Evaluation of PV-Wind Hybrid Energy System for a Small Island DOI: http://dx.doi.org/10.5772/intechopen.85221

#### Figure 8.

Figure 6 shows the wind power density (WPD) on the basis of seasons. The patterns being observed in Figure 6 are very much identical to patterns

of South Korea. Daejeon has the highest solar radiations value (175 W/m<sup>2</sup>

speed and rotor rotational speed are 13.5 m/s and 300 rpm, respectively.

Similarly, Figure 8 shows the average values of daily solar radiations and clear-

This section presents the results such as power production from small Darrieus VAWT. Table 2 summarizes the important details about the wind turbine whereas Figure 9(a) shows the geometrical dimensions and Figure 9(b) shows the power curve of wind turbine installed at Deokjeokdo island. The blade height and chord of the turbine rotor are 3 and 0.2 m, respectively. Design blade section profile is NACA0015, while the rotational diameter of the turbine rotor is 2 m. Rated wind

Figure 10 shows diagram for data acquisition system to obtain experimental data from the wind turbine and the wind master. Turbine performance data is measured between turbine and power transducer, thus contains power generator loss. Power output is stored in battery bank first, then supplied to users after

The commercial code, SC/Tetra, has been employed in the present numerical simulation. It solves the governing fluid dynamics equations, which consist of

) [10].

).

) over different major cities

) whereas

Figure 7 shows the average solar radiations (W/m<sup>2</sup>

ness index over Deokjeokdo island, on monthly basis.

2.3 Estimation of power production from wind turbine

of Figure 4.

2.2 Solar potential estimation

Wind Solar Hybrid Renewable Energy System

Seoul has the lowest (145 W/m<sup>2</sup>

converting to AC voltages.

Figure 7.

170

Solar radiations over different cities of South Korea (W/m2

Solar radiations over Deokjeokdo island [10].


#### Table 2.

Specifications of test Darrieus wind turbine.

Figure 9. Darrieus wind turbine installed at Deokjeokdo island (a) rotor dimensions (b) power curve.

continuity and unsteady Reynolds averaged Navier-Stokes (URANS) equations. The computational domain which consists of rotational and stationary domains, is shown in Figure 11. Tetrahedral, prism and pyramid elements have been used overall but mostly only tetrahedral element type is employed. The total number of meshing elements is around 13 million, whereas the total number of nodes is approximately 3.5 million in complete domain. Shear stress transport (SST) model with a scalable wall function is employed to estimate eddy viscosity. In terms of the boundary conditions, a velocity of 5 m/s is specified at the inlet, and natural outflow condition is imposed at the outlet.

Figure 12 shows the comparisons of turbine power between numerical simulation and experimental measurement for two time averages. In the figure, turbine power obtained by numerical simulation has similar trend to the experimental result. Especially turbine power determined by 10-min average is more similar to

the results of numerical simulation compared to 30-min average. This is considered that 10-min average step having lower SD is more effective to analyze the performance of a small vertical wind turbine. From the above comparisons, it can be said that turbine power obtained by numerical simulation

Wind speed around turbine rotor with wind speed of 5m/s (a) Rotor orientation for maximum CP

Evaluation of PV-Wind Hybrid Energy System for a Small Island

DOI: http://dx.doi.org/10.5772/intechopen.85221

Figure 13 shows contours of wind speed around turbine rotor at two different rotation positions, where maximum and minimum values of power coefficient (Cp) occurred, during one complete revolution. Blade having maximum power surrounded by dashed line in the left side is located at the blade rotation angle of 240° where maximum wind velocity around the blade is occurred without large separation flow along the blade surface. An increase in linear speed of the blade leads to increase the rotational speed of rotor and eventually overall power output is enhanced. Larger separated flow is observed at the blade having

minimum power because inflow in front of turbine rotor directly interfaces to the

This section describes an optimum HRES for Deokjeokdo island based on lowest net present cost (NPC) and levelized cost of energy (LCOE) using HOMER pro software model. Hybrid optimization model for electric renewables (HOMER) pro software can efficiently model and optimize renewable energy plans for a specific region. The optimum HRES must fulfill hourly and annual electricity demand of the island, which corresponds to approximately 7.296 MWh/year without any external

Before starting energy simulations in HOMER pro, one must define pre requisites such as electric load, equipment such as wind turbines, PV panels and other

is correctly analyzed.

(b) Rotor orientation for minimum CP.

Figure 13.

blade surface.

173

3. Optimal design of HRES

assistance such as grid, etc.

3.1 Input data for HOMER pro

essential details like interest rate and project life.

Figure 10. Diagram for data acquisition system.

Figure 11.

Computational domain (left) and grid system around turbine rotor (right).

Figure 12.

Comparisons of turbine power between numerical simulation and experimental measurement for 10-min average (left) and 30-min average (right).

Evaluation of PV-Wind Hybrid Energy System for a Small Island DOI: http://dx.doi.org/10.5772/intechopen.85221

Figure 13.

continuity and unsteady Reynolds averaged Navier-Stokes (URANS) equations. The computational domain which consists of rotational and stationary domains, is shown in Figure 11. Tetrahedral, prism and pyramid elements have been used overall but mostly only tetrahedral element type is employed. The total number of meshing elements is around 13 million, whereas the total number of nodes is approximately 3.5 million in complete domain. Shear stress transport (SST) model with a scalable wall function is employed to estimate eddy viscosity. In terms of the boundary conditions, a velocity of 5 m/s is specified at the inlet, and natural outflow

condition is imposed at the outlet.

Wind Solar Hybrid Renewable Energy System

Figure 10.

Figure 11.

Figure 12.

172

average (left) and 30-min average (right).

Diagram for data acquisition system.

Computational domain (left) and grid system around turbine rotor (right).

Comparisons of turbine power between numerical simulation and experimental measurement for 10-min

Wind speed around turbine rotor with wind speed of 5m/s (a) Rotor orientation for maximum CP (b) Rotor orientation for minimum CP.

Figure 12 shows the comparisons of turbine power between numerical simulation and experimental measurement for two time averages. In the figure, turbine power obtained by numerical simulation has similar trend to the experimental result. Especially turbine power determined by 10-min average is more similar to the results of numerical simulation compared to 30-min average. This is considered that 10-min average step having lower SD is more effective to analyze the performance of a small vertical wind turbine. From the above comparisons, it can be said that turbine power obtained by numerical simulation is correctly analyzed.

Figure 13 shows contours of wind speed around turbine rotor at two different rotation positions, where maximum and minimum values of power coefficient (Cp) occurred, during one complete revolution. Blade having maximum power surrounded by dashed line in the left side is located at the blade rotation angle of 240° where maximum wind velocity around the blade is occurred without large separation flow along the blade surface. An increase in linear speed of the blade leads to increase the rotational speed of rotor and eventually overall power output is enhanced. Larger separated flow is observed at the blade having minimum power because inflow in front of turbine rotor directly interfaces to the blade surface.
