Introduction
Power access is at the forefront of governments’ preoccupations, particularly in nations in which electricity is essential for certain basic activities such as lighting, refrigeration and running of household appliances (Kanase-Patil et al.
2010). The vast majority of rustic communities in developing countries like Peru are not entirely connected to electrical grid due to geographical obstacles and small population, which make the required investments for grid extension unjustifiable. Energy production from available and sustainable sources such as wind and sun has been considered as a viable and environmentally friendly alternative (Mamaghani et al.
2016b). Due to the ever-increasing price of petroleum derivatives on a global scale and concerns regarding the emission of greenhouse gases (GHG) (Najafi et al.
2015), remarkable attention has been directed toward green renewable technologies for catering growing energy demand (Mamaghani et al.
2017).
Renewable energy sources (RES) are abundant in most parts of the world, and, unlike fossil fuels, can be harnessed without any cost for the resource. In this regard, many governments have already started to finance renewable technologies by means of direct grants, loans and tax incentives (Liu et al.
2012). Electricity generation in Peru through hydro, wind, solar, geothermal, biomass, tidal power or other RES is subjected to an annual maximum 20% depreciation regime for income tax purposes (Irena
2014).
Despite the aforementioned upsides of RES, there are a number of technical difficulties which must be resolved to make renewable energy systems reliable and self-sufficient. The most important issue with the electricity generation by RES is the lack of stability which stems from their intermittent nature. Such nature is due to the variations in the atmospheric conditions which can result in substantial fluctuations in power generation seasonally or even daily (Bekele and Boneya
2012). To provide a stable supply of electrical power, the application of power storage systems such as batteries (Fragaki and Markvart
2008) or combining RES with non-renewable technologies such as diesel, natural gas or biomass driven generators (Montuori et al.
2014) have been proposed in the previous studies. Hybrid energy systems, which usually comprise of at least two power sources, have been utilized to reach higher electrical efficiency and more uniform power supply. Another shortcoming of RES is the significantly higher capital cost of such systems, compared to the conventional diesel generators. Nevertheless, with respect to stand-alone diesel generators, hybrid systems require less fossil fuel (Kalantar and Mousavi
2010) (i.e., reducing operational cost), reduce carbon footprints (Bentouba and Bourouis
2016), while enhancing quality of service (Valente and De almeida
1998). For some configurations of RES projects including the wind turbine-based units, the cost of energy (COE) and net present cost (NPC) can be notably decreased by expanding the capacity of the installed power system and addressing a higher electrical load (Diab et al.
2016). Since several factors [such as different possible combinations of RES and non-RES sources, the demand profile, seasonal availability of RES, capital cost of components, and the fuel cost (Aminyavari et al.
2016)] must be considered while attempting to determine optimal configuration of hybrid energy systems, optimization tools should be utilized in order to obtain a comprehensive evaluation of different scenarios (Gu et al.
2017). Genetic algorithm (Najafi et al.
2011), cuckoo search algorithm (Ray et al.
2018), modified electric system analysis (Zahboune et al.
2016), and game theory (Khare et al.
2016) are some of the frequently utilized techniques that are employed for optimizing the sizing of components (Rajkumar et al.
2011) aiming at minimizing the cost (Yousefi et al.
2017) of these systems. Arceo et al. (
2018) demonstrated that, by utilizing the optimal configuration of a hybrid electrification system in remote areas of Western Australia, the overall environmental impact is reduced by 16%, although it leads to increasing the total life cycle costs by 4%. Roy and Kulkarni (
2016) determined the optimal configuration of a PV–diesel generator hybrid system for rural areas in India, using which 70% of the energy demand is met by the diesel generator and 30% is addressed by the PV panels. Flores et al. (
2016) optimized (through minimizing the COE) the configurations of hybrid wind, PV, and biomass-based generation for rural electrification in Honduras. Hrayshat (
2009) showed that utilizing the optimal configuration of hybrid wind–diesel generation units in remote Jordanian settlements leads to an annual reduction of 21.3% in the diesel consumption.
Several works have utilized hybrid optimization model for electric renewables (HOMER) software to perform techno-economic feasibility study, sensitivity analysis, and optimization (Singh and Baredar
2016) on hybrid microgrids (Dekker et al.
2012). The optimal configuration of PV and battery system, which was obtained using HOMER in a study conducted by Alsharif (
2017), was demonstrated to be an energy efficient and cost-effective alternative for supplying heterogeneous cellular networks. In another study conducted using HOMER, Brandoni and Bošnjakovic (
2017) demonstrated that using the obtained optimal configuration of a hybrid system (constituting of PVs, wind turbines and internal combustion engines) 33–55% of the energy demand of a wastewater facility located in Sub-Saharan Africa can be addressed, while the COE is lower than the local cost of electricity. Marneni et al. (
2015) instead used HOMER to find the optimal sizing of solar photovoltaic generation to enhance the voltage profile of a rural feeder (3.06 MW peak load) in Mysuru, India.
It is generally accepted that answering the electrical demand by hybrid systems (i.e., more than one RES or non-RES) is more logical than only depending on RES. This stems from the fact that naturally reliance on a single RES necessitates over-sizing the system to be able to cater the demand considering the variations in solar irradiation/wind speed throughout the day or seasonally. Many studies have been dedicated to performance evaluation and feasibility analysis of hybrid systems such as PV–wind units (Arribas et al.
2010), wind–diesel–battery, and wind–fuel cell systems (Khan and Iqbal
2005). Shaahid and Elhadidy (
2007) performed a techno-economic feasibility analysis on a hybrid PV–diesel–battery system. In a similar study conducted for the case study of Ireland, it was found that, owing to the climatic characteristics of the area, wind is the dominant component of the majority of optimal hybrid power systems (Goodbody
2013). In a study comparing PV–diesel and PV–battery systems, it was concluded that the former is by far more cost-effective for loads higher than 13 kWh/day while the latter is more economical for 3–13 kWh/day range (Lilienthal
2015). PV–wind–diesel–battery hybrid system was observed to be the most practical option (Bekele and Palm
2010) to supply a community model living in an Ethiopian remote area.
Regarding the environmental impacts of hybrid systems, Hafez and Bhattacharya (
2012) assessed the emissions of a microgrid arrangement including diesel, wind, PV, battery, and hydro and the CO
2 emission were estimated to be 1078.4 t/year. A study conducted by Ajlan et al. (
2017) revealed that the PV–wind and PV–wind–diesel can reduce the CO
2 emission by 100% and 70% and the COE by 30% and 45% with respect to the diesel generators. In another study (Shezan et al.
2015), it was shown that the optimal configuration of wind–DG–battery systems results in a renewable fraction (RF) of 0.0914. In another conducted by Hossain et al. (
2017), which was focused on electrification for tourist resorts in Malaysia, it was concluded that the obtained optimal configuration of wind–diesel–battery hybrid system results in a lower COE (0.279 vs 0.343 USD/kWh) and CO
2 emission (2,571,131 kg/year vs 5,432,244 kg/year) compared to the diesel-only system; which make it a promising alternative for reducing the carbon emission intensity (Hossain et al.
2015) in these areas. Rajbongshi et al. (
2017) showed that the COE for a grid-connected hybrid system is lower than an off-grid one for similar load profiles due to the fact that grid-tied systems allow export of excess electricity into the grid rather than storing it with battery. Regarding the impact of projected variations in influential parameters, Dorji et al. (
2012) stated that 20% drop in the price of PV led to 4.9–8% decrease in NPC.
Despite the promising potentials of RES for power production in Peru and existence of abundant resources, feasibility studies to explore green and cost-effective technologies such as PV or wind are scarce. To the best of our knowledge, there is no thorough study on techno-economic analysis of hybrid systems (PV–Wind–Diesel) in Peru. The present work aims at finding the optimal combination of available RES to satisfy the energy demand of three off-grid villages in Peru. These territories have been selected according to geographical and population consultation centre of Peru (INEI
2012). INEI (
2012) provides statistical data such as population, access to power network, and distance from large urban areas. Meteorological data of solar irradiation and wind speed were borrowed from NASA atmospheric science data center using the location of each community (NASA
2017). Solar irradiation, wind speed, and electricity demand of each community are provided as inputs to HOMER software to conduct the techno-economic analysis. Seven different possible scenarios including single component systems (diesel, solar, or wind) and hybrid ones (Solar–Wind, Solar–Diesel, Wind–Diesel, or Solar–Wind–Diesel) are considered. Each of these scenarios is modeled in HOMER software and, considering the NPC as the economic main index, their corresponding optimal sizing is determined. The obtained configuration is next evaluated based on various economic and environmental criteria including the initial capital cost, operating cost, COE, RF and pollutants emission rates. Since HOMER is utilized in this study, it incorporates all of the limitations of the corresponding models; however, it has extensively been recognized as a promising tool in the literature to achieve the defined aims of the present study.
Conclusions
Techno-economic performance of stand-alone electricity generation systems for off-grid communities located in different climatic areas of Peru was investigated. Seven scenarios, including different combinations of diesel generators, wind turbine units, and solar panels, were assessed. Optimal sizing of each configuration, which minimizes the corresponding NPC, was determined and the achieved optimal systems were also evaluated considering other economic indices and their environmental performance. The analysis demonstrated that, for all of the investigated communities, the hybrid solar–wind–diesel system is the most economically viable configuration. For the case of Campo serio, although the initial capital cost of the diesel-only configuration is almost one-ninth of that of the mentioned hybrid system, the latter results in the lowest NPC in a long-term analysis. For the case of Campo serio, the optimal configuration requires an initial capital of USD 116,092, and corresponds to an operating cost of 6359 USD/y, a total NPC of USD 227,335 and a COE of 0.4738 USD/kWh.
The optimal hybrid configuration for Campo serio resulted in renewable fraction of 94% leading to 4578 kg/y of CO2 emissions which is 6.1% of the emissions of the diesel-only configuration (23,858 kg/y of CO2 emissions). The latter ratio is determined to be 2.7% for the case of El potrero and 9.9% for Silicucho. The variance in the obtained ratios is due to differences in the availability of renewable sources and the load characteristics of the considered areas.
The Peruvian authority can play a notable role in facilitating the utilization of such technologies in the rural areas. A depreciation regime for the income tax is the only support which is presently provided to the RES-based electricity generation plant in Peru. In case adequate incentive policies would be provided, the COE of the proposed system will be notably reduced which will aid the mentioned communities to install the proposed systems.
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