Review of Techno-Economic Analysis Studies Using HOMER Pro Software ^†

Abstract

With decreases in cost accompanying advances in technology, renewable energy is becoming increasingly viable. Much software is available for the techno-economic analysis of energy systems, and HOMER Pro software is frequently applied for micro-grid and industrial analysis. Around the globe, techno-economic analyses of a variety of renewable energy systems have been undertaken using HOMER Pro Version 3.16.0. This study reviews the primary techno-economic findings of past research to investigate recent trends. Based on high-level trendline analysis, it appears that the costs of renewable energy systems have decreased in academic HOMER Pro-based literature. Of the articles analyzed, the LCOEs for 100% renewable energy systems have decreased from $0.91/kWh to $0.70/kWh, while the LCOEs for 0% renewable energy systems have increased from $0.74/kWh to $0.78/kWh.

1. Introduction

Increasingly, people are becoming more supportive of many renewable energy (RE) technologies, due to pessimism about the future of the fossil fuel industry and concerns about climate change [1]. In addition, RE alternatives are becoming increasingly attractive options due to profound economic disruption. For decades, RE was cost-prohibitive, which barred its meaningful inclusion. More recently, the costs of RE have dropped considerably [2] and its widespread incorporation into energy systems is underway. Alongside these various disruptions, RE research has experienced a major spike in interest, sparking an exponential increase in the number of associated articles. Previous research has identified the benefits of RE in emission reductions, and also the technical challenges of its incorporation. An energy transition to RE will affect the functioning of society altogether. The technical, economic, social, and political challenges are numerous and complex. The focus of the literature is widespread and interdisciplinary, encompassing technical, economic, social and political research. The key sub-topics of literary focus include the following:

• The technical feasibility of RE systems:

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  This comprises a large portion of the literature group. This literature tends to rely on applied science in evaluating the technological capabilities and environmental benefits of RE.

• The economic viability and impact of RE systems:

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  This literature group focuses on comparing the costs of RE systems with conventional means of power generation. This literature can also consider macro-economic impacts, econometric analysis, life cycle assessments, and energy market analysis.

• Socio-political and institutional dimensions:

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  This group focuses on governance structures and citizen participation in an energy transition. The literature can be focused on various levels of society and government.

Given the breadth of research areas, there are few standardized methodologies for energy system research. Often, the research includes some system modelling of techno-economic performance. Less commonly, evaluation incorporates political, social, or environmental impacts. Some contemporary techno-economic literature findings include the following:

• The main goal of energy transition is curtailing carbon emissions.
• Electricity is the preferred energy carrier for decarbonized systems.
• Wind, solar, and batteries are the foundation of low-carbon energy systems.
• Energy efficiency and management are critical for RE-integration.
• Energy models are used to simulate energy transition strategies and explore various scenarios.

Academic literature has revealed a considerable number of software available for energy system research. Most energy system models can be classified according to their purpose and approach. The three most common approaches to energy system modelling include: optimization (the use of linear programming to either maximize or minimize a feature; to some extent, the realized system design is endogenous to the modeller); simulation (a computer simulates operation of an energy system in time steps. These are often bottom-up models testing the impacts of different scenarios, and the realized system design is exogenous to the modeller input definition); and equilibrium (a larger econometric model of society which considers the dynamics of supply, demand, and prices in an economy where several markets interact). Though many energy system software exist, the selection of them is task-specific; some software are especially useful for analyzing industrial applications, while others can model national energy grids [3].

The majority of scientific papers that focus on techno-economic factors utilize HOMER for RE system simulation and optimization [4]. HOMER was originally developed by the National Renewable Energy Laboratory (NREL), but is now enhanced and distributed by UL Solutions. HOMER is especially effective for small-scale microgrid systems and industrial applications. In HOMER, the user inputs microgrid components, electrical loads, the existing energy grid, and resource availability. Following user input, HOMER simulates different configurations and combinations of components to generate optimized results and evaluate the feasibility and technical merits of alternatives. HOMER has shown the capacity to recreate economic evaluation found in other studies [5] and has been technically scrutinized by many algorithms [6].

Working effectively with HOMER requires an understanding of its three core capabilities: simulation, optimization, and sensitivity analysis [7]. Simulation is HOMER’s attempt to simulate a viable system for all possible combinations of the equipment under consideration, optimization follows all simulations where the various systems are sorted and filtered according to modeller-defined criteria, and sensitivity is a step that allows the user to impose variability onto certain parameters that are beyond modeller control (for instance, average annual wind speed or fuel costs).

Contributions and Study Objectives

The exponential increase in RE research makes literature reviews both necessary and simultaneously complex. By the time any lengthy literature review is completed, enough additional research may have been produced to make any previous findings outdated. As such, any literature reviews in the RE field need to be targeted, specific, and systematic. This review only focuses on recent techno-economic research, using a highly utilized software, HOMER. Furthermore, this review undertakes a high-level trend line analysis of techno-economic findings. Since social and political research is complex and subjected to unique, different approaches across the globe (and is often non-quantifiable), it has been excluded.

2. Materials and Methods

Increasingly, literature is reviewed systematically. A systematic review is a methodological tool that employs clearly formulated questions and explicit methods of locating and analyzing literature. The systematic process was chosen for its effective and efficient research capabilities, but also for its ability to filter out irrelevant materials.

A systematic review also minimizes reporting bias by explicitly stating the objectives and search criteria. Effectively, this enables generalizability, consistency, reproducibility, precision, and verification in research. A systematic review is critical for RE since it includes an exceptional breadth of research, ranging from the academic arts, social sciences, and applied science. The key steps of this systematic review include the following:

• Step one (planning):

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  The first step focuses on developing questions to guide the literature review. The main research questions include: What are the recent RE techno-economic levelized cost of electricity (LCOE) findings using HOMER Pro for micro-grids and industrial applications? Across all projects, how have these LCOE findings progressively changed since 2007? And, within each independent project, how have the relative costs of 0% and 100% RE systems changed?

• Step two (search and primary article screening):

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  The primary databases relied upon were ScienceDirect and IEEE Access to target high impact journals, as well as the University of Regina Quick Find Library for a breadth of coverage. A literature matrix was then developed in Microsoft Excel to maintain a catalogue of the literature review. The matrix included: authorship; year of publication; type of project; and key LCOE findings. Zotero was used for reference management.

• Step three (title, publication date, and abstract secondary article screening):

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  Due to the enormous size of preliminary literature results, it is inefficient to read every article. A secondary screening was conducted by progressively reviewing the title, publication date, and abstract as a coarse filter for articles of minimal relevancy.

• Step four (introduction, conclusion and tertiary article screening):

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  Any of the remaining articles underwent a tertiary screening by progressively reviewing the introduction and conclusions to filter articles of lesser relevancy.

• Step five (evaluation):

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  This step includes a full reading of the remaining articles. Each article was scrutinized for coherent writing, sound methodologies and clearly explained results.

• Step six (extraction and writing):

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  The Excel-based literature matrix was completed to answer the research questions. Since the literature search spanned 2007–2023, all LCOE findings were cost-adjusted to 2023 USD. Their adjustment relied upon the Industrial Product Price Index. Data were reviewed, synthesized, and reported on.

3. Results

Following the search and screening process, a total of 45 peer-reviewed HOMER-based articles were reviewed [8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52]. The articles were restricted to the publication years 2007–2023 and focussed on micro-grid analysis. The geographical coverage was widespread (see

Table 1. HOMER-based articles used in current study.

Country	Articles
Nigeria	[8,22,25,35,51]
India	[9,15,27,46,49]
Canada	[10,41,48]
Bangladesh	[11,34]
Turkey	[12,13,17,37,38,44,45]
Iraq	[14]
Algeria	[16,36]
Iran	[18,20,21,24,26,33,40]
Indonesia	[19]
Malaysia	[23,31,39]
Oman	[28,29]
Pakistan	[47]
Ivory Coast	[30]
Benin	[32]
Colombia	[50]
Saudi Arabia	[42,43]
Ethiopia	[52]

).

Since there were no explicit restrictions on geographical location or project type, the LCOE results varied considerably. The energization of some projects were low-cost, while others were prohibitively expensive (see Figure 1). Typically, studies included some combination of 0% RE, 100% RE, and optimized systems.

The LCOE data has also been organized by date of publication (see Figure 2). By organizing the results chronologically, there appears to be a pattern of cost reductions for both 100% RE and optimized systems, while the costs for 0% RE systems appear to be trending upwards. Further to this, the average cost trendline of optimized systems appears to be consistently lower than in both alternatives, and it appears that a synergistic benefit in optimization remains.

4. Discussion

Though some value in the simple comparison or temporal organization of past literature may exist, this may oversimplify the complexities associated with differences in geography, publication date and project type. For instance, if we consider the comparison between an article comparing a solar project in Nigeria to a wind project in Canada, this is further complicated by the fact that one article was written in 2008, and the other in 2023. Though it is difficult to entirely remove potential sources of research bias, this study cleaned the data to consider the difference in relative cost between 100% RE and 0% RE systems, and the difference in relative cost between optimized and 0% RE systems (see Figure 3). By only considering the relative costs of systems while holding the project constant, some of the biases associated with inter-project differences are reduced. According to the trend lines, the relative cost of 100% RE and optimized systems is increasingly favorable compared to 0% RE systems.

Though this analysis offers insight into the most recent RE research using HOMER, it does not provide any detailed statistical analysis; rather, it should only be considered a high-level overview of recent trends. Within the 45 articles analysed, there are many differences among project types and geographic locations, and these nuances remain largely unconsidered. For instance, we should consider the significant limitations of comparing [14], which was undertaken in 2010 and investigated energization options for a health clinic in Iraq, with [11], which investigated rural hybrid irrigation energy systems in Bangladesh in 2018. It is emphasized that this analysis simply regresses LCOE into the date of publication to offer a high-level correlation; therefore, no causation can be concluded from this work.

While it would be unrealistic to review every single recent peer-reviewed RE article, this review only considered a sample size of 45 HOMER peer-reviewed articles out of thousands. Beyond HOMER, there are many additional peer-reviewed energy system publications. Though it would be expected that a more expansive review would identify similar trends, this research does not suggest that the 45-article sample is highly representative of all the literature.

Though trendlines appear favorable for energy systems that include RE, there remain many circumstances where RE systems continue to be prohibitively expensive and the relative benefit remains project- and location-specific.

5. Conclusions

To analyze the costing trends of energy systems, this research has reviewed 45 HOMER-based peer-reviewed articles published since 2007. It has been found that the costs of both 100% RE and optimized energy systems have trended downwards over the past decade, particularly in comparison to 0% RE systems. The articles have been split into two temporal groups and the LCOE averages have been tabulated (see

Table 2. Time-based LCOE averages.

	Articles	100% RE	0% RE	Optimized
Average LCOE 2007–2015 (2023 $/kWh)	[14,19,21,23,37,39,40,41,42,43,44,45,52]	0.91	0.74	0.50
Average LCOE 2016–2023 (2023 $/kWh)	[8,9,10,11,12,13,15,16,17,18,20,22,24,25,26,27,28,29,30,31,32,33,34,35,36,38,46,47,48,49,50,51]	0.70	0.78	0.42

). The research has been constrained to a simple regression of costs based on publication date, and while some high-level correlation has been identified, no detailed causation has been investigated.

Future research should evaluate the primary recent techno-economic findings for other popular software, especially for software used for analyzing larger-scale energy systems.