Vertical Farm Energy Yield Balance Calculator
This Vertical Farm Energy & Yield Balance Calculator helps you translate a vertical farming layout and operating strategy into annual crop production, electricity demand, operating costs, and carbon impact. By adjusting layer count, lighting power, photoperiod, HVAC load, and prices, you can quickly test how design choices affect both kilograms harvested and kilowatt-hours consumed.
The tool is aimed at vertical farm planners, operators, and investors who need a first-pass view of whether a concept is technically and economically plausible. It does not replace a detailed engineering design, but it can frame conversations about crop selection, lighting strategy, and energy infrastructure in controlled environment agriculture (CEA).
What this calculator estimates
The model combines your inputs to estimate several high-level metrics for an indoor vertical farm:
- Annual production (kg/year): Marketable crop output based on cultivated area, number of layers, yield per square meter per cycle, and cycle length.
- Lighting energy use (kWh/year): Electricity consumed by grow lights, driven by lighting power density, illuminated area, and daily photoperiod.
- HVAC and dehumidification energy (kWh/year): Additional energy required to manage temperature and humidity, expressed per kilogram of product.
- Total electricity demand (kWh/year): Sum of lighting and HVAC loads.
- Operating economics: Revenue from crop sales, variable costs for energy and packaging, plus fixed annual labor and overhead to approximate gross profit.
- Carbon impact (kg CO₂e/year): Greenhouse gas emissions associated with grid electricity, using your chosen emissions factor.
Key formulas and relationships
At its core, the calculator scales a few simple relationships. The effective cultivated area is your floor area per layer multiplied by the number of productive layers:
where A is the total cultivated area, Alayer is the floor area per layer, and L is the number of layers. Yield per cycle is then:
Annual production assumes continuous operation with cycles repeating throughout the year:
Lighting power is proportional to area via the lighting power density. Daily lighting energy is that power multiplied by the photoperiod (hours of light per day). Over a full year, lighting energy is:
(dividing by 1000 converts watt-hours to kilowatt-hours). HVAC and dehumidification energy is expressed per kilogram of product:
Total electricity use is Etotal = Elight + EHVAC. Multiplying by your electricity price gives annual energy spend, and multiplying by the grid emissions factor gives annual carbon emissions.
How to interpret your results
Once you enter your assumptions, focus on the balance between production, cost, and emissions:
- High yield, high energy: Short cycles, many layers, long photoperiods, and high lighting power density will typically boost yield but can drive very high electricity use and HVAC loads.
- Moderate yield, lower intensity: Fewer layers, conservative lighting, and longer cycles can reduce energy and carbon per kilogram, but may limit total annual output and revenue.
- Economics vs. sustainability: In high-electricity-price regions, optimizing for kWh per kg may also improve profitability. In low-carbon grids, you may prioritize yield over marginal emissions improvements.
The annual gross profit shown by the model is indicative only. It does not include capital expenditure, financing, maintenance, or detailed staffing. Use it as a screening tool to compare configurations, not as a full business case.
Worked example: leafy greens facility
Consider a hypothetical leafy greens farm with the following characteristics:
- Cultivation floor area per layer: 500 m²
- Number of productive layers: 5
- Harvestable yield per m² per cycle: 3 kg
- Cycle length: 28 days
- Daily photoperiod: 18 hours
- Lighting power density: 200 W/m²
- HVAC and dehumidification load: 1.5 kWh/kg
- Electricity price: $0.12/kWh
- Crop sale price: $6.00/kg
- Packaging and distribution cost: $1.20/kg
- Annual labor and overhead: $600,000
- Grid emissions factor: 0.35 kg CO₂e/kWh
The effective cultivated area is 500 m² × 5 = 2,500 m². Yield per cycle is 2,500 m² × 3 kg/m² = 7,500 kg. With 365 / 28 ≈ 13 cycles per year, annual production is roughly 97,500 kg.
Lighting power is 2,500 m² × 200 W/m² = 500,000 W, or 500 kW. Daily lighting energy is 500 kW × 18 h ≈ 9,000 kWh, or about 3.29 GWh per year. HVAC energy adds 97,500 kg × 1.5 kWh/kg = 146,250 kWh, for a total of around 3.44 GWh.
At $0.12/kWh, annual electricity spend is roughly $412,800. Revenue is 97,500 kg × $6.00/kg = $585,000. Packaging and distribution cost is 97,500 kg × $1.20/kg = $117,000. Before capex and financing, a simple gross profit proxy would be:
- Gross profit ≈ $585,000 − $412,800 − $117,000 − $600,000 = −$544,800
This illustrative example shows how sensitive profitability is to yield, price, and energy intensity. You can use the calculator to test higher yields, lower power density LEDs, or improved HVAC efficiency to see what it would take to move into positive territory.
Comparing vertical farm scenarios
A major use of this calculator is to compare alternative farm designs or operating strategies. The table below outlines how changing a few core assumptions typically affects outcomes.
| Scenario lever | Typical effect on yield | Typical effect on energy & emissions | Economic implications |
|---|---|---|---|
| Increase number of layers | Higher total annual kg (more growing area) | Higher lighting and HVAC kWh; emissions rise with kWh | Revenue grows; profitability depends on whether extra revenue exceeds added energy and labor costs |
| Increase lighting power density | Potentially higher yield per m² if crops are light-limited | Lighting kWh rises roughly linearly with power density | May improve revenue but can sharply increase energy spend in high-tariff regions |
| Lengthen photoperiod | More daily light, often higher yield up to a crop-specific limit | Lighting kWh and cooling loads both increase | Can be attractive on low-cost, low-carbon grids; risky with expensive or carbon-intensive electricity |
| Improve HVAC efficiency (lower kWh/kg) | Yield unchanged; better climate may slightly support performance | Lower non-lighting energy per kg; reduced emissions | Improves operating margin; may justify higher capex for efficient systems |
| Target premium crop pricing | May involve specialty cultivars with different yields and cycles | Energy per kg may increase or decrease depending on crop | Higher sale price per kg can offset energy and overhead, but market size and stability matter |
To compare scenarios, run the calculator several times, changing one or two inputs at a time (for example, "baseline LEDs" vs. "high-efficacy LEDs with lower W/m²"). Record annual production, total kWh, and gross profit proxy for each run to see which configuration best matches your objectives.
Assumptions and limitations
This calculator uses a simplified representation of vertical farm physics and economics. Keep the following assumptions and limitations in mind when interpreting any result:
- Continuous operation: The model assumes the farm operates 365 days per year with back-to-back cycles and no downtime for cleaning, commissioning, or unexpected outages.
- Uniform performance: Yield per m² per cycle is treated as constant across layers and time, although real farms see variation due to microclimates, genetics, and operational issues.
- Marketable yield only: The yield input is assumed to represent saleable product. Losses from culls, quality defects, or post-harvest handling are not modeled separately.
- Single crop type: Mixed-crop operations with different cycle lengths and yields are not represented. The model best fits a dominant crop (e.g., leafy greens) or a weighted average.
- Electricity-focused energy: Only electricity for lighting and HVAC/dehumidification is considered. Other loads (pumps, controls, CO₂ supplementation, facility services) are not explicitly included.
- Static prices: Electricity, labor, and crop prices are assumed to be constant over the year, with no time-of-use tariffs, demand charges, or seasonal pricing.
- Grid emissions factor: Emissions are calculated with a single average grid factor. They do not reflect hourly marginal emissions or the impact of on-site renewables or storage.
- Not financial advice: Results are approximate and for planning support only. They should not be interpreted as investment advice or as a bankable business plan without further, project-specific analysis.
Because of these simplifications, treat outputs as directional indicators. Use them to compare alternative concepts and to identify where deeper engineering or financial modeling is warranted.
Linking to related vertical farming concepts
Vertical farms operate within the broader field of controlled environment agriculture. Decisions around lighting power density are often informed by LED efficacy (µmol/J), target photosynthetic photon flux density (PPFD), and the light-response curves of specific crops. Similarly, HVAC and dehumidification loads are driven by plant transpiration, sensible heat from lighting, and how tightly you control temperature and humidity setpoints in a sealed environment.
Different crop classes lead to very different input assumptions. Leafy greens and herbs typically have shorter cycles and moderate yield per m², while fruiting crops like tomatoes or strawberries may require longer cycles, higher cumulative light, and more complex climate control. When you adapt the inputs for your own scenario, be sure they are consistent with the crop type, system design, and local energy context you have in mind.
Understanding the Vertical Farm Energy Yield Balance
Indoor agriculture has matured from futuristic concept to mainstream business, yet entrepreneurs and investors still struggle to translate equipment specs into crop output and economic performance. Most vertical farm calculators focus on a single dimension, such as photon flux or gross yield. This tool fills an unmet need by simultaneously modeling crop output, electricity use, ancillary energy, carbon footprint, and net profitability based on a core set of operational inputs. By keeping the interface consistent with our other calculators, we aim to make a sophisticated subject approachable to growers, financiers, and policymakers alike.
The model starts with your cultivation floor area per layer and the number of productive layers. These two inputs define the total active canopy area that receives light and produces biomass. Multiply floor area by layer count and you obtain the effective growing footprint. We then apply the harvestable yield per square meter per cycle. This value can be derived from actual harvest records, seed supplier recommendations, or academic literature. Dividing the days in a year by the cycle length shows how many harvests you can achieve annually. Multiply harvests per year by yield per cycle and you have annual production per square meter, which is finally multiplied by total growing area to deliver total kilograms produced each year.
Lighting is the heartbeat of controlled environment agriculture, so the calculator pays special attention to photoperiod and power density. Lighting power density (LPD) in watts per square meter, when multiplied by the canopy area and the hours of light per day, yields daily energy consumption. Extending that to a year considers 365 days of operation. Because vertical farms rarely switch off, we assume every day delivers the same photoperiod. If you need to model seasonal modulation, you can change the photoperiod input to reflect shoulder seasons versus peak growth periods. The calculator automatically converts wattage to kilowatts to keep units consistent, avoiding confusion when comparing outputs to utility bills or sustainability reports.
HVAC and dehumidification energy can rival lighting in mature facilities. To keep the tool flexible, we let you specify ancillary energy on a per-kilogram basis. This is not a perfect representation of thermodynamic behavior, but it mirrors how many operators track energy intensity in their key performance indicators. The value can be derived from data loggers, building management systems, or vendor references. By multiplying the per-kilogram energy by total production, we derive annual HVAC energy use. This approach also captures how efficiency upgrades or better latent load management reduce the energy per kilogram figure.
Net revenue is calculated by multiplying crop price per kilogram by annual production. Packaging and distribution costs, also specified per kilogram, are subtracted alongside labor and overhead costs that you enter as an annual lump sum. The result is an annual profit figure, which can be negative if operating expenses exceed gross revenue. We display this value so that stakeholders can assess whether a particular combination of layer count, photoperiod, and yield meets their investment criteria. Because vertical farming often attracts venture financing, understanding the sensitivity of profit to crop price swings or energy costs is crucial.
Carbon accounting is increasingly important in indoor agriculture as sustainability-conscious retailers scrutinize supply chains. The calculator multiplies total kilowatt-hours consumed by lighting and HVAC systems by the grid emissions factor you supply. For operators powered by renewable energy, that factor might be near zero; for those in carbon-intensive grids, the value could be high. By converting energy use into metric tons of CO₂e, we give you a metric that can be compared to traditional greenhouse or field production footprints.
The core energy balance can be summarized using MathML. The equation below shows annual energy consumption combining lighting and HVAC loads:
In this expression, A is total growing area in square meters, L is lighting power density in kilowatts per square meter, P is the photoperiod hours per day, h is the number of days in a year, d is a conversion from watts to kilowatts, Y is total annual yield in kilograms, and k is the HVAC energy per kilogram. The first term captures lighting energy, while the second reflects climate control energy. This balance demonstrates how two different levers—photons and latent load—interact to define the overall sustainability and cost structure of an indoor farm.
Let us walk through a detailed example. Imagine a facility with 400 square meters per layer and eight layers, for a total canopy area of 3,200 square meters. Each cycle yields 3.2 kilograms per square meter and lasts 28 days. That means 13 harvests per year, translating to 41.6 kilograms per square meter annually. Multiply by total area and the facility produces 133,120 kilograms of leafy greens per year. Lighting power density is 210 W/m² and the photoperiod is 16 hours. Lighting energy therefore equals 3,200 × 0.21 kW × 16 hours × 365 days, or roughly 392,000 kWh. HVAC energy intensity is 1.1 kWh per kilogram, totaling about 146,000 kWh. Combined energy use is 538,000 kWh.
Suppose electricity costs $0.095 per kilowatt-hour, crop price is $5.20 per kilogram, packaging and distribution cost $0.85 per kilogram, and annual labor and overhead total $410,000. Revenue equals $692,224. Packaging costs account for $113,152, labor and overhead remain $410,000, and energy costs sum to $51,110. The resulting annual profit is approximately $117,962, demonstrating that disciplined cost control can keep the business in the black even with premium energy tariffs.
The carbon footprint at an emissions factor of 0.32 kg CO₂e per kWh is approximately 172 metric tons per year. With this example, investors can judge whether the margin supports debt service and whether carbon reductions compared with long-haul trucking are sufficient. Operators can tweak photoperiod or upgrade to more efficient LEDs to see how the bottom line shifts.
To illustrate sensitivity, consider how varying layer count and photoperiod changes profitability. The first table holds all other inputs constant while changing the number of layers. The second table adjusts photoperiod. These comparisons show how quickly energy costs can erode gains if lighting is overused or if mechanical systems cannot keep up with higher loads.
| Layers | Annual Production (kg) | Annual Profit ($) |
|---|---|---|
| 6 | 99,840 | $63,540 |
| 8 | 133,120 | $117,960 |
| 10 | 166,400 | $172,380 |
| Photoperiod (hours) | Annual Energy (kWh) | Profit Margin (%) |
|---|---|---|
| 14 | 472,000 | 18.5% |
| 16 | 538,000 | 17.0% |
| 18 | 604,000 | 15.2% |
Several limitations deserve attention. The calculator assumes homogeneous conditions across all layers, yet in practice, airflow and temperature gradients can cause upper layers to behave differently from lower layers. Crop rotations, cleaning downtime, and disease interruptions are not explicitly modeled; you can approximate them by reducing effective photoperiod or increasing cycle length. Nutrient solution energy for pumps is omitted, though it could be lumped into the HVAC energy per kilogram input. Water usage is also outside the scope. Additionally, market price volatility might be more severe than the static value you enter, so scenario planning is recommended.
Despite these simplifications, the tool enables a rigorous first-pass feasibility study. Prospective farm builders can benchmark their plans against peers, lenders can stress-test assumptions before financing projects, and policymakers can evaluate how vertical farms fit into urban resilience strategies. Because the calculator shares a consistent structure with our vertical farm energy demand calculator and underground mushroom farm CO₂ ventilation planner, users familiar with those tools will feel at home here.
Use the interactive interface to translate agronomic ambition into grounded projections. Whether you are validating a pitch deck, planning a retrofit of an underperforming farm, or weighing the emissions impacts of local food production, the vertical farm energy yield balance calculator delivers the clarity you need.