Feasibility study of hybrid wind-solar stand-alone energy systems using HOMER software

Previous research

Due to Uzbekistan’s diverse geographic and climatic conditions (most of its northwestern part is occupied by the Kyzyl-Kum Desert, while the east is made up of the feitile Fergana Valley), the population is unevenly distributed among the country’s viloyats (regions). Geographic isolation makes some small settlements in remote areas prone to electricity supply disruption, sometimes caused by outdated infrastructure and high transmission losses (some of the transmission lines can be 40-50 years old and have not been properly maintained), which can cause system failures during peaks in power demand. In such situations, diesel generators became an alternative to grid sources of electricity generation.

Due to these problems, a number of pilot small-scale stand-alone renewable energy systems have been installed across hard-to-reach regions in Uzbekistan through initiatives and support from international organizations, local NGOs, and other sources of external funding.1 More recently, privately financed renewable energy system installations have slowly started to emerge, with the aim of supplying electricity to individual households.

Some experts claim that many of these projects have been successful.' However, there is a lack of data on their actual outcomes, and thus far, no comprehensive technical and economic analysis has looked at the optimization of renewable energy systems (with the ultimate aim of minimizing the cost of the electricity provided by them). Previous studies have mainly made preliminary technical and resource potential assessments, as described in the following. For instance, Zakliidov et al. (1995) attempted to model wind patterns to predict the output of wind turbines to define the best turbine sizes for different regions of Uzbekistan. Zakliidov et al. (2000) criticized the methodology used by Wijk et al. (1994), Gartsman et al. (1994), and in the “Recommendation on Defining Climatic Characteristics of Wind Power Resources” (1989) for the assessment of potential wind power, as they used annual average wind speed or the specific power of wind flows (which is problematic in the case of Uzbekistan due to its diverse terrain and variability of wind patterns). Zakliidov et al. (2000) also note issues related to the density and distribution of weather stations, which are missing in many parts of the country, and estimate that Uzbekistan has substantial wind power potential, which could produce 330 GWh per year. Essentially, due to climate differences and variations in geographical terrain, wind patterns in the country vary significantly - both in magnitude and direction - throughout the year, season, month, day, and hour. Thus, Tadjiev et al. (2015) attempted to identify the teclmical and economic parameters that would govern wind turbine deployment in different regions in Uzbekistan using NASA data for wind speeds at a 50-m height. However, satellite data on wind speed might not necessarily be as accurate as actual ground measurements.

Veiy limited research has used real meteorological data to study hybrid stand-alone energy systems and then performance in remote regions of Uzbekistan. For instance, Abdullaev and Isaev (2005) discussed the electricity output of wind turbines and PV panels under real conditions in the Charvaq region. Later, Zakliidov et al. (2015) emphasized the fact that a significant part of Uzbekistan is characterized by its many unevenly distributed villages and small settlements, which use little electricity. In such a situation, the power supply to such remote areas could be improved through the use of distributed power generation. They conclude that the modernization and extension of the grid would be expensive and economically unviable due to shortages of generation capacity in some regions. These authors also conclude that the use of distributed power generation sources (namely, renewables such as wind and solar power) is a promising way to improve the energy supply in remote regions. However, none of these studies have attempted to analyze the actual cost viability and performance of these systems using real atmospheric data. Conducting such studies with real meteorological data is of crucial importance if the installed systems are to be successful, as for renewable systems to succeed, they must be both teclmical and economically viable.

To address this important gap in the literature, this study uses data from Uzbekistan’s meteorological agency and analyses it through HOMER software to determine the most desirable strategy to ensure a sustainable energy supply to remote villages. In doing so, this chapter addresses the following questions: to what extent are wind and solar energy systems feasible in countries that are well endowed with fossil fuels? What are the aspects in which they can represent an alternative to existing diesel-run systems? What are the factors that may have an impact on this process?

By answering these questions, the present study contributes to research on developing countries that are undergoing a transition from government- led economic models to the postsocialist model of economic governance. Moreover, by nuancing the current development of renewable energy markets in such countries through an analysis of the economic viability of wind/solar energy systems in Uzbekistan, this chapter provides an outline of major problems that go beyond the issues faced by CA countries and that are often felt by many other postsocialist countries (tightly related to political, economic, and social systems). Finally, the chapter also offers insights into the particularities of transitioning from traditional energy resources to renewable energy consumption in developing countries, touching on certain important elements related to government policy.

The choice of methodological tools to answer the questions raised earlier is as follows. There are a number of widely accepted methodologies to model optimal RES systems (Erdinc and Uzunoglu, 2012). Zhou et al. (2010) attempted to analyze the algorithms hidden inside some software tools for solving multi-objective tasks and to reveal their limitations. When focusing simultaneously on several objectives, it is typical that some may conflict with others (Collette and Siany, 2004; Angelis-Dimakis et al., 2011). Multiobjective optimization attempts to simultaneously resolve various objectives: Pelet et al. (2005), Bemal-Agustin et al. (2006), Bemal-Agustin and Dufo-Lopez (2009). The HOMER software package has been used for many remote and hard-to-reach regions using control strategies based on Barley Winn (1996). The design, control, and optimization of a hybrid system is usually a very complex task, and HOMER can be used to find optimum solutions in the design of a hybrid energy system with the least LCOE and net present cost (NPC) while also considering aspects such as climate conditions, technological advancements, and other economic indicators.

Due to their intermittency, neither wind nor solar energy systems can provide a continuous power supply for stand-alone systems. Integrating several energy sources thus helps improve the efficiency and reliability of the energy supply, reducing energy storage requirements when compared to systems comprising only a single type of RES (Yang et al., 2008). Khan and Iqbal (2005), in a prefeasibility study of hybrid stand-alone energy systems, conclude that fuel cells could prove to be an important alternative for conventional batteries, potentially decreasing the capital costs of hybrid RE S in the future. Moreover, they note that instead of using single stand-alone units, larger hybrid RES systems would be more cost-competitive for remote communities due to economies of scale. Asrari et al. (2012) conducted an economic evaluation of a hybrid RES system for a remote village, critically examining whether it is cost-effective to extend the national grid to that location due to high capital costs and providing evidence that supports the development of hybrid RES systems. Other studies (Kaldellis, 2010; Ngan and Tan, 2012; Hafez and Bliattacharya, 2012; Dalton et al., 2009) have also expressed support for diversifying electricity generation in favor of renewables to lessen the reliance on the prices of fossil fuels, which are highly volatile, and reduce concerns about greenhouse gas emissions and climate change.

As stated earlier, despite the proliferation of such studies worldwide, to date, very limited work has been done for the case of Uzbekistan, and no studies have attempted to analyze the actual cost viability and performance using real atmospheric data. To address this important gap in the literamre, this study employs data gathered front Uzbekistan’s meteorological agency and utilized HOMER softwar e to determine the most desirable strategy (from a socioeconomic point of view) to ensure the sustainable energy supply of remote villages in the country. Later, other social considerations of such systems are outlined.

Outline of case study sites

To fill the missing gaps, as identified above, this study engaged in a prefeasibility study on six electricity consumer units in five different regions (viloyats) in Uzbekistan. This research is categorized as a “prefeasibility study”,3 as it uses metrics and data specific to the hypothetical projects that could be considered, even though the projects do not represent any particular villages but rather use general hypothetical villages in each of the regions considered. The first part of this study evaluated a variety of RES and diesel-hybrid energy systems, referred to later as “scenarios”, using HOMER simulation software based on the cost-effectiveness and environmental consequences of each system (in terms of GHG emissions).

The regions considered in this study all have different weather conditions and are distributed throughout the territory of Uzbekistan, enabling an identification of the areas that would be most suitable for the introduction of stand-alone RE systems. The locations of the weather stations utilized in this study are depicted on Map 5.1 and summarized in Table 5.1,

Map 5.1 Geographical locations of weather stations near case study sites Source: Created by the author using an unage fi'om Google Maps




Region (viloyat)



Population density in regional centers (hab./km2)

Electricity supply challenges






Tashkent, the capital city-7,213

While there are no major power supply issues in the central part of the city, subur ban parts of the region experience seasonal and daily outages and brownouts.




Fergana Valley (Yodiy) includes 3 regions







Andijan-688.5, Fergana - 508.9, Namangan -369.4

Due to the high concentration of population in a geographically detached part of the country (surrounded by mountains), the area is prone to seasonal and peak-hour powder outages.


37°1 l'N




Termez - 122.5

This region is located in the southern part of Uzbekistan, close to the border with Afghanistan.






Navoi - 8.6

This large territory has a sparsely distributed population and includes the Kyzyl-Kum Desert. The weather station is located 192.66 km away from major electricity-generating capacities.




The Republic of Karakalpakstan


Nukus - 11.3

This station is located in the vicinity of the regional center of Nukus.


44°5 l'N


This station is located in the most northwestern part of Uzbekistan, 341.48 km away from major electricity-generating capacities.

Source: Compiled by author and a brief description of the areas surrounding them is also provided. Note that while there are other weather stations in Uzbekistan, the stations used in this study essentially represent all stations that record both solar irradiation and wind speed data, as other stations in the country do not measure solar irradiation.

Methodology and system design

As stated earlier, this chapter utilizes HOMER to investigate the potential of hybrid RES deployment as an alternative to gr id extension or diesel- run power, or at least as a complementary source of power, in the most remote areas of Uzbekistan. The general algorithm followed when using the HOMER software is depicted in Figure 5.1. Additionally, this chapter elaborates on how changes in discount rate policy affect the economics of particular RES projects through a sensitivity case study assessment. It should be noted that the scenarios presented are deemed to be “conservative”, as the PV and wind power technologies used in the simulation employed technical and economic parameters that are less favorable than state-of-the-art

Flowchart of simulation and optimization in HOMER Source

Figure 5.1 Flowchart of simulation and optimization in HOMER Source: Created by author technologies available in other countries (the parameters utilized were obtained from local RE S installation and production companies, and if better technologies are included, the results of the present work would make renewables even more cost-effective).

Data inputs

Daily average solar irradiation, wind speed, and air temperature data were obtained from the national weather agency UzHydroMet for all the weather stations described in the previous section.

The average solar radiation data for each case study location are shown in Figure 3.2 (Chapter 3), indicating that solar radiation in some regions reaches a minimum of 1.7 kVh/m2/day in January and a maximum of 14 kWh/m2/day during the summer months.

Wind speeds and patterns vary significantly throughout the territory of Uzbekistan. Although the wind speed in most regions does not reach the lowest level indicated as feasible for wind-generated electricity, this inquiry includes wind power for the purpose of smoothing the intennittency of solar-generated electricity. The average wind speed data for each site at a 10-m elevation are shown in Figure 3.3. The lowest wind speed during the year varies for each particular region, although there is an increase during spring and winter in most areas, with the highest wind speed typically occurring in December. The windiest regions are concentrated around the Aral Sea in Karakalpakstan (northwest), the Plato Ustyurt, and Navoi and Bukhara viloyats, which include the Kyzyl-Kum Desert.

Because hourly load profiles for the selected sites were not available, HOMER was used to synthesize the load profiles by entering the average values of electricity consumption for a typical day for an average household, with an amiual peak demand in winter (during January, due to heating season) and daily peak occurring at approximately 6 p.m.4 Then, a synthetic load was created for ten average households, which together equaled the size of the proposed “case study village projects” at each of the study sites. Both day-to-day and time-step-to-time-step randomness were set at 3%, and the monthly average load profiles for the case study village for each month of the year are shown in Figure 5.2. Using these data, the daily average load profile can also be found, as shown in Figure 5.3.

System design and operation

To arrive at the optimum power mix, it is necessary to take into account a number of possible power mixes. To do so, this study considered different combinations of the five potential elements that could be used by

104 Wind-solar stand-alone energy systems

Monthly average load profiles for the case study village

Figure 5.2 Monthly average load profiles for the case study village

Daily average load profile the system

Figure 5.3 Daily average load profile the system (diesel generators, PV panels, wind turbines, power converters, and batteries). Wien detailing the different scenarios, it ensured that the maximum capacities of each type of energy source were capable of entirely supplying the “case smdy project village” with electricity (i.e., it was possible, for example, that energy demand could be folly satisfied with either solar or diesel power), although all combinations of lower capacities were computed as long as they could satisfy the overall electricity demands specified in Figures 5.2 and 5.3. The best size combinations for each region are described in the following section. For an assumed project lifetime of 25 years, the annual discount rate was taken at 9%, as officially set by the CBU up to 2017 (note that changes to this discount rate will be investigated later in this chapter).

The general flowchart of the RES system operation for the various system configuration scenarios is given in Figure 5.4.5

Flowchart of RES system operation for the various system configuration scenarios

Figure 5.4 Flowchart of RES system operation for the various system configuration scenarios

Source: Created by author

Optimization results for six selected study sites: summary

The data set described earlier, other system parameters set for this research, and economic indicators for Uzbekistan (such as discount rate and inflation rate) were fed into HOMER software. More than 1,000 solutions were simulated by the software for each case study. Then, the solutions that were categoiized as feasible, in terms of design and functioning, within established system constraints were further optimized to find the scenarios with the lowest NPC. Based on the optimization results, all feasible systems for each selected location were presented in tables with information on design, LCOE, NPC, GHG emissions, fraction of renewables, and other technical and economic parameters. Then, the systems with the lowest LCOE from each region were chosen for analysis and compared to find the most promising areas in the country to install renewable energy systems. The remainder of this section provides a summary of the optimization results for six selected study sites, while the detailed energy system scenarios in each region considered for analysis are analyzed by Djalilova and Esteban (2018).

Table 5.2 summarizes the optimization results for the best RES systems in terms of the lowest LCOE; this summary serves to compare the economic feasibility and environmental footprint of the potential types of projects that could be envisaged for different regions. The cost of employing RES systems is lower than that of using diesel generators, even in regions that are comparatively less rich in solar and wind power resources (Tamdi). The optimization results for Karakalpakiya revealed two different configurations that had an LCOE lower than any of the other five case study sites. Such an endowment in both wind and solar power clearly offers substantial flexibility for any potential project developers and investors. However, in most of the case studies, wind power in the electricity generation mix is negligible. Despite a small input of electricity from wind turbines, wind power is mostly relevant as a tool to compensate for the intermittency of solar energy delivered by the system. This situation could be changed if more advanced technologies were deployed in such hybrid RES systems in accordance with the specifics of local wind patterns.

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