The main goal of this work is to propose a methodology
for the implantation of solar roofs in the city of Nova Veneza, located in the
State of Goiás (GO), and to carry out an economic feasibility study of the
implantation of photovoltaic systems, taking into account different scenarios,
in the cities of Goiânia-GO and Nova-Veneza-GO.
The demand for energy in the world has been increasing
and along with this need, there is still growing concern about supplying this
demand using renewable and sustainable sources.
The Research & Development (R&D) Project No. 253
of Celg Distribution (Celg-D) entitled “Application of Intelligent Network
(Smart Grid) on the Supervision of Electricity Supply Medium and Low Voltage
Using Different Communication Technologies” was carried out between 2012 and
2013 with the R&D program funds approved by the National Electric Energy
Agency (Aneel) 1. The project covers different areas of applications related
to Smart Grids as Advanced Metering Infrastructure (AMI), Distribution
Automation (DA) and Integration of Celg-D systems. In addition, it was
developed a consumer portal, opinion polls with consumers and a methodology for
positioning of concentrators in a Mesh Network (MN). Thus, the R&D project
No. 253 allowed the Energy utility to have a direct contact with technologies
and systems for testing and technical evaluation in these areas 2.
Fig. 1 shows a simplified scheme for the installation of
meters, with the need of hiring a GPRS data circuit (General Packet Radio
Service) to allow sending data collected from the meters for The Supervision
Center, located in Goiânia-GO, based on the premises of Celg-D. Thus, meter data
are forwarded to a concentrator device as GPRS Data Connection that takes
readings directly to the energy utility 2.
development of the R&D Project No. 253 the integration and the automation
of the System of Service Orders and the measurement system was carried out by
proposing that the service request is not created only by the Commercial
Billing System (CBILL), but directly in the Technical System of Operation
Management (SGT-OPER). The process was based on information collected from the
meters of Customer Consumer Units (CCU) and consolidated by the Measurement
Center (MC). The advantage of this proposal is to eliminate the user’s need to
notify the Call Center, concentrating the interface between the Measurement
Center and the SGT-OPER, thereby increasing the efficiency of the system 2.
In the R Project No. 253, it was also proposed an
approach for positioning concentrators in a ZigBee Mesh Network (ZMN) of smart
meters in order to minimize the average delay of messages sent to the GPRS concentrators,
resulting in a better network performance. The K-means clustering algorithm is
used to distribute the meters into subnetworks. Queuing Theory is used to
estimate the average network delay and Binary Linear Programming (BLP) to
determine the location of the concentrators. In addition, computer simulations
were carried out to identify network performance from the position determined
by the proposed methodology 2. Other relevant work of the R Project No. 253
were documented and published in 3 4 5 6 7.
The R Project No. 253 provided excellent results
and expertise, leading us to propose the R Project No. 364 “51 Rooftops
in Nova Veneza-GO” 8.
In order to verify the feasibility of Grid-Connected
Photovoltaic Systems in the city of Nova Veneza, state of Goiás (GO), it was
conducted a historical survey of the electricity consumption for consumers
connected to the TA and TB transformers shown in Fig. 1.
It is important to note the existence of a Smart Metering
System that monitors 123 consumers of Class B. There are 62 consumers being
linked to the extension of low voltage transformer called TA, with nominal
power of 112.5 kVA, and 61 consumers linked to the extension of low voltage
transformer called TB with the same rating.
The Smart Metering System has the function of record and
send data on the energy consumption of Customer Consumer Units (CCU) for the
Measurement Center of Celg-D utility with the possibility to acknowledge power
failure in certain three-phase consumer units. The system also checks the
status of the difference between the power delivered in the secondary of the
transformer and the power actually consumed by the CCU, i.e., non-technical
Considering the historical survey of electricity
consumption for consumers connected to the TA and TB transformers, it was
proposed a methodology to choose 51 roofs in Nova Veneza-GO. The methodology
consists of ten stages ranging from the grouping of consumers with the same
power consumption profile using a Neural Network (NN), that is, a Non
Parametric Self-Organizing Map (PSOM) 9, until the complete and optimal
allocation of financial resources by an Integer Linear Programming (ILP).
In the following sections will be presented the
methodology for allocating the financial resources of the R Project No.
364, as well as a grouping (clustering) proposal for the curves of consumption
profiles of the consumer units of Nova Veneza-GO using Artificial Neural
Networks. It will be also presented the traditional method used to project the Photovoltaic
(PV) systems that will be connected to the grid of Nova Veneza-GO and a
socioeconomic feasibility study for implementation of solar energy using Grid-Tie
Systems with and without financial incentive for all consumers of Group B of
Nova Veneza-GO taking into account different values of PV Performance Rate.
Also shown in the following sections is a socioeconomic feasibility study for
the capital of Goiás, Goiânia. In this case, two scenarios were taken into
consideration, with and without incentive for 5% and 30% of all consumers of