Optimum scheduling of shared greenhouse solar dryer in Thai community

Abstract

Drying agricultural products is crucial in improving product quality and reducing post-harvest losses, ultimately increasing income for farmers. Greenhouse solar dryers (GSD) amplify these benefits by enhancing quality, preserving nutrients, and extending shelf life, thus elevating the economic worth of agricultural products. However, optimizing GSD utilization faces challenges from seasonal crop patterns, limited variety, and uncertain yields, curbing their full economic potential. Therefore, GSDs must be shared among farmers to address the underutilization of the infrastructure and increase the community’s overall profit. In addition, prioritizing higher value-added goods further maximizes gains from the shared infrastructure. Considering these factors, this research aims to demonstrate the financial benefits of sharing GSDs within a community. To determine the optimal sharing schedule, a mixed-integer linear programming (MILP) model is formulated that considers the monthly production of fresh and dried products, with their corresponding prices and value-added. We tested the model’s performance under three different sharing schemes using the data of a typical Thai agricultural community. It is clearly shown that by sharing the GSDs and importing products to fill empty days, the utilization rate of the GSD can be increased from 23% to 62% by following the optimal schedule. Besides, this approach can boost the overall profit of the community by 1.6 times compared to individual GSD utilization practices. The proposed concept provides a robust schedule for dependable and profitable sharing, even amid unpredictable conditions. However, realizing these benefits entails managing additional challenges, highlighting the need for intelligent unit support for successful community-sharing GSD implementation.