Journal of Energy
Volume 2015 (2015), Article ID 828745, 10 pages
http://dx.doi.org/10.1155/2015/828745

Research Article

Development of a Cost-Effective Solar/Diesel Independent Power Plant for a Remote Station

Okeolu Samuel Omogoye, Ayoade Benson Ogundare, and Ibrahim Olawale Akanji

Electrical and Electronics Engineering Department, Lagos State Polytechnic, Ikorodu Campus, PMB 21606, Lagos, Nigeria

Received 1 October 2015; Revised 29 November 2015; Accepted 30 November 2015

Academic Editor: Mattheos Santamouris

Copyright © 2015 Okeolu Samuel Omogoye et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The paper discusses the design, simulation, and optimization of a solar/diesel hybrid power supply system for a remote station. The design involves determination of the station total energy demand as well as obtaining the station solar radiation data. This information was used to size the components of the hybrid power supply system (HPSS) and to determine its configuration. Specifically, an appropriate software package, HOMER, was used to determine the number of solar panels, deep-cycle batteries, and rating of the inverter that comprise the solar section of the HPSS. A suitable diesel generator was also selected for the HPSS after careful technical and cost analysis of those available in the market. The designed system was simulated using the HOMER software package and the simulation results were used to carry out the optimization of the system. The final design adequately meets the station energy requirement. Based on a life expectancy of twenty-five years, a cost-benefit analysis of the HPSS was carried out. This analysis shows that the HPSS has a lower cost as compared to a conventional diesel generator power supply, thus recommending the HPSS as a more cost-effective solution for this application.

1. Introduction

The term remote station as used in this paper refers to a remote weather station, an espionage listening post, or a telecommunication repeater tower, and so forth, that is located where public utilities have not yet been made available. Such stations require electricity to operate the installed data communication and control equipment. In the past, before the prevalence of solar supply system, diesel generators were used to power the stations necessitating the stationing of human operators nearby to regularly visit the stations to carry out necessary maintenance services on the diesel generators, a situation similar to what is obtained for Nigerian global system for mobile (GSM) base stations. With the current preference for renewable energy sources, these remote station power supplies are being redesigned to take advantage of available technologies in renewable energy. This paper discusses the design of a hybrid power supply system (HPSS) comprising both solar and diesel complementary power plants taking into account the cost-effectiveness of the design system for a remote station. The design was carried out on the HOMER computer software platform. Section 1 discusses the introduction. Section 2 discusses the details of the design materials and methods. Section 3 discusses the simulation results, optimization, and cost-benefit analysis of HPSS while Section 4 discusses the conclusion and recommendation.

2. Materials and Methods

2.1. Station Power Demand Assessment

From the data obtained from the station, a profile is developed in Tables 1 and 2. The daily average load variation is depicted in Figure 1 and tabulated in Table 2. Assume that the load is constant for everyday of the year. The daily peak load of 98.86 kW is observed between 9:00 AM and 10:00 AM with 716.224 kWh d⁻¹ energy consumption.

Table 1: Remote station daily load demand.

S/N
Power consumption
Power (W)
Quantity
Load (W)
Load (kW)
Hour/day
On-time (time in use)

1
Air condition
2000
18
36000
36
8
08:00–16:00

2
Fans
56
78
4368
4.368
8
08:00–16:00

3
Lighting
40
152
6080
6.08
8
08:00–16:00

4
Printers
800
11
8800
8.8
8
08:00–16:00

5
Desktop computer
264
14
3696
3.696
8
08:00–16:00

6
Security light
60
9
540
0.54
8
08:00–16:00

7
Refrigerator
100
12
1200
1.2
8
08:00–16:00

8
Pumping machine
1119
1
1119
1.119
2
10:00–12:00

9
Television
60
12
720
0.72
4
12:00–16:00

10
Tachometer
16.1
1
16.1
0.016
3
13:00–16:00

11
Transformer trainer
600
1
600
0.6
3
13:00–16:00

12
Feedback power tester
675
1
675
0.675
3
13:00–16:00

13
Battery charger
4400
1
4400
4.4
6
10:00–16:00

14
System trainer
4.56
1
4.56
0.00456
3
13:00–16:00

15
Projector
210
2
420
0.42
6
10:00–16:00

16
Thurlby PL(320)
480
1
480
0.48
3
13:00–16:00

17
Function generator
500
1
500
0.5
3
13:00–16:00

18
Photocopy machine
1100
12
13200
13.2
6
10:00–16:00

19
Soldering iron
480
8
3840
3.84
7
09:00–16:00

20
DC power supply
375
1
375
0.375
3
13:00–16:00

21
Electric water heater
2990
12
35880
35.88
2
08:00–10:00

22
Oscilloscope
255
3
765
0.765
3
13:00–16:00

23
Signal generator
1000
2
2000
2
3
13:00–16:00

24
Feedback amplifier
155.9
1
155.9
0.1559
3
13:00–16:00

Table 2: The electrical load (daily load demands) data for remote station.

Time
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Total (watt)
Total (kwatt)

00:00–01:00

540

540
0.54

1:00–2:00

540

540
0.54

2:00–3:00

540

540
0.54

3:00–4:00

540

540
0.54

4:00–5:00

540

540
0.54

5:00–6:00

540

540
0.54

6:00–7:00

0
0

7:00–8:00

0
0

8:00–9:00
36000
4368
6080
8800
3696

1200

35880

96024
96.024

9:00–10:00
36000
4368
6080
8800
3696

1200

3840

35880

99864
99.864

10:00–11:00
36000
4368
6080
8800
3696

1200
1119

4400

420

13200
3840

83123
83.123

11:00–12:00
36000
4368
6080
8800
3696

1200
1119

4400

420

13200
3840

83123
83.123

12:00–13:00
36000
4368
6080
8800
3696

1200

720

4400

420

13200
3840

82724
82.724

13:00–14:00
36000
4368
6080
8800
3696

1200

720
16.1
600
675
4400
4.56
420
480
500
13200
3840
375

765
2000
155.9
88295.56
88.29556

14:00–15:00
36000
4368
6080
8800
3696

1200

720
16.1
600
675
4400
4.56
420
480
500
13200
3840
375

765
2000
155.9
88295.56
88.29556

15:00–16:00
36000
4368
6080
8800
3696

1200

720
16.1
600
675
4400
4.56
420
480
500
13200
3840
375

765
2000
155.9
88295.56
88.29556

16:00–17:00

0
0

17:00–18:00

0
0

18:00–19:00

540

540
0.54

19:00–20:00

540

540
0.54

20:00–21:00

540

540
0.54

21:00–22:00

540

540
0.54

22:00–23:00

540

540
0.54

23:00–00:00

540

540
0.54

716224.7
716.2247

Figure 1: Station average daily load variation, Ikorodu, Lagos [7].

2.2. Solar and Wind Data for the Station Location

2.2.1. Photovoltaic Energy

Solar energy is one of the inexhaustible energy sources for renewable energy implementation of solar photovoltaic energy with a readily available standalone diesel generator [1]. Nigeria enjoys average daily sunshine hours of 6.25 hd⁻¹ ranging between about 3.5 kWh m⁻²d⁻¹ in coastal areas and 9.0 kWh m⁻²d⁻¹ at far northern boundary [2]. In Nigeria, two main seasons are usually experienced because of the variation of climate from tropical to subtropical. The seasons are dry, which normally spans between October and March, and wet season, which usually spans between April and October. Variation in the stipulated months is usually experienced in the northern part of the country where the weather is very hot and dry. In the region, the raining season may vary between April and September, while in the southern part of the country, where the weather is usually hot and humid, rainy season may occur between March and December [3]. The coastal area rarely produces temperature above 32°C while the temperature in the north may range between 32°C and 42°C with average humidity of about 95° Fahrenheit [4]. Ikorodu town in Lagos state has temperature of about 22°C, wind speed at 16 kmh⁻¹ and 78% humidity [5].

2.2.2. Wind Resources

The wind speed in Ikorodu, Lagos, is very low and not suitable for a hybrid power system. This speed is averagely about 16 kmh⁻¹ throughout the year. Because of this reason, wind turbine is not considered in this work. In this work, solar renewable energy resources are used. The solar data for clearness index and radiation index were obtained from NASA surface meteorology [6]. Ikorodu is a town and a Local Government Area in Lagos state, Nigeria, located along the Lagos lagoon. It shares boundary with Ogun state. The weather condition is 31°C, wind speed at 16 kmh⁻¹, 78% humidity at location latitude of 6.6000°N and longitude of 3.5000°E. Table 3 shows the solar resource profile for Ikorodu, Lagos, Nigeria. The latitude 6.6 and longitude 3.5 were chosen to run the HOMER data file from NASA surface meteorology of solar energy. The annual average monthly radiation incident on a horizontal surface is obtained as 4.74 kWh m⁻²d⁻¹ for year 2015.

Table 3: Daily averaged solar incident on a horizontal surface.

Month
Clearness index
Daily radiation (kWh/m²/day)

January
0.628
5.280

February
0.596
5.490

March
0.543
5.460

April
0.494
5.210

May
0.448
4.760

June
0.383
4.040

July
0.374
3.950

August
0.378
3.980

September
0.402
4.090

October
0.483
4.550

November
0.578
4.950

December
0.636
5.170

Annual average monthly radiation (kWh m⁻²d⁻¹: 4.74) [6, 7].

Table 3 and Figure 2 reveal that February 2015 is the sunniest month of the year with solar energy of 5.49 kWh m⁻²d⁻¹, while July gave the lowest sunny month of the year with solar energy resource of 3.95 kWh m⁻²d⁻¹. However, starting from the month of August to February, the solar radiation gained solar energy with differences from month to month cycle as (0.03), (0.11), (0.46), (0.40), (0.22), (0.11), and (0.21), respectively, whereas there are decreases in solar radiation from the months of March, April, May, June, and July with these values of solar (0.03), (0.25), (0.45), and (0.72), respectively. During these former months when the solar radiation dropped drastically, the standby diesel generator can stand in to compensate for the energy needed because the whole system setup is optimized.

Figure 2: Station graphic display for solar radiation of Ikorodu, Lagos [7].

2.2.3. Design of Station Solar Power Subsystem

The software used for the design and simulation of the PV/Diesel hybrid power system is HOMER optimization software. The input data used to run the HOMER program include

(a)hourly load demand profile,(b)sample of monthly solar radiation value of year 2005 PV system,(c)the initial cost of each component of renewable energy, photo voltaic panel system, backup diesel generator, converter, and battery bank,(d)the cost of AGO and yearly real interest rate of the project life cycle.

The hourly load demand data were gotten from load consumption of the station; the sample of monthly solar radiation value was gotten from NASA online data. 2005 data were the latest available data at June 1, 2015 [6, 7].

The initial capital cost of PV panel, diesel generator, battery, and converter was sought from Nigeria venture in Naira and later converted to dollars in order to be used in HOMER software [8]. HOMER software recognizes US dollars only. The current price of AGO was gotten from NNPC marketers for this simulation. Excel spreadsheet program is used to compute hourly load profile. HOMER is used for simulation of the system operation for 25 years. It reveals the energy balance calculation for every hour in each year. The configuration is sorted to be based on the life cycle cost (LCC) of the system. This (LCC) could be referred to as total net present cost (TNCP) [9]. The calculation here gives information about any cost which could occur during the stipulated project lifetime cycle of 25 years. These include initial setup costs, component replacement cost, maintenance cost, and fuel energy cost.

Designing a hybrid system demands correct components selection and sizing with appropriate operational strategy [10, 11]. In this work, solar energy is used with a diesel generator. The hybrid components include electric load demand, solar panels, battery, and converter. The architectural design of Figure 3 is obtained from HOMER V2.68.

Figure 3: Hybrid renewable energy system architectural design [7].

For this work, the sensitivity variables were chosen based on monthly solar radiation and diesel fuel price. The simulation was based on life cycle cost (LCC) which reflected the total net present cost (TNPC).

HOMER was used to perform the optimization of the selective variables. This optimization gave the best hybrid renewable energy system size.

From the discussion so far, the four main components in PV/Diesel hybrid system are the PV panels, diesel generator, batteries, and converters. In order to determine the economic advantage of a hybrid system, one must determine the number of the above components units to be used, capital costs, replacement cost, and operation and maintenance cost. Operating hours must be stated in order for HOMER software to give accurate simulation.

2.3. HOMER Input Data

2.3.1. Solar Photovoltaic (PV)

The photovoltaic module needed to power the station load of 716.224 kWh d⁻¹ is estimated to cost $116,609 with the installation charges. The modules are expected to last for 25 years. The parameters used for the simulation of solar photovoltaic (PV) are suggested by HOMER.

2.3.2. Battery

The commonly used battery in hybrid system is the surrette 4kS25P.

2.3.3. Converter

800 kW converter was used as input data for converter in this design.

2.3.4. Diesel Generator

A linear curve characterized by slope and intercept at no load is used to model the generator fuel consumption in HOMER. The graph of Figure 4 displays the load slope and intercept of 0.2372 (L/hr/kW output) and 0.0391 (L/hr/kW rated), respectively.

Figure 4: Fuel curve for generator set [7].

2.4. Design of the HPSS Components

2.4.1. Selection of Diesel Generator

The generator rated 725 kW was chosen on the HOMER software since the load requirement for the design is 716.224 kWh d⁻¹. The site specific input of diesel generator was analysed as follows.

( 1) Lifetime (Hours). This is the number of hours in which the generator is expected to provide service before replacement.

For the generator operating on minimum of 4 hours daily on weekdays, its lifetime in hours is calculated as follows:

(a)Hours/week = 4 × 5 = 20 hours/week.(b)Hours/month = 20 × 4 = 960 hours/month.(c)Hours/year = 80 × 12 = 960 hours/year.(d)Lifetime hours (25 years) = 960 × 25 = 24000 hours/25 years.

For the generator working on weekly (7 days) basis, its lifetime in hours is calculated as follows:

(a)Hours/week = 4 × 7 = 28 hours/week.(b)Hours/month = 28 × 4 = 112 hours/month.(c)Hours/year = 112 × 12 = 1344 hours/year.(d)Lifetime hours (25 years) = 1344 × 25 = 33600 hours/lifetime.

( 2) Minimum Runtime (Minutes). This is when the dispatch starts the generator.

For the generator working on weekdays only, its minimum runtime in minutes is calculated as follows:

(a)Minutes/day = 4 × 60 = 240 minutes/day.(b)Minutes/week = 240 × 5 = 1200 minutes/week.(c)Minutes/month = 1200 × 4 = 4800 minutes/month.(d)Minutes/year = 4800 × 12 = 57600 minutes/month.(e)Lifetime minutes (25 years) = 57600 × 25 = 144000 minutes/25 years.

For the generator operating a minimum of 4 hrs daily on weekly basis, its minimum runtime in minutes is calculated as follows:

(a)Minutes/day = 4 × 60 = 240 minutes/day.(b)Minutes/week = 240 × 7 = 1680 minutes/week.(c)Minutes/month = 1680 × 4 = 6720 minutes/month.(d)Minutes/year = 6720 × 12 = 80640 minutes/year.(e)Lifetime minutes (25 years) = 80640 × 25 = 201600 minutes/25 years.

( 3) Minimum Load Ratio (%). This is the minimum allowable load on the generator expressed as a percentage of its capacity. For minimum capacity of 0.54 kW, 82.724 kW, and 83.123 kW, the minimum load ratio is calculated as follows:

( 4) Fuel Curve. This provides assistance in calculating the two fuel curve inputs on the generator window.

( 5) Schedule. HOMER schedule decides each time step. It operates and control the generator operation based on the electrical power demand. The operational schedule plan is shown in Figure 5.

Figure 5: Generator operation schedule chart for diesel generator [7].

2.4.2. Solar Photovoltaic

A generic flat plate of 350 W rating was chosen for the design. PV capacity and cost are analysed as follows:

 Total load of 716.224 kWh d⁻¹ divided by hours of sunlight per day (8 hrs) = 716.22/8 = 89.5275 kWd⁻¹. For 0.35 kW panel capacity, this will give .

The price cost of 0.35 kW panels in dollars is $455 [12]. Therefore, 256 panels will cost .

2.4.3. Battery

The CELLCUBE FB 200–800 battery of 800 kW capacity was chosen.

2.4.4. Power Converter

The generic system AC/DC inverter of 800 kW capacity was chosen for the design of this work.

3. Results and Discussions

3.1. Simulation Results

The simulation displayed information on the economic cost, electricity production, and environmental characteristic of each system component. The results obtained are presented in Tables 4, 5, and 6, respectively. The simulation reveals the optimized sizes of the solar photovoltaic panel, battery bank, converter, and diesel generator as used in this work. This led to the design specification of the system components. Since the input data are the load requirement of the station, the hourly solar radiation and ambient temperature of the station obtained from NASA website were used. The analysed solar radiation gave the best optimized tilt angle of 48.65° for the PV panel. The result of the simulation reveals that hybrid system of 750 kV PV array, 3 units of 800 kWh battery, and 800KW AC/DC inverter would generate electricity of 1077343 kWh yr⁻¹ while 725 kW diesel generator generates 24321 kWh yr⁻¹, making total power generation of 1101664 kWh yr⁻¹ altogether at the cost of $62,050 (#12,410,000) [13].

Table 4: HOMER simulation result showing sensitivity case only.

Architecture
Cost
System
Gen725

PV (kW)
Gen725 (kW)
FB
200–800
Converter (kW)
Dispatch
COE ($)
NPC ($)
Operating cost ($)
Initial capital ($)
Ren Frac (%)
Fuel (L)
Hours

750

2
400
CC
0.489
1,651,149
5,346
1,582,035
100

750
725
1
400
CC
1.057
3,572,806
144,519
1,704,535
91
88,454
2,919

725
2
400
CC
1.212
4,096,615
241,893
969,535
0
214,852
2,919

Table 5: HOMER simulation result showing optimization case with categorized option.

Architecture
Cost
System
Gen725

PV (kW)
Gen725 (kW)
FB
200–800
Converter (kW)
Dispatch
COE ($)
NPC ($)
Operating cost ($)
Initial capital ($)
Ren. Frac (%)
Fuel price ($/L)
Hours

750

2
400
CC
0.489
1,651,149
5,346
1,582,035
100
0.75

Table 6: HOMER simulation result showing optimization case with overall option.

Architecture
Cost
System
Gen725

PV (kW)
Gen725 (kW)
FB
200–800
Converter (kW)
Dispatch
COE ($)
NPC ($)
Operating cost ($)
Initial capital ($)
Ren Frac (%)
Fuel (L)
Hours

89.6
725
3
400
CC
1.190
4,021,437
208,503
1,326,015
0
166,871
2,919

750
725
3
400
CC
1.203
4,064,293
145,408
2,184,535
100
82,734
2,919

0.4
725
2
400
CC
1.212
4,095,415
241,746
970,235
0
214,656
2,919

725
2
400
CC
1.212
4,096,615
241,893
969,535
0
214,852
2,919

750
725
3
400
CC
1.219
4,119,949
149,713
2,184,535
91
88,474
2,919

89.6
725
3
800
CC
1.227
4,147,168
208,559
1,451,015
0
166,734
2,919

750
725
3
800
LF
1.240
4,189,552
145,428
2,309,535
100
82,734
2,919

0.4
725
2
800
CC
1.249
4,220,674
241,766
1,095,235
0
214,656
2,919

3.2. Optimization Results

From the optimization results, Tables 5 and 6 showcase the optimization results with overall option. These results displayed the comparable results of the system configuration. The results analysed here are the system components sizes and numbers, initial capital cost and operating cost, NPC and COE, renewable fraction, and fuel consumption [13]. Tables 5 and 6 displayed the best optimal combination of energy system components. (one 725 kW diesel generator and 256 solar panels were used to assemble one 750 kW solar PV array, three 800 kW cell cube battery cycles charging, and one 800 kW converter). This hybrid system provides the lowest total net present cost when compared to existing diesel standalone generator as displayed in Table 7, with enough excess energy to meet the remote station energy demand if compared with the standalone diesel system as shown in Table 9. The presence of storage battery raises the initial capital cost of the system but battery storage reduces the operating hours of diesel generator in a system referring to the operational schedule in Figure 5 and therefore saves the world from global warming caused by high emission of toxic substances from generators and therefore reduced fuel consumption.

Table 7: Comparison simulation of economic results between existing system and a hybrid system.

Parameter
Existing diesel-only system
Proposed hybrid (PV/Diesel) system

Value
Dollar ($)
Naira (#)
Dollar ($)
Naira (#)

Initial cost
1,574,535
314,907,000
2,184,535
436,907,000

Operating cost
416,895
83,379,000
145,408
29,081,600

Total NPC
6,963,954
1,392,790,800
4,064,293
812,858,600

3.3. Cost-Benefit Analysis of HPSS

3.3.1. Existing System/Proposed Hybrid System

The existing diesel generator has lower initial capital cost, higher operating cost, and higher total net present cost for the whole project as shown in Table 7 and as illustrated on chart of Figure 6. This system emits more carbon monoxide (CO) and NO₂ as a result of fuel combustion of a lot of AGO. The hybrid solar PV/Diesel system can supply renewable energy corresponding to 98% of the daily energy demand to the station. The hybrid solar PV/Diesel system has reduced total net present cost as a result of less fuel consumption as shown in Table 7 and displayed in chart of Figure 7.

Figure 6: Cash flow analysis of NPC of existing diesel-only generator set [7].

Figure 7: Cash flow analysis of NPC of optimized hybrid energy system [7].

3.3.2. Economic Cost

The NPC involved in the two cases of standalone diesel generator and hybrid systems is displayed in Table 7. Subtracting the hybrid NPC from Standalone diesel NPC, the standalone system is $2,899,661 (#579,862,200) costlier if compared with the newly designed hybrid system NPC. An hybrid system saves cost and allows the station to enjoy optimum economic conditions. Moreover, the operational life of diesel only is low (2 years) as predicted by HOMER software in Table 8, while in Hybrid system its operational life is extended (5 years) as shown in Table 8.

Table 8: Comparison simulation of existing system (diesel only) and proposed hybrid system.

Quantity
Diesel only
Diesel in hybrid system

Value
Units
Value
Units

Operational life
2.0
yr
5.0
yr

Capacity factor
12
%
3
%

Hours of operation
7,008
h yr⁻¹
2919
h yr⁻¹

Fuel consumption
274,877
L yr⁻¹
88,474
L yr⁻¹

Table 9: Comparison of simulation results of electricity production (kWh yr⁻¹).

Quantity
Diesel only
Hybrid system (Solar PV/Diesel)

kWh yr⁻¹%
%
kWh yr⁻¹%
%

Load consumption

AC primary load
261,422
100
261,422
100

Production

PV array
None
None
1,077,343
98

Diesel generator
321,686
100
24,317
2

Total energy
321,686
100
1,101,660
100

Excess electricity
26

761261

3.4. Electricity Production

The standalone diesel generator set produces 321,686 kWh yr⁻¹ (100%) of the total electricity with a capacity factor of 12% compared to the proposed hybrid system that will produce 1,077,343 kWh yr⁻¹ (98%) from solar PV array and 24,317 kWh yr⁻¹ (2%) from diesel generator with a capacity factor of 3% making a total of 1,101,660 kWh yr⁻¹ (100%). The load demand is 261,422 kWh yr⁻¹, while excess electricity from the existing system is 26 kWh yr⁻¹; the proposed project has excess electricity of 761,261 kWh yr⁻¹ as shown in Table 9. This information is displayed graphically in Figures 8 and 9, respectively:

Figure 8: Monthly average of electrical power production of diesel-only generator set [7].

Figure 9: Monthly average of electrical power production of hybrid energy system [7].

3.5. Environmental Pollution

The standalone diesel generator set operates for 7,008 h annum⁻¹, with total fuel consumption of 74,877 L annum⁻¹. It generates 721.420 tonnes of CO₂, 3.026 tonnes of CO, 0.346 tonnes of UHC, 0.087 tonnes of PM, 1.485 tonnes of SO₂, and 3.024 tonnes of NO₂ as shown in Table 10. In contrast, in hybrid PV/Diesel system, the diesel generator operates for 2,919 h annum⁻¹ and has a fuel consumption of 88,474 L annum⁻¹ as shown in Table 10. This system emits 232.201 tonnes of CO₂, 0.97 tonnes of CO, 0.111 tonnes of UHC, 0.028 tonnes of PM, 0.478 tonnes of SO₂, and 0.973 tonnes of NO₂ annually. Considering the environmental hazard, the higher the operational hours of a diesel generator, the higher the pollutant emission, and vice versa. Therefore, standalone generating set poses more danger to the environment if compared with a hybrid system.

Table 10: Comparison of simulation results of emissions from standalone diesel generator set and proposed system.

Pollutant
Emissions (kg yr⁻¹)

Existing diesel only
Proposed hybrid system
Difference

(kg yr⁻¹)
(ton yr⁻¹)
(kg yr⁻¹)
(ton yr⁻¹)
(ton yr⁻¹)

Carbon dioxide
721,420
721.420
232,201
232.201
489.219

Carbon monoxide
3024
3.024
973
0.973
2.054

Unburned hydrocarbon
346
0.346
111
0.111
0.235

Particular matter
87
0.087
28
0.028
0.059

Sulphur dioxide
1485
1.485
478
0.478
1.007

Nitrogen oxide
3024
3.024
973
0.973
2.051

3.6. Economics and Constraints

The project lifetime is fixed to be 25 years at annual interest rate of 5.88%. The safety margin of the operating reserve ensures the reliability of the power supply irrespective of the load variation. No capacity shortage was noted. The operating reserve as expressed in percentage of hourly load was 10%. Meanwhile, the operating reserve as a percentage of solar power output is fixed at 25%.

3.6.1. System Economics

The capital costs for all the system components prices as quoted in this paper were sorted from local suppliers in Nigeria and outside Nigeria [8]. The costs estimates used in this paper were obtained from series of internet search. These prices may slightly defer from the actual prices. This is due to fluctuation of market prices in Nigeria. The replacement cost is assumed to be the same as the initial cost in this paper. The system components maintenance costs are estimates based on approximate time of 25 years required for the station. One dollar conversion to naira at the time that this work was done is N200 of Nigerian currency [14].

4. Conclusion

The analysis shows that the optimal hybrid system discussed in this paper is economically profitable for use in a remote station compared to using a diesel-only power generating set. This hybrid system reduces the fuel consumption and carbon dioxide (CO₂) by 32.18%, from Tables 8 and 10, respectively. From the environmental point of view, global warming could be controlled if we all embrace the advantages of this renewable energy technology. The simulation results analysis made it known that if battery is used with a hybrid PV/Diesel system, a high reduction in NPC and emission of toxic substances is also possible. In the same vein, this system meets the annual load demand of the remote station at a reduced cost and it is reliable with cheap maintenance cost. The objectives of this work are to provide reliable, clean, and environmentally friendly alternative power supply to the station at a much reduced cost. The analysis shows that a photovoltaic/diesel hybrid power system is reliable and economically viable for use at this proposed site.

4.1. Recommendation

These few recommendations are, however, worth noting. The excess energy generated in this paper could be used to power the neighbouring community but in the case of a station where no one lives around, multiple generators are used instead of one generator with higher capacity to reduce the amount of excess electricity generated in order to minimize energy wastage [15]. The emission from diesel generators in both cases is too high and this causes global warming; therefore equipment like carbon capture could be used to reduce the emission. During the design, each component must be stated accurately with respect to load demand and each component size must be at least 10% greater than the load demand. The input voltages of the converter and the battery must be the same. Many sensitivity variables required a lot of simulation time to run; therefore too many sensitivity variables may be avoided.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

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