Demand-Side Optimal Sizing of a Solar Energy–Biomass Hybrid System for Isolated Greenhouse Environments: Methodology and Application Example

Abstract

The water–energy–food nexus has captured the attention of many researchers and policy makers for the potential synergies between those sectors, including the development of self-sustainable solutions for agriculture systems. This paper poses a novel design approach aimed at balancing the trade-off between the computational burden and accuracy of the results. The method is based on the combination of static energy hub models of the system components and rule-based control to simulate the operational costs over a one-year period as well as a global optimization algorithm that provides, from those results, a design that maximizes the solar energy contribution. The presented real-world case study is based on an isolated greenhouse, whose water needs are met due to a desalination facility, both acting as heat consumers, as well as a solar thermal field and a biomass boiler that cover the demand. Considering the Almerian climate and 1 ha of tomato crops with two growing seasons, the optimal design parameters were determined to be (with a solar fraction of 16% and a biomass fraction of 84%): 266 m2 for the incident area of the solar field, 425 kWh for the thermal storage system, and 4234 kW for the biomass-generated power. The Levelized Cost of Heat (LCOH) values obtained for the solar field and biomass boiler were 0.035 and 0.078 /kWh, respectively, and the discounted payback period also confirmed the profitability of the plant for fuel prices over 0.05 /kWh. Thus, the proposed algorithm is useful as an innovative decision-making tool for farmers, for whom the burden of transitioning to sustainable farming systems might increase in the near future.

Modeling and Performance Evaluation of Hybrid Solar Cooling Systems Driven by Photovoltaic and Solar Thermal Collectors—Case Study: Greenhouses of Andalusia

“…The TRNSYS TYPE-1503 is used for the control, which simulates the operation of a thermostat. Equations ( 6) and (7) represent the maximum charging temperature (T CTES(max) ) and the minimum charging temperature (T CTES(min) ). These reference temperatures are used for the activation of the signals (Sg) of the diverge (Div), the CTES pump and the ON/OFF of the chiller system (CH I).…”

“…However, agricultural greenhouses present important challenges in temperature control due to their low thermal insulation efficiency. Therefore, the demand for heating and cooling is affected by seasonal changes and the incidence of solar radiation [7]. Although solar energy is an accessible renewable source in the agricultural sector, the installation area must be minimized to maximize agricultural production [8].…”