IEEE Power & Energy Magazine - March/April 2017 - 49

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E

ECONOMIES OF SCALE, INCENTIVES, AND TECHNOLOGICAL
advances have made photovoltaic (PV) systems more affordable and common
in developed nations. In Latin America, however, cost and regulation are still
barriers for their widespread adoption, particularly by residential and commercial customers. In Costa Rica, there has only recently been interest in rooftop
PV systems thanks to a major pilot project carried out from 2010 to 2015 by
the Costa Rican Institute of Electricity (Instituto Costarricense de Electricidad,
ICE), the administrator of the generation, the transmission system operator, and
one of the eight distribution network operators (DNOs) who also supply electricity. The hundreds of installations involved in this project created the momentum
needed by the local emerging PV industry to push for changes in the regulatory
framework and demonstrate the economic benefits, given the relatively high
electricity prices. Although this project represented only a modest PV penetration, ICE recognized that the ability of distribution circuits to host rooftop PV
systems should be adequately assessed. This prompted the Ministry of Energy
and Environment to create a new and important requirement for Costa Rican
DNOs: the generation-hosting capacity of distribution circuits should be quantified considering a comprehensive set of studies, with most of them requiring
detailed network models.
The diversity in the installed capacity of rooftop PV systems (from a few to
hundreds of kilowatts), as well as in the voltages they are connected to (from
low to medium voltages), means that DNOs in Costa Rica-and many others
around the world-need to have network studies that not only cover large areas
but also adequately model small- and medium-scale customers. To successfully achieve this, Costa Rican DNOs have collaborated with the University of
Costa Rica in a pioneering project to develop advanced open-source simulation
tools that integrate distribution network analysis software and data from multiple geographical information systems (GISs) that include valuable information
about distribution network components and customers stored by DNOs ranging
from sun irradiance to socioeconomic statistics.
This article reviews the different aspects to be considered when integrating GIS data sources and distribution network analysis software. The practical challenges involving data errors and modelling, the adopted solutions,
and, ultimately, the open-source tools developed for the Costa Rican DNOs
employing Quantum GIS (QGIS), OpenDSS, and Python are described. The
use of these tools, created to assess the impacts of PV systems, are illustrated
on a real, large-scale distribution network located in the metropolitan area
of Costa Rica.

Using Geographical
Information Systems to
Assess Rooftop Photovoltaics
in Costa Rica

The Greener, the Better

Costa Rica is a country in Central America with
almost 5 million inhabitants. Its electricity sector
is characterized by a highly renewable generation mix and a national electricity access above
99% provided by the eight DNOs (see Figure 1 for
their locations), all regulated by the Regulatory
Authority of Public Services (ARESEP).
Costa Rica has been committed to generating electricity from renewable energy sources,
particularly hydro. By 2015, approximately
80% of the total installed capacity (exceeding 3 GW) was from renewable
technologies (see Table 1). In terms of energy, 99% of the total generation
(10.6 TWh) was produced from clean energy sources: 75% hydro, 10% wind,
13% geothermal, 1% fossil fuel, and about 1% other technologies (biomass
and solar).

march/april 2017

ieee power & energy magazine

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Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - March/April 2017

IEEE Power & Energy Magazine - March/April 2017 - Cover1
IEEE Power & Energy Magazine - March/April 2017 - Cover2
IEEE Power & Energy Magazine - March/April 2017 - 1
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IEEE Power & Energy Magazine - March/April 2017 - Cover3
IEEE Power & Energy Magazine - March/April 2017 - Cover4
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