Simulation modeling and experimental validation of solar photovoltaic PMBLDC motor water pumping sys

Abstract

Keywords: Renewable energy; Photovoltaic panel; Simulation; Solar PMBLDC motor water pumping system; Error analysis

Introduction

A rapid increase in industrialization and population has almost doubled the energy demand of India. India’s total installed capacity is 349.3 GW as on 31 January

2019, in which thermal energy contribution is 63.7 %, Nuclear is 1.93 %, hydro energy 12.85 %, and contribution of renewable energy is 21.14 % [1]. To meet India’s huge power requirement, the sustainable solution is maximizing

*Corresponding author. *E-mail address: deokarvinay@gmail.com This paper was recommended for publication in revised form by Regional Editor Mustafa Kılıç Published by Yıldız Technical University Press, İstanbul, Turkey Copyright 2021, Yıldız Technical University. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

renewable energy potential. Solar power has emerged as a prominent source of green energy in all renewable energy sources, which will contribute to the growth of countries like India. For 1 kW electricity generation using non-renewable energy sources 1 kg of CO2 is emitted in the environment which is very harmful to living organs. There are huge energy crises in India and only 10 h of energy is available for the agricultural sector in alternate day and night time which is insufficient. Mostly diesel engine water pumps are used in the absence of grid energy which is harmful to the environment. Therefore, there is a large scope to tap solar energy for the fulfillment of energy needs. India is aiming for a high rise in tapping renewable energy potential to reach 175 GW by 2022 excluding large hydropower plants. The average intensity of irradiation available in India is 4–7 kWh/m2 for 250–300 days [2, 3]. The solar water pumping system is a prominent way to meet water demands by using clean energy. The huge running cost is associated with the system running on-grid energy or on diesel engines which can be minimized by using the solar energy water pumping system. A well optimum sized Photovoltaic systems additional advantage is in the form of the reduced payback period. Simulation helps in the optimum designing of the system as per the water requirement. The solar photovoltaic system is one way to convert solar energy into electric energy which is subsequently used in the number of applications [4, 5]. For Simulation two internal characteristics series and parallel resistance (Rs and Rp) are the most important parameters, and the Simulink model of the photovoltaic panel with these two parameters gives the best results [6–17]. As the PV panel output and characteristics are non-linear these should be modeled with the maximum power point tracker (MPPT) which figure out the best suitable output as per load requirement [18–19]. The solar photovoltaic water pumping system is one of the popularity gaining application now a day’s as its running maintenance cost is very negligible as compared to diesel engines. The payback period of the solar photovoltaic water pumping system is generally 12 years and the expected life of the system is 25 years. The simulation of the solar PV water pumping system consists of the number of subsystems like PV panel, MPPT, motor, and pump [20–27]. Brushed DC motor or AC induction motors are mostly used in solar water pumping but brushes of brushed DC motor needs to be replaced frequently, and for induction motor inverter is needed as it runs on AC supply whereas PV panels output is DC only [28–37]. In this context, this work presents the use of a solar photovoltaic submersible permanent magnet brushless DC motor (PMBLDC) water pumping system. The objective of this study is optimum designing and installation of the solar photovoltaic water pumping system which will operate efficiently and fulfill water requirements in the remote areas by using a clean solar energy source. Optimum system

design will result in reduced overall system cost so that the payback period will also minimum. Also, the minimum running maintenance cost for the system is expected. By keeping objectives in mind 0.5 hp PMBLDC solar water pumping system is proposed which runs on clean renewable solar energy only. This will help to reduce CO2 emissions in the environment. Especially to overcome the maintenance of frequent brush changing in brushed DC motor and eliminating inverter to convert DC to AC as it runs directly on DC. The use of energy storing devices avoided minimizing initial as well as the maintenance cost of the system. Step by step detailed modeling of the subsystems like photovoltaic panel, MPPT, PMBLDC motor, and the pump was carried out in MATLAB/Simulink. All the subsystems connected and the entire Simulink model of solar photovoltaic water pumping system presented. Furthermore Experimental setup of components used in the simulation was built. The optimum value of irradiation for an efficient system of working found out. Simulation results of the proposed system validated with the help of experimental results obtained by extensive experimental field trials and presented with error analysis.

Modeling Of Photovoltaic Pmbldc Motor Water Pumping System

The photovoltaic water pumping system consists of the number of components like the PV panel for energy conversion, Buck-Boost converter, PMBLDC motor, and the pump. Modeling and simulation of individual subsystems are carried out separately and then these are combined to get a complete system. Mathematical Model of Photovoltaic Panel Figure 1 shows a practical model with series and parallel resistance used for PV panel modeling. In this model, the effect of Rs and Rp is considered as the efficiency of the PV solar cell gets affected due to these parameters [6, 7]. By applying Kirchhoff ’s law, I = Iph - Id - Ip

The total output current of a PV panel I calculated using the above equation [6].

PV panel photocurrent Iph is calculated using the equation  Isc + Ki (Top − Tref )  * G /1000 Iph =

Where G is irradiation (W/m2), Ns is the number of cells in series, Tref is a reference temperature taken (25 oC) [6]. Diode current Id is calculated with using the equation   V + Irs   = Id Is exp   − 1   NsAVt   Vt =

the PV panel is carried out by using mathematical equations 1 to 8. Photocurrent Iph calculated at the beginning based on irradiation (G) and operating temperature (Top) as shown in Figure 2. The input parameters and their respective constant values used for simulation are shown in Figure 3. The Vt and Irs calculated based on Top and Voc as shown in Figure 4 & 5. Panel saturation current (Is) calculated by taking the output of the Irs as shown in Figure 6.

 q * Eg  1  Top  1  Is Irs   exp  Ak  Tref − Top   Tref     

Where Vt is the thermal voltage depending on the operating temperature Top and Is panel saturation current. V is the output voltage of the panel [7]. Irs is calculated using the equation Irs =

The output current I of the PV panel calculated using the equation   V * Irs   V + IRs I = Iph − Is exp   − 1 − Rp   NsAVt  

Simulink Modelling of the PV Panel Eldora VSP.72.AAA panel data is used as a reference data panel for the simulation. Table 1 shows the details of the specifications. The step by step Simulink modeling of

Experimental Setup And Testing

The Solar Photovoltaic Water pumping experimental setup consists of three major components solar panel, Buck-Boost Converter, and PMBLDC motor pump which is described as follows [32–34]. Solar Panel For driving 0.5 hp PMBLDC motor pump Eldora VSP.72.AAA PV panel is used, Fig 18 (A) shows this panel. The maximum power output of the panel at the standard testing condition (STC) is 320 W. Parametric specifications of the PV panel are as per Table 1. The panel is selected by considering the Buck-Boost converter and PMBLDC motors input requirements. For the efficient work of the Buck-Boost converter, the input voltage should be in the range from 24 V to 48 V and the selected PV panel meets this requirement. The panel is capable to give the required input to the converter for continuous pump operation as the irradiation reaches 330 W/m2. Buck-Boost Converter Buck-Boost converter is used to maximize power extraction from the PV panel. Buck-Boost converter is shown in Figure 18 (B). The dry run sensor is fitted at the top of the pump in which a circuit breaker is used. Whenever there is sufficient water in the source then the sensor gives the signal for the starting of the motor, on the other side whenever the water level falls below the sensor then it gives a signal for stopping the motor. After 10 minutes converter gives the signal to start the motor and it again checks the dry run sensor signal. If there will be sufficient water in the source then and then only the motor starts. The converter starts the motor only when there is sufficient input voltage present at the PV panel output and stops the motor when it’s less than the input requirement of the motor.

Figure 18. A) Solar PV 320 W panel B) Buck-Boost Converter C) PMBLDC motor submersible pump.

PMBLDC Motor Pump For small applications like livestock drinking water, garden fountains PMBLDC motors are used. For the same size, the reliability and efficiency of the DC system are higher than the AC system. Figure 18 (C) shows the 0.5 hp PMBLDC submersible pump used for field trials. Table 2 shows the specifications of the PMBLDC motor submersible Pump. The pump normally takes 27 V and 2.7 A input. The current consumption of the motor increases as the head goes on increasing and it tries to keep the discharge maximum. Data Logger and Sensors The data logger system is used for measuring and recording the irradiation, water flow, voltage, and current observations. For water flow measurement rotor type electronic water flow sensor is used. The observations of the experimental setup are continuously monitored, processed, and stored in the memory of the data logger.

Experimental Setup

Location of the experimental setup Place – A/P-Vadanage, Taluka – Karvir, District – Kolhapur, Maharashtra, India, 416229 Latitude angle of location – 16.7o N A 320 W solar PV panel was fitted on a steel structure at a latitude angle 16.7o with due south. The output of the panel was given to the MPPT to which a 0.5 hp PMBLDC motor submersible pump was connected. It is used to lift water from the source. The total lift of the water was 12 m. Figure 19 shows the schematic diagram of the experimental setup.

Figure 19. Schematic diagram of the experimental setup. pump started lifting water as the irradiation reached 175 W/ m2 with low water discharge. From irradiation 175 W/m2 to 330 W/m2 the discharge increased linearly with irradiation. The pump started discharging full water 19.9 L/min from irradiation 330 W/m2 and continued the same till irradiation 330 W/m2 was available. Whenever the irradiation was fallen below the 330 W/m2, the pump was running but the discharge decreased proportion to irradiation. The discharge of the pump was observed directly proportional to the fallen solar irradiation during testing. Table 3 shows the experimental test summary.

Testing of the Solar PV Water Pumping System The solar drying experimental study was conducted on-site during 15th November 2019 to 20th December 2019. The Number of experimental trials was conducted. Results obtained on perfectly sunny days 26th & 27th November 2019 are presented here. The observations irradiations, time, voltage, current, and water flow are recorded with the help of all sensors attached to the system. Based on voltage and the current available output power was calculated. As the solar irradiation fell on the PV panel it started generating the electricity. Initially, up to 160 W/m2 irradiation, as the power output was insufficient to start the pump it was at rest. The

Interpretation of Experimental Setup Results Observation taken on the trial days plotted in the form of the graphs. Figure 20 shows the irradiation – time characteristics of 26th November 2019 which is in the form of bell-shape. The observation was taken from 7.16 am to 5.18 pm. The minimum irradiation observed was 35 W/ m² at

Interpretation Of Simulation And Experimental Results

Table 4 shows the observations of water flow ‘Q’ of simulation and the experimental setup for the respective irradiation level. It is observed that the experimental water flow values were lesser than the simulated water flow values for a particular irradiation level. The variation in observation at particular irradiation was varied from 0–4.9 %. Initially, at lower irradiation value the variation percentage was large which reduced as the irradiation was increased. The average variation observed during the testing was 1.2 %. The variation observed in results was lower when irradiation available was above 330 W/m2. The observations of Table 4 are plotted with the help of Figure 24 which shows the water flow – Irradiation characteristic curve of simulation and experimental observation. The characteristic curve shows water flow increased linearly with irradiation in the simulation and experimental observation from 175 W/m2 to

Figure 24. Water flow – Irradiation characteristic curve of Simulation and experimental observations. 330 W/m2. Constant water flow was observed around 19.9 L/min at irradiation above 330 W/m2 up to 888 W/m2. The irradiation level above the 330 W/m2 does not change water discharge from 19.9 L/min but it was constant and the characteristic curve shows this with a horizontal parallel line to the x-axis after the linear increment. Error Analysis For evaluating the accuracy of experimental testing results random errors resulted due to the entire experimental procedure and systematic errors due to measuring

Experimental

instruments are considered. Absolute error and % relative error in the experimental and simulation water flow result is calculated by using Eqn. 11 & 12 and mentioned in Table 4. Relative random error is estimated based on extensive measurements taken while testing. Table 5 shows the accuracy and relative random error of the measuring instruments. The following correlations are used for error analysis of the entire system by considering efficiencies of the various subsystems [35–37]. Absolute error and % relative error in the experimental and simulation water flow ‘Q’ is given by, Absolute error ε = TV - MV

Where the ‘δEloss’ is the combined loss due to connecting cables, MPPT controller loss, motor, and water pump loss. Finally the total efficiency of the entire system ‘ηtot’ is given by,

By using equation 13 and Figure 20 irradiation data along with pyranometer total permissible error the solar energy on the 2 m2 320 W photovoltaic panel surface is, Esol = 10160 ± 305 Wh. Photovoltaic panel energy output by considering current and voltage measurement with instruments permissible error using Equation (14) is,

The Solar energy available on the surface of the photovoltaic panel given as,

The efficiency of the photovoltaic panel using Equation (15) is estimated as:

Photovoltaic panels energy output is estimated using the following relation, EPV =

Using Equation (11) and (12) the efficiency of the photovoltaic panel calculated by using the following relation,

The total water lifted on a test day was 9667 liters. Uplifted waters dynamic energy using equation (16) at 35 m elevation and considering instrumental permissible error is calculated as: Ew = 922 ± 18.5 Wh. Sum of other losses estimated using equation (17) is δEloss = 374.41 ± 44.4 Wh. The efficiency of the entire system using equation (18) is estimated as:

Uplifted waters dynamic energy is given by EW = ρ × g × h × Vtot

Table 5. Accuracy and relative random error of measuring instruments

ηtot = 9.07 ± 0.45 % The average relative error in experimental and simulation results observed during the testing was 1.1 %. For normal running condition power required for the motor is 110 W and at irradiation 175 W/m2 PV panel was unable to develop it. The PMBLDC motor requires higher starting torque. Though the power was insufficient MPPT figured out suitable voltage and current to start the pump, lots of power portion was consumed to rotate the rotor and lift the water. Hence we observed maximum (4.8 %) relative error from initial starting condition to normal running condition. Error analysis of every component of the system is carried out considering accuracies of the measuring instruments used. But after achieving the required power 110 W at the 330 W/m2, very little error was observed in simulation and experimental results. The total energy available on

the panel surface was 10160 ± 305 Wh from which 1296.41 ± 25.92 Wh was converted into electricity by the photovoltaic panel. The losses ‘δEloss’ due to system cabling, MPPT controller, motor losses, and pump losses observed were 374.41 ± 44.4 Wh. The efficiency of the photovoltaic panel observed was 12.76 ± 0.64 % while for entire solar water pumping system was 9.07± 0.45 %.

Conclusion

This work presents Simulation modeling and its result validation by the extensive field trials on the 0.5 hp experimental setup. The increment in operating temperature above 25 oC showed an effect on the output power of the PV panel. 50 W power losses observed at the same irradiation level of 1000 W/m2 because of temperature increment by 40 oC than STC. The optimum requirement of the irradiation for efficient of working found was 330 W/m2, where voltage and current were 35.1 V and 3.1 A respectively and power produced by the panel was 110 W. During experimentation water flow varied from 8.3–19.9 L/min when irradiation level was 175–330 W/m2 and remained constant around 19.8 L/min after further increment in irradiation. The average relative error in experimental and simulation results observed during the testing was 1.1 %. The total energy available on the panel surface was 10160 ± 305 Wh from which 1296.41 ± 25.92 Wh was converted into electricity by the photovoltaic panel. The losses ‘δEloss’ due to system cabling, MPPT controller, motor losses, and pump losses observed were 374.41 ± 44.4 Wh. The efficiency of the photovoltaic panel and the entire solar water pumping system observed was 12.76 ± 0.64 % and 9.07 ± 0.45 % respectively. The water flow-Irradiation characteristics curve and percentage variation show a good agreement between ­simulation and experimental observations. Solar photovoltaic water pumping system shows its usability in remote and rural areas for fulfilling drinking or agricultural water needs. As it runs on clean solar energy the CO2 emission is eliminated and large cost of grid construction in remote areas saved. The system helps farmers in water lifting in the day time as per the requirement to overcome the energy shortage problem. The use of PMBLDC motor shows a great advantage in terms of reduced maintenance cost of frequent carbon brush changing and systems running cost. Simulation modeling helped in the optimistic design of the system which resulted in minimizing the payback period to 10 years. One can enjoy the system for a further 15 years at negligible maintenance cost. The system lifts 10000 L/day water to fulfill 100 people daily water requirements with overall 9.07 % efficiency. The system simulation will help to visualize the performance behavior of the system in real climate conditions before mounting the system and finding its optimum working conditions. The obtained results will help in selecting the pump capacity and all system components

specifications by knowing the amount of water requirement and total water-lifting head. Furthermore, error analysis provides the factors responsible for variation in numerical and experimental results.

Nomenclature

PV Photovoltaic G Irradiation W/m2 Rs Series resistance Rp Parallel resistance MPPT Maximum power point tracker k Boltzmann’s constant 1.380*10–23 J/K A Diode ideality factor Top Cell operating temperature STC Standard Testing Condition (G = 1000 W/m2, Top = 25 oC) I PV panel output current Iph Photocurrent Diode current Id Leakage current Ip Short circuit current Isc Coefficient for temperature (0.0022 A/ oC) Ki Top Cell operating temperature Irs Reverse saturation current Is Saturation current Eg Forbidden energy band gap (1.2 eV) q Electron charge (1.602*10–19 C). Q Water flow L/min TV True value MV Measured value Esol Solar  energy available on the surface of the ­photovoltaic panel (Wh). EPV Output of photovoltaic panel (Wh). EW Dynamic energy of the water (Wh). PMBLDC Permanent Magnet Brushless Direct Current

Authorship Contributions

Completed Design of the system, experimental testing, Manuscript writing: V.H.D.; Procedural design of experimentation, Critical review: R.S.B.; Data collection and analysis, Report writing and formatting: T.V.D.

Data Availability Statement

No new data were created in this study. The published publication includes all graphics collected or developed during the study.

Conflict Of Interest

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics

There are no ethical issues with the publication of this manuscript. [13]

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