The Open Electrical & Electronic Engineering Journal




(Discontinued)

ISSN: 1874-1290 ― Volume 13, 2019
RESEARCH ARTICLE

The Calculation and Optimization Research of Renewable Energy Investment Efficiency under Uncertain Conditions



Tao Yi1, Yifan Zhang1, *, Yanfeng Guo2
1 North China Electric Power University, Bei Nong Lu No.2, Changping District, Beijing, China
2 Beijing Electric Power Economic Research Institute, No.15, West Street, Guanganmen Station, Xicheng District, Beijing ,China

Abstract

Background:

In the renewable energy investment market, there are risks such as fossil fuel price fluctuations, environmental risks caused by pollutant emissions, electricity price fluctuations caused by energy policies, and so on, which bring certain difficulties to measure the investment efficiency.

Methods:

In this regard, the paper applies the portfolio theory to the Data Envelopment Analysis (DEA) model to evaluate investment efficiency. First of all, the Monte Carlo method is used to simulate the four uncertain factors of fuel unit price, feed-in tariff, annual operating hours, and carbon price, so as to quantitatively measure the risk and return of different power generation. According to the portfolio theory, it evaluates the portfolio risks and returns, respectively as input and output indicators, so as to build a Data Envelopment Analysis (DEA) model to estimate investment efficiency.

Conclusion:

The simulation and experimental results demonstrate the effectiveness of the presented method. In details, we select a poor efficiency sample, and then, we propose an optimization measure to improve the efficiency. By adjusting the proportion of its investment, the result proves that increasing the proportion of renewable energy can realize optimization and validity of renewable energy investment. Thus, it provides auxiliary support for the investment decision of renewable energy and realizes the coordinated allocation and efficient utilization of renewable energy.

Keywords: Renewable energy, Uncertain conditions, Portfolio theory, Investment efficiency, Data Envelopment Analysis, Monte Carlo.


Article Information


Identifiers and Pagination:

Year: 2018
Volume: 12
First Page: 52
Last Page: 62
Publisher Id: TOEEJ-12-52
DOI: 10.2174/1874129001812010052

Article History:

Received Date: 16/3/2018
Revision Received Date: 16/7/2018
Acceptance Date: 20/7/2018
Electronic publication date: 31/08/2018
Collection year: 2018

© 2018 Yi and Zhang.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


* Address correspondence to this author at the School of Economics and Management, North China Electric Power University, Beijing, Changping District, 102206, China; Tel: +86-13718807916; E-mail: 1944506154@qq.com



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