Facilitating Investment in Photovoltaic Systems in Iran Considering Time-of-Use Feed-in-Tariff and Carbon Market

Author:

Seyedzahedi Asrin,Bahramara SalahORCID

Abstract

Photovoltaic (PV) systems are the leading solutions for reducing carbon dioxide (CO2) emissions in Iran’s energy system. However, there are some challenges to investing in PV systems in Iran, such as the low energy market price and the high investment cost of PV systems. Although the flat feed-in tariff (FiT) is defined to help purchase energy from the PV systems, it is not attractive to investors. In this paper, a mathematical formulation is developed for the planning problem of the PV systems with battery energy storages (BESs) considering two incentive policies: (1) Designing time-of-use FiT to encourage the PV systems to sell energy to the grid at peak hours (2) Participating in the carbon trading energy market. The insolation in Iran is calculated regarding mathematical formulations which divide Iran into eight zones. The results of the base case show high payback periods for all zones. In the presence of the incentive policies, the payback period decreases considerably from 5.46 yrs. to 3.75 yrs. for the best zone. Also, the net present value increases more than 170 percent in some zones compared to the base case.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference27 articles.

1. (2021, December 25). Our World in Data. Iran: CO2 Country Profile. Available online: https://ourworldindata.org/co2/country/iran.

2. (2021, December 25). Iran CO2 Emission. Available online: https://countryeconomy.com/energy-and-environment/co2-emissions/iran,countryeconomic.com.

3. Modeling of a solar-powered thermo-electric air-conditioning system using a random vector functional link network integrated with jellyfish search algorithm;Almodfer;Case Stud. Therm. Eng.,2022

4. A new random vector functional link integrated with mayfly optimization algorithm for performance prediction of solar photovoltaic thermal collector combined with elec-trolytic hydrogen production system;Elaziz;Appl. Therm. Eng.,2021

5. A hybrid system coupling spiral type solar photovoltaic thermal collector and electrocatalytic hydrogen production cell: Experimental investigation and numerical modeling;Senthilraja;Process. Saf. Environ. Prot.,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3