arXiv subjects

Andrea Baccioli

Publications and source records attributed to Andrea Baccioli.

4 recordsLinked to original sources

arXiv2026

From Crop and Energy Data to Optimized Lighting Scheduling: A Surrogate-Based MILP Framework for Vertical Farming

Vertical farming enables high productivity and stable crop production under controlled conditions, but its economic feasibility remains limited by electricity demand for artificial lighting and climate control. This study develops a surrogate-based optimization framework for cost-minimizing lighting management in hydroponic vertical farms. A key contribution is a procedure for converting crop-energy response data into relationships suitable for mathematical programming. The method can be applied to experimental datasets or outputs from validated dynamic models, provided that relevant ranges of control variables, crop stages, and energy responses are represented. The framework is applied to lettuce cultivation in an industrial-scale vertical farm in northern Italy. Synthetic data generated by a verified agri-energy model are used to derive surrogate relationships for fresh biomass growth, leaf area index, and electricity demand for lighting, heating, and cooling. These relationships depend on photosynthetic photon flux density, crop stage, and outdoor temperature. Different temporal aggregation levels are examined to evaluate the trade-off among surrogate accuracy, scheduling flexibility, and computational compactness. The surrogate model reproduced crop and energy trends of the reference model with sufficient accuracy for optimization. Compared with fixed-lighting benchmarks, optimized schedules reduced electric energy consumption by up to 15.9% and electricity cost by up to 17.8%, while achieving the target harvest weight. Results indicate that moderate light intensities combined with flexible photoperiods are more cost-effective than high-intensity lighting under the investigated conditions. The proposed framework offers a tractable and generalizable approach for integrating crop growth, energy demand, and electricity price variability into vertical farming lighting strategies.

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arXiv2026

Can sunlight replace LEDs in vertical farms? A critical assessment of optical-fiber daylighting strategies

Vertical farming is a promising approach for increasing food production in controlled environments while reducing land use, water consumption, and dependence on external climatic conditions. However, its large electricity demand, mainly driven by artificial lighting, still limits its energetic and economic sustainability. This study evaluates the techno-economic potential of an optical-fiber daylighting system designed to transport concentrated sunlight directly to the crop growing zones of a vertical farm. A validated transient vertical farm model was coupled with Tonatiuh ray-tracing simulations to assess a single-axis solar-tracked Fresnel concentration system. Five optical fiber typologies and three daylighting strategies were compared in terms of crop production, specific electrical energy consumption, and light cost, and benchmarked against light-pipe and rooftop photovoltaic solutions. The optical-fiber system achieved an annual useful-PAR delivery efficiency of 19-27%, depending on fiber typology. By distributing daylight across all rack shelves and limiting heat gains through a UV-IR filter, it reduced electricity consumption by 35-89%, compared with 12% for the light-pipe configuration. The daylight-only strategy achieved the lowest SEEC, equal to 1.81 kWh kg^-1, but caused a 52% crop productivity reduction. Hybrid LED-optical-fiber strategies avoided this penalty and achieved electricity savings of about 50%, with a minimum SEEC of 3.16 kWh kg^-1. However, current optical fiber costs make the system economically unattractive, requiring an estimated capital cost reduction of about 90% to become competitive. Rooftop photovoltaics covered 22% of annual electricity demand and achieved an 11-12-year payback, making PV the most economically viable rooftop solar option under current market conditions.

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arXiv2026

Solar Daylighting to Offset LED Lighting in Vertical Farming: A Techno-Economic Study of Light Pipes

Vertical farming is a controlled-environment agriculture (CEA) approach in which crops are grown in stacked layers under regulated climate and lighting, enabling predictable production but requiring high electricity input. This study quantifies the techno-economic impact of roof-mounted daylighting in a three-tier container vertical farm using a light-pipe (LP) system that delivers sunlight to the upper tier. The optical chain, comprising a straight duct and a tilting aluminum-coated mirror within a rotating dome, was modelled in Tonatiuh to estimate crop-level photon delivery and solar gains. These outputs were coupled with a transient AGRI-Energy model to perform year-round simulations for Dubai. Tier-3 strategies were compared against a fully LED benchmark, including daylight-only operation, on/off supplementation, PWM dimming, UV-IR filtering, variable-transmittance control, and simple glazing. Ray-tracing predicted an overall LP optical efficiency of 45%-75%, depending on solar position, quantifying the fraction of incident daylight at the collector aperture delivered to the target growing zone. Daylight-only operation reduced the total three-tier yield by 17% and was not economically viable despite 27-29% electricity savings. Hybrid daylight-LED strategies preserved benchmark yield while reducing electricity use. PWM dimming combined with UV-IR filtering achieved the lowest specific electricity energy consumption (6.32 kWh/kg), 14% below the benchmark. Overall, viability remains CAPEX-limited because achievable electricity savings are insufficient to offset the added investment and thus improves mainly under high electricity and carbon-price contexts, although the LP system delivers a 15-38% lower light cost than an optical-fiber reference under identical incident daylight.

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arXiv2025

Beyond yield: integrating energy, water, cost, and carbon to benchmark indoor vertical farming viability

The interest in vertical farming arises from its ability to ensure consistent, high-quality, and pest-free vegetable production while supporting synergies with energy systems and urban development. While previous studies have assessed energy use and cost-effectiveness in vertical farming using simplified models, this study fills a gap by providing a comprehensive analysis of how individual input parameters affect efficiency, sustainability, and economic viability through a detailed modeling framework with sensitivity and correlation analyses. 162 scenarios were evaluated by combining three levels of temperature, photosynthetic photon flux density, and CO2 concentration across three distinct localities, namely Trondheim, Shanghai, and Dubai regions, which differ from a socio-environmental viewpoint. Two insulation thicknesses were also tested in each scenario. Results indicate that, due to the heating, ventilation, and air conditioning and dehumidification system, crop productivity could be kept optimal regardless of insulation or the external climate. Photosynthetic photon flux density was the dominant growth factor (correlation: 0.85), followed by CO2 (0.36) and temperature (0.22), and also the driver of energy consumption (0.73). The lowest specific energy consumption coincided with the lowest productivity (55 kg/m2). Levelized cost of lettuce identified the most cost-effective setup as 24{\deg}C, 250 umol/m2s photosynthetic photon flux density, 1400ppm CO2, with insulation (102kg/m2). Only decarbonized energy systems can support vertical farming without increasing CO2 emissions compared to imported lettuce. These findings guide practitioners and policymakers in selecting cost-effective, sustainable vertical farming strategies and provide validated data for research and implementation across diverse climatic and energy contexts.

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