Determination of Peer-to-Peer Tariff Based on Levelized Cost of Energy and Utility Rate

Vikram Cherala, Sushanta Banerjee, P. Yemula
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Abstract

The growing rate of gated communities and limited residential rooftop solar provide opportunity for peer-to-peer (P2P) solar energy sharing among the residents. The very first and utmost requirement for a resident is to know the base rate, above which the energy could be sold for getting profit. To calculate the base rate, the present work develops the levelized cost of electricity (LCOE) of 5kWp rooftop solar system by considering all the design factors including geographical location and other costs related to installation, operation & maintenance. As the geographical parameters effecting solar generation changes with location, the P2P minimum energy cost also varies. In order to study the effect of different locations, a simulation is carried out in system advisory model (SAM) software for 25 districts of Telangana state. With changes in unit rate, the model determines the base price to choose a tariff for residents to sell their solar energy in a P2P energy market. A case study of P2P energy transaction for 35 homes in a gated community is made and profit is calculated for PV and non-PV investors. This study calculates minimum price of selling solar units and it's respective profits which motivate investors and non-investors to engage in P2P energy trading. It also helps the policymakers to derive new policy required for P2P energy trading and for distribution companies to fix unit rate of feed-in-tariff (FIT).
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基于均一化能源成本和公用费率的点对点电价确定
日益增长的封闭式社区和有限的住宅屋顶太阳能为居民之间的点对点(P2P)太阳能共享提供了机会。对居民来说,首要也是最重要的要求是知道基本费率,高于该费率的能源可以出售以获得利润。为了计算基本费率,本工作通过考虑所有设计因素,包括地理位置和与安装、运行和维护相关的其他成本,开发了5kWp屋顶太阳能系统的平准化电力成本(LCOE)。由于影响太阳能发电的地理参数随位置的变化而变化,P2P的最小能源成本也随之变化。为了研究不同位置的影响,在系统咨询模型(SAM)软件中对泰伦加纳邦的25个地区进行了模拟。随着单位费率的变化,该模型确定了基础价格,以选择居民在P2P能源市场上销售太阳能的电价。本文对一个封闭式社区中35户家庭的P2P能源交易进行了案例研究,并计算了光伏和非光伏投资者的利润。本研究计算了太阳能发电机组的最低销售价格及其各自的利润,以激励投资者和非投资者参与P2P能源交易。它还有助于政策制定者制定P2P能源交易所需的新政策,并为配电公司确定单位上网电价(FIT)。
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