Grant Agreement nº:
613680
Project acronym:
BISIGODOS
Project Title:
High value-added chemicals and BIoreSIns from alGae
biorefineries produced from CO2 provided by industrial emissions
Funding scheme:
Collaborative project
Start date of project:
01/11/2013
Duration of project:
42 months
Deliverable# & title:
D3.4 Technical report on the simulation tool functionalities
and results
Due date:
30/06/2016
Actual date:
28/06/2016
Partner responsible:
CASPEO
Date of the last version of the Annex I against which the assessment
05/11/2015
will be made:
Project coordinator:
AIMPLAS
Dissemination Level
PU
Public
PP
Restricted to other programme participants (including the Commission
Services) to a group specified by the consortium (including the
RE
Restricted
Commission
Confidential, Services)
only for members of the consortium (including the
CO
Commission Services)

BISIGODOS
Deliverable 3.4
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BISIGODOS
Deliverable 3.4
Index
Introduction ................................................................................................................... 4
1.
2.
Tool structure and methodology of use .................................................................. 4
1.1
3D geometry definition .................................................................................... 5
1.2
Solar radiation calculation ............................................................................... 7
1.3
Dynamic energy balance ................................................................................ 8
Simulation results ................................................................................................ 11
Conclusion and perspectives ...................................................................................... 13
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BISIGODOS
Deliverable 3.4
Introduction
BISIGODOS is a European research project whose objective is to develop high addedvalue chemicals and bioresins from algae growing in photobioreactors. One work
package of the project is dedicated to the optimization of outdoor photobioreactors
based on mathematical modelling and numerical simulation.
In this respect, Caspeo, who is specialized in the mathematical modelling and
simulation of industrial processes, has proposed a mathematical model describing the
dynamics of heat transfer between the culture contained in photobioreactors and its
environment1. Then, this model has been implemented in a simulation tool.
The aim of this tool is to facilitate the design of microalgae photobioreactors, to perform
feasibility studies for the implantation of new microalgae facilities and to optimize
existing microalgae production systems.
This document describes the structure and functionalities of this simulation tool
dedicated to outdoor microalgae production in photobioreactors.
1. Tool structure and methodology of use
The structure of the photobioreactor simulation tool is summarized in Figure 1. The tool
is composed of three modules that are successively used in this order:
-
A module for the definition of the geometry of the photobioreactor;
-
A module for the calculation of the hourly solar radiation impinging on the
external surface of the photobioreactor;
-
A module for the dynamic energy balance calculation.
The three modules of the photobioreactor simulation tool are implemented in the
Rhino/Grasshopper3D software solution. Rhino2 is a versatile 3D-modeler commonly
used in architecture and design. Grasshopper3 is a graphical programming editor
integrated with Rhino’s 3D-modelling tools.
We will now detail the functionalities and way of using the three modules of the
photobioreactor simulation tool.
1
The mathematical model has been detailed in Deliverable 3.2 of BISIGODOS project, which is
entitled “Mathematical model of the photobioreactor, implemented in a simulation tool “. Please
contact Caspeo ([email protected]) for more information about the photobioreactor model.
2 More information on https://www.rhino3d.com/eu/
3 More information on http://www.grasshopper3d.com/
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BISIGODOS
Deliverable 3.4
Figure 1. Structure of the photobioreactor simulation tool
1.1
3D geometry definition
The first step towards performing a calculation consists in the definition of the geometry
of the photobioreactor. Indeed, as shown in Figure 1, the geometry of the
photobioreactor is used to perform both the solar radiation calculation and the dynamic
energy balance.
Therefore, at the beginning of a new project, the user has to model the geometry of the
photobioreactor in three dimensions, either directly in Rhino using graphical 3D
modeller, or through a Grasshopper program. The advantage of using Grasshopper is
that all the geometrical parameters of the 3D model, such as diameters or height, are
parameterized in the Grasshopper program and can be modified and processed in
subsequent calculations, such as volumes and areas. On the other hand, direct
drawing in Rhino offers more flexibility in terms of design and shapes.
Whatever the drawing method used – Rhino or Grasshopper program - the main
advantage of using a 3D modeller is that any photobioreactor geometry can be defined
in three dimensions in a user-friendly manner. For instance, Figure 2 shows the 3D
model of a field of nine vertical tubular photobioreactors, each one composed of 36
vertical columns; while Figure 3 shows a horizontal tubular structure modelled with the
Rhino drawing tool.
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BISIGODOS
Deliverable 3.4
Figure 2. 3D model of a field of 9 photobioreactors designed in Rhino
Figure 3. Drawing a horizontal tubular structure in Rhino
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BISIGODOS
1.2
Deliverable 3.4
Solar radiation calculation
Once the geometry of the photobioreactor has been modelled, it can be used to
perform the calculation of the hourly solar radiation impinging on the external surface of
the photobioreactor.
The hourly solar radiation impinging on any 3D geometry can be calculated numerically
using the Ladybug4 plugin for Grasshopper. However, this calculation requires a high
computing power and can be very time-consuming. Instead, the solar radiation on the
ground is available in weather databases for a specific location and it takes only a few
seconds to retrieve it for a whole year.
Therefore, we introduced a dimensionless coefficient, named Krad, which corresponds
to the ratio between the solar radiation impinging on a given object and the solar
radiation on the ground at the same time. The value of Krad is determined by the
geometry of the object and by the sun position. Consequently, for a given geometry,
Krad depends only on the sun position, i.e. altitude and azimuth, varying with it on daily
and yearly basis. After having performed the calculation of Krad with Ladybug during
summer and winter solstices, a correlation between the sun position and Krad can be
set. This allows to quickly estimate the values of Krad, and then the solar radiation
impinging on the structure, for the whole year. For example, Figure 4 shows the values
of Krad versus sun altitude, obtained with Ladybug for various days of the year in winter
and in summer. In this case, the impact of the azimuth has been neglected because
BFS photobioreactors have been considered as symmetrical with respect to their
centre in the horizontal plane.
Krad
350
300
250
200
150
100
50
0
10
20
30
40
50
60
70
80
Sun altitude (°)
Figure 4. Calculation of Krad as a function of sun altitude (Alicante, Spain, with BFS
photobioreactors geometry)
4
Roudsari, M. S., Pak, M., Smith, A. (2013). Ladybug: a parametric environmental plugin for
Grasshopper to help designers create and environmentally-conscious design. Proceedings of
13th Conference of International Building Performance Simulation Association, Chambéry,
France, August 26-28.
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Deliverable 3.4
The methodology to be followed for using the solar radiation calculation module is as
follows:
1. Selection of the geographical location to be studied and loading of the
corresponding “.epw” weather data file in Ladybug. Such weather data files can
be downloaded from the website: https://energyplus.net/weather.
2. Calculation of the total solar radiation impinging on the external surface of the
3D photobioreactor model for various hours around summer and winter
solstices (using Ladybug). An example of such calculation is illustrated by
Figure 5.
3. Calculation of the values of Krad obtained by dividing the values of total solar
radiation calculated in step 2 by the corresponding values of solar radiation
impinging on the ground.
4. Establishment of the correlation between Krad and the sun altitude and azimuth,
by regression of the values of Krad obtained with Ladybug and the
corresponding sun position values. This step can be achieved apart from
Rhino/Grasshopper, for instance in an Excel spreadsheet, as it was done with
the values of the example of Figure 4.
For a given 3D photobioreactor model at a given geographical location, the calculation
of hourly solar radiation is performed once and for all and does not need to be
reiterated when modifying any other input parameter of the dynamic energy balance
module. On the contrary, these four steps have to be performed for each new 3D
photobioreactor model or geographical location.
Figure 5. Calculation of solar radiation impinging on the surface of a vertical tubular
photobioreactor surrounded by identical photobioreactors using the Ladybug plugin for
Grasshopper3D
1.3
Dynamic energy balance
The third module of the photobioreactor simulation tool enables to perform the dynamic
energy balance between the culture and its environment. It consists of a
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BISIGODOS
Deliverable 3.4
Grasshopper3D program. The core of this module is an ordinary differential equation
(ODE) describing the evolution of the culture temperature with time as a function of
radiative, convective and conductive heat transfer terms. The program for ODE
resolution (Figure 6) is coded in a VB.NET script embedded in the Grasshopper
program.
Grasshopper
interface
VB.NET
script editor
Figure 6. ODE resolution program coded in VB.NET in Grasshopper interface
The evolution of the culture temperature is governed by solar radiation and by
convective and conductive heat transfer between the culture and the external air (and
the heating or cooling fluid when the temperature regulation system is activated).
The hourly values of solar radiation impinging on the structure all year long are
calculated using the correlation between Krad and the sun position, obtained by the
solar radiation calculation module (as described in 1.2).
The simulation of convective and conductive heat transfer throughout the year requires
the hourly values of external air temperature and wind speed. These climatic data are
imported from a “.epw” weather data file. Moreover, the convective and conductive heat
transfer terms depend on geometrical, operating and design parameters which are
listed in Table 1.
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Deliverable 3.4
Table 1. List of input parameters required to perform the dynamic energy balance
Input parameter
Way of acquisition
PBR external surface area
(m2)
Geometrical
parameters
Culture volume (m3)
Thickness of the wall
between culture and external
air (or heating/cooling water)
(mm)
Liquid flow rate (m3.s-1)
Gas flow rate (m3.s-1)
Operating
parameters
Culture temperature
regulation system:
heating/cooling fluid flow rate
(m3.s-1) and temperature (°C);
heating/cooling set-points
(°C)
Algae optimal temperature
range (Tmin and Tmax, in °C)
Thermal
properties of
constitutive
material
Optical properties
of constitutive
material
Thermal conductivity of the
wall between culture and
external air (or
heating/cooling fluid)
(W.m-1.K-1)
Transmittance of the wall at
different wavelengths
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Calculated from PBR geometrical
parameters (here: number of PBR
columns, their height, external
diameter, etc.)
Determined by the PBR constructor
Range determined by the liquid and
gas feeding system and PBR
geometry
Determined by the operator
according to the heating/cooling
facility equipment
From literature or experiments
Literature (determined by the
material)
Literature (determined by the
material)
BISIGODOS
Deliverable 3.4
2. Simulation results
The ODE resolution enables to obtain the following simulation results:

The evolution of culture temperature on an hourly basis throughout an entire
year, without and with a temperature regulation system (Figure 7);

The annual cooling and heating energy requirements that have to be
subtracted or added to the system to ensure that the culture stays within a
certain range of temperature (Figure 8);

An estimate of the monthly average biomass production in t/ha/month and
the corresponding annual biomass productivity in t/ha/year (Figure 9).
These results can be obtained with various geographical locations or PBR geometries,
enabling to compare scenarios for new PBR design and sizing, or for optimization of an
existing plant.
Figure 7. Simulation results: evolution of culture temperature throughout the year
without (a), and with (b) a cooling system. Black lines indicate the acceptable range of
temperature.
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BISIGODOS
Deliverable 3.4
Figure 8. Simulation results: annual cooling/heating energy requirements
Figure 9. Simulation results: estimate of the biomass production throughout the year
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BISIGODOS
Deliverable 3.4
Conclusion and perspectives
The PBR simulator that has been developed during the BISIGODOS project constitutes
a powerful simulation platform to perform feasibility studies. The three modules of the
PBR simulator are implemented in a single software solution, Rhino/Grasshopper3D,
with the main advantage of using a 3D modeller in a user-friendly manner.
In projects aiming to build new microalgae production facilities, the PBR simulator
enables to:

assess the energy required to maintain the culture temperature in its optimal
range throughout the year;

predict the evolution of culture temperature with time on an hourly basis;

simulate the action of temperature regulation systems;

size heating/cooling equipment;

optimize the design of the PBR (geometrical parameters, materials);

compare various geographical locations;

estimate the monthly average microalgae production.
For instance, the PBR simulation tool has been successfully used to find ways of
reducing power requirement in BFS pilot plant in Alicante. The results of this study
have been presented in Deliverable 3.3 “Predictive control strategy for industrial
photobioreactors report” of the BISIGODOS project.
The PBR simulation tool has been developed and validated with the specific case of
BFS technology, i.e. vertical tubular PBRs with airlift. However, as it is modular, it can
be adapted to any other PBR type, provided that the equations for heat exchange by
convection and conduction are updated in the dynamic heat balance.
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