Solar Solar Cooling Cooling for Agriculture for Agriculture Do It - - PowerPoint PPT Presentation

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Solar Solar Cooling Cooling for Agriculture for Agriculture Do It - - PowerPoint PPT Presentation

Solar Solar Cooling Cooling for Agriculture for Agriculture Do It Yourself! Do It Yourself! Technical Training Promotion Conference March 18 th 22 nd 2019 Nairobi, Kenya In cooperation with: Media Partner: Institute of Agricultural


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1 Institute of Agricultural Engineering│Tropics and Subtropics Group

Solar Solar Cooling Cooling for Agriculture for Agriculture

Do It Yourself! Do It Yourself! Technical Training Promotion Conference March 18th – 22nd 2019 Nairobi, Kenya

In cooperation with: Media Partner:

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2 Institute of Agricultural Engineering│Tropics and Subtropics Group

Get your soft copy of all materials presented during the day

http://solar-cooling-engineering.com/details-training-and-conference-kenya-2019

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3 Institute of Agricultural Engineering│Tropics and Subtropics Group

DAY 1 Monday March 18th Academia

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DAY 2 Tusday March 19th Companies

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Where is Hohenheim?

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6 Institute of Agricultural Engineering│Tropics and Subtropics Group

Who are we?

University of Hohenheim

9,500 Students(15% international) 40 Degrees, 2,000 Staff members

Tropics/Subtropics group of the Institute of Agricultural Engineering

  • 5 Departments (Professors)
  • 150 Staff members

Attached to the multidisciplinary:

Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg)

  • 10 Departments (Professors)
  • 100 Researchers
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7 Institute of Agricultural Engineering│Tropics and Subtropics Group

Tropics/Subtropics group (Prof. Dr. Joachim Müller)

■ Solar Drying ■ Irrigation (Solar) ■ Plant oil extraction (Solar) ■ Use of biogas/biomass ■ Postharvest technologies ■ Solar cooling

20 PhD Students 6 Post. Docs. 5 Technical staff 2 administrative staff From 15 countries!

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Solar Cooling Team

Juliet Farah Victor Florian Julian Kilian Muaz Ana

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Facilities of the Institute of Agricultural Engineering

Metal Workshop Wood Workshop Electric/Electronic Laboratories Research hall Greenhouse

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Solar cooling testing facilities

Climate chamber PV Simulator Weather profile Solar Power profile

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Our work since 2014 with commercial available solar refrigerators

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Small scale milk cooling

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Implemented projects

Colombia 2018 4 systems Tunisia 2016 10 systems Kenya 2016 3 systems Kenya 2018 2 systems

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Even though a technical solution is economically feasible, that doesn't mean this will be adopted by the industry

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Farmer / Cooperative

Preserve quality Increase production Storage Processing New markets

Technology supplier

Business models

Product development Testing Production Distribution Marketing

Challenges

  • High transportation cost
  • Lack of investments for R&D
  • Expensive distribution and

maintenance in rural areas

  • No quality based pricing
  • Seasonal fluctuations
  • Strong informal market
  • Unreliable customers
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Business models

„This technology is not 100% adapted to my needs and too expensive“ „I can not invest in innovations to my farmer customers“ Farmer / Cooperative Technology supplier

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Farmers often don´t have access to the technology they need and would be ready to pay for

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20 Institute of Agricultural Engineering│Tropics and Subtropics Group

Promote key components instead of key systems

Locally produced solar cooling systems Solar cooling units + Electronics and sensors + Know-how

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Solar Cooling Unit (Key component) Ice-packs Battery free solar refrigerator (Final System) Insulated box (Suitable for local production)

+ + =

Example for solar refrigerator

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One key component … many options

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Refrigeration machines

Refrigeration methods Refrigerant free Thermoelectric (Peltier) Thermomagnetic With refrigerant Without phase change Air compression Vórtex tube Stirling engines With phase change Open circuit Evaporative cooling Closed circuit (cycle) Vapor compression (heat pumps) Absorption Adsorption

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Heat pumps theory

■ The efficiency of refrigeration systems is measured by the Coefficient Of Performance (COP) which indicates the ratio between extracted heat and energy input. In the case of vapor compression systems, the ratio between refrigeration effect and mechanical or electrical work. The maximal COP of a refrigeration cycle is defined by the second law of thermodynamics and depends on the temperature of the warm and cold source as described by Carnot (1824) in following equation:

Where Q is the thermal energy, P the mechanical work, α the ideality factor of the refrigeration cycle and T the temperature of the warm and cold source respectively

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Coefficient of Performance (COP)

■ COP Carnot (Ideal) T warm (°C) 20 30 40 T cold (°C) 4 17.3 10.7 7.7

  • 10

8.8 6.6 5.3 ■ COP Refrigeration cycle (real) * * Different for each refrigeration system T warm (°C) 20 30 40 T cold (°C) 4 2.6 2.1 1.8

  • 10

1.6 1.4 1.1

Source: https: / / www.dimplex.co.uk

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Importance of climate friendly refrigerants

■ R134a has Global Warming Potential (GWP) of 1400 kg CO2 equivalent per kg ■ Natural refrigerants as R290(Propane) or R600a(Isobutane) have GWP of around 3 kg CO2 equivalent per kg. The refrigerant of a typical solar refrigerator with R134a implies the Co2

  • eq. emissions that are saved through the

use of PV-Panels during almost 7 years!

Good to know! Therefore, Solar always with natural refrigerants!

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Cost comparison

  • 68%
  • 42%
  • 48%
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Better cost efficiency Tailored to customers Higher local added value Promising performance

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Household Refrigerator Water chiller for Cold rooms

  • r

Milk tanks

Get into the market with several system configurations!

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3 Example Systems

Example System 3: Water Chiller for cold rooms And water bath milk cooling Example System 2: Refrigerator battery-free Example System 1: Solar ice-maker

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Construction Materials

Solar cooling unit Polystyrene plates Acryl glass plates Wooden box Technology Stability Insulation Water proof

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Solar ice-maker

  • 2 cooling units
  • Power: 140 W
  • 2 fans for increased heat transfer (x3)
  • Space for nominal 54 kg ice

(max. capacity: 72 kg)

  • 3 chambers

20 °C 30 °C 40 °C 0 kWh/m2 day

  • 2.4 kg
  • 3.5 kg
  • 4.7 kg

2 kWh/m2 day 10.3 kg 5.6 kg 0.6 kg 4 kWh/m2 day 23.3 kg 15.8 kg 6.7 kg 6 kWh/m2 day 30.4 kg 23.2 kg 14.1 kg 8 kWh/m2 day 31.4 kg 24.2 kg 15.1 kg

Daily ice production in kg/day powered by 400 Wp and 2 x 40 Ah Batteries

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Solar ice-maker (Performance)

  • 23 kg ice within 24 hours at 30°C ambient
  • Faster cooling in the middle chamber
  • 3 Days autonomy through ice stored in the side

chambers

Temperature (°C) Time (hh:mm) Evaporator Air

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  • Directly connected to PV
  • icepacks around the evaporator

→ Energy storage in ice

Battery free refrigerator

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Battery free refrigerator (Stages during Assembly)

  • Case with Insulation and

acrylic glass box

  • Top is removed to allow Solar

Cooling Unit assembly

  • Solar Cooling Unit is installed
  • Ice Storage is beeing installed
  • n both sides of Evaporator

plate

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Battery free refrigerator (Performance)

  • 30 Liter Water per day 25°C-> 4°C
  • Autonomy of 24 hours at 35°C ambient temperature
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  • Evaporator plate directly immersed in water
  • Ice storage for fast cooling or as substitute of electrical batteries

Water chiller

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Water chiller (Performance)

  • 25 kg Ice per 24 h operation (@ 30°C ambient)
  • Storage up to 45 kg ice (electronically controlled)
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Water chiller - Cold room application (Performance)

  • 25 kg ice cool down a cold room of 9 m³ air in 1 h

from 30 to 15°C with a thermal power of max. 700 W (Total energy aprox. 85 Wh per kg ice stored)

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Water chiller - water bath application

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Water chiller - waterbath application (Performance)

  • Cooling 80 L Milk in 3 hrs from 35 to 6°C (25 kg ice

consumed)

  • Suitable for storage of milk up to 48 hours
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42 Institute of Agricultural Engineering│Tropics and Subtropics Group

Thank you for your attention!

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43 Institute of Agricultural Engineering│Tropics and Subtropics Group

Solar Solar Cooling Cooling for Agriculture for Agriculture

Do It Yourself! Do It Yourself! Basis on refrigeration Calculations of cooling demand Solar system design

In cooperation with: Media Partner:

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Basis on cooling technologies

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Motivation of storage

■ Saves nutritional value and taste ■ Minimizes mass loss ■ Reduction of respiration (slows ripening) ■ Controls rate of growth of microorganisms

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Chilling damage

Source: UC Davis Postharvest Technology Center, University of Delaware

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Optimal storage conditions

https: / / www.crcpress.com/ Postharvest-Physiology-and- Pathology-of-Vegetables/ Bartz-Brecht/ p/ book/ 9780824706876

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48 Institute of Agricultural Engineering│Tropics and Subtropics Group

Milk Cooling

■ Raw milk has around 37°C after milking ■ Highly perishable due to rapid bacteria growth ■ Preservation of milk quality through reduction of temperature

5 10 15 20

Time after milking (h)

0.5 1 1.5 2 2.5 3 3.5 4

Bacteria count (10 6 cfu / ml) Limit Germany Limit Tunisia 37°C 37°C 20°C 15°C 10°C Limit Kenya

Source: Modified from Bylund (1995)

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49 Institute of Agricultural Engineering│Tropics and Subtropics Group

5 Times better quality after 2.5 h Effective quality preservation up to 16 h!

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Water cooling

Source: http: / / swvafarmersmarket.org/ hydro-cooling/ https: / / www.munckhof.com

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Air cooling (cold storage rooms)

Source: http: / / www.mdr.de

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How can I calculate the cooling demand

  • f a system?
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Heat transfer during cooling process

Cooling process Respiration Cold Air

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Heat capacity cp

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Cooling load

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■ Heat to be extracted to a product to decrease its temperature ■ Heat produced by the product (respiration and transpiration/evaporation) ■ Heat loss through the insulation of a cooling room ■ Heat and vapor load due to infiltration of warm air inside a cooling room ■ Heat generated by ventilators, pumps, lights and persons

Cooling load

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Heat loss through the insulation of a cooling room

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How fast will my product cool down?

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Thermal properties of the product

Mass and density Heat capacity Heat conductivity Heat transfer coefficient (Air-Product) Cold Air

Time (h) Temp (°C)

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Heat conduction (k)

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Heat convection to cooling medium(h)

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Diffusivity

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Cooling curve calculation

Y is analog zu „Moisture Ratio MR“ for a drying curve

Coefficients j and f depend on Biot Number, Diffusivity und Geometry of the product

k: Heat conduction h: Heat convection to cooling medium Cp: Heat capacity α: Diffusivity L: Dimension of the product (For sphere products is the radius) Tm: Temperature Cooling medium Ti: Start temperature θ: Time (s)

Learn more with the ASHRAE - Refrigeration Handbook(2010) Charpter 20 “Freezing and cooling times of food”

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How can I design the appropriate solar system?

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■ Cooling system ■ Batteries/battery free ■ PV Modules ■ Inverter?

Components for solar cooling

Example system 2 Battery free Refrigerator Example system 3 Water chiller for cold rooms

  • r

milk tanks

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Solar Radiation + Loads PV Modules + Batteries

System Design

PV Panels Charge Controller Batterie s MPPT Inverter

Loads AC DC Loads

? ? ? ? ?

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■ Estimate daily solar irradiance (monthly values) ■ Determinate best module slope for your location ■ Calculate power reduction due to temperature ■ Choose the “worst case” month ■ Calculate the daily loads considering losses at inverter.

How much PV Power (Wp)?

Average solar irradiance Average Load energy

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■ Estimate maximal days without solar radiation (Autonomy days) ■ Calculate the daily loads considering looses at inverter ■ Consider charge controller efficiency ■ Consider minimal SOC of the battery

How much Battery capacity(Ah)?

Average Load energy Autonomy days?

  • Min. SOC 30%

I* min?

Minimal Irradiation

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Use the Hohenheim solar cooling design tool (excel based)

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Solar cooling design tool

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Solar cooling design tool

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Solar cooling design tool

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Solar cooling design tool

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Solar cooling design tool

Solar Cooling Manual

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Solar cooling design tool

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When do I need ice-storage?

■ Highly depends on □ Cost of cooling units in comparison to batteries: Cooling with ice-storage usually has a higher investment(2-3 times more cooling units are needed). However, it requires less maintenance and saves the replacement of batteries. □ Final temperature of the product: If it is higher than 0°C then COP can be much higher when cooling through batteries than cooling through ice-storage) making the process more efficient if you have batteries ■ When your system needs it for short-time cooling. This is the case of all systems for milk cooling (e.g. example system 3) ■ When you need ice for transport. Example system 1 ■ When ice-storage is more cost efficient than batteries. Not always!

Do we need batteries at all?

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Special control strategy: Smart ice-maker (Example systen 1)

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Efficient Mode -10°C Sleep mode 0°C

  • Max. power

mode – 20°C Stop Energy saved in the batteries

Operation Strategy for solar ice-maker

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How was the system designed? (Example for Kisumu, Kenya)

Economical

  • ptimum

Specific cost €-cent/kg Daily ice production kg/d

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Daily ice production in dependence on weather conditions

50 Kg ice storage provide up to 4 days autonomy

Kenya 16 kg/day with 0% LOL

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81 Institute of Agricultural Engineering│Tropics and Subtropics Group

Solar Solar Cooling Cooling for Agriculture for Agriculture

Do It Yourself! Do It Yourself! Technology aspects

In cooperation with: Media Partner:

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Local available materials

Structural material Insulation Materials Waterproof food-safe materials Solar components

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Condensing unit with evaporator Electronic control and sensors Ice-packs Adaptive control unit with Bluetooth connection and SD logging

  • Temp. sensors

Switch Casing PV cables Compressor cables PAYGO Kit Battery-free Electronic kit Fan with Temp. sensor

Solar cooling unit components

Solar cooling unit

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Cost comparison

Solar Refrigerator Solar Cooling unit Compressor + electronics Ice storage Imported

Retail price Germany 800 USD 1040 USD Retail price Kenya (profit margin 30%) 940 USD Air Freight Charges 0% VAT TOTAL 1,980 USD Retail price Germany 500 USD 600 USD Retail price Kenya (profit margin 20%) 250 USD Air Freight Charges 0% VAT TOTAL 850 USD

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Cost comparison

PV-Panels PV-Panels Batteries Solar Refrigerator DC/DC Converter Charge Controller Solar Cooling unit Compressor + Electronics Ice storage Imported

Produced locally

Insulation box

1980 USD Refrigerator 200 USD PV Panels 120 USD Batteries 50 USD Charge controller TOTAL 2,350 USD 850 USD Solar Cooling unit 200 USD Insulation box 200 USD PV Panels TOTAL 1,250 USD SAVINGS 1100 USD ( 47% cost reduction)

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Cost calculation Example 2

Solar Cooling unit Compressor + electronics Ice storage

Retail price Germany 500 USD 600 USD Retail price Kenya (profit margin 20%) 250 USD Air Freight Charges 0% VAT Imported components 850 USD

PV-Panels Solar Cooling unit Compressor + Electronics Ice storage

Produced locally

Insulation box

850 USD Solar Cooling unit 200 USD Insulation box 200 USD PV Panels TOTAL 1,250 USD

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PAYG Options

■ Own system (e.g. over Bluetooth) on or offline ■ Commercial systems (e.g. Angaza)

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Data logging

■ SD / Bluetooth

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PV Simulation

  • Use Simulation to find the optimal PV design for

DC appliances

  • Calculate the power PDC(t) independence of

fixed parameters and input time series

  • State-of-the-Art modelling:
  • Conversion solar energy → electrical energy
  • Parameters:
  • Slope and Azimuth
  • Characteristics of PV Modules
  • Time varying:
  • Solar radiation,
  • Temperature,
  • Wind,
  • Many more

?

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PV Simulation

  • Simulation Results show effect of degrees-of-freedom on:
  • Performance
  • Overall costs
  • Introduction to Simulation Tool: System Advisor Model („SAM) from

National Renewable Energy Laboratory ("NREL"): https://sam.nrel.gov/

  • License is free of cost
  • Access to
  • PV Performance models
  • Module Databases
  • Open Data Portals
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PV Simulation - Example

  • Design questions:
  • how can my system start as early as possible?

(„startup time“ → slope in direction of sunrise)

  • How can I use the most available energy

(„yield“)

  • SAM can help to find answers
  • Small PV System with 300 WP
  • Location: Nanyuki, Laykipia County, Kenya
  • Using meteorological data from MERRA 2

http://www.soda-pro.com/web-services/meteo- data/merra

  • → Data Website
  • → Program
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PV Simulation Results: Yearly and monthly Yield

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PV Simulation Results: Start-up time

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Thank you for your attention!