Analysis of solar PV development and policies in Bogota

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Published Sep 10, 2021
Sebastian Zapata Diego Rua Andres J Aristizabal Monica Castaneda Isaac Dyner

Abstract

The urban expansion that takes place in developing countries has important impacts on environment, for that reason, it is important to supply household energy needs through renewable energies such as solar PV (photovoltaic). Which is one way to accomplish energy needs through generation of renewable energy on-site, also known as solar PV distributed generation [1]. Notwithstanding, as the adoption of solar PV panels in households must overcome important barriers, different environmental policies are applied around the world, such as feed in tariff and net metering [2].

Although economic growth of developing countries is associated to fossil fuel technology, it is necessary to seek alternatives to growth without increasing emissions [3]. In this sense, designing and analyzing the necessary policies to encourage the inclusion of renewable energies in developing countries is important.

The mix of Colombian electricity generation is mainly concentrated in two sources, hydro and fossil fuel power plants [4]. However, Colombia has been committed with making efforts to reduce greenhouse gas emissions in the electricity sector [5]. In Colombia, photovoltaic distributed generation presents many advantages for its deployment, especially in Bogota, whose electricity consumption is the highest in the country [6].

Using scenario analysis, this article intends to analyze different policy mechanisms to encourage solar energy in Bogotá, the largest city in Colombia. Given that, solar panels have a very good potential to supply electricity to homes and businesses in Bogotá [4]. Today, the residential sector in this city is the most electricity intensive, followed by the commercial, industrial and institutional sectors [7].

This paper assesses following scenarios that consider policies to encourage solar PV adoption in the residential sector: a feed in tariff is applied, net metering scheme is applied, none policy is applied.

A simulation model was built using system dynamics methodology, which considers the feedback loops, delays, and non-linearities inherent to the diffusion of solar PV. The simulation model may be represented through a subsystem diagram, where the system contains smaller subsystems that depicts the dynamics of the key relationships played at the simulation model (see fig.1). The subsystem diagram is composed by following components: wholesale electricity market, environmental indicators, PV policies and PV adoption. In next subsection the main equations are described by each component of the subsystem diagram.

 

The solar PV adoption is analyzed in terms of installed capacity, adopter households, potential adopter households, solar PV generation and avoided CO2 emissions.

Findings suggest that feed in tariff policy provides the best results to environment, as under this policy the highest levels of CO2 emissions are reached. However, Feed-in tariff may create windfall profits for PV producers. Policy designers must carry out adjustments according to learning curves given that solar PV is expected to get cheaper as PV installed capacity increases in the future. Additionally, potential adopters must perceive positive economic conditions for investing in PV systems—despite the application of a degression mechanism—to avoid any drop in PV investments.

Fig.1. Subsystem diagram

This article is organized in the following way: Section 2 corresponds to a literature review that includes an overview of the most popular economic instruments to encourage RET’s adoption (subsection 2.1) Section 3 explains the methodology of the work, Section 4 the discussion and results, and finally, the conclusions are presented in Section 5.

How to Cite

Zapata, S., Rua, D., Aristizabal, A. J., Castaneda, M., & Dyner, I. (2021). Analysis of solar PV development and policies in Bogota. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/243
Abstract 13 |

Article Details

References
[1] Y. Yamamoto. Energy, 86(9), 2678–2685 (2012). https://doi.org/10.1016/j.solener.2012.06.001
[2] R. Cullen. Australian Journal of Agricultural and Resource Economics, 61(1),1-18, 2017. https://doi.org/10.1111/1467-8489.12175
[3] I. Hanif. Energy,141, 170–178 (2017). https://doi.org/10.1016/j.energy.2017.09.054
[4] UPME. National Energy Plan 2050 (in Spanish), 184, (2015).
[5] Enersinc & DNP. Energy Supply Situation in Colombia. 1–163 (2017).
[6] Fedesarrollo. Análisis de la situación energética de Bogota y Cundinamarca. (2012).
[7] SUI. Sistema Único de Información de Servicios Públicos Domiciliarios. (2018).
Section
General Session: Technologies For Smart Connected Societies

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