Next Article in Journal
Investigation of Dielectric Measurement Model for Coconut Fiber Water Content and the Associated Factors
Next Article in Special Issue
Learning-Based Approaches for Voltage Regulation and Control in DC Microgrids with CPL
Previous Article in Journal
Analysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networks
Previous Article in Special Issue
Model Predictive Control of a PUC5-Based Dual-Output Electric Vehicle Battery Charger
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Developing an Integrated Soft-Switching Bidirectional DC/DC Converter for Solar-Powered LED Street Lighting

1
Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran
2
Electrical Engineering Department, Future University in Egypt, Cairo 11835, Egypt
3
Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11535, Egypt
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(20), 15022; https://doi.org/10.3390/su152015022
Submission received: 28 August 2023 / Revised: 27 September 2023 / Accepted: 11 October 2023 / Published: 18 October 2023

Abstract

:
In the current era marked by the growing adoption of renewable energy sources, the use of photovoltaic-powered LED streetlights, known for their enhanced efficiency and extended lifespan, is on the rise. This lighting solution encompasses essential components such as a photovoltaic (PV) panel, an energy storage system, LED luminaires, and a controller responsible for supervising power distribution and system operations. This research introduces a novel approach involving a ZVS (zero-voltage switching) bidirectional boost converter to manage the interaction among the PV panel, LED lights, and battery storage within the system. To elevate system efficiency, a modified version of the conventional bidirectional boost converter is employed, incorporating an auxiliary circuit encompassing a capacitor, inductor, and switch. This configuration enables soft switching in both operational modes. During daytime, the converter operates in the buck mode, accumulating solar energy in the battery. Subsequently, at night, the battery discharges energy to power the LED lights through the converter’s boost operation. In this study, the PET (photo-electro-thermal) theory is harnessed, coupled with insights into heatsink characteristics and the application of a soft-switching bidirectional boost converter. This integrated approach ensures optimal driving of the LED lights at their ideal operating voltage, resulting in the generation of optimal luminous flux. The proposed LED lighting system is thoroughly examined, and theoretical outcomes are validated through simulations using the PSCAD/EMTDC version 4.2.1 software platform.

1. Introduction

With the advancement of technology, the increase in population, and the growth in electrical devices, the amount of energy demanded is increasing. If this problem continues along with this trend, in the near future we will face a fuel problem for electricity generation. In order to deal with this challenge, the use of renewable energy as a viable solution has been suggested by many researchers. Solar energy, which is one type of renewable energy, is considered one of the most popular types of renewable energy due to its easy access. Power electronic converters are one of the main components of these renewable energy systems. Considering that the output power of solar systems is DC, DC/DC converters are extremely important in the structure of photovoltaic systems [1,2,3,4,5,6,7].
Bidirectional DC/DC converters are used in a variety of applications such as fuel cell vehicles, battery chargers/dischargers, and uninterruptible power supply (UPS) systems. These converters play a very important role in renewable systems such as fuel cell systems, PV systems, and wind power systems [8,9,10,11,12,13]. There are two classifications of bidirectional DC/DC converters: isolated and non-isolated types [14,15,16]. The isolated bidirectional converter, with more than four switches and an isolated transformer, exhibits higher conduction losses and lower efficiency compared with its non-isolated counterpart. Conversely, the non-isolated bidirectional converter offers high efficiency due to its simpler configuration [17,18,19]. To enhance efficiency, one suggested approach is the utilization of the soft-switching technique, where the power switches operate with zero-voltage switching, reducing switching losses during transitions and improving overall efficiency [20]. Also, several research studies have been conducted in recent years about various control methods for DC/DC converters [21,22].
As mentioned, photovoltaic systems that utilize solar energy to generate power can be used in various applications. This energy can be used in large and small scales such as in solar power plants and in street lighting [23,24]. Streetlights can be powered independently by PV systems, even without a network connection. The energy received from the sun during the day and solar panels charges the battery, and this energy is used at night to turn on the lights. Statistics show that PV-powered LED (light-emitting diode) streetlights are widely employed in three main types of applications—commercial, residential, and industrial—all over the world. Among these, commercial applications are the most commonly utilized [25,26,27].
Due to their advantages such as high luminous efficiency, better vision, and long lifetime, high-intensity-discharge (HID) lamps are used for street lighting [28,29,30]. However, these lamps have disadvantages, such as excessive glare, containing harmful substances (such as metallic mercury), and needing some seconds to get to full brightness. High-brightness LEDs can be a good replacement for these lamps due to the lack of these problems. LED technology has progressed rapidly over the last two decades. LEDs have high reliability, the absence of ultraviolet and infrared rays, a long lifetime, and high luminous efficiency, and are energy-saving, environmentally friendly, etc. Figure 1 shows the structure of a streetlight LED system powered by a PV panel.
Two parameters of LED voltage and current are very effective in system design. Indeed, efforts should be made to drive these systems in almost constant current and voltage because any increase in these parameters leads to an increase in the junction temperature and a reduction in the optical flux and efficiency [31,32]. LEDs have optical, electrical, and thermal characteristics that are dependent on each other. In [33], the relationship between the luminous output (photometric variables) and thermal behavior was reported. Considering these three mentioned characteristics, a suitable LED system can be designed. The LEDs used in various systems currently have extremely low efficiency. These LEDs turn about 87–90% of their consumed energy into heat by burning at their nonoptimal points [34]. To reach the maximum optical efficiency and to maximize the luminous flux from the LEDs, they must work at the optimal point of their voltage and current. Two LED streetlight systems are proposed in [35,36]. These systems are powered by solar energy as the primary source and batteries as the secondary source. In [37], using a two-way buck–boost converter and a microcontroller, the charging and discharging of the lighting system is controlled. This is also performed in [38], using a two-way Zeta–Sepic converter. Due to improper design, this structure cannot operate at its optimal point. Also, due to this issue, this structure cannot use the soft-switching technique. In [39], the authors introduced a model for LED devices which incorporates thermal resistance and light output as variables. However, it should be noted that this model specifically focuses on the LED device itself and does not cover the entire LED system, which includes aspects such as electric power control and thermal design of the heatsink. In order to relate the optical, electrical, and thermal aspects of LEDs, a unified model is presented in [40]. This method shows how to achieve a current for the optimal flux. In [41], a two-stage LED driver is proposed, which has a boost circuit and a new resonant converter. The resonant circuit of this converter, which is of the CLCL type, is a new circuit that has soft-switching conditions. Also, in [42], an LED driver is presented that has a CLL resonant converter. In [43], a single-stage LED driver is proposed. This driver is based on a boundary conduction mode (BCM) boost circuit and an LLC resonant converter.
In this paper, a single-stage bidirectional buck–boost converter is presented to control battery storage, LED light, and the PV panel. In this converter, to improve efficiency, an existing soft-switching structure of the converter is used. The employed converter is derived by incorporating an LC series resonant tank into the conventional bidirectional DC/DC converter. The soft-switching cell structure consists of passive elements and does not require any other switching device. The applied topology performs soft switching in both buck and boost operational directions. Throughout the daytime, the energy generated by the PV panel is stored in the battery via the buck operation direction of the converter. In addition, the battery supplies the LED light with the necessary power through night via the reverse boost operation direction of the converter. The voltage regulation in this case can be detected for input and output. This performance provides MPPT (maximum power point tracking) to the PV panel, SOC (state of charge) for the battery, and light control with the LED light. Regarding the LED lights that are used, an optimal relationship is established between light, electricity, and thermal factors to maximize the ratio of luminous flux to input power. In this article, the LED lights are driven at the operating voltage where the optimal luminous flux occurs using a combination of heatsink characteristics, the PET theory, and a soft-switching buck–boost converter. The proposed LED light system is studied, and the results of theories are simulated and validated using PSCAD/EMTDC software. In general, the main contributions of this paper are as follows:
  • Design of a soft-switching single-stage bidirectional buck–boost converter.
  • Using a modified version of the conventional bidirectional boost converter, incorporating an auxiliary circuit encompassing a capacitor, inductor, and switch.
  • Using the presented structure for supplying energy to LED streetlights.
  • Effective energy management between the renewable system and the battery in order to power the load.

2. Proposed System Configuration and Operation

The proposed system is shown in Figure 2. This system has a soft-switching bidirectional dc/dc converter to harvest PV energy and feed LED light. As is observed in the figure, the proposed converter is fed current at both input and output ports which is a desirable feature of the converter in terms of the battery, PV energy, and LED light. Compared with the battery voltage level, the PV source and LED light have higher voltage ranges; therefore, the high-voltage side of the converter is connected to them using a static relay. As a result, throughout the day the PV energy is stored in the battery by the converter’s buck operation mode, while at night the LED light is fed by the battery through the converter’s boost operation mode.
As shown in Figure 3, during the day, the converter works in the buck circuit because the PV panel voltage is greater than the battery voltage. In this case, the relay is closed to the PV module and the Q1 switch is activated using PWM, while the Q2 switch is constantly off, and when the Q1 switch is off, diode D2 conducts. On the other hand, as shown in Figure 4, at night, the converter operates in the boost circuit and without PV power, the battery should supply a higher-voltage LED light. As a result, the relay is closed to the LED light and while the Q1 switch is constantly off, Q2 is switched in PWM. In this case, diode D1 conducts during the Q2 off-times. Now, if during the conduction interval of each diode at the same time the corresponding inverse parallel switch of that diode is turned on, the function of the circuit becomes acting as a synchronous rectifier for both buck and boost operation circuits, resulting in a reduction in converter conduction losses. Therefore, a pulse width modulation signal is applied to the Q1 switch (with a duty ratio of d1), and at the same time, the Q2 switch operates in the opposite state of Q1 (with the duty ratio of 1 − d1); that is, when Q1 is on, Q2 is off and vice versa. For this situation, the voltage across the capacitor C1 is given as
v C 1 = v B 1 d

3. Proposed Control System

Figure 5 shows the proposed converter control system. According to the figure and during the day, the duty ratio d1 is selected as the controlling variable to regulate the PV module current at the IMPP and thereby control its generated power at PMPP. Therefore, by using the MPPT algorithm, the maximum power operating current (IMPP) of the PV module is determined. Then, to determine the converter’s first switch duty cycle d1, this obtained current is applied to the utilized PI controller. Meanwhile, during the night, the duty ratio d1 is chosen as the controlling variable to adjust the LED light current at its optimum current value. Therefore, to determine the duty cycle of the converter d1, first, using the PET theory [44], the optimal operating current (IOpt) of the LED light is obtained and this value is applied to the PI controller.

4. State of Charge (SOC) Unit of the Battery

The SOC block has the task of determining the power current of the converter after checking and analyzing it in such a way that the battery voltage is within the allowed range of VBmin < VB < VBmax. (i.e., for lead–acid batteries VBmin = 11 V and VBmax = 13.5 V). The decisions made by the SOC unit are implemented in the converter through the utilization of two control signals, K and VK, in conjunction with the Vsel switch. The flowchart depicting the battery SOC is presented in Figure 6, and its corresponding rules are discussed as follows:
VB < VBmin: This mode occurs at night when the battery supplies the LED light for a long time. As a result, the battery does not have enough charge and its voltage falls lower than VBmin, so, the shutdown signal for the system is turned on by the SOC unit. When the shutdown signal arrives, the relay is disconnected from the LED. Simultaneously, the duty ratio of the converter becomes zero.
VBmin < VB < VBmax: In this state, by setting K = 1, the Vsel signal can be considered as VMPP, and by d1, the PV voltage can be adjusted at VMPP. This can lead to the battery charging with PB = PMPP.
VB > VBmax: In this situation, when the battery is fully charged, the PV module is not operated at its MPP by setting the K signal of SOC to 0 (K = 0). Consequently, the SOC output signal VK selects the Vsel signal (noting that VK is usually greater than VMPP). To keep the battery voltage constant at VBmax, the VK signal is quickly adjusted by the SOC unit. As a result of this process, the average current of the battery becomes almost zero.

5. Proposed Converter Operation Analysis

In the proposed converter, using sufficiently large capacitance and inductance values for L2, C1, and C2, these components function as nearly constant current and voltage sources for IL2, VC1, and VC2, respectively. As a result, we have VC1 > VC2. Meanwhile, the state variables iL1 and iLr are depicted with their ripple contents. In the converter analysis, if any inductor current moves to positive values, it is considered to be in a charging operating condition. Otherwise, if the inductor current moves to negative values, it is considered to be in a discharging operating condition.

5.1. Zero-Voltage Switching (ZVS)

ZVS techniques, which lead to soft switching of the converter’s power switches, have been highly regarded by designers of power electronic converters in recent years. The conventional square power conversion during key on-time with resonant switching transitions can be defined as ZVS. In general, it should be said that the basis of this function is equalizing the relationships obtained from the volt/second law at the input and output of the system. In soft-switching performance, when the switch is off, the LC circuits resonate. By doing this and by conducting the current, they bring the voltage across the switches to zero before turning it on again. Another technique that is used is the zero-current switching (ZCS) technique. In this technique, the switch is triggered when the current through it reaches zero. Similar to ZVS, the use of ZCS helps reduce switching losses [45,46].
Turning on the switch when the voltage across it is zero significantly reduces switching losses, leading to increased circuit efficiency. The following are the main advantages of using the ZVS technique:
  • Reduced switching losses.
  • Increased efficiency.
  • Ability to withstand short circuits.
  • Absence of current exceeding the peak current.
  • Reduced electromagnetic interference (EMI).
  • Possibility of high-frequency switching.
In addition to its advantages, ZVS has some disadvantages. ZVS methods may not perform effectively at light loads due to the requirement for a minimum current. Also, this method requires deadtime between switching switches. For more information about ZVS and ZCS, the reader is recommended to refer to Refs. [47,48].

5.2. Buck Operation Mode

In this section, we conduct an analysis of the operating mode of the proposed converter when it functions in buck mode, meaning that the PV-generated power is stored in the battery. As a result, negative and positive average current values are recognized for the converter’s first and second inductors, i.e., IL1 < 0 and IL2 > 0. The buck operation mode is divided into eight operating states, illustrated in Figure 7 and Figure 8, which display the converter’s key waveforms and its eight operating circuits, respectively. In each operating circuit shown in Figure 8, the actual flowing directions of the converter components are denoted by red arrows for better comprehension. The converter’s eight operating states are explained as follows.
Before the time t = 0, the antiparallel diode D1 is conducting the negative current iL1, providing ZVS conditions for the upcoming turning-on moment of the Q1 switch. The Q2 and Q3 switches are also turned off and the resonant current iLr is positive and steadily decreasing from its maximum value (ILrmax) toward zero through the Q3 switch’s antiparallel diode D3.
State I (0 ≤ t < t1): This state begins when the Q1 switch is turned on with ZVS conditions because its antiparallel diode (D1) is conducting from the preceding operating state. Two circuit loops of VB:L1:Q1 and C1:C2:D3:Lr:Q1 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are put in charging and discharging operating conditions, respectively, as follows:
i L 1 = I L 1 m i n + V B L 1 t i L r = i L r ( 0 ) V C 1 V C 2 L r t
This interval ends at t1 = ΔTs, where the resonant inductor current iLr approaches zero and, thus, the diode D1 stops conducting in ZCS conditions.
State II (t1 ≤ t < t2): In this operating state, the Q2 and Q3 switches remain turned off, while the Q1 switch is turned on. Similar to the previous state, the negative current iL1 is still in increasing mode through the circuit loop VB:L1:Q1. In addition, the resonant current iLr remains zero until the next operating state starts. Therefore, we have the following:
i L 1 = I L 1 m i n + V B L 1 t i L r = 0
State III (t2 ≤ t < t3 = dTs): In this operating state, the Q1 and Q2 switches remain turned on and off, respectively, while the Q3 switch is turned on at t = t2. Therefore, two circuit loops of VB:L1:Q1 and C1:C2:Q3:Lr:Q1 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are again put in charging and discharging operating conditions, respectively, as follows:
i L 1 = I L 1 m i n + V B L 1 t i L r = i L r ( t 2 ) V C 1 V C 2 L r ( t t 2 )
For this operating state, the increasing current iL1 and the decreasing resonant current iLr reach their maximum and minimum values of IL1max and ILrmin, respectively. Moreover, at the end of this operating state at t = t3, the first switch current (iS1 = iL1 − iLr) becomes positive since |iL1(t3)| < |iLr(t3)|.
State IV (t3 = dTs ≤ t < t4): At t = t3 = dTs, the Q1 switch is turned off, then its flowing positive current quickly transfers to the antiparallel diode D2 of Q2. This situation is the converter’s first switching deadtime, lasting for a short period of time to provide ZVS conditions for the Q2 switch at its upcoming turning-on moment. The inductor currents, iL1 and iLr, are expected to remain relatively stable compared with the previous operating state, maintaining their respective values at IL1max and ILrmin.
State V (t4 ≤ t < t5): At the initial time of this state, the Q2 switch is turned on with ZVS, while the Q3 switch is still turned on. Therefore, two circuit loops of VB:L1:Q2:C1 and C2:Q3:Lr:Q2 are recognized for the converter inductors L1 and Lr, respectively. Neglecting the previous short deadtime operating state, these inductors are put in discharging and charging operating conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r ( t d T s )
At t = t5 the increasing resonant current iLr reaches zero, which ends this operating state.
State VI (t5 ≤ t < t6): This operating state is similar to the prior state, except that the charging current of the resonant current iLr now flows with positive values, passing through the antiparallel diode D3 of Q3. Therefore, two circuit loops of VB:L1:Q2:C1 and C2:D3:Lr:Q2 are again recognized for the converter inductors L1 and Lr, putting them in discharging and charging operating conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r ( t d T s )
State VII (t6 ≤ t < t7): At the beginning of this state, the Q3 switch is turned off with ZCS, since its antiparallel diode D3 is conducting the positive current of the resonant inductor. All the other circuit conditions remain similar to those in the previous operating state, so that two circuit loops of VB:L1:Q2:C1 and C2:D3:Lr:Q2 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are still put in discharging and charging conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r + ( t d T s )
For this operating state, the decreasing current iL1 and the increasing resonant current iLr reach their minimum and maximum values of IL1min and ILrmax, respectively. At the end of this operating state t = t7, the second switch current (iS2 = −iL1 + iLr) is positive.
State VIII (t7 ≤ t < Ts): At t = t7 the Q2 switch is turned on, then its flowing positive current quickly transfers to the antiparallel diode D1 of Q1. This situation is the converter’s second switching deadtime, providing ZVS conditions for the Q1 switch at its upcoming turning-on moment. The inductor currents, iL1 and iLr, are expected to remain relatively stable compared with the previous operating state, maintaining their respective values at IL1min and ILrmax.

5.3. Boost Operation Mode

In this section, the operating mode of the proposed converter is analyzed when it operates in boost mode, i.e., when the battery-generated power is consumed by the LED light. As a result, positive and negative average current values are recognized for the converter’s first and second inductors, i.e., IL1 > 0 and IL2 < 0. The converter’s key waveforms are illustrated in Figure 9. In each operating circuit shown in Figure 9, the real flowing directions of the converter components are denoted by red arrows for better understanding. Additionally, the boost operation mode is also divided into eight operating states, shown in Figure 10. The eight operating states of the converter are explained as follows.
Before t = 0, the antiparallel diode D1 conducts a positive current (iLr − iLr), ensuring ZVS conditions for the upcoming Q1 switch turning-on event. The Q2 and Q3 switches are also turned off and the resonant current iLr is positive and gradually decreases from its maximum value (ILrmax) toward zero through the Q3 switch’s antiparallel diode D3.
State I (0 ≤ t < t1): This state begins when the Q1 switch is turned on with ZVS conditions because its antiparallel diode (D1) is conducting from the preceding state. Two circuit loops of VB:L1:Q1 and C1:C2:D3:Lr:Q1 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are put in charging and discharging operating conditions, respectively, as follows:
i L 1 = I L 1 m i n + V B L 1 t i L r = i L r ( 0 ) V C 1 V C 2 L r t
This interval ends at t1 = ΔTs, where the resonant inductor current iLr approaches zero and, thus, the diode D1 stops conducting in ZCS conditions.
State II (t1 ≤ t < t2): In this operating state, the Q2 and Q3 switches remain turned off, while the Q1 switch is turned on. Similar to the previous state, the positive current iL1 is still in a growing mode over the circuit loop VB:L1:Q1. In addition, the resonant current iLr remains zero until the next operating state starts. Therefore, we have the following:
i L 1 = I L 1 m i n + V B L 1 t i L r = 0
State III (t2 ≤ t < t3 = dTs): In this operating state, Q1 and Q2 remain turned on and off, respectively, while Q3 is turned on at t = t2. Therefore, two circuit loops of VB:L1:Q1 and C1:C2:Q3:Lr:Q1 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are put in charging and discharging operating conditions again, respectively, as follows:
i L 1 = I L 1 m i n + V B L 1 t i L r = i L r ( t 2 ) V C 1 V C 2 L r ( t t 2 )
For this state, the increasing current iL1 and the decreasing resonant current iLr reach their maximum and minimum values of IL1max and ILrmin, respectively. Moreover, at the end of this operating state t = t3, the first switch current (iS1 = iL1 − iLr) is positive since iL1(t3) > 0 and iLr(t3) < 0.
State IV (t3 = dTs ≤ t < t4): At t = t3 = dTs, Q1 is turned off, then its flowing positive current quickly transfers to the antiparallel diode D2 of Q2. This situation is the converter’s first switching deadtime, lasting for a short period of time to provide ZVS conditions for Q2 at its upcoming turning-on moment. The inductor currents iL1 and iLr are supposed to not change significantly compared with the previous operating state and, therefore, they remain at values of IL1max and ILrmin, respectively.
State V (t4 ≤ t < t5): At the beginning of this operating state, Q2 is turned on with ZVS, while Q3 is still turned on from t = t2. Therefore, two circuit loops of VB:L1:Q2:C1 and C2:Q3:Lr:Q2 are recognized for the converter inductors L1 and Lr, respectively. Neglecting the previous short deadtime operating state, these inductors are put in discharging and charging operating conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r + ( t d T s )
At t = t5, the increasing resonant current iLr reaches zero, which ends this operating state.
State VI (t5 ≤ t < t6): This operating state is similar to the previous one, except that the resonant current, iLr, now flows with positive values, passing through the antiparallel diode of Q3. Therefore, two circuit loops of VB:L1:Q2:C1 and C2:D3:Lr:Q2 are again recognized for the converter inductors L1 and Lr, putting them in discharging and charging operating conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r ( t d T s )
State VII (t6 ≤ t < t7): At the beginning of this state, Q3 is turned off with ZCS, since its antiparallel diode is conducting the positive current of the resonant inductor. All the other circuit conditions remain similar to those in the previous operating state, so that two circuit loops of VB:L1:Q2:C1 and C2:D3:Lr:Q2 are recognized for the converter inductors L1 and Lr, respectively. Therefore, these inductors are still put in discharging and charging conditions, respectively, as follows:
i L 1 = I L 1 m a x V C 1 V B L 1 ( t d T s ) i L r = I L r m i n + V C 2 L r ( t d T s )
For this operating state, the decreasing current iL1 and the increasing resonant current iLr reach their minimum and maximum values of IL1min and ILrmax, respectively. At the end of this operating state t = t7, the second switch current (iS2 = −iL1 + iLr) is positive, since |iL1(t7)| < |iLr(t7)|.
State VIII (t7 ≤ t < Ts): At t = t7, Q2 is turned on, then its flowing positive current quickly transfers to the antiparallel diode D1 of Q1. This situation is the converter’s second switching deadtime, providing ZVS conditions for Q1 at its upcoming turning-on moment. The inductor currents iL1 and iLr are supposed to not change significantly compared with the previous operating state and, therefore, they remain at values of IL1min and ILrmax, respectively.

6. Simulation Results

We assume the use of a 60 W LED streetlight, a PV module, and a 12 V battery source for investigating the proposed system. To address the issue of weak brightness from a single LED, we can connect multiple LEDs in series and parallel [49,50]. In the simulation, 20 LEDs are used in two strings, with each string having 10 LEDs in series. Table 1 displays the parameters of the LED streetlight used, with each LED having a maximum power of 3 W. In Figure 11, the P-V output characteristics of the PV module are shown for three different examined environmental conditions. Also, a 12 V lead–acid battery source is used for the proposed system. In this simulation, the PV module should charge the battery during the day under MPPT conditions. However, at night, the battery supplies the LED light at the optimal current. The proposed converter is switched under the soft-switching condition of ZVS in both its operation modes and ZCS. In buck and boost operation modes, and as seen in the simulation waveforms, the voltages of Q1 and Q2 were previously decreased to the zero level, denoting successful ZVS conditions for these switches. Moreover, Q3 is turned off when its current is negative (following through D3), thus providing ZCS conditions for this switch.
In all the simulations, the possible minimum and maximum levels of the solar irradiations and the ambient temperature were considered. The system was simulated by applying PSCAD/EMTDC software. The simulation of the proposed system was conducted in two modes, day and night. System operation in the day and night modes includes three and two operational stages, respectively, which are discussed below.

6.1. Daytime Operation

For day operation times, the simulation was performed in three different stages. In all stages, IL2ref was chosen to be the IMPP of the PV module. The battery voltage VB, PV voltage VPV, currents IL2, VC1, VC2, resonant inductor current iLr, and converter duty ratio are clearly shown in Figure 12.
First simulation stage 0 ≤ t < 0.06 s: The maximum amount of solar radiation (G = 1000 W/m2) at the ambient temperature (35 °C) is considered in this stage. First, by using the MPPT algorithm, the maximum power operating current (IMPP) of the PV module is specified. Then, to determine the first switch duty cycle d, this obtained value is applied to the PI controller. According to the characteristics of the module by duty ratio d = 0.54, the maximum voltage and current of the PV module are obtained as 27.6 V and 2.37 A, respectively. In this mode, PPV = 65.4 W is transmitted through the buck operation mode of the converter to charge the battery with a current of IB = −5.1 A and voltage of VB = 12 V. For more clarification, the currents in the converter’s inductors (IL1, IL2, ILr), the currents in the converter’s switches (Is1, Is2, Is3), the drain–source voltages across the converter’s switches (Vds1, Vds2, Vds3), and the switches’ gate signals are illustrated in Figure 13 for two switching periods.
Second simulation stage 0.06 ≤ t < 0.12 s: The amount of radiation is reduced (G = 600 W/m2) in this stage, but the temperature is still 35 °C. Considering that the voltage and current of the module can be affected by radiation, by using the duty cycle d = 0.48, the magnitude of these values is obtained as VPV = 24.1 V, IPV = 1.44 A. Therefore, the output power of the PV module decreases (PPV = 34.7 W) due to the reduction in radiation. Also, the battery charging current and voltage are reduced to IB = −2.8 A and VB = 12 V, respectively. For more clarification, the currents in the converter’s inductors (IL1, IL2, ILr), the currents in the converter’s switches (Is1, Is2, Is3), the drain–source voltages across the converter’s switches (Vds1, Vds2, Vds3), and the switches’ gate signals are illustrated in Figure 14 for two switching periods.
Third simulation stage 0.12 ≤ t < 0.18 s: At night, the air cools down and the temperature drops below zero. Due to this decrease in temperature, the level of radiation and the temperature of the PV module are equal to 600 W/m2 and −5 °C, respectively. In the duty cycle d = 0.58, the MPPT control sets the values of the voltage, current, and PV power at values of 30 V, 1.4 A, and 42 W, respectively. In this condition, the battery voltage is equal to VB = 12 V and it continues to charge with a current of IB = −3.4 A. For more clarification, the currents in the converter’s inductors (IL1, IL2, ILr), the currents in the converter’s switches (Is1, Is2, Is3), the drain–source voltages across the converter’s switches (Vds1, Vds2, Vds3), and the switches’ gate signals are illustrated in Figure 15 for two switching periods.

6.2. Nighttime Operation

The relay is closed to the LED light at night and its simulation is performed in two different stages. In both stages, Iled is chosen to be set at IL2ref, which is determined by (17) the optimal current of the LED light. The battery voltage VB, the LED light voltage and current Vled, IL2, the voltages VC1, VC2, the resonant inductor current iLr, and the converter duty ratio are clearly shown in Figure 16.
First simulation stage 0 ≤ t < 0.09 s: In this stage, the ambient temperature is considered to be 35 °C due to the effect of temperature on LED light. First, by using PET theory, the optimal operating current of the LED light is determined. Next, to determine the duty cycle of the converter d, this obtained current (IL2ref = −Iopt) is applied to the PI controller. Thus, the streetlight is driven in the optimal current and voltage values of VLED = 37.5 V and ILED = 1.35 A, respectively, which results in a discharging current of IB = 4.5 A and a voltage of VB = 12 V for the battery. For more clarification, the currents in the converter’s inductors (IL1, IL2, ILr), the currents in the converter’s switches (Is1, Is2, Is3), the drain–source voltages across the converter’s switches (Vds1, Vds2, Vds3), and the switches’ gate signals are illustrated in Figure 17 for two switching periods.
Second simulation stage 0.09 ≤ t < 0.18 s: At this step, the ambient temperature drops to −5 °C and other specifications are the same as in the previous stage. Therefore, the optimum operating point of the LED light changes to VLED = 38 V and ILED = 1.2 A, causing the discharging current to be IB = 4 A and voltage to be VB = 12 V for the battery. To provide further clarity, Figure 18 illustrates the currents in the converter’s inductors (IL1, IL2, ILr), the currents in the converter’s switches (Is1, Is2, Is3), the drain–source voltages across the switches (Vds1, Vds2, Vds3), and the gate signals for two switching periods.
As shown in all the presented simulation results, the turning-on and turning-off times of the S1 and S2 switches are opposite to each other. In all cases, the current of the resonant inductor Lr is greater than the current of the other two inductors L1 and L2, which is necessary to create soft-switching conditions. Additionally, soft switching of the power switches of the converter is performed correctly, as shown in the voltage sections of the switches and their gate signals.

7. Conclusions

This article introduces a bidirectional boost converter to manage PV-powered LED lighting and battery storage. To enhance efficiency, a soft-switched version of the converter is created by incorporating an L-C-Switch series resonant circuit into the standard bidirectional DC/DC converter. The adopted topology enables soft switching in both buck and boost operational modes. During the day, the proposed converter operates in a manner that allows it to efficiently transfer PV MPP energy to the battery in the buck operational mode. At night, in boost operation mode, the LED light is powered by the battery. This structure, which can change its mode of operation, offers a cost-effective and simplified design. A comprehensive control strategy is proposed for the system in both cases to regulate current at the converter’s input and output terminals, SOC for the battery, MPPT for the PV panel, and light control for the LED light. The theory used in this system considers the optical, electrical, and thermal characteristics of the LEDs, optimizing the LED light’s operating current to achieve maximum luminous flux. An efficient control system was designed to adjust the LED light voltage, charge the battery, and perform MPPT. The proposed system offers compact and single-stage power conversion. Finally, the system’s performance was successfully validated in various environmental conditions using PSCAD/EMTDC software. Future work can explore alternative methods for achieving soft switching of the power switches and investigate the feasibility of using multiple input sources for the converter.

Author Contributions

Conceptualization, S.D., M.S., J.T. and A.G.R.; methodology, S.D., M.S., J.T. and A.G.R.; validation and formal analysis, M.M.S. and A.S.; visualization, S.D. and M.S.; investigation, all authors; writing—original draft preparation, S.D., M.S., J.T. and A.G.R.; writing—review and editing, M.M.S. and A.S.; supervision, M.S. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liu, X.; Zhao, M.; Wei, Z.; Lu, M. Economic Optimal Scheduling of Wind–Photovoltaic-Storage with Electric Vehicle Microgrid Based on Quantum Mayfly Algorithm. Appl. Sci. 2022, 12, 8778. [Google Scholar] [CrossRef]
  2. Iranmehr, H.; Aazami, R.; Tavoosi, J.; Shirkhani, M.; Azizi, A.R.; Mohammadzadeh, A.; Mosavi, A.H.; Guo, W. Modeling the price of emergency power transmission lines in the reserve market due to the influence of renewable energies. Front. Energy Res. 2022, 9, 944. [Google Scholar] [CrossRef]
  3. Guo, S.; Zhao, X.; Wang, H.; Xu, N. Distributed consensus of heterogeneous switched nonlinear multiagent systems with input quantization and DoS attacks. Appl. Math. Comput. 2023, 456, 128127. [Google Scholar] [CrossRef]
  4. Danyali, S.; Aazami, R.; Moradkhani, A.; Haghi, M. A new dual-input three-winding coupled-inductor based DC-DC boost converter for renewable energy applications. Int. Trans. Electr. Energy Syst. 2021, 31, e12686. [Google Scholar] [CrossRef]
  5. Tang, F.; Wang, H.; Zhang, L.; Xu, N.; Ahmad, A.M. Adaptive optimized consensus control for a class of nonlinear multi-agent systems with asymmetric input saturation constraints and hybrid faults. Commun. Nonlinear Sci. Numer. Simul. 2023, 126, 107446. [Google Scholar] [CrossRef]
  6. Aazami, R.; Heydari, O.; Tavoosi, J.; Shirkhani, M.; Mohammadzadeh, A.; Mosavi, A. Optimal Control of an Energy-Storage System in a Microgrid for Reducing Wind-Power Fluctuations. Sustainability 2022, 14, 6183. [Google Scholar] [CrossRef]
  7. Cheng, F.; Niu, B.; Xu, N.; Zhao, X.; Ahmad, A.M. Fault detection and performance recovery design with deferred actuator replacement via a low-computation method. IEEE Trans. Autom. Sci. Eng. 2023. [Google Scholar] [CrossRef]
  8. Danyali, S.; Aghaei, O.; Shirkhani, M.; Aazami, R.; Tavoosi, J.; Mohammadzadeh, A.; Mosavi, A. A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems. Sustainability 2022, 14, 11731. [Google Scholar] [CrossRef]
  9. Zhang, H.; Zou, Q.; Ju, Y.; Song, C.; Chen, D. Distance-based support vector machine to predict DNA N6-methyladenine modification. Curr. Bioinform. 2022, 17, 473–482. [Google Scholar] [CrossRef]
  10. Teng, J.; Shen, P.; Liu, B.; Chen, S. Circuit configurable bidirectional dc-dc converter for retired batteries. IEEE Access 2021, 9, 156187–156199. [Google Scholar] [CrossRef]
  11. Wu, W.; Xu, N.; Niu, B.; Zhao, X.; Ahmad, A.M. Low-Computation Adaptive Saturated Self-Triggered Tracking Control of Uncertain Networked Systems. Electronics 2023, 12, 2771. [Google Scholar] [CrossRef]
  12. Gorji, S.A.; Sahebi, H.G.; Ektesabi, M.; Rad, A.B. Topologies and control schemes of bidirectional DC–DC power converters: An overview. IEEE Access 2019, 7, 117997–118019. [Google Scholar] [CrossRef]
  13. Cao, C.; Wang, J.; Kwok, D.; Cui, F.; Zhang, Z.; Zhao, D.; Li, M.J.; Zou, Q. webTWAS: A resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Nucleic Acids Res. 2022, 50, D1123–D1130. [Google Scholar] [CrossRef]
  14. Hasanpour, S.; Mostaan, A.; Baghramian, A.; Mojallali, H. Analysis, modeling, and implementation of a new transformerless semi-quadratic Buck-boost DC/DC converter. Int. J. Circuit Theory Appl. 2019, 47, 862–883. [Google Scholar] [CrossRef]
  15. Zhao, Y.; Niu, B.; Zong, G.; Zhao, X.; Alharbi, K.H. Neural network-based adaptive optimal containment control for non-affine nonlinear multi-agent systems within an identifier-actor-critic framework. J. Frankl. Inst. 2023, 360, 8118–8143. [Google Scholar] [CrossRef]
  16. Athikkal, S.; Kumar, G.G.; Sundaramoorthy, K.; Sankar, A. A non-isolated bridge-type DC–DC converter for hybrid energy source integration. IEEE Trans. Ind. Appl. 2019, 55, 4033–4043. [Google Scholar] [CrossRef]
  17. Pan, X.; Li, H.; Liu, Y.; Zhao, T.; Ju, C.; Rathore, A.K. An overview and comprehensive comparative evaluation of current-fed-isolated-bidirectional DC/DC converter. IEEE Trans. Power Electron. 2019, 35, 2737–2763. [Google Scholar] [CrossRef]
  18. Huang, S.; Zong, G.; Wang, H.; Zhao, X.; Alharbi, K.H. Command filter-based adaptive fuzzy self-triggered control for MIMO nonlinear systems with time-varying full-state constraints. Int. J. Fuzzy Syst. 2023, 1–8. [Google Scholar] [CrossRef]
  19. Xu, Q.; Vafamand, N.; Chen, L.; Dragičević, T.; Xie, L.; Blaabjerg, F. Review on advanced control technologies for bidirectional DC/DC converters in DC microgrids. IEEE J. Emerg. Sel. Top. Power Electron. 2020, 9, 1205–1221. [Google Scholar] [CrossRef]
  20. Cheng, X.F.; Liu, C.; Wang, D.; Zhang, Y. State-of-the-art review on soft-switching technologies for non-isolated DC-DC converters. IEEE Access 2021, 9, 119235–119249. [Google Scholar] [CrossRef]
  21. Hussain, M.; Rehan, M.; Ahn, C.K.; Tufail, M. Robust antiwindup for one-sided Lipschitz systems subject to input saturation and applications. IEEE Trans. Ind. Electron. 2018, 65, 9706–9716. [Google Scholar] [CrossRef]
  22. Sorouri, H.; Sedighizadeh, M.; Oshnoei, A.; Khezri, R. An intelligent adaptive control of DC–DC power buck converters. Int. J. Electr. Power Energy Syst. 2022, 141, 108099. [Google Scholar] [CrossRef]
  23. Liu, G. Sustainable feasibility of solar photovoltaic powered street lighting systems. Int. J. Electr. Power Energy Syst. 2014, 56, 168–174. [Google Scholar] [CrossRef]
  24. Duman, A.C.; Güler, Ö. Techno-economic analysis of off-grid photovoltaic LED road lighting systems: A case study for northern, central and southern regions of Turkey. Build. Environ. 2019, 156, 89–98. [Google Scholar] [CrossRef]
  25. Sutopo, W.; Mardikaningsih, I.S.; Zakaria, R.; Ali, A. A model to improve the implementation standards of street lighting based on solar energy: A case study. Energies 2020, 13, 630. [Google Scholar] [CrossRef]
  26. Lagorse, J.; Paire, D.; Miraoui, A. Sizing optimization of a stand-alone street lighting system powered by a hybrid system using fuel cell, PV and battery. Renew. Energy 2009, 34, 683–691. [Google Scholar] [CrossRef]
  27. Purwadi, A.; Haroen, Y.; Ali, F.Y.; Heryana, N.; Nurafiat, D.; Assegaf, A. Prototype development of a Low Cost data logger for PV based LED Street Lighting System. In Proceedings of the 2011 International Conference on Electrical Engineering and Informatics, Bandung, Indonesia, 17 July 2011; IEEE: Piscataway, NJ, USA, 2011; pp. 1–5. [Google Scholar]
  28. Mahmoud, M.M. Economic model for calculating the global saving norm of replacement high-intensity discharge lamps with LED lamp in oil and gas plant. In Proceedings of the 2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), Riga, Latvia, 5–7 November 2020; IEEE: Piscataway, NJ, USA, 2020; pp. 1–5. [Google Scholar]
  29. Borekci, S.; Acar, N.C.; Kircay, A. LED dimming technique without frequency and pulse width modulations. Int. J. Circuit Theory Appl. 2018, 46, 2028–2037. [Google Scholar] [CrossRef]
  30. Hwu, K.I.; Jiang, W.Z.; Chen, W.H. Automatic current-sharing extendable two-channel LED driver with non-pulsating input current and zero dc flux. Int. J. Circuit Theory Appl. 2018, 46, 1462–1484. [Google Scholar] [CrossRef]
  31. Althib, H. Effect of quantum barrier width and quantum resonant tunneling through InGaN/GaN parabolic quantum well-LED structure on LED efficiency. Results Phys. 2021, 22, 103943. [Google Scholar] [CrossRef]
  32. Cheng, J.H.; Liu, C.K.; Chao, Y.L.; Tain, R.M. Cooling performance of silicon-based thermoelectric device on high power LED. In Proceedings of the 24th International Conference on Thermoelectrics, Clemson, SC, USA, 19–23 June 2005; pp. 53–56. [Google Scholar]
  33. Juda, M.; Liu-Ambrose, T.; Feldman, F.; Suvagau, C.; Mistlberger, R.E. Light in the Senior Home: Effects of Dynamic and Individual Light Exposure on Sleep, Cognition, and Well-Being. Clocks Sleep 2020, 2, 557–576. [Google Scholar] [CrossRef]
  34. Qin, Y.X.; Lin, D.Y.; Hui, S.Y.R. A Simple Method for Comparative Study on the Thermal Performance of Light Emitting Diodes (LED) and Fluorescent Lamps. IEEE Trans. Power Electron. 2009, 24, 1811–1818. [Google Scholar]
  35. Kulkarni, S.A.; Mhaisalkar, S.G.; Mathews, N.; Boix, P.P. Perovskite nanoparticles: Synthesis, properties, and novel applications in photovoltaics and LEDs. Small Methods 2019, 3, 1800231. [Google Scholar] [CrossRef]
  36. Kiwan, S.; Abo Mosali, A.; Al-Ghasem, A. Smart solar-powered LED outdoor lighting system based on the energy storage level in batteries. Buildings 2018, 8, 119. [Google Scholar] [CrossRef]
  37. Saeed, M.A.; Kim, S.H.; Baek, K.; Hyun, J.K.; Lee, S.Y.; Shim, J.W. PEDOT: PSS: CuNW-based transparent composite electrodes for high-performance and flexible organic photovoltaics under indoor lighting. Appl. Surf. Sci. 2021, 567, 150852. [Google Scholar] [CrossRef]
  38. Tran, T.K.; Yahoui, H.; Siauve, N.; Nguyen-Quang, N.; Genon-Catalot, D. Construct and control a PV based independent public LED street lighting system with an efficient battery management system based on the powerline communication. In Proceedings of the IEEE Second International Conference on DC Microgrids (ICDCM), Nuremburg, Germany, 27–29 June 2017; pp. 497–501. [Google Scholar]
  39. Baureis, P. Compact modeling of electrical, thermal and optical LED behavior. In Proceedings of the 35th European Solid-State Device Research Conference, Grenoble, France, 12–16 September 2005; pp. 145–148. [Google Scholar]
  40. Wei, J.; Yi, Z.; Wang, L.; Liu, L.; Wu, H.; Wang, G.; Zhang, B. White LED light emission as a function of current and junction temperature. In Proceedings of the IEEE International Forum on Solid State Lighting, Beijing, China, 10–12 November 2013; pp. 166–169. [Google Scholar]
  41. Wang, Y.; Guan, Y.; Xu, D.; Wang, W. A CLCL resonant DC/DC converter for two-stage LED driver system. IEEE Trans. Ind. Electron. 2015, 63, 2883–2891. [Google Scholar] [CrossRef]
  42. Chen, X.; Huang, D.; Li, Q.; Lee, F.C. Multichannel LED driver with CLL resonant converter. IEEE J. Emerg. Sel. Top. Power Electron. 2015, 3, 589–598. [Google Scholar] [CrossRef]
  43. Poorali, B.; Adib, E. Analysis of the integrated SEPIC-flyback converter as a single-stage single-switch power-factor-correction LED driver. IEEE Trans. Ind. Electron. 2016, 63, 3562–3570. [Google Scholar] [CrossRef]
  44. Chen, H.; Lee, A.T.; Tan, S.C.; Hui, S.Y. Dynamic optical power measurements and modeling of light-emitting diodes based on a photodetector system and photo-electro-thermal theory. IEEE Trans. Power Electron. 2019, 34, 10058–10068. [Google Scholar] [CrossRef]
  45. Rodrigues, J.P.; Mussa, S.A.; Barbi, I.; Perin, A.J. Three-level zero-voltage switching pulse-width modulation DC–DC boost converter with active clamping. IET Power Electron. 2010, 3, 345–354. [Google Scholar] [CrossRef]
  46. Lin, B.R.; Dong, J.Y. New zero-voltage switching DC–DC converter for renewable energy conversion systems. IET Power Electron. 2012, 5, 393–400. [Google Scholar] [CrossRef]
  47. Zheng, Y.; Brown, B.; Xie, W.; Li, S.; Smedley, K. High step-up DC–DC converter with zero voltage switching and low input current ripple. IEEE Trans. Power Electron. 2020, 35, 9416–9429. [Google Scholar] [CrossRef]
  48. Liu, K.H.; Lee, F.C. Zero-voltage switching technique in DC/DC converters. In Proceedings of the 1986 17th Annual IEEE Power Electronics Specialists Conference, Vancouver, BC, Canada, 23–27 June 1986; IEEE: Piscataway, NJ, USA, 1986; pp. 58–70. [Google Scholar]
  49. Archibong, E.I.; Ozuomba, S.; Ekott, E. Internet of things (IoT)-based, solar powered street light system with anti-vandalisation mechanism. In Proceedings of the 2020 International Conference in Mathematics, Computer Engineering and Computer Science (ICMCECS), Ayobo, Nigeria, 18–21 March 2020; IEEE: Piscataway, NJ, USA, 2020; pp. 1–6. [Google Scholar]
  50. Vijay, M.D.; Shah, K.; Bhuvaneswari, G.; Singh, B. LED based street lighting with automatic intensity control using solar PV. In Proceedings of the 2015 IEEE IAS Joint Industrial and Commercial Power Systems/Petroleum and Chemical Industry Conference (ICPSPCIC), Hyderabad, India, 19–21 November 2015; IEEE: Piscataway, NJ, USA, 2015; pp. 197–202. [Google Scholar]
Figure 1. PV-powered LED streetlight system.
Figure 1. PV-powered LED streetlight system.
Sustainability 15 15022 g001
Figure 2. Proposed soft-switching bidirectional DC/DC converter for LED streetlight system.
Figure 2. Proposed soft-switching bidirectional DC/DC converter for LED streetlight system.
Sustainability 15 15022 g002
Figure 3. Daytime operation.
Figure 3. Daytime operation.
Sustainability 15 15022 g003
Figure 4. Nighttime operation.
Figure 4. Nighttime operation.
Sustainability 15 15022 g004
Figure 5. Proposed control system.
Figure 5. Proposed control system.
Sustainability 15 15022 g005
Figure 6. Flowchart representing the battery SOC unit.
Figure 6. Flowchart representing the battery SOC unit.
Sustainability 15 15022 g006
Figure 7. Converter waveforms in buck operation mode.
Figure 7. Converter waveforms in buck operation mode.
Sustainability 15 15022 g007
Figure 8. Different converter operating states in buck operation mode.
Figure 8. Different converter operating states in buck operation mode.
Sustainability 15 15022 g008aSustainability 15 15022 g008b
Figure 9. Converter waveforms in boost operation mode.
Figure 9. Converter waveforms in boost operation mode.
Sustainability 15 15022 g009
Figure 10. Different converter operating states in boost operation mode.
Figure 10. Different converter operating states in boost operation mode.
Sustainability 15 15022 g010aSustainability 15 15022 g010b
Figure 11. P-V output characteristics of the utilized PV module.
Figure 11. P-V output characteristics of the utilized PV module.
Sustainability 15 15022 g011
Figure 12. Transient visions of different waveforms of the proposed converter during the daytime simulation test.
Figure 12. Transient visions of different waveforms of the proposed converter during the daytime simulation test.
Sustainability 15 15022 g012
Figure 13. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the first simulation stage of the converter’s daytime operation.
Figure 13. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the first simulation stage of the converter’s daytime operation.
Sustainability 15 15022 g013
Figure 14. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the second simulation stage of the converter’s daytime operation.
Figure 14. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the second simulation stage of the converter’s daytime operation.
Sustainability 15 15022 g014
Figure 15. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the third simulation stage of the converter’s daytime operation.
Figure 15. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the third simulation stage of the converter’s daytime operation.
Sustainability 15 15022 g015
Figure 16. Transient visions of different waveforms of the proposed converter during the nighttime simulation test.
Figure 16. Transient visions of different waveforms of the proposed converter during the nighttime simulation test.
Sustainability 15 15022 g016
Figure 17. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the first simulation stage of the converter’s nighttime operation.
Figure 17. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the first simulation stage of the converter’s nighttime operation.
Sustainability 15 15022 g017
Figure 18. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the second simulation stage of the converter’s nighttime operation.
Figure 18. Two switching periods of the currents IL1, IL2, ILr, Is1, Is2, Is3, voltages Vds1, Vds2, Vds3, and gate signals S1, S2, and S3 during the second simulation stage of the converter’s nighttime operation.
Sustainability 15 15022 g018
Table 1. LED streetlight simulation parameters.
Table 1. LED streetlight simulation parameters.
SymbolsSimulation ParametersSymbolsSimulation Parameters
WLED 0.14 (m)M18
LLED0.16 (m)ke−0.0045
Wb0.20 (m)khs200 (w/m·k)
Lb0.22 (m)E078.5 (lm/w)
tb0.015 (m)hfluid95 (w/m·k)
tf0.005 (m)Rjc8 (°C/W)
Hf0.01 (m)M18
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

Danyali, S.; Shirkhani, M.; Tavoosi, J.; Razi, A.G.; Salah, M.M.; Shaker, A. Developing an Integrated Soft-Switching Bidirectional DC/DC Converter for Solar-Powered LED Street Lighting. Sustainability 2023, 15, 15022. https://doi.org/10.3390/su152015022

AMA Style

Danyali S, Shirkhani M, Tavoosi J, Razi AG, Salah MM, Shaker A. Developing an Integrated Soft-Switching Bidirectional DC/DC Converter for Solar-Powered LED Street Lighting. Sustainability. 2023; 15(20):15022. https://doi.org/10.3390/su152015022

Chicago/Turabian Style

Danyali, Saeed, Mohammadamin Shirkhani, Jafar Tavoosi, Ali Ghazi Razi, Mostafa M. Salah, and Ahmed Shaker. 2023. "Developing an Integrated Soft-Switching Bidirectional DC/DC Converter for Solar-Powered LED Street Lighting" Sustainability 15, no. 20: 15022. https://doi.org/10.3390/su152015022

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