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Solar power energy in some countries can be the most potential renewable energy to overcome lack of energy and environmental problems. Indonesia is one of the examples. One of the promising cities to install photovoltaic (PV) systems is Makassar, which has average 5.83 kWh/m
^{2}/day of solar irradiance (Meyta, 2011). However, until 2016, there is still no solar panel installation in Makassar (PLN, 2015). In addition, general lack of research in assessing potential of PV systems in Makassar makes PV system difficult to develop. This study therefore set out to assess PV system potential in Makassar which its objectives are to determine 1) total available area for rooftop and large-scale PV systems in Makassar, 2) economy feasibility and 3) environmental impact due to PV installation. Three cases have been analyzed in this study, first, PV systems for residential rooftop, second, PV systems for large-scale (mega solar) in Makassar, and third, PV systems for large scale in outside Makassar and radius 20 km from center of Makassar. ArcGIS10.3 software is carried out to estimate available area for PV installation. Furthermore, RetScreen 4 software was used to conduct PV system capacity and its energy yield and to evaluate economy analysis such as internal rate of return and cost of energy. As the result, the total available area for residential rooftop PV system is evaluated to be 13.8 km
^{2}, which potential installed capacity is estimated to be 2044 MW. Total available area for large-scale PV system in Makassar and outside Makassar are 19.3 km
^{2} and 231.3 km
^{2}, which estimated 851 MW and 10,179 MW of installed capacity, respectively.

Indonesia is located in south East Asia and consists of five big islands, namely, Sumatera, Java, Kalimantan, Sulawesi and Papua. They spread from east to west, which has total area of 1,910,931 km^{2}. Over the past decade, Indonesia has been achieving economic and population growth making that quality of life of each individual person improves and ultimately causing energy final consumption to grow (

Nonetheless, there is an increasing concern that these fossil energies will be no longer cost competitive due to changes in relative price caused by policies or resource depletion. In addition, fossil energy accounted high percentage to CO_{2} emission, as we know, CO_{2} is the most prominent substance that leads to environmental problem. Due to notions explained earlier, it can be concluded that the importance to supersede non-renewable energy with the renewable ones is rising for energy consumption sector.

In addition, Indonesia is an archipelago that consists of thousand islands that are not connected into one grid system due to high cost of installations, as the main problem. Thus, up to this point of time, each island needs to produce energy in their areas in order to cover local energy demands. Objectively, Indonesia has a big potential in solar energy because it’s located in the equator line, therefore the solar radiation spread in all Indonesia is relatively constant everywhere. One of the prosperous advantages of solar power energy is that it does not produce CO_{2} as the results of production residue. According to this reason, solar energy can be one of the most potential renewable energy resources to overcome energy challenges in Indonesia.

Furthermore, technology development in solar power energy and the increased amount of installation of solar power generation all over the world in recent years make the module price of solar panel significantly reduced [

As shown in ^{2} areas, and the average solar radiation is about 5.83 kWh/m^{2}/day [

There are three case setting categories that are modeled in this study, those are the assessment of rooftop PV system in Makassar, the assessment of large scale

PV system (mega solar) in Makassar and lastly, the assessment of mega solar outside Makassar with radius 20 km from center of Makassar. Each case estimates total area that can be installed for PV system, the impact from its installation to environment and analysis in economic feasibility. The overview of case setting is shown in

Estimation of PV-suitable rooftop area is determined by using GIS (Geographic Information System) with specifically is examined by using ArcGIS 10.3 software. PV power generation, environmental impact and analysis in economy are conducted using RetScreen 4, which is software that used for simulating and calculating a clean energy project such as renewable energy and energy efficiency.

The proposed methodological approach is visualized in

First, ArcGIS software is used to analyze land use and divides into three cases. Using the same software each case can be extracted and by using RetScreen, with the input of panel characteristic, solar irradiance and temperature, total power generation can be obtained. Using the same software, economic evaluation such

as cost of energy and internal rate of return and environmental evaluation, for instance like greenhouse gas analysis, are conducted to produce more prominent analysis.

1) Rooftop PV System

PV system installation areas are calculated using Equation (1). Land use is carried out to calculate the area of a residential building, while the resulting area that can be introduced residential PV system is calculated by multiplying the coefficients shown in Equation (1). Data of land use were obtained from the Indonesian Ministry of Forestry (2011).

C_{v} is void rate coefficient, C_{s} is shadow rate coefficient, C_{f} is facility rate coefficient, A_{b} is area of the possible building, while A_{a} is the area of the possible housing [

2) Mega Solar

Area that can be installed to mega solar extracted from land of use with the criteria as the following; bush, dry land farming and swamp. From all of these criteria, the total area is calculated, and by multiplying with building coefficient factor, the availability area that can be installed to PV system can be determined. Building coefficient factor value set to 0.9 and for each km^{2} can be installed to 44 MW of PV System capacities [

Makassar laid in equator line which make there is no significant change in seasonal condition. Generally, there are only two seasons in Indonesia, as well as in Makassar which are wet and dry seasons. Nevertheless, based on the historical evidences, Makassar is dominated by dry season. Solar irradiance data is obtained from NASA and from IDMP station which located in University of Makassar [^{2}/day (NASA) and 6.01 kWh/m^{2}/day (IDMP).

1) Panel Characteristic

Panel specification is shows in

2) Calculation of PV Power Generation

The solar radiation amount per time that is incident on the PV array obtained from Equation (2).

Manufacture | BP Solar |
---|---|

Type of PV module | Mono-Si |

Model | BP 2150 S |

Capacity per panel | 185 W |

PV efficiency | 14.80% |

Area per panel | 1.24 m^{2} |

Inverter efficiency | 92% |

H_{t} is hourly irradiance in the plane of the PV array, H is global horizontal irradiance and it’s diffuse and beam components are H_{d} and H_{b}. R_{b} is ratio of incident solar irradiance, β is the slope of PV array, ρ represents the diffuse reflectance of the ground. Calculation of H_{t} is conducted using isotropic model (Duffie and Bekman (1991)) which assume using the combination of diffuse and ground-reflected radiation [

Furthermore, total amount per day of solar irradiance is calculated by summing solar irradiance per hour as shown in Equation (3).

PV array efficiency η_{p} is a function from module average temperature T_{c} and can be calculated using Equation (4).

η_{r} is PV module efficiency at reference temperature (25˚C), β_{p} is coefficient temperature of PV module and T_{r} is average ambient temperature calculated using Evan function. PV power generation E_{grid} is obtained by using Equation (5). This is the calculation of the energy delivered by the PV array (_{p} is miscellaneous PV array losses rate, l_{c} is inverter losses rate and η_{inv} is inverter efficiency.

3) Panel slope and direction setting

Residential house in Makassar city are built in many directions to make it hard to assess the actual potential of PV system when PV panel located solely in particular direction. Due to the form of rooftop in Makassar, possible angle of slope set is restricted and assume to be 20˚. Panel azimuth change with 20˚ interval from 0˚ to 180˚ and it was determined towards azimuth angle of the maxi- mum amount of power generation.

In the case of mega solar, the panel slope angle change between 0˚, 10˚, 20˚, 30˚ while panel azimuth changed from 0˚ (south-facing) until 180˚ (northward) in 15˚ intervals, in order to optimize the annual power generation.

4) Power demand

In 2013, annual electricity demand in the Makassar City is 2.73 million MWh, which make Makassar as the highest power demand in South Sulawesi Province [

Annual CO_{2} emission reduction due to the introduction of the PV system is calculated using Equation (6).

_{2} emission reduction [t-CO_{2}/yr], RFco_{2} (t-CO_{2}/MWh) is CO_{2} emission factor, EG (MWh/yr) is annual energy production by PV systems. According to State Electricity Company (PLN: Perusahaan Listrik Negara), CO_{2} emission factor in Indonesia in 2014 is 0.741 t-CO_{2}/MWh.

In 2013, Ministry of Mineral and Energy Resource has regulated FIT (Feed-in Tariff) regulation. This regulation has been revised in 2016 which the content is to obligates State Electricity Company to buy solar generated electricity by range between 14.5 ~ 23 cents $/kWh depends on the installment location [

1) Rooftop PV System Cost

Based on the previous published research, cost for rooftop PV system will vary between USD 2000 and USD 4000 per kW depends on the location. In Indonesia the cost for rooftop PV system per kW set to USD 2800 as presented in

Item | Cost (USD) |
---|---|

Type of PV module | Mono-Si |

Model | BP 2150 S |

Capacity per panel | 185 W |

PV efficiency | 14.80% |

Area per panel | 1.24 m^{2} |

Inverter efficiency | 92% |

2) Mega Solar Cost

The cost for mega solar is same with the rooftop PV system cost except for additional price on land purchase price. The price is USD 100/m^{2} for inside Makassar City and USD 20/m^{2} for outside Makassar (2014 price) [

According to

^{2} area while for rooftop, all available area can be installed for PV system. The result of the land use in Makassar shared as follow; 40% is residential, 24% for agricultural land (paddy field), 11% for fishpond, 13% is water area and mangrove. Thus, 12% of area in Makassar potentially builds for mega solar.

Item | Total Area (km^{2}) | Capacity (MW) |
---|---|---|

Rooftop in Makassar | 13.8 | 2044 |

Mega solar in Makassar | 19.3 | 851 |

Mega solar outside Makassar | 231.3 | 10179 |

Optimization of annual PV power generation is gained in case the panel slope angle is set to 20˚ when azimuth angle set to direction northward (180˚). The result of PV power generation each month is shown on

Annual PV power generation calculated from NASA solar irradiance is 3.40 million MWh. On the other hand, using IDMP solar irradiance can get 3.48 million MWh of the annual PV power generation. PV power generation can reduce 2.52 Mt-CO_{2 }(NASA) and or 2.58 Mt-CO_{2} (IDMP). There is different measurement method of solar irradiance between NASA and IDMP that lead to different result in PV power generation. However, the result of annual PV power generation and reduction of CO_{2} are not significantly different.

Item | Inverter life time 5 years | Inverter life time 10 years | ||
---|---|---|---|---|

NASA | IDMP | NASA | IDMP | |

Cost of Energy ($/MWh) | 133.2 | 130.2 | 93.6 | 91.5 |

IRR (%) | 3.1 | 3.5 | 6.5 | 6.8 |

The next indicator used in this analysis is cost of energy. Compare to household electricity tariff which is 1460 Rp/kWh (USD2016 0.11/kWh) as of October 2016, cost of energy (with subsidies) of PV system with 5 years’ inverter (around USD 0.13/kWh) is still slightly higher. There is a significant improvement with 10 years’ inverter PV system, to make the cost of energy per kWh is cheaper compare to the household electricity tariff.

To gain the optimization of annual PV power generation panel slope angle is set to 10˚, and azimuth angle set to direction northward (180˚). The result of PV power generation each month is shown on

Annual PV power generation calculated from NASA solar irradiance is 1.44 million MWh. On the other hand, using IDMP solar irradiance can get 1.47 million MWh of the annual PV power generation. PV power generation can reduce by 1.07 Mt-CO_{2 }(NASA) and or by 1.09 Mt-CO_{2} (IDMP). Either NASA or IDMP generate less electricity than its demand in the whole year. Albeit total possible area to install mega solar larger than rooftop, the PV system capacities from mega solar is not directly proportional which make electricity generated from this case does not sufficient to power up Makassar.

Item | Inverter life time 5 years | Inverter life time 10 years | ||
---|---|---|---|---|

NASA | IDMP | NASA | IDMP | |

Cost of Energy ($/MWh) | 147.3 | 144.5 | 108.3 | 106.2 |

IRR (%) | 1.3 | 1.6 | 4.4 | 4.6 |

years’ inverter system. The cost of energy of PV system in this case is range between USD 0.11/kWh to USD 0.15/kWh to make it same for 10 years’ inverter system and much higher for 5 years’ inverter compare to household electricity tariff.

To gain the optimization of annual PV power generation panel slope angle is set to 10˚, and azimuth angle set to direction northward (180˚). The result of PV power generation each month is shown on

Annual PV power generation calculated from NASA solar irradiance is 17.2 Thousand GWh. On the other hand, using IDMP solar irradiance can get 17.5 thousand MWh of the annual PV power generation. PV power generation can reduce by 12.75 Mt-CO_{2} (NASA) and or by 13.0 Mt-CO_{2} (IDMP).

Item | Inverter life time 5 years | Inverter life time 10 years | ||
---|---|---|---|---|

NASA | IDMP | NASA | IDMP | |

Cost of Energy ($/MWh) | 134.5 | 131.9 | 95.5 | 93.6 |

IRR (%) | 2.9 | 3.2 | 6.2 | 6.4 |

Total available area for residential rooftop PV system is evaluated to be 13.8 km^{2}, which is the least when compared to others case. But, it can produce more power when compare to mega solar inside Makassar. This is because PV panel can be inserted in all of available area while for mega solar area is estimated as 44 MW for each km^{2}. In rooftop PV system, potential installed capacity is estimated 2044 MW while for large-scale PV system in Makassar and outside Makassar are 851 MW and 10,179 MW respectively. Total available area for large-scale PV system in Makassar and outside Makassar are 19.3 km^{2} and 231.3 km^{2} which can produce electricity 5 times and 62 times higher than the electricity demand (or about 1.44 million and 17.21 million MWh respectively). The remarkably higher of available area for mega solar outside Makassar is due to small occupancy for settlement and high proportion for mega solar area (dry land farming, bush and swamp) which occupied for about 43.8% of the total area. Mega solar PV power generation has the smallest IRR and the highest cost of energy. When inverter life time is 10 years its value is 4.6% for IRR and USD 106.17/MWh for cost of energy. On the other hand, rooftop PV and mega solar outside Makassar has a higher IRR which is 6.8% and 6.4% respectively. It could be argued that the higher IRR for rooftop results were due there was no additional cost for land purchasing while for mega solar outside Makassar the land price is much cheaper compare to thus inside Makassar. The rooftop PV system has the cheapest cost of energy which is USD 91.51/MWh to make it cheaper compare to household electricity tariff in 2016.

Solar power energy in some countries that are located in equator, such as Indonesia, can be the most potential renewable energy to overcome lack of energy and environmental problems. One of the most promising cities in Indonesia to install photovoltaic (PV) systems is Makassar, which has average 5.9 kWh/m^{2}/day of solar irradiance. Within the scope of this research, three cases have been analyzed, which are PV systems for residential rooftop, PV systems for large-scale

Name | Rooftop PV in Makassar | Mega solar in Makassar | Mega solar outside Makassar |
---|---|---|---|

Aveilabe area (m^{2}) | 13.8 | 19.3 | 231.3 |

Capacity (MW) | 2,044 | 850.9 | 10,179 |

Annual power generation (MWh) | 3.4 million | 1.44 million | 17.21 million |

Cost of energy ($/MWh) | 91.5 | 106.2 | 93.6 |

Economic viability (10 years inverter PV system) | Feasible (IRR = 6.8%) | Feasible (IRR = 4.6%) | Feasible (IRR = 6.4%) |

CO_{2} annual reduction relatively to power demand emission (%) | 124 | 52 | 629 |

(mega solar) in Makassar, and PV systems for large scale in outside Makassar and radius 20 km from center of Makassar. ArcGIS software is used in order to evaluate amount of available PV installation capacity, while RetScreen is carried out to conduct energy simulation and to evaluate economy analysis.

There was no significant different between annual result of solar power generation in each case, although the two different solar irradiance data were used in this study. Energy price calculated from 10 years inverter PV system has possibility to get cheaper as compared to basic electricity price. This is because the maintenance cost due to the replacement of inverter can be reduced highly if the life time expectancy sets to 10 years. Thus, inverter life time has important role for the development of using PV system. Overall, the results of this study indicate that there is possibility for PV market to grow in Makassar although it is limited by some conditions such as inverters life time, thanks to the presence of FIT regulation.

The major limitation of this study is the lack of solar irradiance actual measurement data and PV panel price. Therefore, further studies need to be carried out in order to validate these results using the sensitivity analysis. In addition, future study investigating the effect of carbon price on the financial analysis would also be very interesting to conduct.

Sihotang, M.A. and Okajima, K. (2017) Photovoltaic Power Potential Analysis in Equator Territorial: Case Study of Makassar City, Indonesia. Journal of Power and Energy Engineering, 5, 15-29. http://dx.doi.org/10.4236/jpee.2017.51002