Solar Power Facilities Research Articles

Thermal imaging-based fault detection and energy efficiency analysis in a 1.6 MW photovoltaic system in Bağyurdu OIZ, Türkiye

The present study assesses the influence of thermal imaging defect detection on the energy efficiency of a 1.6 MW solar power facility in the Bağyurdu Organized Industrial Zone (OIZ) in İzmir, Turkey. Thermal imaging has demonstrated efficacy in detecting serious problems in photovoltaic (PV) panels, including hot spots, inoperative modules, faulty connections, and shadowing, which substantially impact system performance. A comprehensive investigation revealed that around 15% of the photovoltaic panels displayed defects, resulting in a 16% decrease in system performance and an estimated yearly energy loss of 0.35 GWh. The study emphasizes the benefits of thermal imaging compared to conventional fault detection techniques, including its capacity for swift and non-invasive identification of localized overheating, which may lead to fires, and its ability to discern fluctuations in energy output due to shading or malfunctioning modules. The results underscore the necessity for routine thermal evaluations and maintenance to guarantee photovoltaic systems’ operational efficacy and dependability. This study enhances the sparse data on large-scale photovoltaic systems in Türkiye and illustrates the effectiveness of thermal imaging as an economical and accurate diagnostic instrument. Future studies should amalgamate thermal imaging with sophisticated diagnostic techniques, like electroluminescence testing and machine learning, to augment fault detection precision and optimize photovoltaic system efficacy.

A study on Activation of Carbon Reduction through Rooftop Greening at Bus Stops

Objectives : Due to climate change, countries around the world, including Korea, are making various efforts to achieve carbon neutrality. Among the various reduction methods for achieving carbon neutrality, the utilization of green space through carbon storage and herbaceous plants, which are the only functions, is increasing. However, due to spatial limitations in everyday life, continuous target sites for green space are needed. Accordingly, this study conducted a study on carbon reduction through rooftop greening to activate covered bus stops.Methods : After analyzing the growth of herbaceous plants, a feasible target group was selected and when herbaceous plants were planted on the rooftops of covered bus stops, the carbon reduction figures and construction costs were compared with the same conditions as solar power facilities. The carbon storage amount was calculated on a nationwide basis and the carbon reduction cost per m<sup>2</sup> was analyzed in comparison with the carbon reduction according to solar power facilities.Results and Discussion : The research results showed that the reduction cost of herbaceous plants per m<sup>2</sup> was 53 KRW, and the carbon reduction cost due to solar power installation was about 116 KRW. It was confirmed that herbaceous plants were about twice as cheap as carbon reduction through solar power generation. In addition, the environmental and economic benefits of herbaceous plants were also confirmed to have additional benefits among local communities or surrounding area.Conclusion : Starting with this study, it is expected that it can be used as basic data to realize green space more efficiently in environmental and landscape aspects by increasing the planting ratio of herbaceous plants in order to increase the amount of CO<sub>2</sub> stored (absorbed) in daily life.

Renewable Solar Energy Facilities in South America—The Road to a Low-Carbon Sustainable Energy Matrix: A Systematic Review

South America is a place on the planet that stands out with enormous potential linked to renewable energies. Countries in this region have developed private investment projects to carry out an energy transition from fossil energies to clean energies and contribute to climate change mitigation. The sun resource is one of the more abundant sources of renewable energies that stands out in South America, especially in the Atacama Desert. In this context, South American countries are developing sustainable actions/strategies linked to implementing solar photovoltaic (PV) and concentrated solar power (CSP) facilities and achieving carbon neutrality for the year 2050. As a result, this systematic review presents the progress, new trends, and the road to a sustainable paradigm with disruptive innovations like artificial intelligence, robots, and unmanned aerial vehicles (UAVs) for solar energy facilities in the region. According to the findings, solar energy infrastructure was applied in South America during the global climate change crisis era. Different levels of implementation in solar photovoltaic (PV) facilities have been reached in each country, with the region being a worldwide research and development (R&D) hotspot. Also, high potential exists for concentrated solar power (CSP) facilities considering the technology evolution, and for the implementation of the hybridization of solar photovoltaic (PV) facilities with onshore wind farm infrastructures, decreasing the capital/operation costs of the projects. Finally, synergy between solar energy infrastructures with emerging technologies linked with low-carbon economies like battery energy storage systems (BESSs) and the use of floating solar PV plants looks like a promising sustainable solution.

Investigating and Analyzing the Influence of a Solar Power Plant’s Life Cycle on the Depletion of Natural Materials and Mineral Resources

The production process requires massive amounts of minerals, fossil fuels, and energy. The efficient use of energy and natural resources appears to be crucial to the state of affairs. It should be noted that the post-consumer management of solar power plant elements results in a certain amount of power and matter, as well as harmful effects on the natural world. The major goal of this study was to examine the environmental effect of the solar power plant throughout its life cycle, taking into consideration the depletion of natural materials and mineral resources, using the ReCiPe 2016 model. A life cycle study was performed on an actual 2 MW solar power facility located in northern Poland. This study was conducted using the ReCiPe 2016 model and the Life Cycle Assessment (LCA) methodology. The analyzed renewable energy system’s impact was assessed utilizing 22 impact categories, focusing mostly on the depletion of natural resources. A Life Cycle Assessment was conducted for two post-consumer development scenarios (landfill and recycling). This research focuses on the full solar power plant, not just the photovoltaic panels. Recycling, as a kind of post-consumer development, can provide major environmental benefits and minimize negative environmental consequences throughout the solar power plant’s life cycle. The exceedingly harmful effects can be evident in losses related to water and the aquatic environment. The obtained study findings enabled the development of sustainable-friendly recommendations towards the continuous advancement of the life cycle of solar power plants, thereby reducing the use of rare earth minerals.

Closed-Loop Pointing Feedback for Heliostats in Concentrating Solar Power

Abstract Concentrating solar power (CSP) facilities need to ensure alignment of all sun-tracking heliostats onto the sunlight receiver. A method is proposed to keep all heliostats in a CSP facility under closed-loop pointing control while also providing feedback on the detailed alignment of the segment mirrors of each heliostat. The method is based on the sunlight directed toward the receiver, and thus works under full operational conditions and without the need of secondary optical alignments. It is based on retroreflectors (“retros”) to simultaneously return samples of the sunlight reflected by each mirror back to that same mirror. It goes beyond previous efforts at using retros by placing them into the concentrated sunlight, instead of in its periphery. Quartz glass will be used for its heat tolerance, and reflectivity modulation for visibility is achieved by rotating the retros. The technology can be retrofitted into existing CSP facilities to improve operational efficiency, and it can be used to relax the stability requirements of heliostats, and thus their cost, in the planning of new ones.

A Cost-Effective Fault Diagnosis and Localization Approach for Utility-Scale PV Systems Using Limited Number of Sensors

As a result of global efforts to combat the rise in global climate change and carbon dioxide emissions, there has been a substantial increase in renewable energy investment for both residential and utility power generation. Solar power facilities are estimated to be among the major contributors to global decarbonization in terms of capacity by 2050. Consequently, the majority of economically significant countries are progressively implementing utility-scale photovoltaic (U-PV) systems. Nevertheless, a major obstacle to the expansion of U-PV generation is the identification and assessment of direct current (DC) faults in the extensive array of PV panels. In order to address this obstacle, it is imperative to provide an evaluation method that can accurately and cost-effectively identify and locate potential DC faults in PV arrays. Therefore, many studies attempted to utilize thermal cameras, voltage and current sensors, power databases, and other detecting elements; however, some of these technologies provide extra hurdles in terms of the quantity and expense of the utilized hardware equipment. This work presents a sophisticated system that aims to diagnose and locate various types of PV faults, such as line-to-ground, line-to-line, inter-string, open-circuit, and partial shading events, within a PV array strings down to a module level. This study primarily depends on three crucial indicators: precise calculation of the PV array output power and current, optimal placement of a limited number of voltage sensors, and execution of specifically specified tests. The estimation of PV array power, along with selectively placed voltage sensors, minimizes the time and equipment required for fault detection and diagnosis. The feasibility of the proposed method is investigated with real field data and the PSCAD simulation platform during all possible weather conditions and array faults. The results demonstrate that the proposed approach can accurately diagnose and localize faults with only NS/2 voltage sensors, where NS is the number of PV array parallel strings.

Analysis of Artificial Intelligence Based MPPT in PV Grid Connected System

The There has been a rise in the demand for electrical power during the past 10 years. Installing a new power generator (PG) is a costly and time-consuming procedure. For this reason, solar power plants are considered a viable alternative for meeting the current energy demand. But crucial maintenance and output power balance are the key issues facing solar power facilities. In order to reduce output power balance and maintenance problems in solar plants, an appropriate approach is required. This study offers a novel method for tracking the maximum power for hybrid photovoltaic (PV) and wind energy systems (WES): single maximum power point tracking, or MPPT. In the proposed MPPT technique, a radial basis function network (RBFN) control mechanism is based on an artificial neural network (ANN).

Reduction in Emissions by Massive Solar Plant Integration in the US Power Grid

Fossil fuels, the predominant energy source in the United States, have been identified as major contributors to environmental pollution through the release of harmful emissions. As a countermeasure, there has been an increasing focus on the exploration and development of cleaner energy alternatives to alleviate the environmental degradation caused by fossil fuels and to satisfy the growing energy needs. This study conducted scenario analyses to evaluate the impact of integrating solar energy into specific US power grids on reducing carbon emissions. The analysis encompassed electrical systems within California, New England, New York, and the Southwest, utilizing datasets from the Energy Information Administration and National Renewable Energy Laboratory. The Energy Information Administration dataset includes information on net generation according to each source and carbon emissions according to fuel type, whereas the National Renewable Energy Laboratory dataset provides hourly projections for 6000 theoretical photovoltaic installations and detailed solar energy output data every five minutes over a year. Our findings indicated a notable decrease in carbon dioxide emissions following the introduction of solar power facilities. The most significant reductions were observed in the Southwest and California, attributed to solar plant integration. Conversely, New York and New England were identified as regions requiring additional policy measures and incentives to meet the emission reduction goals.

Design optimization of Solar Power Inverter using the GRA Method

Among the most crucial components of a solar-powered system is an inverter. It is an apparatus that transforms the direct current (DC) produced by solar panels into the alternating current (AC) required by the electric system. Flashing hybrid solar inverter is the best solar inverter for home which offers the following features: - Its operating voltage is between 100-290V. - It has 700 VA of power. 5kW solar inverter price budget starts at $2,000 for excellent single-phase devices and $1,000 for existing datasets (like Sungrow) (eg Fronius or SMA). The most popular size, 5kW, can accommodate arrays up to 6.6kW in power. A solar charge controller can only function effectively during the day, because when the ultraviolet irradiance is strong and, the system's Voltage rating must reach the inverter at a moderate DC voltage level in order for it to function. Your photovoltaic systems and inverter operate at night power will be off. The inverter doesn't run overnight because it doesn't want to draw electricity. Instead, it rises again in the morning when the sun shines. Your home and solar system are connected to the utility grid. By switching to solar PV-based power generation from the airport's current conventional energy source, the carbon footprint of the facility can be decreased. Power distribution solar PV power facilities may be built in regions that are required to be broad and free of obstructions around runways. Based on first year operating data, the current study seeks to evaluate the operational efficiency of a 12 MWp solar-powered airport at Cochin Airport Limited (CIAL), India. With the aid of the most well-liked PV simulation programmes, such as Deterioration in quality and Solar Gis, the plant effectiveness is precisely rendered. The software's performance metrics were discovered to perfectly resemble the observed values. Economic and ecological studies of Kochi airports powered by solar energy attest to its efficiency in lowering carbon footprint, resulting in an airport with almost no emissions that is clean, green, and sustainable.Gray correlation analysis is widely used to measure the degree of relationship between sequences through the gray correlation coefficient. Gray relational analysis has been used by many researchers to optimize control parameters with multiple responses through gray relational grading. The fundamental tenet of the GRA approach is that the chosen option must have the "greatest degree of Green relation" to the positive-ideal solution and the "minimum of grey relation" to the negative-best answer. A technique for determining whether or not variables are connected and how much they are correlated is called grey correlation coefficient analysis. The primary method of determining these curves' geometric similarity is by the construction of characteristic series curves. Type of Solar Module, No of modules per string, No of string, No of inverters and No of transformers Short circuit current (ISC), Open circuit voltage (VOC), Operating Temperature and Dimension. Stress Management in Healthcare Institutions in Work overload is got the first rank whereas is the Overtime is having the lowest rank.

Developing a Deep Learning and Reliable Optimization Techniques for Solar Photovoltaic Power Prediction

Due to its significant solar energy generation, solar PV power facilities have recently been utilized. Although PV power stations are highly preferable, the state’s fundamental drawback is that its output current qualities are unpredictable. Consequently, to ensure a balance and complete functioning, it would be crucial to build systems that allow accurate future projections of solar PV production in the short or medium term. Research postulates a strategy for using deep learning to estimate the short-term electricity generated by solar photovoltaic facilities. This study offers a novel method for predicting photovoltaic systems output power utilizing a Hybrid Deep Neural Network framework, making significant advancements in the field of deep learning applications to transmission system prediction issues. CNN and LSTM are combined in the postulated HDNN paradigm. Traditional deep learning techniques are employed in the initial stage. The effectiveness assessments of these techniques are instead presented in greater detail after they have been trained using firefly optimization techniques. The method with the highest reliability is chosen out of all the techniques used in previous research. Deep learning and power efficiency create a combination that appears to have a successful future, predominantlyin improving sustainable management and the digitalization of the electrical sector.

Long-term power prediction of photovoltaic panels based on meteorological parameters and support vector machine

<span>Solar energy is the most generally accessible energy in the entire globe. Proper solar panel maintenance is necessary to reduce reliance on imported energy. Continuous monitoring of the solar panel's power output is required. The deployment of internet of things (IoT) monitoring of solar panels for maintenance is the basis for the current research. A multi-variable long-term photovoltaic (PV) power production prediction approach based on support vector machine (SVM) is developed in this study with the aim of completely evaluating the influence of PV panels performance and actual operational state factors on the power generation efficiency. This study examines the use of SVM and climatic factors to forecast the long-term output of power from solar panels. A solar power facility in a semi-arid area provided the data utilized in this investigation. Temperature, humidity, wind speed, and sun radiation are some of the meteorological variables that were considered in the study. To anticipate the power generation of the panels, the SVM is trained using the climatic factors and the power generation data. The findings demonstrate that the SVM model consistently predicts the panels' long-term power generation with a high degree of accuracy.</span>

Simulation of Maximum Power Point Tracking with Fuzzy Logic Control Method on Solar Panels Using MATLAB

One of the newest sources energy is the sun. To limit the usage of fossil fuels, solar power facilities that harness sunlight are beginning to be created. Currently, research on solar panels is increasingly being carried out. Because solar panels are an unlimited source of energy. And solar panels can reduce exhaust emissions from conventional vehicles by 92%. However, the performance of solar panels is strongly influenced by several factors such as sunlight intensity and ambient temperature. So that solar panels can reach the maximum power point, the Maximum power point tracking (MPPT) method is employed to maximize the performance of solar panels. In this research, an mppt system will be created using fuzzy logic control in matlab simulink. Fuzzy logic control is a method that can control the system against load changes. To analyze this fuzzy logic-based mppt system, simulations are carried out using matlab simulink. Simulink is software used to model, simulate, and analyze dynamic systems. From the simulations that have been carried out, solar panels without mppt have a duty cycle change time of 0.1 seconds while with mppt the duty cycle change is 0.7 seconds, where the duty cycle change time without mppt is faster but the operating value is unstable while power tracking with mppt the duty cycle change time is longer but the operating value is more stable.

Flash point and safety evaluation of binary mixture of diphenyl ether + biphenyl: A commonly utilized heat transfer fluid

The binary mixture of diphenyl ether and biphenyl finds wide applications in various industries. Notably, it is widely utilized in renewable energy systems such as concentrated solar power (CSP) facilities. This study addresses the lack of research on the flash point (FP) behavior of this blend, crucial due to high operating temperatures in related processes, especially when used as a heat transfer fluid. This study fills the research gap by analyzing the entire composition range, using experimental measurements, and a unique mathematical method based on SLE data; unlike the conventional method that relies on VLE data. The FP prediction results demonstrated satisfactory outcomes when compared to the experimental data. The findings of this study can be employed to mitigate the fire and explosion risks associated with processes using the binary mixture of diphenyl ether + biphenyl.

India's Odyssey to Sustainable Energy Triumph-Assessing the Impact of Access to Energy and Renewable Power in the Indian Electricity Sector

Purpose: The purpose of this paper is to comprehensively examine the challenges hindering India's sustainable energy development, focusing on access to electricity, competition within the energy market, and the pivotal role of technology transfer and energy storage in overcoming growth hurdles. Theoretical Reference: The theoretical framework revolves around the intersection of Indian legislation and energy access, emphasising the significance of competition law in fostering a fair and inclusive energy landscape. The paper also draws on the theoretical foundations of technology transfer and energy storage as catalysts for sustainable growth in the renewable energy sector. Method: The methodology involves an in-depth analysis of India's renewable energy sector, exploring the impact of monopolies, anti-competitive practices, and the rapid expansion of solar power facilities. The study considers the role of competition law, technology transfer, and energy storage as key components in navigating the challenges of sustainable energy development. Result and Conclusion: The results underscore the interconnected nature of technology, energy storage, and competition legislation in India's energy revolution. The conclusion highlights public policy imperatives, emphasising demand-side management, resolution of contractual disputes, and the imperative need for efficient and cost-effective energy storage systems. The paper concludes with a call for a policy framework encouraging private sector participation and capacity building in the power sector. Implication of Research: The implications of this research extend to shaping public policy imperatives in the electricity sector, emphasising the need for demand-side management, resolution of disputes, and a policy framework to promote private sector participation. The research highlights the significance of these imperatives in developing efficient and cost-effective energy storage systems and achieving 'Round the Clock' renewable power. Originality/Value: The originality and value of this research lie in its comprehensive examination of the interconnected challenges and solutions in India's renewable energy sector. The findings contribute to the discourse on public policy imperatives, technology transfer, and competition law, offering insights that can guide policymakers, regulators, and businesses in fostering a competitive, sustainable, and resilient energy system. The study provides valuable guidance for maximising the benefits of renewable energy, ultimately contributing to increased energy access, sustainability, and economic growth in India.

Estimation of hourly solar irradiation on tilted surfaces

Tilted photovoltaic panel (PVP) are extensively utilized in solar power installations. To model and design them, you must understand the solar irradiation on a tilted surface over time scales of an hour, day, week, month, or other period. However, most meteorological stations only record global horizontal irradiance (GHI). In this research, a method is proposed for translating hourly worldwide horizontal irradiation from the NASA POWER database into hourly global sun irradiation on a tilted surface utilizing regression analysis methods and numerical modeling methods based on an isotropic model of solar irradiation. In addition, this work proposes a method for establishing the regression reliance of the diffuse transmittance index on the clearness index for geographic areas where this relationship has not yet been empirically proven. To assess effectiveness, the results of the proposed technique and other authors' methods are compared with monthly average NASA POWER climatological data using evaluation methods such as mean bias error (MBE), mean absolute bias error (MABE), and root-mean-square error (RMSE). The study's findings can be used to construct, optimize, or anticipate the functioning of solar power facilities at any angle of tilt and in any geographic area.

Identifying fouling mechanism in a novel hybrid cooling tower's bundles: Application in concentrated solar power (CSP) plant

In this paper, structural, chemical, and thermos-physical characteristics of fouling and tube materials for hybrid cooling tower bundles in Concentrated Solar Power (CSP) facilities are addressed. Toward an in-depth understanding and a comparison of the fouling mechanism on galvanized steel and polymer tubes, results obtained from the characterization studies and the experimental test correlations were used to calculate the sticking probability (P) and deposit bond strength (ξ) based on the Kern-Seaton model. According to the data, the polymer tube had three times higher the adhering probability of the galvanized steel tube with a value of PPf = 3.15*102 Ns/m2, whereas the deposit bond strength was two times lower with a value of ξPf = 3.49*10−8. The results revealed that when it comes to polymer tubes, the ones with a finer surface structure tend to attract foulants from deluge water more readily. However, once foulants are attached to the heat transfer surface, it's simpler to be removed. The substantial increase in kaolinite and gypsum phases can explain this occurrence. On the other hand, galvanized tubes, exhibit the opposite behavior. It is anticipated that this constructive study will shed light on performance-enhancing fouling mechanisms and offer a scientific basis for thermal engineers.

Beyond the merit order effect: Impact of the rapid expansion of renewable energy on electricity market price

A drop in the average electricity market price owing to renewable energy with low marginal costs has been identified and explored as merit order effect. However, diffusion of variable renewable energy leads to concerns about the need for flexibility, decline of supply capacity, and volatility increase of electricity prices. For both decarbonization and stable electricity systems, understanding the drivers of market price is critical, but it is challenging because electricity markets are non-linear and affected by multiple factors. Hence, this research proposes a model based on machine learning techniques and explainable artificial intelligence (XAI) and estimates the multi-directional impact of renewable energy on the Japanese electricity market. The results reveal that the contribution of demand to market price is the largest, followed by solar generation and operable power facility capacity. This research identifies a large decline in the price triggered by solar power during the daytime; however, the effect of solar power varies by the time of day, season, and demand. Additionally, the results suggest that the market price increases when demand is high and solar generation is low, such as during summer evenings. Using XAI, this study quantitatively and visually demonstrated that interactions between solar power, demand, and operable power facility capacity are the key factors behind the high market volatility and price surge. It is important to manage the pace of plant installation and energy transition. Our study provides insights into how and when the market price changes with variable renewable energy and other policy-making factors.

Effects of solar energy development on ants in the Mojave Desert

AbstractLand‐use change from solar energy development may affect desert ecosystems and the soils, plants, and animals therein, yet our understanding of these interactions is nascent. With their ubiquity, criticality as ecosystem constituents, and sensitivity to environmental variation, ants may be useful study organisms for elucidating ecological effects of solar energy development in deserts. Our objectives were to disentangle the response of a desert ant community to solar energy development decisions and test the efficacy of ants as bioindicators at a solar power facility (392 MW) in the Mojave Desert, USA. We used pitfall traps to collect ants in treatments representing different solar energy development decisions, including variably intense site preparation practices: blading (i.e., bulldozing) and mowing, and establishment of undeveloped patches in solar fields, replicated across three power blocks comprising the facility and in undeveloped control sites surrounding the facility. We determined that ant abundance, species richness, Shannon Diversity Index, and functional richness were lower in bladed treatments than in all other treatments and controls. For most taxonomic and functional ant responses, we detected no difference between nonbladed treatments and controls; these results suggest that less intensive site preparation and increased spatial heterogeneity (i.e., undeveloped patches in solar fields) can reduce the negative effects of solar energy development on desert ants. However, our results indicate that ants may serve as useful bioindicators of the severity of anthropogenic disturbance from solar energy development in deserts, and indicator analysis signifies that solar energy infrastructure may negatively affect some species with high ecological value (e.g., harvester ants). Negative effects of solar energy development on ants can have significant implications for desert ecosystem function and integrity, but conservation‐minded solar facility design and construction may lead to avoidance of “bottom‐up” ecological ramifications of increased solar production during the renewable energy transition.

Coupled abrasion Erosion-Oxidation wear from particles in Concentrating solar thermal power facilities

Solid particles represent an attractive heat transfer and energy storage media for next generation solar thermal power facilities for their ability to operate at high temperatures without concerns for freezing or corrosion. A potential outstanding issue that still remains for particles as heat transfer media is the wear on components operating with particles flowing (sliding) in, along, or over them. Prior work has shown that even at the low velocities (∼1 cm/s to ∼ 1 m/s) expected in solar thermal facilities, material wear will still occur, and the lifetime and performance of components undergoing wear needs to be well understood. Abrasion erosion occurs when particles come into contact with containment materials at extremely shallow angles, and is likely to be seen in heat exchangers, storage bins, and flow control mechanisms. Additionally, because of the open nature of most of these systems to air, oxidation of metals is also of concern. Here, we show how critical the coupled erosion-oxidation mechanism is to understanding particle/material durability and therefore need for greater in-depth analysis. Abrasive wear experiments are conducted on metals such as SS316 (L and H grades), Inconel 740H, Haynes 230 with different particles (HSP 40/70, Wedload 430, and CarboMax HD) for different operating conditions. Results clearly indicate that oxide spallation and removal is critical to the overall wear seen at high temperatures.

A feasibility assessment of utilizing concentrated solar power (CSP) in the Zimbabwean regions of Hwange and Lupane

The current study assesses the feasibility of Zimbabwe's Hwange and Lupane regions to host a large-scale Concentrated Solar Power (CSP) facility. The study’s overarching goal is to aid in identifying, classifying, and validating suitable sites for hosting a CSP facility. In this paper, suitable sites are identified and classified by coupling the multi-criteria decision-making (MCDM) technique (specifically the analytical hierarchy process, abbreviated AHP) and geographic information system (GIS) software. Following the identification of suitable regions, the validation is carried out by technical and economic measures. As a specific criterion for decision-making, a geographic database was developed utilizing layers provided by various data sets on irradiance, orography, location, and water resources. The final maps using special tools in ArcGIS Pro revealed that the land available for concentrating solar power in Hwange and Lupane is 1792 km2 (5.6% of the study area) and 3771 km2 (11.9% of the study area), respectively. A Monte Carlo Simulation (MCS) of the theoretical power potential revealed that suitable sites in Hwange and Lupane could technically generate power ranging from 380.0 TWh/year to 477.5 TWh/year and 878.8 TWh/year to 1125.0 TWh/year, respectively. The CSP facility without a thermal energy storage (TES) facility has a $ cost per kWh of 0.1879, while the CSP-TES hybrid costs 0.1468. The LCOE for CSP without TES and CSP with TES is $ 0.0679 and $ 0.0268 higher than Zimbabwe’s electricity cost, respectively. Overall, results suggest that Lupane is an excellent location for CSP facilities and supports policymakers in establishing renewable energy tariffs, resulting in economic and sustainable development.