3. Case study

2.4 Fiscal incentives

Wind Solar Hybrid Renewable Energy System

<sup>Δ</sup> <sup>¼</sup> <sup>1</sup> ð Þ 1 � t

investment cost over T2 year.

ACSadj ¼ CCpv þ CCbat

194

þ O&Mbat þ O&MDG

2.5 Objective function: optimization process

the system, the following objective function is used:

Under the Colombian Renewable Energy Law, new clean energy projects will receive up to 50% tax credits, but they can only be applied during the first 5 years. In this work, when the fiscal incentives are considered, it is assumed that the company will receive the 50% of the tax credit equally distributed over the first 5 years of the project. In general, investment tax credits can be calculated as

> <sup>i</sup> <sup>¼</sup> <sup>X</sup> 5

> > j¼1

<sup>d</sup> <sup>¼</sup> <sup>X</sup> 5

� <sup>1</sup> � <sup>t</sup> � <sup>X</sup>

� � � <sup>Δ</sup> <sup>þ</sup> CCDG <sup>þ</sup> RCbat <sup>þ</sup> RCDG

years to apply the investment tax credit, T2 is the useful life of the powergenerating facility for accelerated depreciation purposes (in year) = 5, i is the investment tax credit, and d is the depreciation factor expressed as percentage of

j¼1

Assuming an effective corporate tax income rate of 33% and under the previous consideration, the tax reduction factor Δ for the purpose of this work is given by

> ij <sup>1</sup> <sup>þ</sup> <sup>i</sup> ð Þ<sup>r</sup> <sup>j</sup> <sup>þ</sup><sup>X</sup>

" # !

T1

j¼1

wheret is the effective corporate tax income rate, T1 is the maximum number of

Fiscal incentives granted by the Colombian Act 1715 only apply to not conventional energy source installation and its components. In this way, the incentive tax factor only applies to the capital cost of photovoltaic and battery components:

The objective of this work is sizing hybrid power generation systems (solardiesel) battery-backed, in non-interconnected zones, which minimizes the total cost of the solution and maximize the reliability of supply. To minimize the total cost of

> Cost <sup>¼</sup> ACSadj <sup>þ</sup> ACloss P<sup>8760</sup>

supply the energy demand on an off-grid location. The optimization of these

This work aims to develop an optimization model for sizing an energy system to

� � � CRF ir ð Þþ , R <sup>O</sup>&Mpv

In a similar way, it is assumed that the effect of depreciation is equally distributed each year, and the useful life for accelerated depreciation purposes is 5 years; then

ij ¼ 0:5 (58)

dj ¼ 1 (60)

dj <sup>1</sup> <sup>þ</sup> <sup>i</sup> ð Þ<sup>r</sup> <sup>j</sup>

<sup>t</sup>¼<sup>1</sup> ð Þ ELðÞ�<sup>t</sup> ENS tð Þ (64)

(62)

(63)

i<sup>1</sup> ¼ i<sup>2</sup> ¼ i<sup>3</sup> ¼ i<sup>4</sup> ¼ i<sup>5</sup> ¼ 0:1 (59)

d<sup>1</sup> ¼ d<sup>2</sup> ¼ d<sup>3</sup> ¼ d<sup>4</sup> ¼ d<sup>5</sup> ¼ 0:2 (61)

T2

j¼1

"Santa Cruz del Islote" in Bolivar, Colombia, was used as a location for the case study. This rural community is selected to evaluate the optimization model developed in this work.

### 3.1 Meteorological inputs and load profile

The monthly global irradiance over the horizontal and over the plane of the array was calculated using a MATLAB routine developed in this work and then compared with results obtained from Solargis. Table 1 shows the results obtained.


#### Table 1.

Meteorological input parameters (monthly).

The difference can be accounted to the simplicity of the transposition model used in our MATLAB routine; nevertheless the results are good enough for the purpose of this work.

3.2.1 Photovoltaic module technical data

DOI: http://dx.doi.org/10.5772/intechopen.88830

3.2.2 Diesel genset technical data

Table 3.

Table 4.

197

PV module technical inputs.

Diesel model technical inputs.

by experts consulted in companies of energy sector.

A monocrystalline PV module of 300 Wp, reference JKM300M-60, from the company JINKO SOLAR, is used. Table 3 shows the technical characteristics of the PV module selected. The cost per Wp installed presented in Table 3 includes other costs not related to the price of the PV modules as the cost of charge controller, the PV inverters, and the mounting structure. Also this price includes indirect cost associated to the PV installation as engineering study costs, logistic costs, and certification costs. The cost per Wp presented is taken as reference and is provided

Methodology for Sizing Hybrid Battery-Backed Power Generation Systems in Off-Grid Areas

The input data required by the diesel generation model is presented in Table 4.

Symbol Description Value Ppvstc Maximum power [Wp] 300 Vmpp Maximum power voltage [V] 32.6 Impp Maximum power current [A] 9.21 Voc Open-circuit voltage [V] 40.1 Isc Short-circuit current [A] 9.72 ηpv Module efficiency (%) 18.33 α<sup>P</sup> Power temperature coefficient [%/°C] 0.39 α<sup>V</sup> Voc temperature coefficient [%/°C] 0.29 α<sup>I</sup> Isc temperature coefficient [%/°C] 0.05 NOCT NOCT [°C] 45 cPV Cost per Wp installed [USD/Wp] 2 ρPV Fixed OM factor as ratio of the PV CC 0.01 f PV Photovoltaic derating factor 0.85 ηINV Inverter efficiency 0.9

Diesel input data Symbol Description Value NDG, max Maximum number of DG unit 5 δmin Minimum load ratio allowed 0.3 LDG Lifecycle [years] 10 ρDG Fixed OM value as percentage of the diesel initial investment [%] 0.1 f <sup>C</sup> Fuel cost [USD/l] 0.8

This information is collected from expert opinions on companies in the energy

The load profile data was obtained from the National Monitoring Center (CNM) of the IPSE [22]. Table 2 shows the input data used to generate the daily load profile curve. Figure 4 shows the daily load profile for a week generated by a MATLAB routine developed in this work.
