Next Article in Journal
Application of a Model Based on Rough Set Theory (RST) for Estimating the Temperature of Brine from Vertical Ground Heat Exchangers (VGHE) Operated with a Heat Pump—A Case Study
Previous Article in Journal
Experimental Study of the Corrugation Profile Effect on the Local Heat Transfer Coefficient
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Automation of the Photobioreactor Lighting System to Manage Light Distribution in Microalgae Cultures

Department of Mechanical Engineering and Agrophysics, Faculty of Production and Power Engineering, University of Agriculture in Krakow, ul. Balicka 120, 30-149 Krakow, Poland
*
Author to whom correspondence should be addressed.
Energies 2023, 16(20), 7183; https://doi.org/10.3390/en16207183
Submission received: 31 August 2023 / Revised: 13 October 2023 / Accepted: 18 October 2023 / Published: 21 October 2023
(This article belongs to the Section A4: Bio-Energy)

Abstract

:
Automation of the lighting system for phototrophiccultures in photobioreactors is a process of automation and control of lighting inside. Photosynthetic microorganisms, in order to develop and grow, require a species-specific type of visible light radiation. The automation of the lighting system was based on the industrial PLC Modicon TM221C24T controller according to the submitted and received patent No. 242154. The system was integrated with a quantum sensor, which allows for setting the colour of light and controlling the intensity and exposure time based on protocols set by the operator. The data obtained from the PAR photosynthetically active radiation sensor make it possible to adjust the distribution of light to the actual needs of the culture’s radiant energy. The unit also allows for remote control of multiculture farms. It allows you to simulate sunrise and sunset using the astronomical clock function set for a given species of microalgae. Ultimately, the work was undertaken on the implementation and use of a system for measuring the light spectrum at each point of the bioreactor using a fibre-optic immersion probe.

1. Introduction

Currently, microalgae are attracting considerable interest as a potential alternative energy source [1]. Due to their high biomass yield, ability to grow in different environments and high oil and lipid content, scientists, researchers, and fuel companies consider microalgae as a promising feedstock for biofuel production [2,3]. Microalgae are referred to as a third-generation biofuel. They do not compete with food and terrestrial crops, and they can be cultivated using not only freshwater but also salt water and various types of wastewater [4,5,6,7,8,9,10]. Compared to plants, algae have a high rate of photosynthesis. Under favourable conditions, their growth rate and the yield of biomass obtained are higher than those of terrestrial plants. Additionally, compared to other raw materials, microalgae produce significantly more oil and can be harvested at any time of the year [11,12,13].
Fuels derived from microalgae have advantages such as biodegradability, environmental safety, and high energy content [14]. In addition, cultivation can be carried out in an open system (various types of water tanks) or closed system (photobioreactors—PBR) [5]. According to Vadiveloo et al. [15], photobioreactors are suitable for research and work on improving efficiency in microalgae cultivation, as they allow for controlled light supply and provide more stable culture conditions compared to traditional open-air culture systems. A photobioreactor is an artificial culture system that promotes the growth of selected strains under optimal light, temperature, and pH conditions. Among PRB designs, a distinction is made between tubular, plate, spiral, horizontal, foil, and fermentor-type photobioreactors [16,17,18,19,20], made of transparent acrylic or glass, in which algal cultures are continuously pumped. These units are exposed to natural sunlight or illuminated by artificial light (light-emitting diodes), which enables photosynthesis and algal growth, allowing yields of up to 100 g·m−2·h−1 to be achieved [21].
Algae, like other autotrophic organisms, grow best under certain optimal conditions. Cultivation of algae at the commercial level is difficult in the conditions prevailing in the northern regions of Europe, so cultures of this type are not interesting from an economic point of view. The authors focused on building a photobioreactor for year-round cultivation with the ability to simulate natural conditions for microalgae from different latitudes, including algae with sought-after properties and whose biomass is attractive for a variety of applications. The advantage of the built prototype of the photobioreactor is the possibility to study the light spectrum during the process of conducted cultures and the possibility to optimize the process and the automation of research procedures [22]. It is also worth noting that, unlike most multicellular plants, algae do not need soil and have limited spatial requirements. Therefore, algae can be grown in specially prepared containers or photobioreactors, which eliminates the influence of climatic conditions on their growth [23,24]. Such a solution not only allows algae to be grown all year round but also allows conditions such as light wavelength [25], light intensity, and even the shape of the container [26] to be adjusted to find the optimal growth rate. Furthermore, industrial photobioreactors must be able to remove algae almost continuously.
Another advantage of PRBs over open-water algae-cultivation systems is the prevention or reduction of contamination by bacteria, protozoa, and other undesirable algal species [27]. Growth in PBRs also improves the control of the growth process, such as maintaining balanced growth conditions (nutrients, light, and temperature) for efficient biomass production [23]. Based on these advantages, it can be assumed that PBR will remain an important technology in the algae-cultivation industry under laboratory conditions (in open and closed systems). This is due to the fact that outdoor culture systems and their modifications do not ensure the quality of the product as well as the control of growing conditions. Future challenges for algae-cultivation technology include improving PBR design, reducing energy consumption, and optimising the cultivation process [22].
When considering algal cultures, attention must be paid to maintaining basic physical conditions, such as adequate light, temperature, nutrient solution composition, and bioreactor design that allows for continuous mixing, which determines the free flow of gases and nutrient-solution components.
As mentioned above, light is one of the most important factors influencing the growth rate of photosynthetic organisms. The effect of light energy varies from process to process and species to species. Both excess and deficiency of light negatively affect biomass production. In photobioreactors, the available light conversion depends on the concentration of biomass and, thus, on the optimal distribution of radiant energy so that all cells receive the required amount. The optimal light-flux density for algae is assumed to be in the range of 100–600 μmol·m−2·s−1 and depends not only on the species but even on the genus [28]. In addition, microalgae cells reduce light intensity in the PRB. When they move away from the light source, they become less sensitive to radiation due to mutual occlusion, resulting in a decrease in the growth rate. A process of absorption and scattering called the shading effect occurs [29,30].
The effect of light on the weight gain process of algae has been the subject of many studies [30,31,32,33]. Thus, for example, Liu et al. [34] noted that as microalgae grow, their profile, lipid yield, and photosynthetic activity change significantly at different light intensities and wavelengths. Gordillo et al. [35] found that increasing the light intensity from 700 μmo/m2/s to 1500 μmol/m2/s reduces biomass production in Dunaliella viridis by 63%, and Iqbal [36] reports that exposure of algae to a high light-flux density can be used to increase the amount of extracellular polysaccharides in their organisms. Studies on the effects of colour and light intensity on algal biomass growth can also be found in the literature. Studies suggest that algal growth is strongly influenced by the red-light spectrum, which promotes faster multiplication and growth. On the other hand, the blue-light spectrum causes cell growth [37,38,39,40,41,42].
In addition to light energy, microalgae also need an adequate concentration of oxygen, carbon dioxide, and nutrients such as nitrates, phosphates, or mineral salts. A change in temperature can lead to stopping or accelerating their growth. The growth of microalgae can be affected by pH, the salinity of the environment, and the presence of other organisms competing for food or producing substances that inhibit their growth. The method of mixing contributes to the amount of both the light radiation and nutrients available. Understanding and relating all factors is of colossal importance for the efficient and optimal production of microalgae with specific characteristics [43,44,45].
For example, in the production of biofuels from microalgae, the aim is to obtain biomass with the highest possible fat content. Radiant energy distribution in PBRs is one of the key determinants of biomass growth in closed cultures with desirable properties, such as high lipid content, among others. Photobioreactors are, therefore, suitable for research and work on improving the efficiency of radiation use in microalgal culture, as they allow for controlled light delivery and provide more stable culture conditions compared to traditional open-air culture systems [15].
As part of their research, microalgae biofuel scientists are focusing their attention on various indicators related to light distribution, such as colour, photosynthetically active PAR irradiance, and the ratio between light and dark periods. Findings from studies on the influence of factors on microalgae growth are used to develop optimal culture strategies under controlled conditions and to design modern photobioreactors [42,46,47]. Thus, different photobioreactor solutions can contribute to increased biomass productivity and optimal energy use for the production of valuable bioproducts.
The aim of the study was to develop a photobioreactor to investigate the effects of lighting parameters on the growth of photosynthesising microorganisms under laboratory conditions, according to the algorithm of the established work (Figure 1).
The algorithm of actions at the stage of building the project model included a number of steps aimed at developing assumptions for the concept of the system operation in different regimes. As a part of this stage, a requirements analysis was carried out, project goals were defined, and an initial action plan was developed. Then, all the elements necessary for the construction of the station were completed, including devices, electronic components, tools, and materials.
The electrical design of the stand was made. The development of the electrical design required a thorough knowledge of equipment specifications, as well as standards and regulations related to electrical safety, and ensured the correct operation of the system. Then, based on electrical documentation and electrical diagrams, a physical model of the reactor was created.
After the physical model was made, the software development began. As a part of this stage, the necessary operating systems and programming environments were installed, as well as visualization and driver applications. The software was crucial for the correct operation of the system, enabling control and monitoring of its operation.
The last stage in the process of building the project model was testing and launching the automation system. The tests were aimed at checking the correct operation of the system and detecting any errors and faults. The final solutions were developed based on the results of the tests carried out and the analysis of the needs and requirements of users.

2. Electrical Documentation

The electrical documentation of the photobioreactor was created using AutoCAD Electrical version 2023. It consists of four drawings, which enable precise implementation of the design and expansion of the system. The first page is the title page; it contains a list of all drawings related to the construction of the system. On the second page, there is a detailed connection diagram of the power section. The third page shows the method of connecting the PLC controller, while the last page shows the diagram of the field communication of actuators and the controlled object.
Figure 2 shows a diagram of the AC power supply to the device. On the left side of the figure, there are four signal lines marked as L1, L2, L3, and N, symbolizing the three-phase electricity connection. There are also two power supplies, PS3 and PS12, and overcurrent breakers marked CB13 and CB112, respectively. The PS3 power supply converts alternating voltage with a nominal value of 230 V into 24 V direct voltage used to power the control system. In turn, the PS12 power supply converts the mains voltage into 12 V DC in order to supply electricity to the LED strip and the field-network communication system.
The numbered connections derived from Figure 3 refer to the line numbers in the following drawings of the electrical documentation (Figure 3 and Figure 4). Figure 4 shows the connection diagram of the PLC. From the serial port of the controller with the RJ45 connector (Figure 3), a cable marked with the CBL10 symbol was led out and used for communication by means of the Modbus protocol with field devices. The SL1 communication module, which is connected to the PLC in the form of an expansion card, has two pins, “data+” and “data-”, connected to the serial port of the PC and performs serial communication with the superior control system.
Figure 4 shows the diagram of the electrical assembly of the LED lights. The RESI communication gateway (cat. no. 85389091) is marked with the symbol G0304. This gate is powered with 12 V. An ethernet cable is connected to the gate terminals, which enables communication using the Modbus RTU protocol. The gateway mediates communication between the Modbus RTU protocol and the DMX protocol. The output signal from the communication gate is fed to the input of the LED light controller (the controller is marked as DMC). The signal lines from the LED light controller are routed to individual channels on the terminal strip to which the LED lights are connected.
The controller is equipped with a serial port right next to the analogue inputs. The Modbus RTU protocol in binary format is used for data transmission, and the signal is sent via a category 5E ethernet cable to the protocol gateway. The gateway converts the Modbus RTU protocol to the DMX 512 protocol, which is used to control devices designed to control lighting. From the output of the protocol gate, the signal is transmitted via an ethernet cable to the DMX 512 controller and, from there, to five outputs that are connected to the RGBW LED lamps. The four channels are for the RGBW colours, and the fifth V+ channel next to it in the OUTPUT section provides 12 V power. The DMX controller power (V+ section) and the ground (V− section) are on the opposite side and are taken from a 150 W power supply.
Figure 5 shows the wiring diagram of connections and signals, taking into account the connection of the Quest X spectrophotometer with a fibre-optic probe. A quantum sensor, pH sensor, salinity sensor, temperature sensor, and others are similarly connected, which will be connected if an experiment is needed.
The photobioreactor, like many similar reactors of this type, uses a light source from LEDs (lighting emitting diode), while it is characterized by a tracking system of a cylindrical light jacket that allows you to control the intensity of the radiation emitted to the culture. The entire automation system under construction was designed to secure the operation of the photobioreactor by controlling and piloting the parameters according to the set procedures and recording the data collected from the sensors. The software controlling the photobioreactor is equipped with an intuitive and dynamic interface that allows for online monitoring of all functions, such as light intensity, culture temperature value, optical density value, feeding, and gas parameters. In addition, it is possible to visualize all the measured parameters and create individual user-defined protocols.
Figure 6 shows a block diagram of the automation of the follow-up lighting system for phototrophiccultures of the bioreactor and one of the first stages of the physical implementation of the model.

3. Automation

The physical implementation of the concept began with the construction of automation, giving the ability to turn on and off and control the colour of light, its intensity, and the time of illumination of the culture in various regimes set by the operator. In order to be able to perform more advanced light protocols or turn off the work of the operator supervising the algae cultivation, in the next step, the automation system was coupled with the PAR SQ-522-SS photosynthetically active quantum sensor from Apogee Instruments. The purpose of plugging into the control system and using a quantum sensor was to control the distribution of radiant energy by the real demand for light during cultivation. This allows for the optimization of the lighting of the culture without the supervision of the operator, only based on the transmitted real data from the measurements of the intensity of radiation in the axis, at the central point of the photobioreactor. As a result, there will be an automated supply of light energy to the phototrophicculture, i.e., the regulation of light intensity depending on the actual concentration of biomass.
In subsequent stages, the system was expanded with other sensors: optical density measurement sensor OD, temperature sensor PT 1000, pH sensor, and salinity sensor, leaving room for possible expansion with additional sensors required for new experiments.
The entire automation of the photobioreactor tracking lighting system for phototrophiccultures is based on industrial PLC (programmable logic controller) controllers from Schneider Electric, and the entire system is based on the DMX protocol, which communicates with the RGBW LED controller and the SQ-522-SS immersion sensor of photosynthetically active PAR radiation intensity by Apogee Instruments. The DMX controller, through an advanced control unit, converts (decodes) the received DMX 512 digital signal into a PWM signal for lighting control. When connected to the DMX console, it allows you to achieve various effects such as controlling the process of changing the light intensity, i.e., dimming/brightening, colour-change control, etc. The PLC controller sends Modbus RTU commands to the gate of the DMX controller, whose output is connected to the LED controller (Figure 7). Control is also possible by selecting one of the prepared profiles/programs.

4. Elements of the Lighting System

The photobioreactor lighting system consists of many elements that create a functional and efficient system. The light jacket is made of cylindrical steel with a diameter of 248 mm and a height of 190 mm (Figure 8). The cylindrical shape ensures an even distribution of radiation in the reactor.
The inner side is entirely covered with a strip of RGBW SMD 5050 LEDs, 5.0 × 5.0 mm in size and a power consumption of 0.2 W (600 LEDs: 300 LEDs generate white light, 300 LEDs emit RGB light). Each LED has a minimum luminous efficacy of 80 lm/W and a maximum of 90 lm·W−1. The angle of incidence of light is 120°. As a result, there are as many as 4055 light points per square meter, which ensures even distribution of radiation throughout the bioreactor. The characteristics of the LEDs are listed in Table 1.
The constant voltage of the RBGW LED strip and the current for the entire system are provided by the PMW-120-24 power supply. On the other hand, the LED controller allows for precise adjustment of the colour and brightness of the diodes. The light sensor allows you to automatically adjust the light intensity depending on the conditions in the bioreactor. The parameters of the power supply used are listed in Table 2.
The use of LED strips to create a PBR lighting system allows for flexible adjustment of the light spectrum and its intensity. In order to fully use the possibilities of light regulation and communication in the DMX network with LEDs, a special DMX512 controller/decoder, with parameters presented in Table 3, was used.
The DMX controller is an advanced control unit that converts the received digital signal from the DMX512 protocol into a PWM signal, which is used to control LED lighting. Thanks to this, it is possible to precisely adjust the light intensity and its colour. The use of the DMX controller also allows for the creation of various, including dynamic experimental, procedures related to stressing and distribution of light in the farm. The DMX controller allows for full creativity and freedom in designing the experience.
In the construction of the automation of the PBR photobioreactor, the key device is the PLC controller. Its task is to send commands in the Modbus RTU protocol to the gate of the DMX controller. The gate output of the DMX controller is connected to the LED driver. The DMX512 controller, receiving a signal at the input, converts it into a signal to the PWM switching power supply, and then sends it to the LED strip. Such a combination enables the precise control of individual colours and the process of dimming and brightening the lighting.
The Modbus protocol is a type of client–server communication created by the Modicon (now Schneider Electric: Knightdale, NC, USA) company, used in industrial automation to exchange data between various devices in the implemented project, including temperature and humidity control. The Modbus protocol is available in versions for the serial port and the IP network. In the case of IP networks, the TCP protocol is used on port 502. In the described system, the MODBUS/RTU module was used, which is based on asynchronous data transmission in binary format. It was used to control a DMX-512A lighting system via a serial bus. Host communication is via RS232 or RS485 with a MODBUS/RTU slave protocol.
The MODBUS/RTU module serves as a device that collects information about the condition of technical devices by measuring continuous quantities (e.g., salinity, intensity of photosynthetically active radiation PAR, or temperature) and discrete values (with separate values, e.g., valve open/closed, switch position 1, 2, …, n). The obtained data is then transmitted to the central SCADA system that controls the entire process. The module can also accept commands from the central system and, based on them, affect the devices, e.g., turn them on and off, and set the preset operating parameters. The role of the MODBUS/RTU module in this construction can be performed by a universal PLC controller or a dedicated device that is configured for specific system needs.
In the PBR photobioreactor system, a PLC controller working with a DMX controller and a MODBUS/RTU module provides advanced control of LED lighting, enabling the precise adjustment of colours and light intensity, which is crucial for the effective growth of microalgae and optimal functioning of the entire system.
In addition to the basic RTU functions of data collection and transfer of control commands, they can act as local controllers or security devices, conducting automatic supervision and control of devices (e.g., detecting irregularities in the operation of devices and stopping or switching them off).
The Modicon TM221C24T PLC controller is the central unit used to automatically control all systems of the station in the construction of PBR photobioreactor automation. This controller is programmed in the Ladder Logic language, which allows for automatic decision-making based on readings from connected sensors. Table 4 describes the characteristics of this PLC, including its technical specifications and functional capabilities. The Modicon TM221C24T controller is an advanced device that enables complex tasks of controlling and regulating various processes in the photobioreactor. Thanks to Ladder Logic programmability, the PLC can read data from various sensors in the photobioreactor, such as temperature, pH level, light intensity, pressure, etc. Based on these readings and programmed algorithms, the controller makes decisions and issues appropriate commands to the control devices, such as the DMX controller gate, LED driver, and other components.
The PLC controller plays a key role in the automatic control of the entire lighting system and other parameters in the photobioreactor, enables the optimization of microalgae growth conditions and precise adjustment of LED lighting to the requirements of the culture of microorganisms, and ensures effective and stable operation of the entire station or ensures extreme conditions of culture stress.
Table 5 shows the parameters of the Modicon M221 series insert, which is a part of the Modicon M221 series. The serial line module is a communication extension supporting baud rates from 1.2 kbps to 115.2 kbps for a bus length of 15 m for RS485 and 3 m for RS232. It has nonisolated serial link communication port protocols such as Modbus master/slave and RTU/ASCII or SoMachine Network. The module is compatible with the Modicon M221C PLC. The Modicon M221 controller enables increased productivity with intuitive EcoStruxure Machine Expert Basic software [52].
Table 6 shows the parameters of the ABLS-regulated switched-mode power supply (SMPS) used to power the PLC. The switched-mode power supply supplies DC voltage.
The parameters of one of the main sensors, the quantum sensor used in the project, are listed in Table 7. Typical applications of quantum sensors in outdoor environments or in greenhouses and growth chambers include measuring the incident PPFD and measuring the reflected PPFD. The Apogee Instruments SQ series quantum sensors consist of a cast acrylic diffuser (filter), photodiode and signal processing circuitry mounted in an anodized aluminium housing, and a cable to connect the sensor to the measurement device. SQ-522 sensors output a digital signal using the Modbus RTU protocol via RS 232 or RS 485 [55].
DMX512 is a digital network communication standard, most commonly used in lighting-control systems. Due to its flexibility, the DMX512 system allows for precise control and the creation of a variety of lighting procedures. The control is usually done from the sound engineer’s control console. Communication takes place via a serial interface (RS232 or RS485) or via ethernet. The RESI-DMX-MODBUS converter connects the host with the MODBUS/RTU Master interface to the DMX lighting system. Communication with the host takes place via RS232 or RS485 with the MODBUS/RTU Slave protocol. All 512 DMX registers are supported. Table 8 contains the characteristics of the serial module for controlling the lighting and creating procedures for lighting the culture set by the operator [57].
In order to expand the system for several comparative cultures run in parallel, it is enough to connect an additional DMX 512 controller and power it in the POWER section. Then, using the Daisy Chain topology, feed the output signal from one control device to the input of the other device and, then, from the output of the second device onto the input of the next. Ultimately, by expanding the system with further photobioreactors, the system can be extended using an ethernet cable.

5. The Results of the Pilot Works

In order to achieve the effective use of the energy of light radiation, a system was used that allows for the study of the light spectrum at any given point in the reactor space. Thanks to this, it is possible to optimize and distribute radiant energy in a way that actively simulates the lighting conditions characteristic of a given species in a specific geographical location. The proposed system based on a spectrophotometer and a control system allows for the collection of information about the spectrum and the distribution of light in the reactor. This data is then used in an embedded model of the PBR photobioreactor, which is designed to maximize the conversion efficiency of radiant energy.
The EcoStruxure™ Machine Expert basic programming environment from Schneider Electric was used to program the model, a platform for the configuration, commissioning, and programming of Schneider Electric PLC logic controllers. The data measurement and recording system uses the ethernet link and the ModBus RTU (real-time unit) communication protocol to transfer information. An integral part of the system is a proprietary computer program that enables the visualization of the so-called “Profiles” (selection of measurement data and executive signals). “Profiles” is a set of algorithms supervising the control of actuators and archiving measurement data collected from measuring sensors at predetermined intervals, which are then saved on the measuring computer’s disk.
The program was written in one of the available programming languages defined in the IEC61131-3 standard for PLC controllers. There are five PLC programming languages: Instruction List (IL)—based on a set of list programming instructions, Ladder Diagram Language (LD)—based on a graphic representation of logic in the form of a ladder, Structured Text Language (ST)—based on text notation logic using structures and instructions, Function Block Language (FBD)—based on function blocks connected together in a logical network, and SFC Sequential Function Chart language—based on a sequential presentation of program operation in the form of a diagram [59]. The authors chose the appropriate programming language for the PLC that best suits the needs of their project. In this way, the programming of the PBR model enables the optimization and dynamic adjustment of lighting conditions in the reactor, which contributes to increasing the efficiency of radiation energy conversion and the efficiency of biotechnological processes using the photobioreactor. Figure 9 shows the first test attempts on and off after the set time.
The implemented program uses two steps and two related actions with transition conditions between these two steps. The first step is initialization of the configuration, then checking the condition for the transition to the next step of the program. The program on the controller goes to the second step. In this case, the controller executes only the second program from step two and the actions associated with it. After counting down the experiment time, the program returns to the first step.
Figure 10 shows the pilot works of the photobioreactor automation based on measurement data from the PAR photosynthetic radiation sensor regarding the value of PAR radiation intensity sent to the controller. The experiment involved increasing or decreasing the radiation to a reference value after receiving feedback.
Another pilot experiment involved an attempt to measure the light spectrum at a selected point in the light shell reactor. Figure 11 contains a plan of the measurement points and an example of the light spectrum from the measurement. Diagram (a) shows a single measurement of the relative intensity of PBR radiation. The example measurement point was at a height of 11.5 cm (level 0) from the bottom of the reactor. The measurement was made on the axis of the system. The maximum value falls at a wavelength of about 600 nm. The second graph (b) shows a set of measurement spectra in the axis of the photobioreactor, taken at 1 cm intervals, measured from the bottom of the reactor (level 10) to the culture mirror (level 0).

6. Conclusions

Microalgae have the ability to absorb light from all frequencies in the visible spectrum due to the presence of various pigments: chlorophylls, carotenoids, and phycobilins. However, not all absorbed photons are used for photosynthesis, which affects the efficiency of converting solar energy into products.
Considering various strategies to improve the efficiency of light use by microalgae, from maximizing the quantity and quality of photosynthetically active radiation for photosynthesis, light scattering in cultures, targeted light delivery, cellular engineering introducing genetic changes in organisms to optimize their ability to use light and photosynthesis, to the use of materials that absorb harmful parts of the spectrum, it was decided to design a photobioreactor with a cylindrical fully controlled illumination system.
The proposed control system enables full optimization of the quantity and quality of the type of light in microalgae cultures for selected species, in selected time regimes. Distribution procedures may be predetermined by the operator taking into account the species being reared. Programs can be entered manually with each experiment, or you can use preset recipes. Cultures can be carried out, taking into account the measurement of light distribution inside the photobioreactor, based on data from the immersion PAR measurement sensor and based on the measurement of the light spectrum at any time and in any space of the reactor. The control system will automatically compensate for light distribution based on the operator’s imposed testing regime.
The designed photobioreactor automation system at the University of Agriculture in Krakow enables the creation of hybrid scenarios for research on phototrophic organisms in a closed and strictly controlled system in the PBR. Conducting cultures in such systems can increase the efficiency of PE biomass growth or maximize the growth of desired cell organelles. It is easier to achieve it in closed photobioreactors, especially in the case where given biomatter properties are desirable. The method of providing light to algae cultures in photobioreactors (PBR) is a key aspect affecting the economic viability of mass cultures. The optimal way of providing light should ensure the efficiency of photosynthesis and microalgae growth while minimizing energy costs, which is ensured by our design.
The designed system enables remote control and control over the cultures of many cultures combined with the adjustment of the intensity of light radiation to the density of the cultures. It allows you to simulate sunrise and sunset using the astronomical clock function set for a given type of microalgae from a given latitude of a given species. Ultimately, the work was undertaken on the implementation and use of a system for measuring the light spectrum at each point of the bioreactor using a fibre-optic immersion probe. The maximum value of the relative intensity of radiation falls at a wavelength of about 600 nm for a measurement point located at a height of 11.5 cm from the bottom of the reactor.
The developed design solution was covered by a patent (patent no. 242154) [60].

Author Contributions

Conceptualization B.B. and K.K.; methodology, J.G. and B.B.; software, K.K.; resources, T.H. and F.R.; original draft preparation, B.B.; T.H. and J.G.; visualization, K.K. and F.R. All authors have read and agreed to the published version of the manuscript.

Funding

This paper was financed from the subsidy of the Ministry of Education and Science for the Agricultural University of Hugo Kołłątaj in Krakow for the year 2023.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Acronyms and Abbreviations

PARPhotosynthetically active radiation
PPFDPhotosynthetic Photon Flux Density
DLIDaily Light Integral
PLCProgrammable Logic Controller
DMXDigital Multiplex is a communication protocol that allows for precise control of individual parameters of light sources, such as brightness, colour, or special effects.
EcoStruxure™ Machine ExpertBasic software for programming the Modicon M221 logic controller—modular controller.
Tape LED RGBW SMD 5050Lighting Emitting Diode, SMD Surface Mount Technology LED—denotes the installation variant of the type diode LED.
RTURemote Terminal Unit
LDLadder Diagram
LIInstruction List
GRAFCETGraphic language—a functional diagram showing the operation of the system step by step, detailing the conditions that must be met for the system to be at a given stage (fr. Graphe Fonctionnel de Commande des Étapes et Transitions).
EcoStruxure Machine ExpertBasic engineering design platform for machine automation systems.
SCADASupervisory Control And Data Acquisition—IT system supervising the technological or production process. The system enables the collection of data from devices and machines, their analysis, and visualization over time.
ModbusCommunication protocol is used to communicate with programmable controllers Daisy Chain—a computer network topology in which devices are connected one after the other in a single line to form a chain; in electrical and electronic engineering many devices are connected to each other in sequence or in a ring.
Norm IEC61131Programmable Logic Controllers—INTERNATIONAL STANDARD IEC 61131-3, Second edition 2003-01—an international standard that specifies standards for programmable logic controllers (PLC).

References

  1. Jin, J.; Dupré, C.; Legrand, J.; Grizeau, D. Extracellular hydrocarbon and intracellular lipid accumulation are related to nutrient-sufficient conditions in pH-controlled chemostat cultures of the microalga Botryococcus braunii SAG 30.81. Algal Res. 2016, 17, 244–252. [Google Scholar] [CrossRef]
  2. Sharma, J.; Kumar, S.S.; Bishnoi, N.R.; Pugazhendhi, A. Enhancement of lipid production from algal biomass through various growth parameters. J. Mol. Liq. 2018, 269, 712–720. [Google Scholar] [CrossRef]
  3. Mathimani, T.; Beena Nair, B.; Ranjith Kumar, R. Evaluation of microalga for biodiesel using lipid and fatty acid as a marker—A central composite design approach. J. Energy Inst. 2016, 89, 436–446. [Google Scholar] [CrossRef]
  4. He, P.J.; Mao, B.; Shen, C.M.; Shao, L.M.; Lee, D.J.; Chang, J.S. Cultivation of Chlorella vulgaris on wastewater containing high levels of ammonia for biodiesel production. Bioresour. Technol. 2013, 129, 177–181. [Google Scholar] [CrossRef]
  5. Pancha, I.; Chokshi, K.; Maurya, R.; Trivedi, K. Salinity induced oxidative stress enhanced biofuel production potential of microalgae Scenedesmus sp. CCNM 1077. Bioresour. Technol. 2015, 189, 341–348. [Google Scholar] [CrossRef] [PubMed]
  6. Damiani, M.C.; Popovich, C.A.; Constenla, D.; Leonardi, P.I. Lipid analysis in Haematococcus pluvialis to assess its potential use as a biodiesel feedstock. Bioresour. Technol. 2010, 99, 3389–3396. [Google Scholar] [CrossRef]
  7. Ratomski, P.; Hawrot-Paw, M.; Koniuszy, A.; Golimowski, W.; Kwaśnica, A.; Marcinkowski, D. Indicators of Engine Performance Powered by a Biofuel Blend Produced from Microalgal Biomass: A Step towards the Decarbonization of Transport. Energies 2023, 16, 5376. [Google Scholar] [CrossRef]
  8. Alfonsín, V.; Maceiras, R.; Gutiérrez, C. Bioethanol production from industrial algae waste. Waste Manag. 2019, 87, 791–797. [Google Scholar] [CrossRef] [PubMed]
  9. Da Rosa, M.D.H.; Alves, C.J.; dos Santos, F.N.; de Souza, A.O.; Zavareze, E.d.R.; Pinto, E.; Noseda, M.D.; Ramos, D.; de Pereira, C.M.P. Macroalgae and Microalgae Biomass as Feedstock for Products Applied to Bioenergy and Food Industry: A Brief Review. Energies 2023, 16, 1820. [Google Scholar] [CrossRef]
  10. Kesharvani, S.; Dwivedi, G.; Verma, T.N.; Verma, P. The Experimental Investigation of a Diesel Engine Using Ternary Blends of Algae Biodiesel, Ethanol and Diesel Fuels. Energies 2023, 16, 229. [Google Scholar] [CrossRef]
  11. Huerlimann, R.; de Nys, R.; Heimann, K. Growth, lipid content, productivity, and fatty acid composition of tropical microalgae for scale-up production. Biotechnol. Bioeng. 2010, 107, 245–257. [Google Scholar] [CrossRef] [PubMed]
  12. Hussain, F.; Shah, S.Z.; Ahmad, H.; Abubshait, S.A.; Abubshait, H.A.; Laref, A.; Manikandan, A.; Kusuma, H.S.; Iqbal, M. Microalgae an ecofriendly and sustainable wastewater treatment option: Biomass application in biofuel and bio-fertilizer production. A review. Renew. Sustain. Energy Rev. 2021, 137, 110603. [Google Scholar] [CrossRef]
  13. Alazaiza, M.Y.D.; Albahnasawi, A.; Al Maskari, T.; Abujazar, M.S.S.; Bashir, M.J.K.; Nassani, D.E.; Abu Amr, S.S. Biofuel Production Using Cultivated Algae: Technologies, Economics, and Its Environmental Impacts. Energies 2023, 16, 1316. [Google Scholar] [CrossRef]
  14. Kleiman, R.M.; Characklis, G.W.; Kern, J.D.; Gerlach, R. Characterizing weather-related biophysical and financial risks in algal biofuel production. Appl. Energy 2021, 294, 116960. [Google Scholar] [CrossRef]
  15. Vadiveloo, A.; Kosternik, N.R.; Cosgrove, J.J.; Parlevliet, D.; Gonzalez-Garcia, C.; Lubian, L.M. Phptosynthetic performanceof two Nannochloropsis spp. under different filtered light spectra. Algal Res. 2016, 19, 168–177. [Google Scholar] [CrossRef]
  16. Anto, S.; Mukherjee, S.S.; Muthappa, R.; Mathimani, T.; Deviram, G.; Kumar, S.S.; Verma, T.N.; Pugazhendhi, A. Algae as Green Energy Reserve: Technological Outlook on Biofuel Production. Chemosphere 2020, 242, 125079. [Google Scholar] [CrossRef]
  17. Qiang, H.; Richmond, A. Productivity and photosynthetic efficiency of Spirulina platensis as affected by light intensity, algal density and rate of mixing in a flat plate photobioreactor. J. Appl. Phycol. 1996, 8, 139–145. [Google Scholar] [CrossRef]
  18. Dogaris, I.; Welch, M.; Meiser, A.; Walmsley, L.; Philippidis, G. A novel horizontal photobioreactor for high-density cultivation of microalgae. Bioresour. Technol 2015, 198, 316–324. [Google Scholar] [CrossRef]
  19. Singh, R.N.; Sharma, S. Development of Suitable Photobioreactor for Algae Production—A Review. Renew. Sustain. Energy Rev. 2012, 16, 2347–2353. [Google Scholar] [CrossRef]
  20. Jabłońska-Trypuć, A.; Wołejko, E.; Ernazarovna, M.D.; Głowacka, A.; Sokołowska, G.; Wydro, U. Using Algae for Biofuel Production: A Review. Energies 2023, 16, 1758. [Google Scholar] [CrossRef]
  21. Ullah, K.; Ahmad, M.; Sofia; Sharma, V.K.; Lu, P.; Harvey, A.; Zafar, M.; Sultana, S. Assessing the Potential of Algal Biomass Opportunities for Bioenergy Industry: Review. Fuel 2015, 143, 414–423. [Google Scholar] [CrossRef]
  22. Sukačová, K.; Lošák, P.; Brummer, V.; Máša, V.; Vícha, D.; Zavřel, T. Perspective Design of Algae Photobioreactor for Greenhouses—A Comparative Study. Energies 2021, 14, 1338. [Google Scholar] [CrossRef]
  23. Brzychczyk, B.; Hebda, T.; Pedryc, N. The Influence of Artificial Lighting Systems on the Cultivation of Algae: The Example of Chlorella vulgaris. Energies 2020, 13, 5994. [Google Scholar] [CrossRef]
  24. Brzychczyk, B.; Hebda, T.; Fitas, J.; Giełżecki, J. The Follow-up Photobioreactor Illumination System for the Cultivation of Photosynthetic Microorganisms. Energies 2020, 13, 1143. [Google Scholar] [CrossRef]
  25. Zhang, Y.; Bao, K.; Wang, J.; Chao, Y.; Hu, C. Performance of mixed LED light wavelengths on nutrient removal and biogas upgrading by different microalgal-based treatment technologies. Energy 2017, 130, 392–401. [Google Scholar] [CrossRef]
  26. Hosseini, N.S.; Shang, H.; Scott, J.A. Optimization of microalgae-sourced lipids production for biodiesel in a top-lit gas-lift bioreactor using response surface methodology. Energy 2018, 146, 47–56. [Google Scholar] [CrossRef]
  27. Nwoba, E.G.; Parlevliet, D.A.; Laird, D.W.; Alameh, K.; Moheimani, N.R. Light management technologies for increasing algal photobioreactor efficiency. Algal Res. 2019, 39, 101433. [Google Scholar] [CrossRef]
  28. Schnurr, P.J.; Espie, G.S.; Allen, G.D. The effect of photon flux density on algal biofilm growth and internal fatty acid concentrations. Algal Res. 2016, 16, 349–356. [Google Scholar] [CrossRef]
  29. Kumar, A.; Ergas, S.; Yuan, X.; Sahu, A.; Zhang, Q.; Dewulf, J.; Malcata, F.X.; van Langenhove, H. Enhanced CO2 fixation and biofuel production via microalgae: Recent developments and future directions. Trends Biotechnol. 2010, 28, 371–380. [Google Scholar] [CrossRef]
  30. Chisti, Y. Biodiesel from microalgae. Biotechnol. Adv. 2007, 25, 294–306. [Google Scholar] [CrossRef]
  31. Wei, L.; Huang, X.; Huang, Z. Temperature effects on lipid properties of microalgae Tetraselmis subcordiformis and Nannochloropsis oculata as biofuel resources. Chinese J. Oceanol. Limnol. 2014, 33, 99–106. [Google Scholar] [CrossRef]
  32. Solovchenko, A.E.; Khozin-Goldberg, I.; Didi-Cohen, S.; Cohen, Z.; Merzlyak, M.N. Effects of light intensity and nitrogen starvation on growth, total fatty acids and arachidonic acid in the green microalga Parietochloris incisa. J. Appl. Phycol. 2008, 20, 245–251. [Google Scholar] [CrossRef]
  33. Gim, G.H.; Ryu, J.; Kim, M.J.; Kim, P., II; Kim, S.W. Effects of carbon source and light intensity on the growth and total lipid production of three microalgae under different culture conditions. J. Ind. Microbiol. Biotechnol. 2016, 43, 605–616. [Google Scholar] [CrossRef]
  34. Cheirsilp, B.; Torpee, S. Enhanced growth and lipid production of microalgae under mixotrophic culture condition: Effect of light intensity, glucose concentration and fed-batch cultivation. Bioresour. Technol. 2012, 110, 510–516. [Google Scholar] [CrossRef]
  35. Liu, Z.Y.; Wang, G.C.; Zhou, B.C. Effect of iron on growth and lipid accumulation in Chlorella vulgaris. Bioresour. Technol. 2008, 99, 4717–4722. [Google Scholar] [CrossRef]
  36. Gordillo, F.J.L.; Goutx, M.; Figueroa, F.L.; Niell, F.X. Effects of light intensity, CO2 and nitrogen supply on lipid class composition of Dunaliella viridis. J. Appl. Phycol. 1998, 10, 135–144. [Google Scholar] [CrossRef]
  37. Iqbal, M.; Zafar, S.I. Effects of photon flux density, CO2, aeration rate, and inoculum density on growth and extracellular polysaccharide production by Porphyridium cruentum. Folia Microbiol. 1993, 38, 509–514. [Google Scholar] [CrossRef]
  38. Durairaj, B.; Muthu, S.; Xavier, T. Antimicrobial activity of Aspergillus niger synthesized titanium dioxide nanoparticles. Adv. Appl. Sci. Res. 2015, 6, 45–48. [Google Scholar]
  39. Chen, P.; Min, M.; Chen, Y.; Wang, L.; Li, Y.; Chen, Q.; Wang, C.; Wan, Y.; Wang, X.; Cheng, Y.; et al. Review of the biological and engineering aspects of algae to fuels approach. Int. J. Agric. Biol. Eng. 2009, 2, 64. [Google Scholar]
  40. Markou, G. Effect of Various Colors of Light-Emitting Diodes (LEDs) on the Biomass Composition of Arthrospira Platensis Cultivated in Semi-Continuous Mode. Appl. Biochem. Biotechnol. 2014, 172, 2758–2768. [Google Scholar] [CrossRef] [PubMed]
  41. McGee, D.; Archer, L.; Fleming, G.T.A.; Gillespie, E.; Touzet, N. Influence of Spectral Intensity and Quality of LED Lighting on Photoacclimation, Carbon Allocation and High-Value Pigments in Microalgae. Photosynth. Res. 2020, 143, 67–80. [Google Scholar] [CrossRef]
  42. Ho, S.-H.; Chan, M.-C.; Liu, C.-C.; Chen, C.-Y.; Lee, W.-L.; Lee, D.-J.; Chang, J.-S. Enhancing Lutein Productivity of an Indigenous Microalga Scenedesmus Obliquus FSP-3 Using Light-Related Strategies. Bioresour. Technol. 2014, 152, 275–282. [Google Scholar] [CrossRef] [PubMed]
  43. Singh, S.P.; Singh, P. Effect of temperature and light on growth of algae species: A review. Renevable Sustain. Energy Rev. 2015, 18, 431–444. [Google Scholar] [CrossRef]
  44. Patyna, A.; Witczak, S. Overview of photobioreactors for biodiesel production. Chemik 2016, 10, 634–643. [Google Scholar]
  45. Łaska, G.; Och, B. Microalgae as a Substrate for Biofuel Production. 2013. Available online: www.eko-dok.pl/2013/55.pdf (accessed on 13 February 2023).
  46. Mohler, D.T.; Wilson, M.H.; Fan, Z.; Groppo, J.G.; Crocker, M. Beneficial Reuse of Industrial CO2 Emissions Using a Microalgae Photobioreactor: Waste Heat Utilization Assessment. Energies 2019, 12, 2634. [Google Scholar] [CrossRef]
  47. Deme, M.; Garg, S.; Li, Y.; Narala, R.; Schenk, P.; Sharma, K.; Thomas-Hall, S. Comparison of Microalgae Cultivation in Photobioreactor, Open Raceway Pond, and a Two-Stage Hybrid System. Front. Energy Res. 2016, 4, 29. [Google Scholar]
  48. Available online: www.tme.eu/Document/411c552e8cee3b44c06a65d5c18c2386/HH-RGBWOK-5050GWA.pdf (accessed on 2 April 2023).
  49. Available online: https://www.tme.eu/Document/edc36e305377cbccff0054b95a5edd68/INB-MN-LED-PL.pdf (accessed on 19 July 2023).
  50. Available online: https://led-power.pl/en/kontrolery-dmx/348-kontroler-dekoder-dmx-512-rgb-288576w-12-24v.html (accessed on 17 October 2023).
  51. Available online: www.se.com/pl/pl/product/ABLS1A24031/phaseo-regulowany-zasilacz-impulsowy-100-240-v-ac-24v-3-1-a-1-fazowy-optimized/ (accessed on 7 January 2023).
  52. Available online: https://www.se.com/pl/pl/product/TMC2SL1/modicon-m221-kaseta-komunikacyjna-dodatkowe-%C5%82%C4%85cze-szeregowe-na-bloku-zacisk%C3%B3w-%C5%9Brubowych/ (accessed on 17 October 2023).
  53. Available online: https://www.se.com/ww/en/product/TMC2SL1/serial-line-cartridge-modicon-m221-1-communication-extension/ (accessed on 13 January 2023).
  54. ABLS1A24050—Phaseo, Regulowany Zasilacz Impulsowy, 100...240 V AC, 24V 5 A, 1 fazowy, Optimized|Schneider Electric Polska. Available online: https://www.se.com/pl/pl/product/ABLS1A24050/phaseo-regulowany-zasilacz-impulsowy-100-240-v-ac-24v-5-a-1-fazowy-optimized/ (accessed on 19 July 2023).
  55. Available online: https://https://www.dpstele.com/modbus/rs485-rs232-protocol-data-flow.php (accessed on 17 October 2023).
  56. Available online: https://https://www.apogeeinstruments.com/sq-522-ss-modbus-digital-output-full-spectrum-quantum-sensor/ (accessed on 17 October 2023).
  57. Gebäude Management Folder D10 (resi.cc). Available online: https://www.resi.cc/resipdfdocs/DDC/RESI-DS-RESI-T2-D10.pdf (accessed on 17 October 2023).
  58. RESI Data Sheets. Available online: https://help.resi.io/hc/en-us/articles/4412788142235-Encoder-Setup-and-Data-Sheets (accessed on 17 October 2023).
  59. INTERNATIONAL STANDARD IEC61131. Available online: https://d1.amobbs.com/bbs_upload782111/files_31/ourdev_569653.pdf (accessed on 17 October 2023).
  60. Available online: https://ewyszukiwarka.pue.uprp.gov.pl/search/pwp-details/P.429507?lng=en (accessed on 17 October 2023).
Figure 1. Scheme of the work algorithm for the photobioreactor project.
Figure 1. Scheme of the work algorithm for the photobioreactor project.
Energies 16 07183 g001
Figure 2. Scheme of the device’s AC power supply.
Figure 2. Scheme of the device’s AC power supply.
Energies 16 07183 g002
Figure 3. Scheme of connecting the PLC controller with a PC computer.
Figure 3. Scheme of connecting the PLC controller with a PC computer.
Energies 16 07183 g003
Figure 4. Diagram of LED strip communication. Source: own elaboration.
Figure 4. Diagram of LED strip communication. Source: own elaboration.
Energies 16 07183 g004
Figure 5. The diagram of electrical and signal connections. Source: own elaboration.
Figure 5. The diagram of electrical and signal connections. Source: own elaboration.
Energies 16 07183 g005
Figure 6. (a) Schematic diagram of the automation of the follow-up lighting system for phototrophiccultures of the bioreactor, (b) physical model of automation.
Figure 6. (a) Schematic diagram of the automation of the follow-up lighting system for phototrophiccultures of the bioreactor, (b) physical model of automation.
Energies 16 07183 g006
Figure 7. Schematic diagram of the lighting system. Source: own elaboration.
Figure 7. Schematic diagram of the lighting system. Source: own elaboration.
Energies 16 07183 g007
Figure 8. Cylindrical lightcoat. Source: own study.
Figure 8. Cylindrical lightcoat. Source: own study.
Energies 16 07183 g008
Figure 9. Test trials of the control in the on–off system with the active day–night lighting system.
Figure 9. Test trials of the control in the on–off system with the active day–night lighting system.
Energies 16 07183 g009
Figure 10. Control test trials—adjust the radiation intensity after obtaining a response from the quantum sensor.
Figure 10. Control test trials—adjust the radiation intensity after obtaining a response from the quantum sensor.
Energies 16 07183 g010
Figure 11. Measurement points for the discretization of the photosynthetically active PAR radiation intensity spectrum: (a) single measurement of the relative intensity of PBR radiation, (b) a set of measurement spectra in the axis of the photobioreactor, taken at 1 cm intervals.
Figure 11. Measurement points for the discretization of the photosynthetically active PAR radiation intensity spectrum: (a) single measurement of the relative intensity of PBR radiation, (b) a set of measurement spectra in the axis of the photobioreactor, taken at 1 cm intervals.
Energies 16 07183 g011
Table 1. Characteristics of the RGBW LED strip. Source: own elaboration based on technical documentation [48].
Table 1. Characteristics of the RGBW LED strip. Source: own elaboration based on technical documentation [48].
Drawing/PhotoInformation/DescriptionHH-SRGBW96F012W24-5050 RGBW
Energies 16 07183 i001Led tapeCombination of 5050 RBG + 5050 white colour in one strip
12 mm wide strip-96 LEDs per meter
compatible with most controllers
input voltage 24 V CD
Maximum power 23 W·m−1
Colour:
WW/NW (3000 K/4000 K/5000 K)
R (635 nm) G (515 nm) B (465 nm)
4in1 (6000 K)
Efficiency WW/NW 68 lm·W−1
4in1 40 lm·W−1
Brightness WW/NW 1564 lm
4in1 920 lm
Length 5 m
Size 5000 mm.12 mm
IP65 protection class
Table 2. Characteristics of the power supply for PMW series LEDs. Source: own elaboration based on technical documentation [49].
Table 2. Characteristics of the power supply for PMW series LEDs. Source: own elaboration based on technical documentation [49].
Drawing/PhotoInformation/DescriptionPWM-120-24
Energies 16 07183 i002Power supply for LEDsPSU typepulsed
Applicationfor LED strips
Power supply typeDC
PropertiesPWM output;
rated performance at full load
Tightness classIP67
Number of outputs1
Electrical connectionwires 300 mm
Power consumption without load<0.5 W
Table 3. Characteristics of the DMX 512 RGBW 192/384 W 12–24 V decoder controller. Source: own elaboration based on technical documentation [50].
Table 3. Characteristics of the DMX 512 RGBW 192/384 W 12–24 V decoder controller. Source: own elaboration based on technical documentation [50].
Drawing/PhotoInformation/DescriptionController DMX 512 RGBW Decoder
Energies 16 07183 i003DMX 512 LED controllerController Decoder DMX 512 RGBW 192 W/384 W 12–24 V
Support 512 independent channels
Support for RGBW Strips or other 12–24 V RGBW light sources
DMX 512 signal output input
RJ45 signal connection interface
Voltage supported: 12–24 V
Maximum power: 16 A (4 × 4 Amps)
Operating temperature: −20–60 °C
Dimensions (L/W/H): (177 × 42 × 33) mm
to the PWM signal to control the lighting.
Table 4. Characteristics of the PLC, Modicon™. Source: own elaboration based on technical documentation of Schneider Electric [51].
Table 4. Characteristics of the PLC, Modicon™. Source: own elaboration based on technical documentation of Schneider Electric [51].
Drawing/PhotoInformation/DescriptionTM221C24T
Energies 16 07183 i004PLC driverTM221C24T (screw) 14 sink/source inputs, 10 transistor outputs (0.5 A), 2 logic inputs, 1 serial line port, 24 VDC power controller with removable terminal blocks:
5 V: 520 mA/24 V: 200 mA
Table 5. Characteristics of the Modicon M221 serial insert communication extension. Source: own elaboration based on technical documentation of Schneider Electric [53].
Table 5. Characteristics of the Modicon M221 serial insert communication extension. Source: own elaboration based on technical documentation of Schneider Electric [53].
Drawing/PhotoInformation/DescriptionTMC2SL1
Energies 16 07183 i005Modicon M221 serial insertTMC2 cassette with 1 serial line (RS 232 or RS 485)
Table 6. Characteristics of the switching power supply for PLC. Source: own elaboration based on technical documentation of Schneider Electric [54].
Table 6. Characteristics of the switching power supply for PLC. Source: own elaboration based on technical documentation of Schneider Electric [54].
Drawing/PhotoInformation/DescriptionABLS1A24031
Energies 16 07183 i006Adjustable switching power supply for PLCAdjustable switching mode
rated input voltage 100 V to 240 V AC single phase
100 … 240 VAC 2 phase
140 … 340 VDC
rated power 75 W
output voltage 24 V DC
power supply output current 3.13 A
Table 7. Characteristics of the SQ-522-SS Modbus Digital Output Full-spectrum Quantum Sensor. Source: own elaboration based on [56].
Table 7. Characteristics of the SQ-522-SS Modbus Digital Output Full-spectrum Quantum Sensor. Source: own elaboration based on [56].
Drawing/PhotoInformation/DescriptionSQ-522-SS
Energies 16 07183 i007Immersion photosynthetically active PAR sensorThe SQ-522-SS model is based on the Modbus RTU communication protocol
input voltage 5.5 V to 24 V DC
average maximum current consumption RS 232 37 mA;
RS 485 quiescent 37 mA, active 42 mA
180° field of view
spectral range 389 nm to 692 ± 5 nm
working environment −40 to 70 °C; 0% to 100% relative humidity; can be submerged in water to a depth of 30 m
dimensions diameter 30.5 mm, height 37.0 mm
5 m shielded twisted pair cable; TPR jacket (high water resistance, high UV stability,
flexibility at low temperatures); pigtail wires; stainless steel (316), M8 connector
Table 8. Characteristics of an ultrathin IO module with a serial interface. Source: own elaboration based on technical documentation [58].
Table 8. Characteristics of an ultrathin IO module with a serial interface. Source: own elaboration based on technical documentation [58].
Drawing/PhotoInformation/DescriptionSerial IO ULTRA SLIM Module
Energies 16 07183 i008Serial module for controlling the DMX-512 lighting systemdimensions: (17.5 × 90 × 58) mm
protocols:
MODBUS/RTU subprotocol
simple ASCII text protocol
baud rates: from 300 bd to 256,000 bd
none/even/odd—parity
one or two stop bits
power supply: 12–48 V
power consumption: 0.5 W
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Brzychczyk, B.; Giełżecki, J.; Kijanowski, K.; Hebda, T.; Rzepka, F. Automation of the Photobioreactor Lighting System to Manage Light Distribution in Microalgae Cultures. Energies 2023, 16, 7183. https://doi.org/10.3390/en16207183

AMA Style

Brzychczyk B, Giełżecki J, Kijanowski K, Hebda T, Rzepka F. Automation of the Photobioreactor Lighting System to Manage Light Distribution in Microalgae Cultures. Energies. 2023; 16(20):7183. https://doi.org/10.3390/en16207183

Chicago/Turabian Style

Brzychczyk, Beata, Jan Giełżecki, Krzysztof Kijanowski, Tomasz Hebda, and Filip Rzepka. 2023. "Automation of the Photobioreactor Lighting System to Manage Light Distribution in Microalgae Cultures" Energies 16, no. 20: 7183. https://doi.org/10.3390/en16207183

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop