development and performance analysis of iot based real

Development and Performance Analysisof IoT Based Real Time Solar PV

Monitoring System

N Ragupathi Muthu1, D Devaraj2,1 PG Student, Department of EEE

2 Sr. Prof., Department of EEE,Dean SEET & Director - Academic

1,2 Kalasalingam Academy of Researchand Education Krishnankoil, India.

Email:[email protected]

July 4, 2018

Abstract

The energy demand and therefore the environmentalpollution are the most important boundaries for the hu-man improvement. Non-conventional energy methodologiesnowadays are harnessed for electricity generation which areconsistent and price reasonable with the standard fuel powerproducers. Nowadays, solar PV power generation is assum-ing increased importance as a natural source. To with ef-ficiency draw power from a collection of solar photovoltaicpanel during a large field we need a lot of electronic circuitsand power electronics parts which are subject to faults, theclimatic condition can also cause faults. Each little faultinside a PV plant will cut back yield and quickly lead tovital monetary losses. The projected system uses the In-ternet of Things Technology and MATLAB software for ob-serve solar Photo Voltaic power generation to reinforce theperformance, maintenance and fault detection of the plant.The voltage, current, temperature, and irradiance, are mea-sured by the sensors. The sensor data are transmitted to

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International Journal of Pure and Applied MathematicsVolume 120 No. 6 2018, 6905-6923ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

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a web server via the internet. The webpage will show theinstant status of the sensor data. It helps to monitor powergeneration and plant condition. This monitoring is donethrough ESP8266 processor and fault detection is done us-ing the MATLAB. This may change precautionary mainte-nance, fault identification of the plant additionally to realtime monitoring.

Keywords: Solar PV system, Web Monitoring, Internetof Things, MATLAB Analysis, Fault Detection

1 Introduction

The present power industries primarily works with conventional en-ergy sources like coal, oil, natural gases or uranium. But, it has lotof drawbacks with them, they produce several kinds of pollutions,and leads to loss of non-conventional resources. There are largequantity of potential obtainable within the renewable energy sys-tem which might be explored and controlled to fulfill the energydemand. One among the natural resource is solar power and thereare many ways in which to use it. One among them is to comeup with electricity. In India as on thirty first October month 2017,the entire solar mounted capability stood at 60158 MW. Solar PVsystem Monitoring and controlling is essential for reliable operationand maximum power generation of any solar photovoltaic system.The simplest monitoring of PV plant is by reading values on in-verter display. Parameters like PV system power, grid voltage, andPV array current are usually available. For PV system monitoringand control purposes environmental data - like panel temperature,solar irradiation, ambient temperature, and wind speed are alsoneeded. This huge scale of solar Photovoltaic electrical power gen-eration needs refined systems for automation of the plant observingremotely using internet based interfaces as majority of them areinstalled in unreachable locations and therefore unable to be mon-itored from a dedicated location. The target of the work is todevelop a system for monitoring the solar PV system.Rahman MM, Selvaraj J, et al. [1] give an overview of variousPV monitoring systems based on different technologies. There arevarious technologies developed for PV monitoring and control, for

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commercial use / research activities. Ngo, Genevieve C., et al. [2]explain about a real-time observing system for the grid connectedsolar PV system installation. The system contains a BeagleBoneBlack that is the device to method the measured value from thevarious power analyzers and the sensing elements. It conjointlyoptions an internet based and Mobile based visualization and ana-lytics platform for user utilization, and provides a statement rule forthe users projected monthly utilization. One amongst the receivingends could be a server that stores the information and hosts theweb application that aggregates, evaluates and presents the over-all power generation and grid consumption to the user. The otherreceiving end, a mobile application, visualize the real-time graphof the generated power and the total energy consumed by the con-sumer.

Forero, N., J. Hernndez, and G. Gordillo. [3] discusses a systemestablished for checking solar PV system generation with help ofa novel technique supported virtual instrumentation method. Themeasurements and process of the data are made using high accu-racy I/O modular field point (FP) equipment as hardware, a datafetching device as software and the package of graphic program-ming, LabVIEW. The scheme is capable to store and visualize theclimatic variables and the solar Photovoltaic system electrical vari-ables, including the plant V-I characteristics. The major aspectof this work is the enlargement of a unit that permits automaticmeasuring of the solar plant V-I curve using a car battery as powersource. The system has been in operation during the last two yearsand all its units have performed well. Kumar, Praveen, and UmeshChandra Pati. [4] Proposed a smart observing and control of thehome appliances as well as door authorization system for interfacebetween the guest and house/office vendor. The control and statusmonitoring (ON/OFF of the appliances) have been implementedusing various ways such as wireless equipment, switches, web, andGUI interface. Using this methodology, the consumer can decreasethe wastage of electrical power by regular monitoring of home ap-pliances or the proper ON/OFF preparation of the devices.Adhya, Soham, et al. [5] used the Internet of Things Technologyfor supervision solar PV electricity generation which might greatlyimprove the performance, observation and maintenance of the plant

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state. With improvement of technologies, the price of renewable en-ergy instrumentation is returning down globally encouraging hugescale solar PV integration. The discussion in this paper is based onimplementation on IoT based latest price effective methodology toremotely monitor a solar photovoltaic plant for performance anal-ysis.The target of this work is to implement the monitoring system for asolar PV System, using Internet of Things. Solar panel power gener-ation and environmental conditions, collection of electrical param-eters and environment parameters are monitored by using sensors,and the data is sent to the cloud storage platform and visualizationis done through a web page and to carryout fault detection usingMATLAB.

2 PROPOSED METHODOLOGY

The work objective is to observe condition of the solar PV powergeneration plant by using Internet of Things. Figure 1 shows theproposed IoT based monitoring system.

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2.1 System Description

Fig. 1: Proposed System Block Diagram

The system consists of temperature sensing element, Irradiancesensing element, DC Voltage sensing element, DC current sensingelement. The power generated by the solar panel depends uponthe provision and intensity of sun then the performance of the so-lar panel depends on atmospheric conditions. Temperature sen-sor is employed for temperature observation and Irradiance sensingelement is employed for sun intensity level activity. The powergenerated by the solar panel will be measured by using DC voltagesensing element and DC current sensing element. These sensors areconnected with a Microcontroller. An ESP8266 Microcontroller isemployed for interfacing sensors with host network. With the as-sistance of web and Microcontroller, the sensing element data aretransmitted to a cloud storage through the internet. The sensorsdata, voltage and current data are updated to the cloud server byusing internet. With the help of cloud storage platform the storeddata can be used for the plant performance analysis, plant faultanalysis, plant control, and can generate monthly power generationreport by an authorized person from anywhere at any time by using

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internet. The cloud datas will be displayed in the form of graphin a webpage, and the cloud datas can be fetch in CSV/html/txtetc. format. This can be accessed from remote locations throughinternet. This cloud data are used to detect fault in solar plant.

2.2 Cloud Setup

ThingSpeak is a freely available IoT application and API (Applica-tion Programming Interface) to store and retrieve data from cloudstorage with the help of the hypertext transfer protocol over theweb or through a Local Area Network. ThingSpeak offer logging ofsensor data, location following, and a social network of things withcondition updates.First the user account is formed. The account contains channelsthat are separate for various works. Channel has the fields that aredifferent for various parameter within the monitoring system. Afterassigning the parameter the system transmit the values to it. Thecloud has integral functions in it that represent the values withinthe graphs format. A channel is the source for the data. Wherewe can store and retrieve data. A channel can have maximum 8fields. It means we can store 8 different data to a channel. Herewe are creating channel to stored data from sensor. Channel Id isthe identity of the channel. API keys are the keys to access to thechannel. We can access the channel in two ways. API Write Keywill be used to update the data, API Read Key will be used toretrieve the data.

2.3 Simulation Setup

Fig. 2: Overview of simulation setup

The simulation model is designed as per the real time data collec-tion plant description. The simulated solar plant is designed like

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real time plant specification. Solar panel inputs are Irradiation,and Temperature. Here the simulated solar plant input is real timesolar irradiation and temperature values collected form the cloudstorage. Therefore the simulated solar plant gives the output forthe real time irradiation and temperature. This output is comparedwith the actual plant output. Based on the comparison the faultpercentage will be calculated.

3 IMPLEMENTATION

3.1 Work Flow

Fig. 3: Proposed system work flow

The solar PV plant voltage is step down by using transducer,then the step down voltage is measured by the voltage sensor. ThePV current, atmosphere temperature and irradiance are measured

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by the current sensor, temperature sensor and irradiance sensor re-spectively. The sensing element and circuit are hook up with theESP8266 microcontroller. The Microcontrollers calculate the sen-sor value as per the programming. Then the data are send to thecloud storage platform with help of internet.

3.2 Hardware Setup

The ESP8266 Microcontroller fetch the Irradiance, Temperature,PV current and PV voltage data through Analog pins from thesensing devices. With the assistance of those sensing devices val-ues, Microcontroller calculates the atmosphere Temperature, Irra-diation, Solar PV plant Current and Voltage. The microcontrollertransmit the Output data to the web server through Internet. Thewebpage displays the sensing element values.The Irradiance sensor is placed in the solar panel tilt angle [Fig.4]. Therefore it can measure the solar irradiance level fall on thatparticular tilt angle. The sensor output is in terms of voltage.Sensor output voltage depends upon the solar radiation. The Tem-perature sensor measures the temperature. This module output isin Volts. It is converted in to the corresponding temperature bythe microcontroller programming. The Voltage sensor and CurrentSensors measure the solar panel voltage and current. These sensoroutputs are read by the ESP8266 microcontroller [Fig.5]. The mi-crocontroller processes the data as per the programming. Then theprocessed data is sent to the cloud using Internet.

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Fig. 4: Irradiance sensor setup

Fig. 5: Microcontroller setup

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Fig. 6: Hardware setup

3.3 Software Details

The freely available Arduino IDE programming software (IDE) isemployed during this system to transfer the code on to board. Thesensing element and circuit are connected to the ESP8266 Micro-controller. We wrote the C language programming in Microcon-troller for sensing and calculating the data from sensors.

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Fig. 7: Workflow of proposed work

Step 1: Sensor Analog Data is read in the A0 pinStep 2: That analog value is converter into digital value by theinbuilt ADC.Step 3: The ADC output value is scaling by the formula:Read = Analog Read (A0) x (Sensor Supply Voltage / 1024);Step 4: Scaled value is sent to the Thingspeak Cloud Platform byusingThingSpeak.writefield (mychannelNumber, 1, Read, myWriteAPIkey);Step 5: The cloud data is collected from the cloud storage in CSVformatStep 6: The collected data is used as a simulated PV module inputStep 7: Simulated module output real time data is compared toidentify the fault.

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4 RESULT AND DISCUSSION

The real time data is collected from a 1kW solar PV plant. It has10 numbers of 100Wp solar PV modules. Each panels are 100Wppanels. Plant output are 36 volt, 28.5 amps. The results of thesystem is displayed on the web page and the format is current inamperes, voltage in volts, irradiance in W/m2 and temperature inCelsius with respect to date and time. The sensing element datais transmitted to the cloud. Its stored in separate fields. Everyfields shows the individual graphs as shown in Fig. 8, 9, 10, &11. Graphs emphasize the main point, make the data additionalconvincing and deliver a compact method of presenting informationto the users. Graphs are schemed for current, irradiance, voltage,and temperature data with respect to time and date. Graphs areaccessed through web from anyplace. These datas can be accessedin the form of CSV file also. The authorized person can downloadthese data from the cloud storage.

Fig. 8: Solar panel current visualization

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Fig. 9: Solar irradiance visualization

Fig. 10: Solar panel voltage visualization

Fig. 11: Temperature visualization

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Fig. 12: Simulink model of the system

The cloud datas are used for the MATLAB Simulink based anal-ysis. The real time plant power generation datas and simulated so-lar PV plant datas are compared. The power generation deviationbetween real time and simulated module helps to know the faultplant percentage and plant performance analysis.

Fig. 13: Simulation model of the system

The cloud datas are used to analyze the fault detection in solarsimulation module in MATLAB. The real time sensor data collected

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from the cloud is used for the simulation module input. That sim-ulated PV module output and the real time solar plant outputs arecompared in the MATLAB identify the output deviation.[Table 1].

Table 1: Real Time Plant Generation and Simulation OutputComparison

5 CONCLUSION

Renewable energy technologies these days are harnessed for elec-tricity generation. Now a days the solar PV power generation is as-suming increased importance as a natural energy source. The SolarPV power generating station having a set of series and parallel as-sociation of solar PV panels. Each small fault among a PV powergenerating station will scale back yield and quickly lead to vitalmonetary losses. To induce the primary alert of faults and creepingchanges, observance and control of a solar PV system electricitygeneration station through a centralized control room is necessary.By this manner the authorized person will introduce maintenanceprocesses and repairs at an early stage and so, avoid expensivedamages. Central observing and management is therefore a nec-essary a part of preventive maintenance. Our work is to monitorthe solar Photovoltaic (PV) plant using Web Monitoring and faultdetection using MATLAB. The sensors are used for the solar plantgeneration measurement and atmosphere condition measurement.The authorized person can monitor the plant condition through awebpage from anywhere with the help of internet. The web basedmonitoring helps to monitor the Solar PV plant energy generation.The CSV file from the cloud is taken for analysis. The cloud in-formation is employed for fault detection by using the MATLABsoftware. This study is evaluated in MATLAB Simulink R2015a

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and through real time implementation, the results are verified.In future the panel monitoring can be carried out for analysis offault in solar PV plant, controlling of plant and predicting the fu-ture values of the parameters considered. The web application areoften developed for interaction with the user; the user may predictvalues of the future events. Within the same approach we will optfor android application also.

References

[1] Rahman MM, Selvaraj J, Rahim NA, Hasanuzzaman M.Global modern monitoring systems for PV based power gener-ation: A review. Renewable and Sustainable Energy Reviews,Elsevier. 2017 Nov 9.

[2] Ngo, Genevieve C., Judd Kristian I. Floriza, Christine MayC. Creayla, Felan Carlo C. Garcia, and Erees Queen B.Macabebe. ”Real-time energy monitoring system for grid-tiedPhotovoltaic installations.” In TENCON 2015-2015 IEEE Re-gion 10 Conference, pp. 1-4. IEEE, 2015.

[3] Forero, N., J. Hernndez, and G. Gordillo. ”Development of amonitoring system for a PV solar plant.” Energy Conversionand Management 47.15 (2006): 2329-2336, Elsevier.

[4] Kumar, Praveen, and Umesh Chandra Pati. ”IoT based mon-itoring and control of appliances for smart home.” In RecentTrends in Electronics, Information & Communication Technol-ogy (RTEICT), IEEE International Conference on, pp. 1145-1150. IEEE, 2016.

[5] Adhya, Soham, et al. ”An IoT based smart solar photovoltaicremote monitoring and control unit.” Control, Instrumenta-tion, Energy & Communication (CIEC), 2016 2nd Interna-tional Conference on. IEEE, 2016

[6] Ali, Mohamed Hassan, et al. ”Real Time Fault Detection inPhotovoltaic Systems.” Energy Procedia 111 (2017), Elsevier:914-923.

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[7] Meliones, Apostolos, and AngelikiNouvaki. ”A web-based ser-vice backend for control and monitoring of solar parks.” In-dustrial Informatics (INDIN), 2012 10th IEEE InternationalConference on. IEEE, 2012.

[8] Adhya, Soham, et al. ”An IoT based smart solar photovoltaicremote monitoring and control unit.” Control, Instrumenta-tion, Energy & Communication (CIEC), 2016 2nd Interna-tional Conference on. IEEE, 2016.

[9] Luo, Yi-You, and Guo-Ping Liu. ”Application of feedbackcontrol on the cloud-based web simulation system.” IFAC-PapersOnLine 50.1 (2017): 343-348.

[10] Corbellini, S., Di Francia, E., Grassini, S., Iannucci, L., Lom-bardo, L., &Parvis, M. (2017). Cloud based sensor network forenvironmental monitoring. Measurement.

[11] Forero, N., Hernndez, J., & Gordillo, G. (2006). Developmentof a monitoring system for a PV solar plant. Energy Conversionand Management, 47(15), 2329-2336.

[12] Punitha, K., D. Devaraj, and S. Sakthivel. ”Artificial neuralnetwork based modified incremental conductance algorithm formaximum power point tracking in photovoltaic system underpartial shading conditions.” Energy 62 (2013): 330-340.

[13] Khera, Neeraj, et al. ”Development of photovoltaic moduletracking and web based data acquisition system.” Appliedand Theoretical Computing and Communication Technology(iCATccT), 2016 2nd International Conference on. IEEE, 2016.

[14] Kumar, Praveen, and Umesh Chandra Pati. ”IoT based mon-itoring and control of appliances for smart home.” RecentTrends in Electronics, Information & Communication Tech-nology (RTEICT), IEEE International Conference on. IEEE,2016.

[15] Sigrist, Lukas, et al. ”Measurement and validation of energyharvesting IoT devices.” 2017 Design, Automation & Test inEurope Conference & Exhibition (DATE). IEEE, 2017.

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[16] Shrihariprasath, B., and VimalathithanRathinasabapathy. ”Asmart IoT system for monitoring solar PV power conditioningunit.” Futuristic Trends in Research and Innovation for SocialWelfare (Startup Conclave), World Conference on. IEEE, 2016.

[17] Correia, Daniel, et al. ”Monitoring system for small sized pho-tovoltaic power plants.” Information Systems and Technologies(CISTI), 2016 11th Iberian Conference on. IEEE, 2016.

[18] Tiwari, Shruti, and R. N. Patel. ”Real time monitoring of so-lar power plant and automatic load control.” Engineering andSystems (SCES), 2015 IEEE Students Conference on. IEEE,2015.

[19] Ngo, Genevieve C., et al. ”Real-time energy monitoring systemfor grid-tied Photovoltaic installations.” TENCON 2015-2015IEEE Region 10 Conference. IEEE, 2015.

[20] Xiaoli, Xu, and QiaoDaoe. ”Remote monitoring and controlof photovoltaic system using wireless sensor network.” ElectricInformation and Control Engineering (ICEICE), 2011 Interna-tional Conference on. IEEE, 2011.

[21] De Jun, Li, Liu Jie, and Tian Yu Kang. ”Research on SolarPhotovoltaic Surveillance System Base on Network.” Intelli-gent Systems Design and Applications, 2008. ISDA’08. EighthInternational Conference on. Vol. 1. IEEE, 2008.

[22] Oh, Jin Seok, et al. ”Web-based real-time sensor monitor-ing system using Smart Client.” Strategic Technology, 2007.IFOST 2007. International Forum on. IEEE, 2007.

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development and performance analysis of iot based real

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