Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators

Abstract

In this study, a comparative sizing design for renewable power systems was developed based on HOMER (Hybrid Optimization of Multiple Energy Resources) and iHOGA (improved Hybrid Optimization by Genetic Algorithms) simulators. A comparative analysis of the solutions obtained with iHOGA and HOMER simulators for the same hybrid renewable power system (HRPS) is presented in detail. The system contained a new hybrid configuration that used fuel cell (FC) as a green energy source, replacing the polluting diesel generator system, as well as other renewable energy sources, namely, photovoltaic panels, wind turbine, a battery stack, power converters, and electric load. The same case study was carried out for the design of the hybrid system using HOMER and iHOGA simulators to perform a comparative analysis of the solutions obtained for potential investment. The analysis showed a higher share of renewable energy for iHOGA (92%) compared to HOMER (81%), so the first design produced 51.61 kg/year less carbon dioxide. Moreover, the operating costs (2134 RON/year for HOMER and 70.56 RON/year for iHOGA) and the cost of electricity were higher by 96% and 2.5%, respectively, for HOMER compared to iHOGA. Taking into account the need for high reliability, safe operation, and lower operation/exploitation costs, the design implemented in iHOGA is clearly more efficient and useful in practice, and this is supported by the three iHOGA case studies.

1. Introduction

Electric power is a key factor for economic and social development of any country, and it is one of the most commonly sought commodities by mankind [1,2]. Global energy demand is rising steadily as a consequence of population growth and higher living standards [3,4]. Currently, fossil fuels continue to be the main source of electricity. However, their share is expected to decrease as a result of the use of renewable energy sources, such as solar, wind, and hydraulic energy [5]. Nowadays, there is great concern over environmental issues and society’s dependence on fossil fuels [6]. Conventional energy sources based on fossil fuels are highly polluting and are also approaching depletion. Combating global warming requires orienting towards renewable sources of energy, with solar and wind energy being especially important as they are inexhaustible and nonpolluting and have shown decreasing cost [7,8].

Renewable energy resources include hydraulic, solar, wind, geothermal, and biomass energy. Generally, a hybrid power system comprising renewable energy consists of the following [9,10]:

• renewable energy sources: solar, wind, hydro, etc.;
• conventional energy sources: diesel generators and AC grid;
• electrical energy storage components: battery pack and ultracapacitor;
• DC–DC or DC–AC converters;
• DC or AC consumers (load).

There are three possible configurations for integrating renewable energy sources, namely, coupling the sources to an AC bus, coupling the sources to a DC bus, and coupling the sources to both DC and AC buses (DC–AC). For hybrid DC–AC systems, the power sources are connected to the DC bus through their own interface circuits, with AC sources and loads being directly connectable to the main interface. This configuration has high efficiency and low cost due to the reduced number of converters used compared to the other two configurations. However, the control and management of the scheme is more complex [11,12]. At the same time, in order to maintain a minimum operating cost and security of the energy system, the solution to the SCUC (security-constrained unit commitment) problem is described in the literature through different optimization methods [13]. Another problem can be represented by distributed energy resources (DERs), which must ensure a stable way of maintaining the frequency response through different optimization algorithms in intelligent power systems [14].

In recent years, various software tools have been developed (for example, HOMER, iHOGA, RETScreen, and Hybrid 2) that help realize the sizing of a hybrid system based on renewable energy. Hybrid 2 software can also achieve hybrid system modeling [15,16,17]. The most commonly used software are HOMER and iHOGA [18]. The HOMER software package is used to design hybrid systems [19,20] and estimate the cost of the life cycle, installation, maintenance, and operation of the system [21]. The HOMER software uses the component costs, electrical load profile, resource data (such as solar radiation and wind speed), and economic constraints (such as fuel price) as input data and output the following variables: component sizing (ratings of PV, wind turbine, battery, diesel generator, and converters for the considered load profile), net present cost (NPC) associated with component size, energy production and consumption, the cost of energy (COE), excess energy, and fuel consumption [22,23].

iHOGA is a software tool used to optimally design hybrid renewable power systems (HRPS) integrated in distributed generation based on the topology of DC or AC type. The simulations can be performed for hybrid systems of any size (from Wh to MWh and GWh daily consumption) that are standalone or connected to the grid with or without load. The total system cost is optimized considering the maintenance during its useful lifespan and the initial investment (NPC) as references. Thus, the optimization function is mono-objective and of the financial type. Nevertheless, iHOGA permits some analysis of multiobjective optimization if other additional variables are considered by the user to be minimized as well, such as the equivalent CO2 emissions and unmet load (also known as not served energy). Of course, in multiobjective optimization, the obtained solutions show a different performance when applied to cost, emissions, or unmet load [24,25].

The iHOGA software uses genetic algorithms for optimization of the system components but also for the control strategy. It is known that genetic algorithms applied to complex problems may produce suitable solutions in a very short time. Consequently, genetic algorithms have been applied to solve different optimization problems in the industry. The obtained solution is better than the ones found with alternative optimization methods [26,27].

In this study, a comparison was made between HOMER and iHOGA using a hybrid system as a case study. The hybrid system based on renewable energy had the following components: PV panels, wind turbine, diesel generator, battery, converter, and electric load. The input data related to primary energy sources (solar and wind) and the load were the same in both programs [28,29].

This study aimed to analyze a new hybrid system configuration that uses fuel cell (FC) as a green energy source, replacing the polluting diesel generator system, in addition to potential renewable energy sources, such as solar, wind, hydro, biomass, and geothermal energy, in Romania.

The case study was the city Ramnicu Valcea in the southern part of Romania, situated at a latitude of 45.1 and a longitude of 24.36. The data on energy resources (solar and wind) as well as the price of fuel are presented. The size and price of the component elements are also defined for both the iHOGA and HOMER programs. The optimal technical–economic size of the hybrid system is compared with the help of the two programs.

The main contributions of this study are as follows:

• A comparative analysis of the solutions obtained with iHOGA and HOMER simulators for the same HRPS is presented in detail.
• Compared to other similar studies in the design of HRPS (mentioned above), all important parameters (such as the share of renewable energy, operating costs, excess energy, energy cost, and pollutant emissions) were systematically analyzed to determine which solution would be optimal for HRPS implementation in the location.
• The obtained results are compared and discussed, highlighting the fact that iHOGA achieved better results than HOMER.
• The comparative analysis of three HRPS projects implemented in iHOGA (with DG, with FC, and without FC and DG) showed that in the HRPS project without DG, the share of renewable energy could increase up to a maximum of 100%, but the NPC also increased by 14.33% (from RON 66,770 to 76,340). Even though iHOGA with DG was the best option from an economic point of view (having the best economic value in terms of initial capital (RON 32,484) and NPC (RON 66,770)), it resulted in higher operating costs compared of the other two cases analyzed, and the pollutant emissions were approximately double those obtained in the case of iHOGA with FC.

The rest of the paper is structured as follows. The mathematical modeling of renewable energy sources used in this study is presented in Section 2. The case study development is detailed in Section 3. The implementation of the hybrid system in HOMER and iHOGA and the results obtained are presented in Section 4 and Section 5, respectively. Comparative analysis and discussion of the results obtained are given in Section 6. The last section concludes the paper.

2. Mathematical Modeling

The HRPS configuration used in this research study is presented in Figure 1.

The modeling of the HRPS components is briefly presented below.

2.1. PV Panel

The photovoltaic current (I_ph) under standard test conditions (STC) given by the manufacturer (T_ref = 298.15 K (25 °C) and G_ref = 1000 W/m²) is given by (1):

$$I_{ph}=\left[I_{sc}+K_i\left(T-T_{ref}\right)\right]\times \frac{G}{1000}$$

(1)

where T, G, I_sc, and $K_i$ are the operating temperature, solar irradiance, short-circuit current, and coefficient with temperature of the short-circuit current, respectively.

The PV panel voltage is given by (2):

$$U_{PV}=U_{DC}\times N_s$$

(2)

where U_DC is the cell voltage, and N_s is the number of cells connected in series.

The power (P) generated by the PV is given by (3):

$$P=I_{sc}\times G\times U_{PV}\times N_s/k_F$$

(3)

where $k_F$ represents the loss factor.

2.2. Wind Turbine

The power generated by a wind turbine is given by (4) [27]:

$$P_{max}=16/27\times P_0$$

(4)

where $P_0$ is the power on the upstream section

$$P_0=1/2\times \rho \times A_r\times v_0^3$$

(5)

and $\rho$ is air density [$\mathrm{kg}/{\mathrm{m}}^3$], $A_r$ is the area swept by the rotor blades$[{\mathrm{m}}^2$], and $v_0$ is the wind speed $[\mathrm{m}/\mathrm{s}$].

So

$$P_{max}=0.296\times \rho \times A_r\times v_0^3$$

(6)

Wind turbine can produce a theoretical maximum of 60% (see Equation (4)) from the power generated by wind. However, this percentage, in reality, is lower, with the value produced being about 40%.

2.3. Battery

The capacity of the battery is given in Equation (7):

$$C=\left(E\times N_{day}\right)/\left({\mathsf{\eta }}_{con}\times {\mathsf{\eta }}_{bat}\times DOD\right)$$

(7)

where$E$ is the charging voltage, $N_{day}$ is the number of days without charging, ${\mathsf{\eta }}_{con}$ is the convertor efficiency, ${\mathsf{\eta }}_{bat}$ is the battery efficiency, and $DOD$ is the depth of discharge. State of charge (SOC) values are set between 45% and 85%.

2.4. Fuel Cell

Fuel cells (FC) are devices that perform the direct conversion of chemical energy into electrical energy. The conversion of chemical energy into electrical energy is carried out based on electrochemical oxidation–reduction reactions that take place at the two electrodes, namely, the anode that is supplied with hydrogen (H₂) and the cathode that is supplied with oxygen (O₂) from air, separated by an electrolyte that allows the transfer of ions between the two electrodes. Energy systems based on fuel cells produce continuous electric current at low voltages and medium intensity, do not pollute the environment, have no moving elements, and exhibit high efficiency. Depending on the electrolyte or fuel used, there are several types of cells, among which the proton exchange membrane fuel cell (PEM-FC) is widely used due to its low temperature operation and fast start-up.

The output voltage of the fuel cell is given by the following relationship (8):

$$V=E-V_{act1}-V_c-V_{ohm}$$

(8)

where $E$ is the internal voltage of the fuel cell (FC), $V_{act1}$ is the temperature-dependent activation voltage loss, $V_c$ is the voltage loss across the capacitor, and $V_{ohm}$ is the voltage loss across the ohmic resistance.

The voltage E across a single cell is given by the following relationship:

$$E=E_0+\frac{RT}{2F}ln\left(\frac{P_{H_2}{P}_{O_2}}{P_{H_{2}O}}\right)$$

(9)

where $E_0=1229 \mathrm{V}$ is the standard potential of the hydrogen/oxygen reaction, R is the universal gas constant, F is the Faraday’s number, $P_{H_2}$ is the partial pressure of hydrogen at the anode, and $P_{H_{2}O}$ and $P_{O_2}$ are the partial pressures of water and oxygen at the cathode, respectively.

3. Case Study Development

Two programs, HOMER and iHOGA, were used for sizing a hybrid system to compare the obtained solutions and determine which solution would be optimal. The hybrid system includes PV panels, converter, wind turbine, battery, diesel generator, and electric load. The prices of the system components were taken from the manufacturers, and the current market prices were taken into account in the simulation.

Based on the results obtained, an analysis was carried out regarding the sizing of the equipment, the net current cost (NPC) associated with the size of the components, and the production and consumption of energy, highlighting the economic aspects and polluting emissions.

The use of renewable energy sources, such as solar, wind, hydraulic, geothermal, and biomass, is a promising solution for humanity. The potential of renewable energy resources in Romania are given in

Table 1. The potential of renewable resources in Romania.

Source	Annual Potential	The Application
Solar energy	60 PJ 1.2 TWh	Thermal energy Electricity
Wind energy	23 TWh	Electricity
Hydro energy	23 TWh	Electricity
Biomass and biogas	318 PJ	Thermal energy
Geothermal energy	7 PJ	Thermal energy

[30,31].

In addition to renewable energy sources in Romania, for the purpose of energy efficiency in reducing the level of greenhouse gases, especially CO₂, a fuel cell (FC) system is integrated into the initial configuration, which can be a good substitute for the classic diesel generator (DG).

3.1. Location

The analysis was carried out in the southern part of Romania. The location chosen was the city Ramnicu Valcea situated at latitude of 45.1 and longitude of 24.36. The exact location is shown in Figure 2.

3.2. Load Profile

The load profile modeling plays an important role in optimal sizing and choice of renewable energy sources. In the case of isolated houses, renewable energy sources are used for lighting and power supply for household consumers.

Table 2. The power consumption for the hybrid system.

Device	Installed Power (W)	Average Usage (h/day)	Daily Energy Consumption (kWh)	Number of Units	Total Energy Consumption (kWh/day)
Computer and screen	200	2	0.4	1	0.4
Portable computer	75	1	0.075	1	0.075
Phone charger	15	2	0.03	1	0.03
Refrigerator	200	8	1.6	1	1.6
Fan	50	10	0.5	2	1
Light bulbs	100	5	0.5	3	1.5

shows the specific values relating to the number of units, the power installed, the daily energy consumption, and the number of hours of operation for different devices supplied by the hybrid energy system. The devices presented in Table 2 were distributed into 24 h to generate a daily load curve. Simulations were carried out by taking into account a load with an average power of 160 W. The average daily energy consumption was 3.95 kWh/day with a power peak of $P_{max}=$ 0.78 kW. For example, light bulbs will be especially used from 18:00 to 23:00, while refrigerators will operate on average eight hours/day.

3.3. Solar Energy Potential of Ramnicu Valcea

Solar radiation values for this location were provided by NASA Surface meteorology. Figure 3 shows the values for each month according to the clarity index. The average annual solar radiation for this location was 3.30 kWh/${\mathrm{m}}^2$/day [32,33].

The data showed that solar radiation had higher values between March and October, enough to produce a good amount of electricity.

3.4. Wind Energy Potential of Ramnicu Valcea

The monthly values of wind speed for the wind power source, also obtained from NASA Surface meteorology, are graphically represented in Figure 4. For Ramnicu Valcea, the minimum and maximum values were 3.4 and 5 m/s, and the average speed was 4.2 m/s [34].

3.5. Analysis Tools

The HOMER software developed by the National Renewable Energy Laboratory (NREL) sizes a hybrid system based on renewable energy both economically and technically. The optimization of the hybrid system is carried out using several possible combinations of input variables to obtain an optimal solution; for this reason, the calculation time is too high compared to the iHOGA software that uses genetic algorithms. The optimization strategy used by HOMER is simple and does not perform a deep optimization of the hybrid system based on renewable energy [35,36,37,38].

The HOMER program realizes the optimal dimensioning of all the components of a hybrid system, namely, the renewable energy sources (solar and wind), diesel generator, and battery, and the analyses carried out are from both technical and economic standpoints. The HOMER software has the disadvantages of a long calculation time and inability to perform multiobjective optimization (with its only objective being the minimization of the NPC) [39,40].

A comparative analysis between the two software (iHOGA and HOMER) regarding the simulation results shows several advantages for iHOGA, such as using more accurate models, performing multiobjective optimization, and deeper technical–economic analysis in a shorter time. However, iHOGA also presents some disadvantages, such as the inability to perform probabilistic analysis and the use of a more complex control strategy due to the use of genetic algorithms, which is more difficult for users to understand [39,40].

4. HOMER Simulator

The renewable energy sources used in the case study were connected to two lines: the DC current bus and the AC current bus. The two lines were interconnected through a bidirectional converter, as can be seen in Figure 5. The daily energy consumed by the electrical load was 3.95 kWh/day. Figure 6 shows a daily load curve, with the peak being from 12:00 to 13:00.

The hybrid system contained five major components that needed to be designed [41], namely, photovoltaic panels, wind turbine, diesel generator, battery, converter, and electric charge. Some economic inputs and component designs are discussed in the following subsection.

4.1. Photovoltaic Panels

The electricity generated by the PV panels was used for the load, with any excess in the case of lower loads being used to charge the batteries. In the simulation, the market price utilized was for the Sun Module SW 100 POLY RIB model photovoltaic panel from the German company Solar World [42].

The lifetime of PV panels is about 25 years. The purchase price was 4500 RON/kW, replacement price was 4000 RON/kW, and the maintenance cost was relatively low at 45 RON/year.

4.2. Wind Turbine

A generic 1 kW DC wind turbine with 10 years lifetime and a hub height of 15 m was selected from the HOMER software. The wind turbine cost was RON 4297.55, with a replacement cost of RON 2835 and a slightly higher maintenance cost of 225 RON/year.

4.3. Diesel Generator

The diesel generator was used as a backup source for the production of electricity. The price of diesel plays an important role in modeling, depending on which the optimal configuration of the hybrid system can be changed [43]. In accordance with Romania Gasoline prices, the diesel price was 8.3 RON/L, which is equivalent to 1.69 Euro/L [44]. The purchase and replacement price for the diesel generator were 2000 and 1800 RON/kW, respectively, while the maintenance price was 0.03 RON/h. The lifetime of a diesel generator is estimated at about 10,000 h of operation.

4.4. Battery

The hybrid system chosen for this configuration was equipped with a lithium-ion battery with the following characteristic parameters: a nominal voltage of 6 V, 167 Ah capacity, and initial SOC of 100%. The battery connection was 5 units per string for each unit of 6 V. The number of batteries used in the simulation was between 2 and 18. The purchase price was RON 700, the replacement price was RON 500, and the maintenance price was 10 RON/year.

4.5. Converter

The hybrid system had three types of converters: DC–DC, AC–DC, and DC–AC. The HOMER program considered these converters as a single entity. For the simulation, the inputs were taken between 1 and 6 kW, and the specification chosen by the program was 1 kW. The power of the converter was 1 kW. Its lifetime is 10 years. The purchase price of the converter was 3400 RON/kW, the replacement price was 2000 RON/kW, while the maintenance price was practically 0 RON/year.

4.6. Simulation Results

Table 3. The simulation results using the HOMER simulator.

Component	Value
PV (kW)	1
Wind turbine 1 kW (units)	2
Diesel generator (kW)	1
Battery (units)	5
Converter (kW)	1
COE (RON/kWh)	1.97
NPC (RON)	36,650
Operating costs (RON/year)	2134
Initial capital (RON)	21,995
Renewable resources (%)	81

shows the resulting solution regarding the optimization of the components of the hybrid system based on renewable energy. The share of renewable energy sources in the system was 81%, and the costs were as follows: energy produced was 1.97 RON/kWh; initial capital of the system was RON 21,995; the net present cost was RON 36,650; and the operating cost was 1134 RON/year.

The annual production of each component of the system is presented in

Table 4. The annual production of each component.

Component	Energy Production (kWh/Year)	Energy Production (%)	Energy Consumption of All Consumers (kWh/Year)
PV	1140	58.63	1441
Diesel generator	271	13.92
Wind turbine	533	27.45
Sum	1944	100

. It can be seen that the annual energy produced was 1944 kWh/year and the annual energy consumed was 1441 kWh/year, with photovoltaic panels having the greatest contribution to energy production at 1140 kWh/year (representing 58.63% of the total annual energy production).

The second contribution to energy production was by the wind turbine at 533 kWh/year, representing 27.45% of the total annual production. The diesel generator had a contribution of 271 kWh/year, representing 13.92% of the total annual production.

The system produced 1944 kWh/year annually at an energy cost of 1.97 RON/kWh, resulting in an annual energy cost of 1944 × 1.97 = 3828.68 RON/year.

The operating cost was RON 2134, resulting in an annual cost of energy production of 3829.68 − 2134 = 1695.68 RON/year.

Table 5. Cost analysis of the system.

Component	Social Capital (RON)	Replacement (RON)	Maintenance (RON)	Fuel (RON)	Recovered Amount (RON)	Sum (RON)
PV	4500	4000	581.74	0	−3800	5081.7
Wind turbine	8595	1807.6	5817.4	0	−1018.7	15,201
Diesel generator	2000	1800	110.92	5385.1	−255	7270
Battery	3500	1060	646	0	−199.6	5007.4
Converter	3500	848.55	0	0	−159.71	4088.8
System	21,995	3716.9	7156.4	5385.1	−1603.7	36,650

shows the analysis of the system costs and highlights the results obtained. When considering the total cost, the wind turbine represented the largest percentage of the total (high social capital cost and maintenance cost), followed by the diesel generator due to the fuel cost. Next were the PV panels, which had low maintenance costs, followed by the battery and the converters making up the lowest percentage of the total cost, with the maintenance cost of the converters being zero. The analysis of the system costs highlighted the following results: initial capital was RON 21,995; replacement price was RON 3716.9; maintenance price was RON 7156.4; fuel price was RON 5385.1; and the net present cost (NPC) was RON 36,650.

Figure 7a,b show the waveforms for the hybrid system and for charging and discharging the battery for 8 January 2022. In the time period 07:45–16:00 (8 January), the load was covered 100% by the photovoltaic panels. In addition, on 8 January between 02:00 and 08:00, wind energy production was maximum, with the wind turbine being able to feed the electrical load and charge the battery. There was an exception between 18:00 and 23:00 when the load had the second peak. For this period, the daily energy consumption was provided by the accumulator battery. As can be seen from Figure 6, the hybrid system could provide energy throughout the day ensuring electrical charge, with no gaps in electricity supply.

Using this solution for electricity generation based on renewable sources, a reduction in the emissions of carbon dioxide, carbon monoxide, unburned hydrocarbons, etc., was obtained. The results are presented in

Table 6. Pollutant emissions (HOMER).

Emissions	Value (kg/Year)
Carbon dioxide	271
Carbon monoxide	0.75

.

5. iHOGA Simulator

5.1. iHOGA with Diesel Generator

The schematic of the hybrid system based on renewable energy involved in the case study using the iHOGA simulator is presented in Figure 8. As in the case of the HOMER simulator, the hybrid system was composed of PV panels, wind turbine, diesel generator, battery, converter and electric load. The daily energy consumption was 3.95 kWh/day.

Figure 9 presents the daily load using iHOGA. Expectedly, it has the same shape as HOMER.

5.1.1. PV Panels

The PV panels were of type Si14—ASI100 of 100 W each. They have a lifetime of 25 years. The photovoltaic panels provided DC electric power and were connected to the battery bank through a charge regulator with MPPT. The acquisition price was RON 450, the replacement price was RON 400, and the maintenance price was 4.5 RON/year for 100 W power. The same ground reflectance as in the case of HOMER simulator (of 18%) was included in the study.

5.1.2. Wind Turbine

The model for the wind turbine considered was Southwest AIRX, whose power was 0.54 kW. It has been designed to maximize the energy efficiency and minimize the turbulence. Its hub was located at a height of 8 m. The lifetime is 10 years. The cost of the wind turbine was RON 2835, the replacement cost was RON 2375.5, and maintenance cost was RON 225. It was made of stainless steel, aviation aluminum, and magnetic material. Wind energy factor for the wind turbine was high at 0.39, the generator efficiency was 0.93, and the working speed was from 2.7 to 25 m/s [45].

5.1.3. Battery

The type of battery used was OPZS-Hawke TLS-3, with a nominal voltage of 2 volts and a capacity of 180 Ah. The purchase price was RON 400, and the maintenance price was 4 RON/year.

5.1.4. Converter

The power converter type was STECA SOLARIX PI 1200 with an apparent power of 900 VA. The purchase price was RON 400.

5.1.5. Diesel Generator

The diesel generator had the apparent power of 1.9 kVA, with the purchase price of RON 3000 and maintenance price of 0.03 RON/h. Its lifetime is 10,000 h. The price of diesel fuel was 8.3 RON/L.

5.1.6. Simulation Results

The simulation results for these components and characteristics in the case of the iHOGA simulator are given in

Table 7. The simulation results using iHOGA simulator.

Component	Value
PV (kW)	1.6
Wind turbine (kW)	0.546
Diesel generator (kW)	1.9
Battery (kWh)	8.6
Converter (kW)	0.9
COE (RON/kWh)	1.92
NPC (RON)	66,770
Operating costs (RON/year)	70.56
Initial capital (RON)	32,484
Renewable resources (%)	92

. The hybrid system produced 92% of the energy production using renewable resources at a cost of produced energy of 1.92 RON/kWh. The initial capital of the system was RON 32,484; net present cost was RON 66,770; and operating costs was 70.56 RON/year.

The system components from the simulation results are shown in Figure 10. The components of the system were as follows: PV panels—aSi12-Schot, ASI100 (100 W), 4 s × 4 p (with a slope of 60 degrees); batteries—OPZS-Hawke, TLS-3 (180 Ah), 24 s × 1 p; diesel generator—1.9 kV; wind turbine—DC AIR X (546.8 W at 14 m/s); inverter—STECA, SOLARIX PI1200 of 900 VA.

Table 8. The annual production using iHOGA simulator.

Component	Energy Production (kWh/Year)	Energy Production (%)	Energy Consumption of Consumers (kWh/Year)
PV	1392	78.86	1389
Diesel generator	104	5.89
Wind turbine	269	15.24
Sum	1765	100

shows the annual production estimated using the iHOGA simulator. From Table 8, it can be seen that the annual energy produced was 1765 kWh/year and annual energy consumption was 1389 kWh/year, with photovoltaic panels having the greatest contribution to energy production at 1392 kWh/year, representing 78.86% of the total annual energy production. The second contribution to energy production was by the wind turbine at 269 kWh/year, representing 15.24% of the total annual production. The diesel generator contributed 104 kWh/year, representing 5.89% of the total annual production.

The energy produced annually was 1765 kWh/year at a production cost of 1.92 RON/kWh, and the cost of energy produced by the system was 1765 × 1.92 = 3388.8 RON/year.

The operating cost was RON 70.56, resulting in an annual net cost of energy produced of 3388.8 − 70.56 = 3318.24 RON/year.

The system cost analysis is shown in Figure 11. Figure 11 highlights the following results: the battery had the highest cost of RON 19,494 (representing 31.48% of the system cost); the convertor was RON 14,201 (22.76%); photovoltaic panels were RON 12,143 (19.61%); wind turbine was RON 11,087 (17.9%); diesel generator was RON 3108 (5.02%); and others (for example, the fuel price of diesel generator) were RON 2002 (3.23%).

In Figure 12, the waveforms for the hybrid system of 8 January 2022 are presented. On 8 January, solar radiation was present in the time period 07:45–15:50, with the maximum load supplied by the PV panels at 450 W (11:00–13:00) for battery charging. From 11:30 to 23:00, wind energy was predominant, and a maximum load of 200 W could be supplied (between 17:00 and 19:00). Between 17:00 and 23:00, the energy supply of the consumers was being ensured through stored energy in the battery and from the wind turbine. The battery could deliver power during periods in which energy sources could not meet the demands of power consumers.

Like in the case of the HOMER simulator, a reduction in the emissions of carbon dioxide, carbon monoxide, unburned hydrocarbons, etc., was obtained using renewable energy compared to the emissions produced by conventional systems. The results for pollutant emissions (carbon dioxide and carbon monoxide) are presented in

Table 9. Pollutant emissions (iHOGA).

Emissions	Value [kg/Year]
Carbon dioxide	219.39
Carbon monoxide	0.54

.

5.2. iHOGA with Fuel Cell

The second case study using iHOGA with FC (instead of DG) is presented in Figure 13 for the same daily energy consumption of 3.95 kWh/day. The components of the hybrid system were as follows: wind and solar energy sources (photovoltaic panels and wind turbine), storage device (battery), converters, electrical load, electrolyzer, and fuel cell.

The electric load, input data for energy sources, and input data for system components were the same as in the previous cases. The simulation results for iHOGA simulator are given in

Table 10. The simulation results for the second case using iHOGA simulator.

Component	Value
PV (kW)	1.2
Wind turbine (kW)	0.547
Battery (kWh)	8.6
Fuel cell (kW)	1
Electrolyzer (kW)	1
Converter (kW)	1.6
COE (RON/kWh)	2.6
NPC (RON)	86,190.7
Initial capital (RON)	44,693
Renewable resources (%)	100

. The share of energy from renewable resources of the system was 100% at an energy cost of 2.6 RON/kWh; the initial system capital was RON 44,693; and the net current cost was RON 86,190.7.

System components from the simulation results are shown in Figure 14. Components of the system were as follows: PV panels—aSi12-Schot, ASI100 (100 W), 4 s × 4 p (slope 60 degrees); batteries—OPZS-Hawke, TLS-3 (180 Ah), 24 s × 2 p; wind turbine—DC AIR X (546.8 W at 14 m/s); inverter—STECA, SOLARIX PI 1200 of 900 VA; electrolyzer, power 1 kW, H₂ tank of 10 kg; fuel cell, rated power 1 kW.

Table 11. The annual production for the second case using iHOGA simulator.

Component	Energy Production (kWh/Year)	Energy Production (%)	Energy Consumption of Consumers (kWh/Year)
PV	2150	69.51	1389
Wind turbine	380	12.28
FC	563	18.2
Sum	3093	100

shows the annual production using the iHOGA simulator based on the simulation results. From Table 11, it can be seen that the annual energy produced was 3093 kWh/year and annual energy consumption was 1389 kWh/year, with PV panels having the greatest contribution to energy production at 2150 kWh/year (representing 69.51% of the total annual energy production). The second contribution to energy production was by the fuel cell at 563 kWh/year (representing 18.2% of the total annual production). The third contribution to energy production was by the wind turbine at 380 kWh/year (representing 12.28% of the total annual production).

The energy produced by the system had a cost of 2.6 RON/kWh and the entire annual production was 3093 kWh/year, resulting in 3093 × 2.6 = 8041.8 RON/year.

The system cost analysis is given in Figure 15 and highlights the following results: electrolyzer + H₂ tank had the highest cost of RON 52,251, representing 60.62% of the system cost; fuel cell was RON 9100 (10.56%); inverter was RON 4107 (5.75%); batteries were RON 6826 (7.92%); photovoltaic panels were RON 3072 (3.56%); wind turbine was RON 3190 (3.7%); and the installation and system costs made up the remaining amount (7.88%).

The results for pollutant emissions (carbon dioxide) are presented in

Table 12. Pollutant emissions for the second case using iHOGA.

Emissions	Value (kg/Year)
Carbon dioxide	116

.

5.3. iHOGA without FC and DG

The third case using iHOGA without FC and DG is presented in Figure 16 for the same daily energy consumption of 3.95 kWh/day. The components of the hybrid system were the wind and solar energy sources (PV panels and wind turbine), storage device (battery), converters, and the electrical load without fuel cell or diesel generator.

The electric load, input data for energy sources and input data for system components were the same as in the previous cases. The simulation results for iHOGA simulator are given in

Table 13. The simulation results for the third case using iHOGA simulator.

Component	Value
PV (kW)	1.6
Wind turbine (kW)	1.093
Battery (kWh)	17.2
Converter (kW)	0.9
COE (RON/kWh)	2.21
NPC (RON)	76,340
Initial capital (RON)	38,821
Renewable resources (%)	100

. The share of energy from renewable resources of the system was 100% at an energy cost of 2.21 RON/kW; the initial system capital was RON 38,821; and the net current cost was RON 76,340.

System components from the simulation results are shown in Figure 17. The components of the system were as follows: PV panels—aSi12-Schot, ASI100 (100 W), 4 s × 4 p (slope 60 degrees); batteries—OPZS-Hawke, TLS-3 (180 Ah), 24 s × 2 p; wind turbine—DC AIR X (546.8 W at 14 m/s); inverter—STECA, SOLARIX PI 1200 of 900 VA. The share of renewable energy sources in the hybrid system was 99.5%; the initial system capital was RON 38,821; the current net cost was RON 76,340; and the cost of energy produced was 2.21 RON/kWh.

Table 11 shows the annual production using the iHOGA simulator based on the simulation results. From

Table 14. The annual production for the third case using iHOGA simulator.

Component	Energy Production (kWh/Year)	Energy Production (%)	Energy Consumption of Consumers (kWh/Year)
PV	1392	72.12	1389
Wind turbine	538	27.88
Sum	1930	100

, it can be seen that annual energy produced was 1930 kWh/year and annual energy consumption was 1389 kWh/year, with photovoltaic panels having the greatest contribution to energy production at 1392 kWh/year (representing 72.12% of the total annual energy production). The second contribution to energy production was by the wind turbine at 538 kWh/year (representing 27.88% of the total annual production).

For the entire annual production of 1930 kWh/year, the energy produced by the system had a cost of 2.21 RON/kWh (resulting in 1930 × 2.21 = 4265.3 RON/year).

The system cost analysis is given in Figure 18. Figure 18 highlights the following results: battery had the highest cost of RON 31,311 (representing 45.09% of the system cost); convertor was RON 2942 (5.5%); photovoltaic panels were RON 12,143 (17.49%); and wind turbine was RON 22,174 (31.93%).

6. Comparative Analysis and Discussion

The comparative analysis of the simulation results for the two simulation programs and the corresponding observations are presented in the next subsection.

6.1. Economic Comparison

From an economical point of view (see

Table 15. Economic comparison for the two simulators (HOMER and iHOGA).

Economic Comparison	HOMER	iHOGA
Initial capital (RON)	21,995	32,484
Operating costs (RON/year)	2134	70.56
Net present cost (RON)	36,650	66,770
Cost of energy (RON/kWh)	1.97	1.92

and Figure 19), HOMER program had the best economy in terms of initial capital (RON 21,995 for HOMER and RON 32,484 for iHOGA) and NPC (RON 36,650 for HOMER and RON 66,770 for iHOGA). However, operating costs and cost of electricity (COE) were higher for the HOMER program (operating costs: 2134 RON/year for HOMER and 70.56 RON/year for iHOGA; cost of electricity: 1.97 RON/kWh for HOMER and 1.92 RON/kWh for iHOGA).

Because the operating costs and cost of electricity were higher by 96% and 2.5% for HOMER compared to iHOGA, it can be confirmed that the resulting equipment using iHOGA program had increased reliability and safer operation, resulting in a higher performance of the equipment, and required lower operating/exploitation costs.

6.2. Comparison of Electrical and Pollutant Emissions

Figure 20 shows the comparison of energy production, energy consumption, energy excess, and energy cost for the two simulators.

From an electrical point of view, the iHOGA software gave the best results in terms of excess energy (503 kWh/year for HOMER and 376 kWh/year for iHOGA) and cost of energy (1.97 RON/kWh for HOMER and 1.92 RON/kWh for iHOGA). The comparison showed that the equipment obtained with the iHOGA software had a higher energy efficiency, a fact highlighted by the lower cost of energy. The excess energy for both simulators was not high and could be used in the future when the load demand will increase.

From the point of view of pollutant emissions (see Figure 21), the iHOGA software gave lower values for carbon dioxide and carbon monoxide. Additionally, the diesel generator modeled with iHOGA had the lowest amount of fuel used (fuel price of diesel generator: RON 5385 for HOMER and RON 2002 for iHOGA) and the lowest maintenance cost, making iHOGA the ideal software for sizing hybrid systems and reducing pollutant emissions to the environment.

6.3. Comparative Analysis of iHOGA Case Studies

Economically speaking (see Figure 22), iHOGA with DG had the best economy in terms of initial capital (RON 32,484) and NPC (RON 66,770). However, operating cost was higher for iHOGA with DG (RON 70.56). The initial capital for iHOGA with FC was 27.3% higher than iHOGA with DG, and the initial capital for iHOGA without FC and DG was 13.1% lower than iHOGA with FC. The NPC for iHOGA with FC was 22.5% higher than iHOGA with DG, and the NPC for iHOGA without FC and DG was 11.4% lower than iHOGA with FC. The price for iHOGA with FC was higher due to the higher cost of the electrolyzer and FC system (see Figure 13).

Electrically (see Figure 23), iHOGA without FC and DG had the best results, both in terms of excess energy at 180 kWh/year (224 kWh/year for iHOGA with FC and 300 kWh/year for iHOGA with DG) and energy cost (1.92 RON/kWh for iHOGA with DG, 2.21 RON/kWh for iHOGA without FC and DG, 2.6 RON/kWh for iHOGA with FC). Energy production had the highest cost for iHOGA with FC (3093 kWh/year). The energy production for iHOGA without FC and DG was 37.6% lower than iHOGA with FC, and the energy production for iHOGA with DG was 42.9% lower than iHOGA with FC.

From the point of view of pollutant emissions (see Figure 24), the lowest values were obtained using iHOGA without FC and DG (90 kg/year); the pollutant emissions for iHOGA with FC was 22.4% higher than iHOGA without FC and DG, and the pollutant emissions for iHOGA with DG was 58.9% higher than iHOGA without FC and DG.

7. Conclusions

This paper presents a comparison between the HOMER and iHOGA simulators by utilizing the same hybrid power system as case study. The hybrid power system consisted mainly of PV panels, wind turbine, diesel generator, battery, converter, and electric load. The input data related to primary energy sources (based on solar and wind energy potential available in the southern part of Romania) and the load were the same in both simulations.

Considering the results presented in the paper and summarized below, iHOGA achieved better results than HOMER.

The most important parameters in the HRPS design were considered and discussed, including share of renewable energy, operating costs, excess energy, cost of energy, and pollutant emissions. The analysis of the simulation results for the iHOGA and HOMER programs showed an increased share of renewable energy for iHOGA compared to HOMER (92% compared to 81%). The operating cost was 96% higher for HOMER (2134 RON/year) compared to iHOGA (70.56 RON/year). Regarding the cost of electricity (COE), HOMER had a 2.5% higher cost compared to the energy produced in the iHOGA program. Regarding pollutant emissions, as expected, they were 23.5% higher in the system with a share of renewable energy of 81%, while the system with 92% share of renewable energy produced less than 51.61 kg carbon dioxide per year.

However, in terms of initial capital and NPC, the resulting equipment using the HOMER software was cheaper. The results showed that in terms of NPC, the HOMER solution was 45% cheaper (RON 36,650) than the iHOGA solution (RON 66,770). The initial capital for the HOMER solution was 32% lower than that provided by iHOGA.

The comparative analysis of the three variants carried out in iHOGA (with DG, with FC, and without FC and DG) showed that in the design without FC and DG, the share of renewable energy increased from 92% to 100% but the NPC increased as well (from RON 66,770 to 76,340) due to the expensive costs of equipment based on renewable energy. It is worth mentioning that from an economic point of view, iHOGA with DG had the best economy in terms of initial capital (RON 32,484) and NPC (RON 66,770), but the operating cost (RON 70.56) was higher compared of the other two cases analyzed. From a pollutant emissions point of view and the assurance of the load demand, it is advisable to use iHOGA with FC (see Figure 24) because the pollutant emissions were approximately half those obtained in the case of iHOGA with DG.

This work contributes to the knowledge and systematic analysis of the potential of renewable energy in a location where an HRPS is aimed to be implemented (one of the southern parts of Romania in the case of this paper), offering interested investors a methodology for comparing design solutions as well as for choosing the optimal one that ensures the load demand is met and pollutant emissions is reduced due to the use of renewable energy and FC instead of fossil fuels.

The obtained results were compared and discussed, highlighting the fact that iHOGA achieved better results than HOMER. As the operating cost and cost of electricity were 96% and 2.5% higher for HOMER compared to iHOGA, respectively, this serves to confirm that the resulting equipment using iHOGA has increased reliability and safer operation, resulting in higher equipment performance, while simultaneously requiring lower operating/exploitation costs.

Future work will be focused on the practical implementation of the optimal solution resulting from this study to compare the simulation and experimental results.