Active and reactive power of solar electric vehicle chargers system

Róbert Istók; Péter Kádár

doi:10.1556/606.2023.00659

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Pollack Periodica

Volume/Issue:: Volume 18: Issue 2

Active and reactive power of solar electric vehicle chargers system

Authors:

Róbert Istók

Róbert Istók Department of Energetics, Institute of Automation and Energy Systems, Kandó Kálmán Faculty of Electrical Engineering, Óbuda University, Budapest, Hungary

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istok.robert@kvk.uni-obuda.hu https://orcid.org/0000-0002-0683-0887

and

Péter Kádár

Péter Kádár Department of Energetics, Institute of Automation and Energy Systems, Kandó Kálmán Faculty of Electrical Engineering, Óbuda University, Budapest, Hungary

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Pages:: 95–100

Online Publication Date:: 17 Apr 2023

Publication Date:: 11 Jul 2023

Article Category:: Research Article

DOI:: https://doi.org/10.1556/606.2023.00659

Keywords:: solar inverter; solar panels; battery management system; active and reactive power; power factor; electric vehicle charger

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Abstract

Increasing the number of electrical vehicles determine an increasing of electrical vehicle chargers number too. The best situation is reach when the zero emission vehicles are charged with electrical energy produced by solar panels or another green energy. This paper presents a solar electric vehicle charger system with energy storage capabilities. The system should be considered as a combination of three systems: solar energy production system, energy storage system and electric vehicle charger system. One of the novelty of the system is that for energy storage is used a 2nd life Nissan Leaf electric vehicle battery. The paper gives information about, simulation and measurement of the annual solar energy production of the system, measurements results of the currents, voltages and powers of the system, and a distribution of the maximum daily energy production.

Abstract

1 Introduction

At the end of October 2021 in Hungary the number of Electric Vehicles (EV) was around of 40,545 [1]. In conformity with The Hungarian Energy and Public Utility Regulatory Authority at the end of second quarter of 2021 the number of public EV chargers in Hungary was 1,627. During this period time from this chargers 2,248 MWh energy was used for EV charging. The used energy amount was with 68.2% higher than the charged energy in second quarter of 2020 and with 22.6% higher than the charged energy in first quarter of 2021 [2]. The above data show a rapidly increasing of the EV number and the EV chargers number, which determine an increasing of the energy consumption too. In August 2021 the electrical energy production in Hungary was 2,905 GWh. This energy production was with 9% higher that the energy production in August 2020. From energy source point of view, the renewable energy was 22.4%. In case of renewable energy production, 68.8% of it was given by the solar energy [3]. It is important to know that in Hungary the capacity of photovoltaic systems on second quarter of 2021 was 2,621 MW. From solar energy production point of view, the capacity of small household size solar power plants was 944 MW and the rest of 1,677 MW capacity was represented by big size solar power plants [4]. On February 1, 2022 at 10:06 the measured energy production of Paks nuclear power plant was: 2,043 MW [5]. According to International Renewable ENergy Agency (IRENA) report on 2030 the global installed capacity of solar systems will be increased by six times compare to 2018, and in 2050 that will reach 8,519 GW [6]. One of the biggest advantages of the solar systems is that the energy produced by it is a green energy, and the carbon footprint is reduced. Unfortunately, the increasing of the number and the capacities of the PhotoVoltaic (PV) systems determine some problems for the Distribution Network Operators (DNOs) as pass over the upper limit of voltage, voltage unbalances, fluctuations, and thermal overloads. This kind of technical challenges is determinate by increasing of amount of power generated by solar systems [7]. For example, a combination of higher solar energy production and a lower level consumption from power grid point of view could cause reverse power flow [8]. The rise of voltage should be determined by reverse flow of power. Voltage rises on Low-Voltage (LV) power supply line determine a limitation of higher number of solar systems connection to the LV grids.

2 Effect of reactive power compensation and solar energy on low voltage power supply line

In Fig. 1 a simple LV circuit is presented. The power consumption of the single consumer is

P_{L}

and

Q_{L}

. The connection of the consumer to the distribution power supply line is done through a line with

R + j X

impedance. To the same connection point as the consumer is connected a PV system with

Q_{P V}

reactive power and

P_{P V}

active power.

∆ V = V_{1} - V_{2} = I^{*} \cdot (R + j X),

(1)

where,

I^{*} = {(\frac{(P_{L} - P_{P V}) + j (Q_{L} - Q_{P V})}{V_{2}})}^{*} .

(2)

Fig. 1.

Example of a simple LV power supply line

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

I^{*}

is substituted to Eq. (1)

∆ V = {(\frac{(P_{L} - P_{P V}) + j (Q_{L} - Q_{P V})}{V_{2}})}^{*} \cdot (R + j X),

(3)

∆ V = \frac{(P_{L} - P_{P V}) R + (Q_{L} - Q_{P V}) X}{V_{2}} + j \frac{(P_{L} - P_{P V}) X - (Q_{L} - Q_{P V}) R}{V_{2}} .

(4)

The

∆ V

from imaginary and real part could be written as in Eq. (5) as

∆ V = {∆ V}_{d} + j {∆ V}_{q},

(5)

where,

\begin{array}{c} {∆ V}_{d} = \frac{(P_{L} - P_{P V}) R + (Q_{L} - Q_{P V}) X}{V_{2}}, \\ {∆ V}_{q} = \frac{(P_{L} - P_{P V}) X - (Q_{L} - Q_{P V}) R}{V_{2}} . \end{array}

(6)

The magnitude of

V_{1}

can be calculated as

V_{1} = \sqrt{{(V_{2} + ∆ V_{d})}^{2} + ∆ V_{q}^{2}} .

(7)

The (X/R) reactance-to-resistance of LV circuit is lower that means

({∆ V}_{q} \approx 0), V_{2}

should be written in a new form:

V_{2} = V_{1} - {∆ V}_{d} .

(8)

V_{2}

is substituted by

V_{1}

the

{∆ V}_{d}

can be written as

{∆ V}_{d} \approx \frac{(P_{L} - P_{P V}) R + (Q_{L} - Q_{P V}) X}{V_{1}} .

(9)

At the common coupling point, the voltage

V_{2}

should have the next form:

V_{2} \approx V_{1} - \frac{(P_{L} - P_{P V}) R + (Q_{L} - Q_{P V}) X}{V_{1}} .

(10)

When the energy requirement is higher than the supplied energy, the voltage drops on the power line as in Eq. (10). When the generated solar energy exceeds demand, then the voltage is increasing. The voltage at the Point of Common Coupling (PCC), is given by Eq. (11),

V_{2} \approx V_{1} + \frac{(P_{P V} - P_{L}) R + (Q_{P V} - Q_{L}) X}{V_{1}} .

(11)

This situation becomes a problem when the voltage limits is reach by the voltage growing due to increasing of number of PV systems ( $P_{P V} ≫ P_{L}$ ). Eqs (10) and (11), show that the reactive power produced by PV inverter and the situation of the consumer influence the PCC voltage. If the PCC voltage reaches the lower limit voltage, then the PV inverter should start to produce reactive power to increase the voltage. If the voltage at the PCC reaches the upper voltage limit, then PV inverter should stop to produce the reactive power and start to consume it to reduce the voltage.

3 Solar system with energy storage and electric vehicle charging capabilities

The solar system and electric vehicle charging with energy storage capability from Óbuda University contains: 24 glass-glass solar panels, a solar inverter, a charger/inverter which supply the Battery Management System (BMS) role too, two EV chargers and used Li-Ion Nissan Leaf batteries.

3.1 Solar panels

The efficiency of a typical commercial PV module is about 13–20% [9]. For construction of this system the used solar panel is SoliTek glass-glass, mono-crystalline 320 W solar panels. The total solar panels capacity is 7680 W.

3.2 Solar inverter

The solar inverter is an 8.2 kW Fronius Symo inverter. The highest amount of produced power was around of 7 kW for short time. In general, the best energy production for longer time is around of 6.5 kW. The reason why the power of the solar inverter has to be higher than the power of the solar panels is that the inverter has to produce not only active power but reactive power too. The production of the reactive power should not decrease the production of the active power, in case of maximum solar energy production. In Figs 2 and 3 the diagrams of input DC voltage and current and the output AC voltage of solar inverter are presented. The differences between two figures are that in first figure is presented the measurement results of a sunny day. The total energy production in Sept. 9, 2021 was 45.38 kWh. The diagram of DC current is quite the same with diagram of the AC current and power output of the inverter. This diagram form is typically for a sunny day. In both cases the level of the DC voltage decreases with increasing of the DC current. The output AC voltage is around of 235 V.

Fig. 2.

The diagrams of input, output of voltage and current in a sunny day

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

Fig. 3.

The diagrams of input, output of voltage and current in a cloudy day

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

3.3 Battery management system

The role of Battery Management System (BMS) is done by a Victron charger/inverter. Another role of it is to interconnect the solar system, EV chargers, batteries and the power supply network. The connection to the internet gives the possibility to use the online Victron Remote Management (VRM) portal. Through the portal not only the momentary information regarding the system should be known, but the historically information too. In Fig. 4 the momentary information of the system through VRM is presented.

Fig. 4.

Momentary status of the system, feed into the grid

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

The status of the system is as follows: the solar system produces 1,135 W, 939 W is fed in the power system, 68 W is used by the EV chargers, which are in standby mode, because no EV on chargers, 75 W is used for charging the batteries.

3.4 Electric vehicle charger

The system contains two Wallbox EV chargers. In Fig. 5 the all energy supplied to the EV charging and the charging time is presented. The 124.97 kWh energy means 53.65 kg CO₂ saved.

Fig. 5.

The energy supplied by the EV chargers

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

Figure 6 shows a nighttime status of the system after a typical day. The PV system operated normally, the energy was fed in the grid into the network. Midday a car arrived for charging so the whole PV production + grid source + the battery supplied the energy for the car charging.

Fig. 6.

Day after an EV charge

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

3.5 Storage batteries

The batteries are used batteries from Nissan Leaf first generation car. This is an important fact because the reduced storage capacity of the batteries is not enough for EV, but for energy storage (electro-chemical storage) in a solar system is acceptable [10].

4 Measurement results

4.1 Energy production of the system

It is well known that the solar energy is not a constant energy source. In this case the nominal capacity of the system is 7.68 kW. The energy production of the solar system presented in this paper was simulated with help of Photovoltaic Geographical Information System (PVGIS) program. In Fig. 7 the result of the simulation and the measured solar energy production is presented. In general, the simulated and the measured energy production are quite equal. Some differences should appear, because of weather from that month.

Fig. 7.

Comparison between simulated and measured solar energy production

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

Month with the biggest difference in simulated and measured energy production was May. In Fig. 8 is presented the measured daily energy production of May and June 2021. The measurement results show that in May was a changeable weather, with a lot of cloudy days.

Fig. 8.

Distribution of energy production for May and June 2021

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

The energy production was very unpredictable for that month. In the sunniest day the maximum energy production was 52.6 kWh. In the lowest energy production day, the total energy amount was 9.91 kWh. The total simulated energy production for May was 1,186.8 kWh, and the measured energy production was 1,014.72 kWh. Compare to May, June was a quite stable month, where the measured energy production was higher that the simulated one. The variation of the energy production was much lower compare to May. The maximum daily energy production was 49. 11 kWh and minimum 33.55 kWh. From minimum energy production point of view in June it was three times higher than in May. The total simulated energy production for June was 1,188.1 kWh, and the measured energy production was 1,294 kWh. The difference between the total simulated and the measured energy was 210.55 kWh that is less than 3% of total measured energy production which was 7,556.85 kWh.

It is well known that the PV systems fed energy in power network systems only if the grid voltage is within specified limits. Peaks of energy production should determine the voltage to reach the upper limit. Reaching of the upper or lower voltage determine a switch down of the solar inverter. In case of Fronius inverter it is switch off at 260 and 180 V.

The voltage stability can be influenced by monitoring the reactive and effective power transmission to the grid. One solution is to reduce the active power generation, but that determine a reduction of the electrical energy supplied to the power supply network [11–15]. Another solution is to manage the reactive power [16–25]. Managing of the reactive power can cause the level of the voltage to rise and to fall. This regulation of the voltage levels can be solved by using of the inverters with smart capabilities.

There are listed some reactive power controls technics:

Fixed power factor control;
Scheduled power factor control;
Power factor control as a function of injected active power;
Voltage-dependent reactive power control (volt-var control).

In case of solar inverter presented in this paper the volt-var control method are used for reactive power output management. In Fig. 9 the measurement results of active power P (W), reactive power Q (var), apparent power S (VA) and the power factor cos φ in a sunny day is presented.

Fig. 9.

Active, reactive, apparent power and power factor in a sunny day

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

Because the power factor is 1, the active power is equal with apparent power. This is the reason why in Fig. 9 only the three wave forms, but four vertical axis (S, P, Q, cos φ) should be seen. The total energy production was 28.97 kWh. The diagram of the reactive power follows the diagrams of active and apparent power. The amount of produced reactive power is 1% of amount of active power. That is meaning in this case the amount of reactive, was around of 290 var.

In Fig. 10 the measurement results for a rainy day is presented. In this case when the energy production is very low, the power factor is lower than 1, and the inverter start to consume the reactive power. The total energy production for that day was 2.31 kWh.

Fig. 10.

Active, reactive, apparent power and power factor in a rainy day

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

In Fig. 11 a simulation of voltage drop, which should appear due the reactive power injected by a solar system on a power system line is presented. For the simulation was used a typically 3 phase power supply line, 95 mm² 3 core aluminum, r = 0.397 Ω km⁻¹, x = 0.0762 Ω km⁻¹. The injected powers by solar system is P = 6,696 W, Q = 65.83 var and the current I = 9.57 A.

Fig. 11.

Voltage drop on power supply line due to reactive power

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

In Fig. 11 it can be seen that at the end of the line the voltage drop should be 1.6 V. If on this power supply line only 20 solar systems with 7 kW capacity are connected, then the voltage drop should be 32 V at the end of line. This kind of problem appear on streets from villages and cities where the most of buildings are family houses where are solar systems installed.

Figure 12 presents the measurement results of daily peak power production from middle of May 2021 till middle of March 2022. Between May and October the daily peak power production is between 6 and 7 kW and the dispersion, is not so significant. Start with end of October the daily peak power decrease and the dispersion become more significant.

Fig. 12.

Distribution of daily peak power production

Citation: Pollack Periodica 18, 2; 10.1556/606.2023.00659

5 Conclusion

This paper presents an electric vehicle charging system where the energy for charging is coming from multiple sources: as solar panels, storage batteries, and power supply network. The measurements on the system give information about output voltage and current of the solar panels, and the output voltage of the inverter in a sunny and cloudy day too. There is presented a comparison of the simulated and measured solar energy production also. The results of the simulation and measurements are quite same. Bigger differences are coming if the weather in a month is different compare to typical weather in that month, rainier and cloudy days, which determine less energy production.

Measurement results about active ad reactive powers and the dependence between them are presented too. In a sunny day the reactive power consumption of the solar inverter is on a low level. This consumption appears in the morning and in the evening when the energy produced by the solar panels is in a low quantity. In a rainy day, the consumption of the reactive power is higher, because the energy produced by the solar panels is lower for longer time. At the end of the paper a distribution of the maximum daily energy production is presented too. Between October and March, the energy production decreasing and the dispersion of the maximum energy production is more significant.

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Pollack Periodica

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Bálint Bachmann (Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Jeno Balogh (Department of Civil Engineering Technology, Metropolitan State University of Denver, Denver, Colorado, USA)
Radu Bancila (Department of Geotechnical Engineering and Terrestrial Communications Ways, Faculty of Civil Engineering and Architecture, “Politehnica” University Timisoara, Romania)
Charalambos C. Baniotopolous (Department of Civil Engineering, Chair of Sustainable Energy Systems, Director of Resilience Centre, School of Engineering, University of Birmingham, U.K.)
Oszkar Biro (Graz University of Technology, Institute of Fundamentals and Theory in Electrical Engineering, Austria)
Ágnes Borsos (Institute of Architecture, Department of Interior, Applied and Creative Design, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Matteo Bruggi (Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Italy)
Petra Bujňáková (Department of Structures and Bridges, Faculty of Civil Engineering, University of Žilina, Slovakia)
Anikó Borbála Csébfalvi (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Mirjana S. Devetaković (Faculty of Architecture, University of Belgrade, Serbia)
Szabolcs Fischer (Department of Transport Infrastructure and Water Resources Engineering, Faculty of Architerture, Civil Engineering and Transport Sciences Széchenyi István University, Győr, Hungary)
Radomir Folic (Department of Civil Engineering, Faculty of Technical Sciences, University of Novi Sad Serbia)
Jana Frankovská (Department of Geotechnics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
János Gyergyák (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Kay Hameyer (Chair in Electromagnetic Energy Conversion, Institute of Electrical Machines, Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Germany)
Elena Helerea (Dept. of Electrical Engineering and Applied Physics, Faculty of Electrical Engineering and Computer Science, Transilvania University of Brasov, Romania)
Ákos Hutter (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technolgy, University of Pécs, Hungary)
Károly Jármai (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
Teuta Jashari-Kajtazi (Department of Architecture, Faculty of Civil Engineering and Architecture, University of Prishtina, Kosovo)
Róbert Kersner (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Rita Kiss (Biomechanical Cooperation Center, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary)
István Kistelegdi (Department of Building Structures and Energy Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Stanislav Kmeť (President of University Science Park TECHNICOM, Technical University of Kosice, Slovakia)
Imre Kocsis (Department of Basic Engineering Research, Faculty of Engineering, University of Debrecen, Hungary)
László T. Kóczy (Department of Information Sciences, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, University of Győr, Hungary)
Dražan Kozak (Faculty of Mechanical Engineering, Josip Juraj Strossmayer University of Osijek, Croatia)
György L. Kovács (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Balázs Géza Kövesdi (Department of Structural Engineering, Faculty of Civil Engineering, Budapest University of Engineering and Economics, Budapest, Hungary)
Tomáš Krejčí (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
Jaroslav Kruis (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
Miklós Kuczmann (Department of Automations, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, Széchenyi István University, Győr, Hungary)
Tibor Kukai (Department of Engineering Studies, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Maria Jesus Lamela-Rey (Departamento de Construcción e Ingeniería de Fabricación, University of Oviedo, Spain)
János Lógó (Department of Structural Mechanics, Faculty of Civil Engineering, Budapest University of Technology and Economics, Hungary)
Carmen Mihaela Lungoci (Faculty of Electrical Engineering and Computer Science, Universitatea Transilvania Brasov, Romania)
Frédéric Magoulés (Department of Mathematics and Informatics for Complex Systems, Centrale Supélec, Université Paris Saclay, France)
Gabriella Medvegy (Department of Interior, Applied and Creative Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Tamás Molnár (Department of Visual Studies, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Ferenc Orbán (Department of Mechanical Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Zoltán Orbán (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Dmitrii Rachinskii (Department of Mathematical Sciences, The University of Texas at Dallas, Texas, USA)
Chro Radha (Chro Ali Hamaradha) (Sulaimani Polytechnic University, Technical College of Engineering, Department of City Planning, Kurdistan Region, Iraq)
Maurizio Repetto (Department of Energy “Galileo Ferraris”, Politecnico di Torino, Italy)
Zoltán Sári (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Grzegorz Sierpiński (Department of Transport Systems and Traffic Engineering, Faculty of Transport, Silesian University of Technology, Katowice, Poland)
Zoltán Siménfalvi (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
Andrej Šoltész (Department of Hydrology, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
Zsolt Szabó (Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Hungary)
Mykola Sysyn (Chair of Planning and Design of Railway Infrastructure, Institute of Railway Systems and Public Transport, Technical University of Dresden, Germany)
András Timár (Faculty of Engineering and Information Technology, University of Pécs, Hungary)
Barry H. V. Topping (Heriot-Watt University, UK, Faculty of Engineering and Information Technology, University of Pécs, Hungary)

POLLACK PERIODICA
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2023
Scopus
CiteScore	1.5
CiteScore rank	Q3 (Civil and Structural Engineering)
SNIP	0.849
Scimago
SJR index	0.288
SJR Q rank	Q3

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