Regardless of its critical role in driving socio-economic development, Malawi has yet to transition from basic energy access to productive use. Therefore, this study investigated barriers that constrain renewable energy adoption for productive use in Lilongwe, Blantyre, Mzuzu, and Mangochi. The study used a mixed approach to achieve the study objectives by using structured questionnaires, key informant interviews, focus group discussions, and literature review methods. The findings revealed that the country experiences an average global horizontal irradiance of 5.8 kWh/m 2 /day and 2138 to 3087 h of sunshine annually, hydropower potential of 1670 MW, including 22 small hydro sites with capacities of between 5 and 2, 250 kW, average wind speeds of 4 to 5 m/s, and geothermal resources (<30→70°C). Wood-based biomass is becoming scarce due to deforestation, but the cities of Lilongwe, Blantyre, Mzuzu, and Zomba generate 553 tons/day, 435 tons/day, 60 tons/day and 52.5 tons/day, respectively. Malawi's grid electricity system remains dominated by hydropower (>90%), and regardless of its vulnerability, it accounts for 80.1% of energy used for productive use, while solar and biomass account for 1.7% and 6.2%, respectively. However, some SMEs use multiple energy sources to cope with the unreliability of the energy supply. Awareness of RE resources is skewed toward solar (29%) and solar-hydro combinations (50%), with wind recognised by only 1%, and the awareness of biogas, gensets, geothermal, and battery storage was at 28.6%, 26.5%, 12.2%, and 6.1%, respectively. A review of 32 RE systems shows 74% are small (10–100 kW), only 56% are fully functional, and just 14 support energy-intensive activities. Key constraints include high energy use costs, installation costs, and unreliable supply at 18.4%, 11.7%, and 11.7%, respectively. Strengthening financing, technical capacity, system design, and policy coordination is essential to scale RE-driven PUE, improve reliability, and support SME growth and national development goals.
South Africa's electricity grid has long depended on coal for over 85% of its power, leading to severe load shedding until mid-2024 and sparking rapid growth in rooftop solar photovoltaic (PV) systems. Rooftop solar capacity jumped from around 1000 MW in 2022 to about 7300 MW by late 2025, as households and businesses sought greater energy security. This study uses System Dynamics modelling and Causal Loop Diagrams to examine the key feedback loops shaping solar PV adoption, including the historical role of power outages, the effects of weather changes, and differences in access across income groups and regions. The results reveal reinforcing cycles where power cuts strongly encouraged people to install solar, cutting grid demand and reducing carbon dioxide emissions by millions of tons each year as capacity grew. However, cloudy weather can reduce solar output, and the high cost of installation (typically R80,000 for 5 kW grid-tied system to R200,000 for 10 kW systems with storage) makes it much harder for rural households to adopt solar, with adoption rates estimated at 5–10% or lower in rural/low-income areas compared to 50–60% proxies in high-income urban areas. Ongoing revenue losses for municipalities from lower grid usage also contribute to higher electricity tariffs, which hit poorer households hardest. Even with load shedding largely suspended since mid-2024 and no recorded major incidents in 2025–2026, adoption continues due to long-term cost savings and energy independence. The study recommends stronger rural subsidies (aiming for 50% coverage), better grid upgrades to support rural areas, and improved storage options for more reliable power. These steps would help achieve the Just Energy Transition Partnership's goal of net-zero emissions by 2050 in a fair and inclusive way. Overall, this work shows how system dynamics can guide equitable renewable energy shifts in countries still heavily reliant on coal.
Hydropower is a vital renewable energy source for West Africa that addresses environmental concerns and energy security challenges. This study employed a geospatial multi-criteria decision analysis (MCDA) framework to assess hydroelectric site suitability across the West African Power Pool (WAPP). Nine biophysical parameters (drainage density, elevation, flow accumulation, geology, land cover, rainfall, slope, soil texture, and stream power index) were sourced from authoritative datasets (SRTM DEM, CHIRPS, FAO, and UNESCO/ISRIC), processed, normalized, and integrated into a Composite Appropriateness Index (CAI) within a GIS environment. The results revealed spatial variability in hydroelectric potential, with the most suitable sites characterized by moderate drainage density, low to moderate elevation (below 536 m), and dendritic flow accumulation patterns. The geology is predominantly Precambrian, with land cover dominated by bare ground and rangeland, and rainfall intensity is higher in coastal regions. Slope gradients are generally low, indicating limited potential energy head for large-scale hydropower but suitability for low-head hydropower technologies. The soil textures are mainly loamy with clay and sand components, influencing infrastructure feasibility. Validation against existing hydropower infrastructure demonstrated strong spatial correspondence, confirming the model's effectiveness for site prioritization. While this study focuses on geospatial suitability mapping, it highlights the implications for hydropower development planning in WAPP and underscores the need for future integration of dynamic hydrological and energy modeling, as well as socioeconomic and infrastructural constraints to provide a comprehensive energy potential assessment. This study offers a valuable spatial decision-support tool to guide sustainable hydropower development and regional energy planning in West Africa.
Hydropower is the leading source of renewable energy and plays a critical role in stabilizing power systems by balancing fluctuations in intermittent and inflexible energy sources. This study evaluated hydropower site suitability in the Central African Power Pool (CAPP) using datasets from CHIRPS (annual rainfall averages from 1981 to 2020), ESRI, SRTM DEM (30 arc-seconds (∼1 km) spatial resolution), FAO, and UNESCO/ISRIC to analyze slope, drainage density, flow accumulation, and related physical parameters. Data preprocessing in ArcGIS Pro ensured spatial consistency by standardizing and resampling all datasets to a uniform spatial resolution of 30 m × 30 m, normalizing, and reclassifying parameters into five suitability categories (1–5) based on predefined thresholds, such as drainage density ranges \(0.0–0.035 km/km 2 for low density), slope intervals (0°–2.14° for gentle slopes), and soil types relevant to hydropower development. The Analytical Hierarchy Process (AHP) structured hydropower suitability evaluation as a multi-criteria decision-making framework, wherein key parameters, including drainage density, slope, elevation, soil type, rainfall, and geology, were compared pairwise to determine their relative importance. Consistency checks validated the logical coherence of these comparisons. Subsequently, a weighted overlay combined these criteria spatially, producing a composite suitability map. Eligibility criteria for hydropower development were defined by reclassifying each parameter into the five suitability classes based on thresholds indicative of hydropower potential. The integrated results indicate that most of the CAPP region exhibits physical and environmental characteristics favorable for hydropower development. Low drainage density and gentle slopes coincide with loamy soils and tree cover, supporting hydropower viability. Elevation profiles and dendritic flow patterns further reinforce suitability, while stable geological formations, mainly undivided Precambrian rocks, underpin foundational stability. Rainfall variability and land use patterns complement these factors, culminating in approximately 74.07% of the CAPP area being classified as moderately to highly suitable for hydropower development. The dominant determining factors were Drainage Density (weight: 0.20), Flow Accumulation (0.18), and Elevation (0.15). These high-weight criteria, combined with favorable loamy soil textures and stable geological formations, represent the primary drivers of suitability in the region.
This study conducted a comprehensive geospatial analysis of wind energy siting suitability within the Southern African Power Pool region, employing Geographic Information Systems and multi-criteria decision analysis. By integrating key biophysical and infrastructural factors, including wind speed, proximity to power lines and roads, elevation, slope, and land cover this study evaluated potential locations for utility-scale wind farm development across 12 SAPP member countries. Comprehensive suitability maps were produced, categorizing areas from very low to very high potential based on a hybrid GIS-AHP framework. The analysis revealed significant spatial variations in suitability, identifying priority zones characterized by high mean wind speeds (exceeding 7–8 m/s), gentle slopes (0°–0.75°), and proximity to existing infrastructure. This study quantified suitable land areas, defining highly suitable parcels as contiguous clusters of high-potential pixels with a minimum mapping unit of 1 km 2 to ensure technical and economic feasibility. Mathematical modeling using Weibull parameters yielded shape factors ranging from 3.10 to 3.80 and scale factors of 11.06 to 12.27 m/s at 50 m heights in high-potential zones. These findings provide a data-driven tool for policymakers and investors to identify priority zones for sustainable wind energy development, fostering regional energy security and cross-border cooperation within the SAPP.
Wireless charging is a technology that is projected to promote the acceptance of Electric Vehicles (EV) due to its capability to reduce transport emissions, improve charging convenience and promote environmental sustainability. Technological advancement in dynamic wireless power transfer has contributed to the expansion of Electric Road Systems (ERS) that offer charging infrastructure for Electric Vehicles (EV). ERS is an emerging technology aimed at electrifying road transport by supplying EV with power enabling EV's with the possibility to charge while driving. ERS is an important technology to enhance the electrification of EV thereby addressing battery limitations and further decrease fossil fuel dependency. Although prior studies have evaluation the potential of ERS. There are fewer studies that extensively explored the applicability of wireless ERS in highways or long-distance corridors. Therefore, this article identifies factors as challenges that influences the deployment of wireless ERS and potential application of wireless ERS for sustainable transportation. More importantly this study investigates the feasibility of wireless ERS to decarbonize road vehicles in long-distance corridors. Key findings from this article assess the maturity level of different ERS technologies by presenting use cases and initiatives of ERS focusing on wireless power transfer subsystem and the development of ERS in highways.
Hospitals are energy-intensive buildings, but they also have potential for applying strategies for solar energy use (SSEU), such as photovoltaic systems (PVS) and/or solar thermal systems (STS). However, existing regulations and incentive schemes rarely consider the specific conditions of healthcare networks, where centralized management, heterogeneous building typologies, and strict sanitary requirements shape energy use. This study proposes a general and adaptable framework to guide the implementation of SSEU in hospital networks. The framework includes the selection of hospital facilities, definition of objectives, diagnosis of current energy and sanitary conditions, assessment of existing systems, formulation of SSEU, and evaluation of energy, environmental, and economic impacts. The methodology is applied to the provincial hospital network of the Micro-Region Gran La Plata (Buenos Aires, Argentina), focusing on replacing natural gas consumption for domestic hot water (DHW) with STS. The analysis incorporates architectural and operational data, DHW demand estimation, theoretical performance of STS using the F-Chart method, and a simplified economic evaluation. Three goals guide the assessment: compliance with WHO recommendations for Legionella prevention, a 27% reduction in GHG emissions, and economic viability. Results show that two strategies combining STS with existing or efficient water heating systems meet the proposed objectives. The study highlights that low natural gas prices and high upfront costs of STS remain major barriers, suggesting the need for targeted subsidies and policy instruments. The proposed framework provides a replicable tool for decision-makers to design energy transition policies in healthcare infrastructure and to promote the broader adoption of renewable energy in public buildings.
Households in socially marginalized settings often face disproportionate energy burdens to attain thermal comfort, driven by weak building envelopes, climatic stress, and uneven tariff structures. This study quantifies those burdens across Mexico's climatic diversity using dynamic building simulations (TRNSYS) for a non-insulated reference household at 13 locations spanning Köppen climate types. We estimate hourly heating/cooling loads, translate them into electricity use with fixed COPs (3.2 cooling; 2.8 heating), and monetize costs under location-specific CFE residential tariffs. Annual electricity consumption ranges from 3924 to 7377 kWh per household (mean 5910 kWh), with cooling accounting for ∼53% of use. Despite universal residential status, effective prices diverge markedly ($0.064–$0.182 USD/kWh), reflecting subsidy rules tied to summer temperatures rather than year-round thermal needs; colder sites incur up to 371% higher costs than heavily subsidized warm regions. Coupling energy results with state-level income data (ENIGH 2022) shows that 77% of modeled cases would require >10% of annual household income for thermal comfort, reaching 44% in extreme instances (e.g., Puerto Escondido). The work contributes a portable assessment framework that fuzes high-resolution thermal simulations with socioeconomic indicators, enabling more equitable targeting of subsidies and retrofits in climates with contrasting heating and cooling demands. Findings are broadly transferable to other countries confronting climatic heterogeneity, constrained housing quality, and subsidy misalignment.
Despite one of the most significant factors reducing photovoltaic (PV) efficiency is still shade of solar panels, the effects of shading vary widely depending on the type, material, and intensity of shading. This study examined the effects of three typical shading materials on the electrical, thermal, and efficiency parameters of an ADH ISO 15 W solar panel erected in Kansanga, Uganda: paper, cloth, and Ficus umbellata leaf. For three months, measurements of current, voltage, irradiance, ambient temperature, and cell temperature were made at 15-min intervals between 9:00 a.m. and 5:00 p.m. Descriptive statistics, efficiency computation, and ANOVA were used to examine the average data. The highest voltage, current, and power output were produced in unshaded situations, according to the results, demonstrating ideal panel performance under full sun exposure. Because of their increased opacity, paper and cloth produced the worst power losses among all shading options; leaf shading, on the other hand, allowed for partial transmission and produced rather moderate savings. More than 94% of the difference in voltage, current, and power was explained by shade, according to an ANOVA, with the paper exhibiting the highest statistical influence across parameters. The results show that even 25% partial shade significantly reduces energy output and modifies thermal behavior, underscoring the vital necessity of minimizing shading and preserving unobstructed panel surfaces in PV installations. These findings offer useful information for PV system installation, design, and shading mitigation techniques in tropical urban settings.
This paper advances prior research on renewable energy policy analysis through the empirical validation of a comprehensive analytical framework. Building on earlier work, which established the framework via a systematic literature review, this study incorporates expert validation and applies the framework to the national context of Aotearoa New Zealand, as well as Norway, Estonia, Brazil, India, and Nigeria. The first phase comprised semi-structured interviews with international energy policy experts, generating 100 factors across seven thematic domains and refining the original framework through the inclusion of cross-cutting elements. The second phase applied the validated framework to Aotearoa New Zealand's renewable energy policy landscape, identifying strong institutional coordination and social acceptance alongside persistent financial, technical, and environmental constraints. The findings confirm that the five foundational domains — coherent institutional arrangements, resilient financial mechanisms, inclusive social processes and efficient technical capabilities and environmentally sustainable practices — remain conceptually robust, while the added cross-cutting themes strengthen the analytical framework.
The global transition toward renewable energy requires efficient and locally sourced solutions to replace fossil fuels while reducing greenhouse gas emissions. Biogas production through anaerobic digestion (AD) represents a sustainable technology that simultaneously manages organic waste and generates renewable energy. However, its performance often remains limited by low conversion efficiency and process instability, particularly when treating high-load organic substrates such as livestock manure. This study investigates the use of catalytic microparticles as an emerging and promising strategy to enhance AD performance and energy yield. Batch experiments were conducted over 50 days using iron (II,III) oxide (Fe 3 O 4 ), biochar, graphite, and Bio-Fe additives at two concentrations (5 and 15 mg/g VS), compared to a control without additives. Biogas production kinetics were evaluated using the modified Gompertz model, which provided excellent fits (R² > 0.96) and negligible lag phases. The control achieved a cumulative biogas yield of 431.8 mL/g VS, while Biochar L2 reached 667.4 mL/g VS, maintaining stable production throughout. Bio-Fe showed the highest biogas production rate (R m = 38.3 mL biogas·g −1 VS·day −1 ), while Fe 3 O 4 maintained consistent productivity over time. Furthermore, iron-based additives reduced hydrogen sulfide (H 2 S) levels by up to 39%, significantly improving biogas quality. These findings demonstrate that microparticle-assisted AD enhances both biogas yield and purity, offering a promising route for efficient renewable energy recovery from livestock waste.
Persistent energy poverty and governance challenges persist in constraining sustainable energy transitions in West Africa, despite the region's abundant renewable energy potential. This study conducted a bibliometric analysis of renewable energy governance research within the ECOWAS region from 2005 to 2025, using 594 Scopus-indexed documents screened through PRISMA protocols. Bibliometrix (R Studio) and VOSviewer were applied to analyse publication trends, collaboration networks, keyword co-occurrence, and thematic evolution. The results revealed an annual publication growth rate of 24.8%, increasing from fewer than 10 articles per year prior to 2010 to 84 publications by 2025. Nigeria (25.7%), Ghana (13.0%), and Senegal (1.6%) accounted for over 40% of total research output, supported by high international collaboration (38.22%), but with limited intra-ECOWAS research linkages. Thematic mapping identified five dominant research clusters: renewable energy technologies and governance frameworks, energy-environment-economy modelling, decarbonisation and planning tools, socio-institutional and gender dimensions, and energy efficiency and circular economy strategies. Emerging research frontiers included hybrid energy systems, green hydrogen, digitalisation, and gender-responsive governance. The novelty of this study lies in its systematic quantification of the intellectual structure, growth dynamics, and thematic evolution of renewable energy governance research in ECOWAS. The findings provide evidence-based insights to guide policymakers, researchers, and development partners in strengthening regional collaboration, aligning governance reforms with energy transition goals, and prioritising future research directions that integrate equity, resilience, and circularity into energy policy design.
The rapid expansion of electric mobility and distributed renewable generation presents new operational challenges for low-voltage (LV) distribution networks, including increased evening peak demand, higher transformer utilization, and phase unbalance, particularly in emerging regions where options for reinforcement are constrained. This paper describes an open-source Python–OpenDSS framework that combines measured slow-charging profiles with Monte Carlo sampling of electric vehicle (EV) location, vehicle model, initial state of charge, and charging start time, with optional single-phase photovoltaic (PV) sized to offset annual customer demand. Each scenario is evaluated with 100 iterations, and 10-minute time-series power-flow simulations over a one-day (24 h) horizon are summarized using ensemble statistics (e.g., mean and selected percentiles). The framework is applied to a real 50 kVA urban LV feeder in Cuenca, Ecuador (62 residential customers), whose model was built from the utility GIS database and corroborated through an on-site inspection, under EV penetration levels of 5%, 10%, and 15% with EV-only and EV+PV configurations. For the range studied, steady-state voltages and voltage unbalance remain within typical LV compatibility limits, while transformer utilization increases from about 59% in the baseline to around 90% at 15% EV penetration. Co-located PV reduces the net daily energy exchanged with the upstream network but has limited impact on evening transformer peaks. A 7-day extension of the 15% EV scenario is included to illustrate multi-day studies using the same workflow.
The transition from centralized to decentralized power generation presents a significant opportunity to enhance grid resilience and energy independence, particularly in regions with unstable grids or vulnerability to natural disasters. Distributed Generation (DG), particularly solar photovoltaics, has become a key component of modern power systems, especially in distribution networks. However, its increasing penetration at both utility and distributed levels poses challenges related to voltage, frequency, and angular stability, requiring advanced monitoring and control strategies. In this context, energy storage systems (ESS) emerge as a crucial player, playing a significant role in mitigating these challenges. ESS stabilizes power supply fluctuations and enhances grid reliability, providing a safety net for the intermittent nature of renewable energy sources. This study examines the impact of DG on the stability and operation of the National Interconnected Electric System (SENI) of the Dominican Republic, with a focus on integrating ESS at both utility and distribution levels. Using DIgSILENT, future scenarios (2027) with high renewable penetration were simulated. The methodology included data collection, modeling of actual automatic load shedding (EDAC) events from 2024, and the simulation of three scenarios: without storage, with utility-scale storage, and with both utility-scale and distributed storage. The results indicate that energy storage systems (ESS) significantly enhance system stability, reducing both the total disconnected load and the number of EDAC steps. In the absence of storage, 640 MW were disconnected; with utility-scale storage, this was reduced to 540 MW, and the addition of distributed storage further decreased the disconnected load to 440 MW while also delaying EDAC activation times. Findings highlight the critical need for ESS investments and grid flexibility mechanisms to accommodate increasing renewable penetration, particularly in Small Island Developing States (SIDS). Future research should optimize ESS deployment and conduct detailed economic analyses to support the development of sustainable power systems.
Photovoltaic solar technology is economically competitive, modular, and has a low environmental impact. The problem addressed is understanding how the reliability of components in a grid-connected solar photovoltaic (PV) system impacts its performance. This review systematically explores the existing literature on the Performance indicators of solar PV systems. Through a structured search process in Scopus and Web of Science databases, a total of 292 references were found from which 21 were selected, organized into five main topics, and a base article was chosen to update knowledge with a practical and statistical approach. The literature review confirms that reliability, availability, and maintainability (RAM) are directly linked to solar PV system performance. Reliability Engineering techniques were applied to study trends, comparisons, and future system behavior. A RAM analysis was developed for seven practical solar PV system designs, using failure and repair rate data from the literature. The RAM study focused on three subsystems: Balance of System (BOS), photovoltaic modules (PV modules), and inverters. Results showed that while all three subsystems are reliable and available over 1 and 20-year periods, the inverter consistently had the lowest reliability and is therefore the most likely component to fail first. Furthermore, the study identifies gaps and proposes avenues for improvement, recommending a shift toward analysis approaches of Useful life Characterization techniques using Distribution ID and Overview Plot Analysis, multivariable analysis and incorporating the Weibull distribution into the study due to its special characteristics and typical bath tube curve for a predictive approach to decision-making that contributes to photovoltaic system performance.
Climate change continues to pose a serious threat to energy systems, with rising temperatures directly influencing the performance of solar photovoltaic (PV) technologies. This study evaluates the effect of increasing ambient and cell temperatures on PV energy generation through experimental data collected from operating solar power plants in India. Performance variations across different PV technologies—monocrystalline, polycrystalline, and bifacial modules—were analyzed, with results showing that cell temperature, rather than ambient temperature alone, plays a decisive role in efficiency reduction. A comparative assessment further examined advanced configurations such as agrivoltaics and floating PV, which demonstrated lower operating cell temperatures (by 4–8 °C) and higher relative efficiency compared to conventional ground-mounted systems. The methodology combined field measurements, temperature–efficiency correlation analysis, and comparative case studies to evaluate the technical and economic viability of these solutions. The findings indicate that next-generation PV installations integrating bifacial, agrivoltaic, and floating systems offer resilience against climate-induced thermal stress while contributing to land and water resource optimization.
The transition to green hydrogen offers a critical opportunity for Ghana to achieve its decarbonisation and sustainable energy objectives. However, its widespread adoption faces significant barriers. This study seeks to identify, prioritise, and propose strategies to overcome these barriers through an integrated multicriteria decision-making (MCDM) framework tailored to Ghana's context. The methodology combined a systematic literature review with expert consultations. The CRITIC method was applied to derive objective weights for barriers. Thereafter, four MCDM techniques, namely, TOPSIS, EDAS, MOORA, and COPRAS, were employed to rank strategies. These methods were deliberately selected since each method captures distinct dimensions of decision-making. Integrating multiple techniques enhanced the robustness and reliability of rankings by allowing cross-validation of results. The final rankings were validated using Spearman's correlation and T-statistic, ensuring statistical consistency across methods. The results highlight barriers such as limited international collaboration, inadequate financing options, and public acceptance challenges. Conversely, prioritised strategies include infrastructure development, training local expertise, and implementing financial incentives. These findings emphasise the importance of strategic infrastructure and capacity building investments to unlock Ghana's green hydrogen potential. The study provides actionable insights for policymakers, emphasising the need for clear regulations, robust incentives, and international collaboration. Addressing these barriers can facilitate the adoption of green hydrogen and position Ghana as a leader in sustainable energy innovation. These strategies align with Ghana's energy transition targets and present an opportunity to bolster economic growth and reduce carbon emissions.
South Africa's energy system faces severe challenges, including persistent load-shedding since 2007, costing businesses USD 0.73 billion in 2015, and heavy coal reliance (72.7% of the energy mix), making it a top global carbon emitter. Population growth (73.9% since 1990) has driven a 52.8% rise in energy demand, exacerbating grid instability. The Integrated Resource Plan (IRP) 2019 targets 30.7 GW of renewable energy by 2030 to mitigate load-shedding, reduce emissions, and enhance energy security, yet intermittency and infrastructure constraints pose significant hurdles. This study employs system dynamics (SD) modelling to evaluate renewable energy integration, addressing a gap in holistic analyses of South Africa's energy transition. By simulating feedback loops, the model quantifies the impacts of 30%, 50%, and 70% renewable penetration by 2035 on emissions, load-shedding, and system costs. Results show a 50% renewable share could reduce emissions by 50% and load-shedding by 40%, while a 70% share achieves 65% and 55% reductions, respectively, though costs rise by up to 25%. Policy pathways, informed by global best practices, emphasise storage subsidies, demand-response measures, and phased coal retirements to enhance South Africa's energy transition. Community-led initiatives, like Enkanini's solar projects, enhance adoption. Limitations include incomplete rural demand data, necessitating improved data collection via satellite imagery and surveys. Policymakers should prioritise targeted subsidies and regulatory coherence to balance costs and reliability, offering a scalable model for Sub-Saharan Africa's coal-heavy systems, with future research focusing on refining rural energy projections.
This study develops a computational methodology to assess the performance of a flat plate solar collector system for dairy pasteurization, integrating computational intelligence methods. A heat exchanger tank captures thermal energy from the collectors, with an auxiliary heater compensating for any unmet thermal demand. The analysis considers four climate types—temperate, arid, dry, and tropical—along with four auxiliary fuel options: diesel, fuel oil, natural gas, and LP gas. Design variables include solar field area, heat exchanger tank volume, fuel type, and climate conditions. A dataset is generated by varying these parameters, incorporating governing equations for solar technology, industrial thermal requirements, and regional climate data. This dataset trains a surrogate artificial intelligence (AI) model based on artificial neural networks, where input neurons represent the design variables, and output neurons correspond to economic-environmental indicators: net present value, total life cycle cost, and carbon dioxide emission reduction. To identify optimal system configurations, multi-objective optimization is performed using three different algorithms: particle swarm optimization, genetic algorithms, and the whale optimization algorithm. These algorithms generate Pareto diagrams that facilitate the analysis of trade-offs among the performance indicators. Results indicate economic and environmental feasibility across all climate regions when using diesel as auxiliary fuel, with Jalisco's temperate climate being the most suitable for implementation. This methodology offers a flexible framework for evaluating the feasibility of solar technologies in industrial processes, supporting sustainable energy integration.
