Optimizing On-Farm Solar-Powered Hybrid Drier System Performance

Thesis Abstract

As smallholder farmers in sun-drenched agricultural regions increasingly rely on post-harvest preservation to reduce losses and add value, traditional drying methods often suffer from inconsistent thermal profiles, high energy costs, and environmental pollutants, necessitating the development of an on-farm solar-powered hybrid dryer system that combines solar thermal collectors with supplemental low-emission energy inputs to deliver controllable, uniform drying performance. This study aims to optimize the design, operation, and evaluation of an on-farm solar-powered hybrid dryer to maximize drying efficiency, minimize quality degradation, and reduce total energy consumption, thereby improving post-harvest outcomes for major crops such as peppers, maize, and shallots. The specific objectives are (1) to evaluate the performance of a hybrid dryer integrating a parabolic trough solar concentrator, a thermal storage unit, and an auxiliary biomass or electric heater under varying solar irradiance and ambient conditions; (2) to develop and validate a dynamic energy balance model and heat and mass transfer model for key crops to predict moisture removal, drying rate, and product quality indicators; (3) to identify optimal operating trajectories using multi-objective optimization that balances energy use, drying time, and product quality (color, rehydration ratio, vitamin retention); (4) to assess economic viability through a life-cycle cost analysis and a sensitivity analysis of capital, operating, and maintenance (O&M) costs; and (5) to formulate practical design guidelines and control strategies for scalable on-farm deployment. The research adopts a convergent mixed-methods design, combining quantitative experimentation with qualitative validation. The population comprises smallholder farmers and extension technicians in a rural agricultural district with average solar insolation of 5.2 kWh/m2/day. A purposive sample of 60 on-farm drying campaigns will be conducted across three crops, with 20 dryer operating cycles per crop selected to capture seasonal and operational variability. Data collection instruments include calibrated thermocouples and humidity sensors for temperature and moisture profiles, a solar irradiance pyranometer, a data-logging control system recording receiver and storage temperatures, heat input, and drying duration; portable spectrophotometers for color and pigment changes; high-performance liquid chromatography (HPLC) for vitamin A and C quantification where applicable; a moisture analyzer for final moisture content; and semi-structured interview guides for farmer feedback. Validity and reliability are ensured through calibration procedures, pilot testing of the control algorithm, intra- and inter-rater reliability checks for qualitative components, and cross-validation of the drying models using 30% of the data withheld from model fitting. Data analysis employs regression analysis to quantify the relationships among solar input, heat transfer, and moisture ratio; ANOVA and multifactorial design of experiments to assess the effects of operating variables on drying rate and product quality; and a multi-objective genetic algorithm to identify Pareto-optimal operating points. The analytical framework integrates a combined heat and mass transfer model with a dynamic energy balance, subsequently validated against experimental data with root mean square error (RMSE) and coefficient of determination (R2). The study anticipates findings showing significant improvements in energy use efficiency and reduction in total drying time when the solar-driven unit operates in conjunction with the auxiliary heater during periods of low solar irradiance, with product quality metrics within acceptable industrial standards demonstrated by Pepper color scores and maintained vitamin levels. The contribution to knowledge includes a validated design-operations framework for on-farm solar-powered hybrid drying, an adaptable dynamic model for predictive control of hybrid dryers across crops, and a techno-economic evaluation that informs policy and extension services on scalable low-emission post-harvest technologies. The main conclusion posits that the hybrid dryer provides robust, energy-efficient, and crop-tolerant performance under variable solar conditions, given an adaptive control strategy that modulates auxiliary heat input and storage discharge. Recommendations emphasize developing farmer-friendly control interfaces, modular storage options for seasonal operation, and policy support for subsidies and training to promote widespread adoption in smallholder contexts.