Power Quality Monitoring of the grid-connected PV System at CDER, Algeria A. Hadj Arab, S. Ould Amrouche, K. Abdeladim, S. Bouchakour, F. Cherfa, B. Taghezouit Centre de Développement des Energies Renouvelables, CDER, Route de l’observatoire, BP. 62, 16340, Bouzaréah, Algiers, Algeria Abstract A grid connected PV system was installed at the “Centre de Développement des Energies Renouvelables”(CDER), Algiers, back in 2004, the system is still in operation [1]. A study dealing with the power quality monitoring of the PV is presented in this paper, including the quality of the electrical power generated and injected into the network. The observation is based on the electrical implementation upstream and downstream tester of the PV inverter connected to the network. Recommended in most professional’s applications, the power analyzer ZIMMER LMG450 is the main instrument of our test bench. The measurements and processing of the data are achieved under LabVIEW environment. The observation and analytical exploitation of electric data PV system will help us to evaluate the performance of our PV system connected to the network, in view of establishing a behavioral model of our PV system. Keywords: PV system; power quality; grid-connected PV system; monitoring, LabVIEW.
1. Introduction The amount of photovoltaic (PV) systems in the distribution network is expected to grow. Increasing penetration levels of distributed grid-connected PV systems may affect the control and the configuration of distribution network. For this reason, the supervision of these PV array generations remain a crucial issue. The actual models to describe solar panel performance are more related to physics, electronics and semiconductors than to power systems. Some of the models require several parameters such as the temperature coefficients, photon current, open circuit voltage, series/shunt resistance of the device, etc. In addition, manufacturer data sheets do not provide some of the required parameters in those models, so it is required to find the information in other sources. At the same time, these models can be impractical and too complex for common tasks in power systems such as power flow, harmonic analysis, sensitivity analysis, load matching for maximum power transferred from the source to the load, etc [2], [3]. To solve these problems and to maximize the use of information provided by field tests, the power quality behaviour of grid connected PV systems has been investigated. The solar photovoltaic system power plan, currently in service, since 2004. The installation is located on the roof of CDER in Bouzaréah, Algiers (latitude 36.8°N, longitude 3°E and 345m of altitude). The electricity produced by photovoltaic solar panels is injected directly into the SONELGAZ grid (public company) without storage device. The purpose of this work is to present and evaluate measurements based on power quality quantities obtained from the PV system. The power quality parameters measured are: AC active/ reactive power, current/ voltage TRMS and power factor. The DC active power and DC current/ Voltage have also been measured. Finally, a program was designed under LabVIEW environment for the monitoring of our PV system. A description will be given for each step leading us for the design of such program.Our task is to monitor data which are needed in order to calculate the different characteristics of the installation such as different yields and other parameters. In this study we put emphasis on how to develop a friendly interface, which includes all information gathered from the system. In the same interface, another part is dedicated to the results obtained from simulations we have performed using the called platform.
2. Monitoring of the grid connected PV system In this work, a modeling and simulation applied to a grid connected PV system has been investigated (Fig.1). The PV system is made of 90 PV modules (Isofoton 106Wp-12 at standard conditions (STC)) divided in three sub-array of 3, 18kWpof nominal power for each one. The sub-array is made of two parallel strings of 15 PV modules in series. Each sub-array is connected to a single phase inverter of 2.5 kW (IG30 Fronius) that injects the generated energy into a phase of the public low voltage distribution (LV) network of the National Company (Sonelgaz). It started operating on June, 2004; the electricity produced by photovoltaic solar panels is injected directly into the local grid (220 V, 50 Hz) without storage device. Fig. 1 shows a diagram of the grid-connected PV system. The electrical energy was measured using several energy meters; monophasic energy meter measures the electric energy generated by each sub-array PV, three phases energy meter is a bidirectional meter that measures the energy imported or exported to the grid.
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NuRER – 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, TURKEY, 26-29 Oct. 2014
Figure1. Considered PV system connected to the grid In Fig.2, a scheme of the sub-array is presented, including the monitoring system, where the following electrical measurement items are measured and recorded with Power Meter: AC voltage and current, AC active power and reactive power, DC voltage and current, DC active power and power factor. The monitored results were collected using 1 second step. The recorded data are exported and averaged every 1 min and stored in hard disc for analysis and evaluation.
Figure 2. Overview of the PV sub-array and one of the devices constituting the monitoring system In order to monitor the data, a program dedicated to the acquisition data was developed, a schematic presentation of the program is given in figure 3
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NuRER – 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, TURKEY, 26-29 Oct. 2014
Figure 3. Schematic presentation for the data acquisition program section
3. Modeling & Simulation A modeling and a simulation were performed in this study.
3.1 Photovoltaic system modelling The objective of the simulation of the grid connected-PV system is to obtain expected evolution of voltages and currents at the DC side of the system as well as at the AC side and at the inverter output. So, simulation results will give the expected behavior, in a dynamic way of the whole system taking into account real climatic conditions. The simulation of the whole grid connected PV system is based on the models presented below for both PV modules and for the inverter and is carried out in LabVIEW environment. The flowchart of the simulation process is depicted in figure 4.
Figure 4. Simulation process 3.1.1Photovoltaic module modelling The model proposed [1,4] was used. It’s takes into consideration the manufacturer data sheet, the air temperature, and the irradiation value, it’s possible to model the generation system for a photovoltaic installation. It is expected that this model will be used for future applications in the area of power systems where most of the existing models cannot be used to calculate power flow, harmonic analysis, optimal load for maximization of the power, etc. The current - voltage relationship is given by: (1) The model includes a short circuit current Isc_xat any solar irradiance and temperature conditions, an open circuit voltage Voc_xat any solar irradiance and temperature condition and an I-V characteristic constant b which is defined between 0.01 and 0.18, where smaller is the b, greater is the produced power. Isc_x and Voc x can be obtained using equations: (2) (3) Isc_ref and Voc_ref are the short circuit current and open circuit voltage at Standard Test Conditions (25°C and 1000W/m²) respectively. Voc_max is the open-circuit voltage at 25°C and more than 1200W/m² (slightly superior to Voc_ref). Tcell is the solar cell temperature in °C with nominal temperature Tn = 25°C. Ei is the effective solar irradiation in W/m² with nominal effective solar irradiance Ein = 1000W/m². TCv is the temperature coefficient of Vocin V/°C. TCi is the temperature coefficient of Isc in A/°C. The variable s is the number of PV panels with the same electrical characteristics connected in series and p is the number of PV panels with the same electrical characteristics connected in parallel.
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NuRER – 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, TURKEY, 26-29 Oct. 2014
Table 1. Characteristics of the PV module Physical Characteristics Dimensions 1 310*654*39,5 mm Weight 11,5 kg number of cells in series 36 number of cells in parallels 2 TONC (800 W/m², 20°c, am 1.5, 1m/s) 47°C Electrical Characteristics Standard Test Conditions : 1000 W/m2, 25 ºC, AM=1,5 Isc_ref [A] 6.54 Voc_ref [V] 21.6 Impp_ref [A] 6.03 Vmpp_ref [V] 17.6 The PV panel characteristic constant is b = 0,098, which was calculated using the Fixed Point Theorem (6) and STC parameters (Table 1). The variable ε is the maximum allowed error to stop the iteration. While: (4) Using Linear Reoriented Coordinates Method (LRCM) [3,5], the current and voltage equations at the maximum power point (MPP) are given as follows: (5) (6) 3.1.2 Inverter model The following equations define the behavioral model developed by Sandia National Laboratories [6-7]. As independent variables, the both DC power and DC voltage are used to calculate the inverter AC power. The parameters with the “o” subscript are constant values that define a reference or nominal operating condition. (7) Where: (8) (9) (10) The values of performance parameters are provided by manufacturers Table.2, and also from detailed measurements given by recognized testing laboratory (SANDIA, CEC, Spec…). Table 3 shows the inverter performance parameters [8-9]. Table.2. inverter specification, FORNIUS IG 30 Input DC nominal power [W] 2690 max. input current [A] 19,2 max. input voltage [V] 500 max. MPP-voltage [V] 400 min. MPP-voltage at nominal Uac [V] 150 Output AC-nominal power [Va] 2500 power factor [Cos phi] 1 min. AC frequency [Hz] 49,8 max. AC frequency [Hz] 50,2 min. AC grid voltage [V] 195 max. AC grid voltage [V] 253 Efficiency max. efficiency [%] euro. efficiency [%]
94,3 92,7
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NuRER – 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, TURKEY, 26-29 Oct. 2014
Table.3. Inverter Performance Parameter, Sandia National Laboratories Database Parameters of inverter model maximum AC-power at reference operating condition, P aco [W]
2700
DC-power level at which the AC-power is achieved at the reference operating condition P dco[W]
2879
DC-voltage level at which the AC-power is achieved at the reference operating condition Vdco [V]
277
self-consumption by inverter, Pso [W]
27.9
Constant parameters of inverter model C0 [1/W] C1[1/V] C2 [1/V] C3 [1/V]
-1.009e-5 -1.367e-5 -3.587e-5 -3.421e-3
3.2 PV system performance The yields of the PV system are expressed as reference yield (Yr), given in [hr], array yield (Ya) given in [hr]and final yield (Yf)given in [hr], as well as the performance ratio (PR) expressed in [%], they can be obtained from the simulation results using the following formulas[9] (11)
(12)
(13) (14)
3. Monitoring using LabVIEW environment The layout of the developed virtual instrument can be viewed in front panel format for an interactive user interface. The home menu interface is depicted in figure 5.
Figure 5. Front panel (Home) In figure 6, is given the graphical presentation of the performance ratio, as can be seen a good agreement is found between simulation results and monitored data. .
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NuRER – 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, TURKEY, 26-29 Oct. 2014
Figure 6. Daily performance ratio.
4. Conclusion Using LabVIEW platform has allowed us to perform the monitoring of the PV system existing at our level. Thanks to a friendly platform, many information can be given and displayed. Note that in this study is we were dealing with the first experience in grid-connected PV system. It has also allow us also to deal with injections problems. Furthermore, while performing simulations in order to validate our measured data, results has shown a good agreement, which confirm the choice of the models we have used in this work.
References [1] A. Hadj Arab, F. Cherfa, A. Chouder and F. Chenlo. “Grid-Connected Photovoltaic System at CDER-Algeria”, 20th European Photovoltaic Solar Energy Conference and Exhibition. Barcelona. 6-10 June 2005. [2] Ortiz-Rivera E., Peng F., Analytical model for a photovoltaic module using the electrical characteristics provided by the manufacturer data sheet, in Power Electronics Specialists Conference. IEEE 36th, pp. 2087–2091. (2005) [3] Ortiz-Rivera E., Modelling and Analysis of Solar Distributed Generation, PhD, 2006, East Lansing, MI, USA. [4] The Institute of Electrical and Electronics Engineers, IEEE Recommended practice for utility Interface of photovoltaic (PV) systems, IEEE Std. 929-2000, NY, (2000). [5] Ortiz-Rivera E., Peng F., A Novel Method to Estimate the Maximum Power for a Photovoltaic Inverter System, Proceedings of the 35th IEEE Power Electronics Specialists Conference, , pp. 2065-2069, Aachen, Germany.(2004) [6] David L. King, Sigifredo Gonzalez, Gary M. Galbraith, William E. Boyson, Performance Model for GridConnected Photovoltaic Inverters, SAND2007-5036, Sandia National Laboratories, , Albuquerque, NM, (2007). [7] David L. King, Boyson W.E., Kratochvill J.A., Photovoltaic Array Performance Model, SAND2004-3535, Sandia National Laboratories, Albuquerque, NM, (2004). [8] Chouder A., Silvestre S. Sadaoui N., Rahmani L., Modelling and simulation of a grid connected PV system based on the evaluation of main PV module parameters, Simulation Modelling Practice and Theory, 20 (2012), pp. 46–58. [9] Chouder A., Santiago S., Taghezouit B., Karatepe E., Monitoring, modelling and simulation of PV systems using LabVIEW. Sol. Energy, (2012).
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