以利用SPBSs节省的剩余能量。为了克服可扩展性、稳健性和成本优化方面的挑战,我们建议使用区块链技术创建BS2G网络。区块链是一种分布式账本,旨在以透明、轻量级和防篡改的方式记录交易。为了使基站与电网之间的能源交易具有成本效益,本文还采用了博弈论的方法。该模型简化了能源交易过程,同时使其成本最优。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A blockchain-based framework for energy trading between solar powered base stations and grid
The rapidly increasing mobile traffic across the globe has proliferated the deployment of cellular base stations, which has, in turn, led to an increase in the power consumption and carbon footprint of the telecommunications industry. In recent times, solar-powered base stations (SPBSs) have gained much popularity in the telecom sector due to their ability to make operations more sustainable. However, some potential energy benefits rendered by the SPBSs have not yet been realized. In areas with dense base station deployment or low mobile traffic, SPBSs store surplus energy, which, in most instances, gets lost due to limited charge storage capacity of the batteries. To limit the wastage of energy, an appropriate mechanism enabling the utilization of excess energy produced by these base stations can be adopted. To this end, we model a Base Station-to-Grid (BS2G) network in which the grid can utilize surplus energy spared by the SPBSs. To overcome challenges in regards to scalability, robustness, and cost-optimization, we propose using the blockchain technology to create the BS2G network. Blockchain is a distributed ledger designed to record transactions in a transparent, lightweight, and tamper-proof manner. To make energy trade between base stations and the grid cost-effective, a game-theoretical approach has also been adopted in this paper. The proposed model simplifies the process of energy trading while also making it cost-optimal.
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