Luo converter Research Papers

Analysis of SEPIC Converter at Different Switching Frequencies

2025, International Journal of Electrical and Electronics Research

Single Ended Primary Inductance Converter (SEPIC) which is commonly devoted as a switched power supply in many applications is presented in this work to conclude the effect of switching frequency on the output voltage time response,... more

descriptionView Paper arrow_downwardDownload

Optimizing Solar PV Array Reconfiguration for Maximum Power Extraction Using Hippopotamus Algorithm under Partial Shading

by FOREX Publication

2025, International Journal of Electrical and Electronics Research (IJEER)

This research paper presents an innovative approach to maximizing power extraction from solar photovoltaic (PV) arrays under partial shading conditions by employing the Hippopotamus Optimization Algorithm (HOA). Partial shading is a... more

descriptionView Paper arrow_downwardDownload

Solar and battery input super boost DC-DC converter for solar powered electric vehicle

by International Journal of Applied Power Engineering (IJAPE) and

2025, International Journal of Applied Power Engineering (IJAPE)

The electric vehicle (EV) is increasingly emerging as an attractive solution to reduce reliance on fossil fuels in India. In commercial EVs, solar photovoltaic (PV) technology is employed both to charge the battery and power the vehicle.... more

descriptionView Paper arrow_downwardDownload

Grid connected solar water pumping system

by International Journal of Applied Power Engineering (IJAPE)

2025, International Journal of Applied Power Engineering (IJAPE)

A grid-connected solar water pumping system (SWPS) uses solar power to pump water while simultaneously drawing power from the grid when necessary. These systems can benefit farmers in a variety of ways, including reliable power, lower... more

descriptionView Paper arrow_downwardDownload

Comparison of MPP methods for photovoltaic system

by International Journal of Applied Power Engineering (IJAPE)

2025, International Journal of Applied Power Engineering (IJAPE)

Solar electricity is usually a ubiquitous photovoltaic (PV) power source that converts sunlight into electricity. This makes solar energy a key factor in meeting the growing global demand. However, solar energy production from... more

descriptionView Paper arrow_downwardDownload

A Photo-Voltaic System Voltage Controller with Battery Storage for Independent Uses

by Editor JETS

2025, Surya Publishers

The research develops a brand-new voltage regulator system for stand-alone photovoltaic installations incorporating battery storage elements. The PV array output experiences fluctuations based on weather factors which result in... more

descriptionView Paper arrow_downwardDownload

Speed control analysis of voltage source inverter fed brushless DC motor

by International Journal of Applied Power Engineering (IJAPE)

2025, International Journal of Applied Power Engineering

The brushless DC (BLDC) motor requires to be controlled at the preferred speed in order to operate. A brushless DC motor's speed can be adjusted by adjusting the input voltage. In general, speed increases with voltage. The application of... more

descriptionView Paper arrow_downwardDownload

Performance improvement in photovoltaic-grid system using genetic algorithm

by Indonesian Journal of Electrical Engineering and Computer Science

2024, Indonesian Journal of Electrical Engineering and Computer Science

In recent, photovoltaic (PV) power generation has increased in importance. The growing significance of PV power production has generated the demand for enhancing energy efficiency via continuous operation at the maximum power point (MPP).... more

descriptionView Paper arrow_downwardDownload

Independent swarm grid vehicle charging by a logical DC-DC converter with hybrid boundary conduction mode

by Indonesian Journal of Electrical Engineering and Computer Science

2024, Indonesian Journal of Electrical Engineering and Computer Science

A modern and expanding civilization now takes for granted that future environments will be clean, efficient, and carbon neutral. Energy-efficient electrical loads, such as vehicle charging now often used in schools, companies, and gated... more

descriptionView Paper arrow_downwardDownload

Preliminary design report for the power distribution block Project

by MARINA SOCORRO PROL PEREZ

2024

This document reports the preliminary design of the Power Distribution Unit (PDU) of the NEWTON instrument. The PDU supplies energy to the Control Unit (CU) and the Sensor Unit (SU) and it is composed by two different blocks, the power... more

D3.3 - Preliminary design report for the power distribution block FIGURE 1. Block Diagram of the NEWTON muti-sensor instrument for prototype 1 and prototype 2.

FIGURE 2. Block Diagram of the NEWTON multi-sensor instrument for prototype 3.

FIGURE 3 shows the block diagram of the DC/DC converter. As it can be seen, the converter receives the primary power from the rover in the case of prototype 1 and 3, and from external batteries in the case of prototype 2, and provides three different output voltages with different power consumptions which interface with the sensor unit and the electronic control block respectively. As already mentioned in section 2, prototype 1 and 2 will be tested in field campaigns on different scientific demonstrations sites so external portable batteries will be used to emulate the primary power. In the case of prototype 3, which will be tested on the laboratory, commercial power sources will be used. Although, there is no concrete requirements in terms of efficiency, the target is to achieve maximum efficiency (>90%) in order to save a maximum electrical power due to the scenarios of application of all prototypes are a limited energy scenario. Similarly, there is no concrete requirements with respect to size and weight. However, the target is also to reduce the size and weight of the conversor while the efficiency is maximized.

FIGURE 4 shows different non-isolated and isolated switch model power supply (SMPS). At this stage of the project, different solutions have been analyzed in order to find the most suitable solution for NEWTON instrument taking into account the requirements of the three prototypes which are being developed within the project.

FIGURE 5. Flyback circuit configuration. The Flyback is the simplest and most common of the isolated topologies for low-power (5-150W) and low cost with possibly the lower component count. The output voltage isolation is guaranteed with two coupled inductances, a primary inductance, L,, and a secondary inductance, L;. On the input side there is only one winding, Lp, which means that only one power transistor is required. On the output side there is only the output capacitor, C,, and one switch, which can be a power diode or a power transistor in the case of synchronous rectification. Therefore, there is no need to use an external inductor to filter the output voltage, which means less space required.

As it’s shown in FIGURE 6, during t., energy is stored in the transformer magnetic core through L, inductance, while the output capacitor delivers energy to the load. During to; the energy stored in the core is transferred to the output, resulting on a current in Ls inductance which forward-biases the output diode and delivers current to the load while charging the output capacitor as well. FIGURE 7 shows some waveforms present in the Flyback converter operation depending on the state of the switch. FIGURE 6. Flyback converter operation: On-state (switch closed) and Off-state (switch open).

Taking into account the analysis presented above, a Flyback operating in CCM is selected for its implementation. FIGURE 8 illustrates the block diagram and the schematic of the Flyback DC/DC converter.

TABLE 3. Comparative analysis between Flyback and Forward converters. DOUBLE-ENDED CONVERTERS (MEDIUM POWER): HALF-BRIDGE VS PUSH-PULL D3.3 - Preliminary design report for the power distribution block

D3.3 - Preliminary design report for the power distribution block

TABLE 1. Requirements for the design of the PDU.

aim of activating the clamping circuit as soon as possible. FIGURE 9 shows the circuits and Vd: waveform. In some occasions, and depending of the transformer manufacture, the leakage inductance could be placed in the secondary side, affecting the voltage over the rectifier. Due to the parasitic of the output diode (commonly a capacitance in parallel) and that undesired and not-coupled induction an oscillation or transient could happen in Vd. As shown in FIGURE 10 this effect can be minimized by placing a RC circuit to snub that overvoltage oscillation. D3.3 - Preliminary design report for the power distribution block

FIGURE 12. Opto-coupler and feedback circuitry.

The evaluation of the Flyback converter has been carried out using PSPICE simulator. FIGURE 13 shows the schematic used in the simulations. Simulations have been done with non-ideal components excluding feedback. FIGURE 13. Schematic of the Flyback converter (open loop simulation).

FIGURE 16. Basic schematic of the Half-bridge converter.

FIGURE 18. Simulation schematic of the Half-bridge converter. D3.3 - Preliminary design report for the power distribution block

D3.3 - Preliminary design report for the power distribution block FIGURE 21. Basic circuit configuration of a buck converter.

FIGURE 22. Buck converter operation: On-state (switch closed) and Off-state (switch open).

At this point, a synchronous buck converter operating in continuous conduction mode is considered. The inductor current is continuous and never reaches zero during one switching period (Ts), the relation between output and input voltage is given by:

FIGURE 24 shows the basic schematic of a synchronous buck converter. As can be seen, it is composed by two MOSFET, and output inductor and output capacitors.Q1, is connected directly to the input voltage circuit. When Q1 turns on, IUPPER is supplied to the load through Q1. During this time, the current through the inductor increases and Q2 is off. When Q1 turns off, Q2 turns on and ILOWER is supplied to the load through Q2. During this time, the inductor current decreases [10],[11]. At this stage of the project, a commercial solution based on GaN technology has been used to validate the concept and to analyzed experimentally the advantages and disadvantages of the buck converter. This solution is based on GaN-on silicon E-HEMT transistor (GS61008P). The properties of GaN allow for high current, high voltage breakdown and high switching frequency which combine to provide very high efficiency power switching. The validation of the concept has been carried out by means of using a demo board of a synchronous buck DC/DC converter provided by GaN Systems [12]. This demo board comprises a universal GaN half bridge with open loop control and on-board PWM dead time generation which is used to implement a 48-12V synchronous buck DC/DC conversor. The circuit schematic of the evaluation board is shown in FIGURE 25.

2. LEVEL 2 - INTELLIGENT POWER INTEGRATION (PROPORTIONAL CONTROL): This integration level add: additional digital control to the standard analog design and Level 1 basic control features to actively adjust the output voltage, voltage limits, current limits and thermal limits. At this level, most of the operating parameters of the analog power supply can be digitally controlled and monitored. For instance, the output voltage can be fine-tuned to provide coordination between multiple power supplies in a system. Depending on the system I/O requirements, 8-bit solutions, like in the PIC12, PIC16 or PIC18 device families, car provide good performance, while larger systems may require the flexibility of a 16 bit microcontroller, as the included in PIC24 family. Intelligence can be added to an existing power supply design with minimal modifications. Level integration typically involves monitoring and basic control functions, so microcontrollers which integra‘ voltage comparators and ADCs are good choices. Additionally, communications peripherals may k required. Many microcontrollers, as Microchip's PICLOF and PIC12F 8-bit low pin count and small packag microcontrollers with built-in peripherals, such as ADC, PWM and GPIOs, can make the existing analc oower supplies intelligent by controlling the output sequencing and monitoring of input/output voltag: current and temperature.

A Level 2 control system has much greater integration with the power supply and allows better power supply environment monitoring. Integrated comparators can also be used to ensure fast response to system events or faults. A PWM peripheral is used to provide direct control of the analog PWM circuitry of the power unit, and can control the power-up conditions to provide soft-start. The MCU can monitor the power supply input current during the soft-start to ensure that components are not over-stressed. Serial

=: 3. LEVEL 3 - INTELLIGENT POWER INTEGRATION (TOPOLOGY CONTROL): In addition to Level 1 and Level 2 features, this level permits the standard analog design to be reconfigured, including changing the analog loop configuration and alternating between two different analog control loop filters. For example, a power supply can change from a PWM control loop to a hysteretic control loop at light loads, thereby increasing system efficiency. Switching frequency adjustment can also be used to minimize losses. Microchip's entire range of PIC® MCUs and dsPIC® DSCs can assist in Level 3 control applications. communication peripherals allow coordination from a host device, control and monitoring of cooling fan and temperature sensors.

For instance, Microchip’s family of Digitally-Enhanced Power Solution offer a Programmable, Hybrid Power Controller combining a mid-voltage analog power stage (including analog control loop, MOSFET drivers, and sensing) with a microcontroller, enabling a user-configurable power converter. So, as an example, the PIC16F785 can be used in a Level 3 application due to the on-chip analog peripherals. The device has two analog PWM modules that can control power stages. Two error amplifiers and two high-speed comparators

1. LEVEL 4 - FULL DC/DC CONVERSION: Full digital control replaces the standard analog design and also provides the power management functions of Levels 1-3 integration. 1 The power supply regulation unction is directly controlled by the digital circuits on the processor and the software running on the rocessor. The full digital solution allows the designer to employ techniques t hat are not possible with the inalog solution, including proprietary digital compensation algorithms and non-linear control techniques. The full digital solution enables a customized response to power input change or load change events, which -an lower system cost and increase system efficiency. Microchip's 16-bit ds solution. Feedback from the power supply is obtained using high-speed -ontrolled using specialized high-speed PWM peripherals. The PWM module dower supply topologies and the CPU core allows digital compensation algori PIC DSCs enable the Level 4 ADCs. The power supply is can directly drive all popular thms to be executed quickly. isPIC DSCs can be used for various power conversion and power control applications, and they offer higher Jower densitv. lower svstem cost improved reliahility. and lower manufacturing and maintenance cost.

e PFC with Advanced Digital Control: Power Factor Correction (PFC) is essential in higher wattage power supplies to reduce harmonic contents, system losses and radiated emissions. In this example, the dsPIC DSC simplifies implementing Boost-PFC algorithms with the Average Current Mode Control technique. The current signal is calculated digitally by computing the product of the rectified input voltage, the output of voltage error compensator and output of voltage feed-forward compensator. Implementing the digital PFC function uses little of the DSC resources, leaving plenty of additional capability to perform the rest of the primary side control. e AC-DC Conversion with Completed Digital Control: To design an efficient, reliable, cost effective AC-DC power supply with advanced features, the family of dsPIC DSCs can help optimize design cycles effectively. The high-speed PWM module with multiple advanced operating modes helps implement various advanced conversion stages such as PFC, phase shift, zero voltage, transition converter with full- bridge conversion and synchronous rectification and multi-phase buck converters. The microcontroller’s high-speed ADC can be triggered on an edge of the PWM to sample the various voltages and currents for high speed processing. The high-performance CPU helps in implementing advanced PID digital control loops and compensators in software.

This last approach would be the better for NEWTON design, but as a previous stage, it is necessary t develop a solution with a more modest 8 bit microprocessor, to test the validly of the system as ilt is showr in next point.

The system basically must obtain two symmetrical outputs of +-40V and a very high current, to excite the solenoid that generates the heavy magnetic field, used to drive the detection head.

D3.3 - Preliminary design report for the power distribution block FIGURE 40 shows the PCB designed for the current source of NEWTON instrument prototype 3. This board is under manufacturing, therefore it has not been possible to validate the performance of this part of the design. This taks will be developed during the next stage of the project.

FIGURE 40. Picture of the board designed for the source of the prototype 3.

FIGURE 41. Prototype manufactured for the validation of the Flyback converter. FIGURE 41 shows the prototype manufactured for the validation of the Flyback converter. The performance of this prototype has been evaluated in the laboratory for an output voltage of 12V. The results obtained from the validation of this PCB are shown in TABLE 6 while FIGURE 42 represents the main parameters obtained from the validation of the Flyback converter.

D3.3 - Preliminary design report for the power distribution block The results obtained from the measurements of the Flyback converter asses the performance observed during the design period. Though this kind of DC/DC converters are suitable for medium power applications, the fact of having only one switch doesn’t provide good efficiency at very low loads, due to the intrinsic losses of this architecture.

FIGURE 43. Prototype manufactured for the validation of the Half-Bridge converter. FIGURE 43 shows the prototype manufactured for the validation of the Half-Bridge converter. TABLE 7 anc FIGURE 44 represent the results obtained from the measurement of the converter in the laboratory.

D3.3 - Preliminary design report for the power distribution block There are some possible improvements to be consider for a future stage, such as selecting a more suitabl. transformer which allows the use of a better duty cycle, closer to 40-45% in order to stress both switche: and rectifier diodes in a more symmetrical way, or study each individual component requirements trying not to oversize each element in excess. Some derating must be considered when we are designing thi converter, even more knowing the critical application in which it’s going to be placed, but a trade-off mus be carefully carried out during the final design and selection of components process.

FIGURE 45. Demo Board for the proof-of-concept of the buck converter. FIGURE 45 shows a picture of the demo board used for the validation of the buck converter topology. 4.1.3. Buck DC/DC converter

FIGURE 46. Measurement setup for the validation of the Buck converter.

FIGURE 47. Buck converter main PWM signal. D3.3 - Preliminary design report for the power distribution block

FIGURE 48. Measurement results obtained from the validation of Buck converter.

TABLE 4. Comparative analysis between CCM and DCM Flyback converters. Flyback converters have two basic energy-transfer modes of operation: Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). In DCM, the Flyback period will continue till the output winding current drops to zero, so that all the stored energy in the Flyback transformer is transferred to the load. On the contrary, in the CCM, there is some residual energy stored in the transformer at the end of the ON and OFF periods. In general, DCM is recommended for high voltage and low current output applications while CCM is preferred for low voltage and high current applications. A comparison between CCM and DCM is presented in TABLE 4.

TABLE 5. Interfaces of the DC/DC converter. 3.2. AC CURRENT POWER SOURCE (Prototype 3) At this stage of the project, the preliminary interfaces defined in TABLE 5 have been defined. As already indicated in section 2, the PDU of the NEWTON instrument is composed of the DC/DC conversor and the AC current source. The AC current source drives the primary winding of the sensor unit. In the case of prototype 1 and 2, it is not required to implement an individual AC current source, therefore the generation of the AC current will be implemented as part of the Electronic Control Unit by means of using a frequency generator and an external amplifier placed in the Sensor Unit. In the case of prototype 3, the demand of the AC current needs and ad hoc development, which is based on a Full-Bridge switching as described in this section. In this preliminary stage, the design of this source has been developed. D3.3 - Preliminary design report for the power distribution block

TABLE 6. Results obtained from the validation of the Flyback converter.

TABLE 7. Results obtained from the validation of the Half-Bridge converter.

TABLE 8. Results obtained from the validation of the Buck converter.

descriptionView Paper arrow_downwardDownload

Optimal control strategy of photovoltaic system based autonomous micro grid for power quality improvement

by Syed Syed

2024

Due to the increasing number of distributed generation units being used in remote regions, the need for reliable and flexible operation of these systems has led to the development of microgrid technology. When a microgrid operates in an... more

descriptionView Paper arrow_downwardDownload

Performance improvement in photovoltaic-grid system using genetic algorithm

by sankar rangasamy

2024, Indonesian Journal of Electrical Engineering and Computer Science

In recent, photov oltaic (PV) power generation has increased in importance. The growing significance of PV power production has generated the demand for enhancing energy efficiency via continuous operation at the maximum power point... more

descriptionView Paper arrow_downwardDownload

A Modified Step-Up Converter with Small Signal Analysis-Based Controller for Renewable Resource Applications

by Jens Bo Holm-Nielsen

2024, Applied sciences

Solar energy is one of the most important renewable sources due to its advantages such as simple structure, convenient installation, diverse applications, and low maintenance costs. Low power generation is the main concern with solar... more

descriptionView Paper arrow_downwardDownload

A Hybrid ANFIS-ABC Based MPPT Controller for PV System With Anti-Islanding Grid Protection: Experimental Realization

by Jens Bo Holm-Nielsen

2024, IEEE Access

This paper introduces a novel control system with maximum power point tracker (MPPT) for the photovoltaic system with grid integration. Hybrid adaptive neuro-fuzzy inference system (ANFIS) and artificial bee colony (ABC) algorithm... more

descriptionView Paper arrow_downwardDownload

Grey wolf optimizer for the design optimization of a DC-DC boost converter

by beei iaes

2024, Bulletin of Electrical Engineering and Informatics

Design optimization of a DC-DC boost converters for minimizing overall operational losses is the problem under study. The optimum design contains selecting the best value of circuit inductance, capacitance, and switching frequency for the... more

Figure 1. Electrical circuit of a DC-DC boost converter [30] Where, i in (1) represents the current flowing in the inductor and output voltage is given by Vc. The switch state is represented by the parameter u in (2) and (3) where the on state (u=1) (under this condition the Q; is on and D, is inactive) and OFF state (u=0) (under this condition Q; is off and Dj is active) determine the operation of the switching device. The initial value of u functions as the control signal to regulate how the converter operates. The circuit parameters representing the inductor, capacitor, input voltage, and load resistance are denoted by L, C, Vi, and R respectively. The ripple in the current and voltage along with the dimension of the inductor for the CCM operation and the bandwidth limitation impose the constraints to the optimization problem. They are calculated as (4)-(8):

Grey wolf optimizer for the design optimization of a DC-DC boost converter (Barnam Jyoti Saharia) Where the switching frequency is given by f,=1/T;, Ts being the switching period and fs the switching frequency, and a is a percentage of fs. The total power loss calculations depend on the losses incurred during the converter's operation as well as any losses brought on by parasitic resistance loss and parasitic capacitance induced switching losses. In addition, the device operation loss due to the on-off state transitions at the conclusion of each cycle also effect the power calculation and hence the efficiency of the converter. The equation for the total power loss for one complete cycle of operation of the boost converter denoted by Pgoost is given as (9)-(15):

Figure 2. Convergence curve of the GWO, MFO, PSO, SA, and FFA Table 3 compares the optimal outcomes achieved by various optimization methods. It can be observed that the best optimized result is attained with the GWO with lowest power loss and highest efficiency in the converter design. The more significant finding is that the optimized design uses the lowest value of filter inductor, among the algorithms which is often the limiting criterion when considering the converter economics [35]. The obtained results also indicate an improvement in the design when compared with the work of [33] from three aspects namely, the optimized power loss in the converter, the efficiency, and filter inductor. This indicates the efficacy of GWO for finding an improved optimized result for minimizing the power loss by 16%, which is a significant improvement.

Grey wolf optimizer for the design optimization of a DC-DC boost converter (Barnam Jyoti Saharia) The range of the design parameters and the constraints of the optimization problem considered hav been taken from [33] for all values as listed in Table 1. Utilizing the GWO optimization technique, t! ‘otal operational losses are at a minimum. The converter design problem is formulated in the octave [3 simulation software for the constraint based power minimization of the DC-DC boost converter. Because t iterations. The population size or number of search agents, moths, particles, and fireflies are all considered be equal to 30 for GWO, MFO, PSO, and FFA to have consistency in evaluation of the performance of t! average value, worst value, standard deviation, computational time, no of hits, and the p-value. The resu are presented in Table 2. optimal combination of design parameters is determined for the DC-DC boost converter in a manner tha optimization techniques are stochastic, each of the algorithms modelled are run for a minimum of 10( algorithms. Comparison is made based on the statistical performance parameters that include the best value ne 4 ne t ne t

From Table 2, the best value and optimized solution to the DC-DC converter is 1.4085 And therefore, the overall efficiency of the converter designed is 98.12%. It is also observed W (Pgoost). that all the optimization algorithms reach this result which indicates that the global optimum has been attained. The results obtained are best for the GWO considering the standard deviation as well as requiring t the computational time for 100 iterations for each run of the algorithms. While the average va he minimum ues are also seen to be equal for the GWO, MFO, and PSO, however in terms of standard deviation and worst values within the 100 runs considered, GWO clearly outperforms MFO and PSO. Figure 2 shows the convergence characteristics of all the algorithms for their best runs. It is clearly evident that the GWO takes t he lowest no of iterations to reach the minima, thus establishing its superiority when compared with the other algorithms.

4.1. Solution quality The statistical assessment of the GWO is carried out using the Wilcoxon rank sum test. The test is used to find the statistically significant results obtained at the end of the optimization process which translates in our situation, to the optimized objective value at the end of the iterative process. The test detects the substantial variation in the results of two algorithms when applied pairwise. For an algorithm to show sufficient satisfactory results, evidence from the results should conclusively indicate that the null hypothesis doesn’t hold true. The P-value, which is less than 0.05, provides strong evidence to refute the null hypothesis.

descriptionView Paper arrow_downwardDownload

A novel voltage lifting technique of switched-inductor cell based modified LUO converter topology for water pumping system

by International Journal of Applied Power Engineering (IJAPE)

2023, International Journal of Applied Power Engineering (IJAPE)

The persistent exhaustion of traditional energy sources with their impacts on the environment has been initiating a significant interest in a selection of renewable-energy sources (RES) based water-pumping system. Among several renewable... more

descriptionView Paper arrow_downwardDownload

Model Predictive Current Control of Grid Connected PV Systems

by Keerthi Deepika

2023, Indonesian Journal of Electrical Engineering and Computer Science

This paper deals with the design and simulation of an efficient solar photovoltaic system with a maximum power point tracking system (MPPT). Maximum power point (MPP) is obtained by using Perturb and Observe (P&O) algorithm. The output... more

descriptionView Paper arrow_downwardDownload

A new approach of variable step-size maximum power point tracking algorithm used in photovoltaic systems

by Ramadhan Masmoudi

2023, Indonesian Journal of Electrical Engineering and Computer Science

To exploit the maximum power generated by the photovoltaic (PV) panel, it is necessary to use the maximum power point tracking (MPPT) controller. The main concern of MPPT algorithms is how to reach the maximum power point (MPP) quickly... more

descriptionView Paper arrow_downwardDownload

Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system

by Suman Patra

2023, Indonesian Journal of Electrical Engineering and Computer Science

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting... more

descriptionView Paper arrow_downwardDownload

Grid integrated photovoltaic system with fuzzy based maximum power point tracking control along with harmonic elimination

by Nouman Ashraf

2023, Transactions on Emerging Telecommunications Technologies

Efficient extraction and conversion of solar power is an important research area in the field of renewable energy integration. Although, literature is enriched with different power extraction, conversion, and harmonics elimination... more

descriptionView Paper arrow_downwardDownload

Four switch Three-Level Soft Switched Converter

by Chandrabhan Sharma

2023, International Journal for Scientific Research and Development

A Three-level, constant-frequency, isolated converter which employs a coupled in conductor to achieve zero-voltage switching. Three level DC converter has been introduced hare. This converter consists of four switches, which give the two... more

descriptionView Paper arrow_downwardDownload

Adaptive neuro fuzzy inference system based method for faults detection in the photovoltaic system

by Indonesian Journal of Electrical Engineering and Computer Science

2023, The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

As the case with all electrical and electronic systems, a photovoltaic (PV) system can be exposed to several failures causing it to malfunction; several studies have found that the reliability of the PV systems is highly dependent on the... more

A simulation of a PV system composed of 16 PV modules (4 strings) connected to a load R is built on the MATLAB/Simulink environment. The characteristic of the PV solar which has 36 cells, where the power maximum generated is approximately 52 W at a maximum voltage of 21.9 Volt, in standard conditions (25 °C and 1,000 W/m7). Figure 3 shows the block diagram of PV system studied. The component power is constructed using the Simulink System Library and consists of a solar panel, a buck converter with control that includes an MPPT algorithm, a battery, and a load [17]. The static current-voltage (I-V) and power-voltage (P-V) to model the PN junction of the cell. The series resistance (Rs) and the shunt resistance (Rsh) represent the non- ideal state of the cell. The series resistance represents the resistivity of the material in which is made the cell, the contact resistance between metal and semiconductor and the resistance interconnection between cells. Parallel resistance represents all paths that the leakage current traverses, either parallel to the cell or at the edge of itself. It results usually from crystal damage or impurities in or near the junction [14], [15]. The mathematical equations of a single diode electrical circuit as shown in the Figure 2, it is 4 equations with two unknowns (I and V) and parameters [16]. And these parameters we summarize them in the Table 1. Adaptive neuro fuzzy inference system based method for faults detection ... (Younes Lahiouel)

Figure 3. The PV system studied characteristics of the solar field can be used to describe it. Figure 4 depicts the I-V and P-V characteristics of a PV field under typical operating conditions.

Figure 4. P-V and I-V characteristics PV systems can be subject to several faults during their operation, and two main types can be istinguished [18], [19]:

Figure 5. The different signals of the PV system (a) I-V characteristic of PV faults, (b) P-V characteristic of PV faults, (c) buck converter output with charging faults, and (d) battery voltage with charging fault

Figure 6. General structure of the proposed technique Each parameter (Pmax, Voc, Isc, Vc, Vb) of normal and failed systems is calculated, after that comparator system run for obtain the values (Cpmax,Cvoc, Cisc; Cve, Cyp) are shown in Table 4. The result depends first on Cpmax in other words the power maximum generated by failed system and Ci others values. Then, the neuro-fuzzy controller is started [25]. The diagram of the proposed neuro-fuzzy algorithm of fault detection is illustrated in Figure 7.

Figure 7. Flowchart of the proposed neuro-fuzzy algorithm for fault detection

The ANFIS method is a technique for optimizing fuzzy type inference systems Takagi Sugeno proposed by Jang [26]. This uses to adjust the system settings; the least squares method combined with the gradient descent method. This method is based on the use of multilayer networks. Figure 8 shows the structure of the evaluation decision-making stage ANFIS. The architecture consists of five main layers [27], each layer consisting of a number. The number of nodes is dis-tributed as follows: 5-30-6-6-1.

Figure 8. Architecture of ANFIS Layer 1: each node i in this layer has a membership function in the Gaussian form and is a square le as shown in (6).

Figure 9. System ANFIS 5 inputs, one output ANFIS uses hybrid learning algorithm is shown in Figure 9. The role of learning is the adjustment of fuzzy inference system parameters. These are therefore the premises parameters and consequent parameters. In other words, the learning process is used to optimize the premise parameters (membership function parameters) and the consequence parameters (the output coefficients) [28], [29]. The learning procedure of the ANFIS system can be done in two phases as indicated: the first aims to adjust the premise parameters while keeping the consequent parameters fixed using the error gradient backpropagation method. With this method we calculate the gradient of the error to adjust each parameter (weight), linked to the nodes by calculating the squared difference E between the predicted output and the observed output [26]:

Figure 10. Illustration of the ANFIS for PV fault detection state (a) training data, (b) training error with 100 epochs, and (c) red stars indicate FIS output, fully tracked the blue circles that represent the training data

Figure 12. The fuzzy thinking mechanism diagram of ANFIS

descriptionView Paper arrow_downwardDownload

Grey wolf optimizer for the design optimization of a DC-DC boost converter

by Barnam J Saharia

2023, Bulletin of Electrical Engineering and Informatics

Design optimization of a DC-DC boost converters for minimizing overall operational losses is the problem under study. The optimum design contains selecting the best value of circuit inductance, capacitance, and switching frequency for the... more

descriptionView Paper arrow_downwardDownload

Design of Fuzzy-ACO Based Controller for Cuk Converter in Electric Vehicles

by Muhammed A Ibrahim

2023, Journal Européen des Systèmes Automatisés

The voltage output of an energy storage device utilized in electric vehicles (EVs) is modulated in response to the load, and the elevated voltage of the DC link poses challenges for vehicle engineers when integrating energy storage... more

descriptionView Paper arrow_downwardDownload

Design of Fuzzy-ACO Based Controller for Cuk Converter in Electric Vehicles

by Salam I Khather

2023, Journal européen des systèmes automatisés

The voltage output of an energy storage device utilized in electric vehicles (EVs) is modulated in response to the load, and the elevated voltage of the DC link poses challenges for vehicle engineers when integrating energy storage... more

descriptionView Paper arrow_downwardDownload

Optimal control strategy of photovoltaic system based autonomous micro grid for power quality improvement

by Indonesian Journal of Electrical Engineering and Computer Science and

2023, The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

Due to the increasing number of distributed generation units being used in remote regions, the need for reliable and flexible operation of these systems has led to the development of microgrid technology. When a microgrid operates in an... more

descriptionView Paper arrow_downwardDownload

Comparision of Voltage Stress Across the MOSFET Switch of a Flyback Converter with Various Snubbers

by R S Geetha

2023, International Journal of Innovative Science and Research Technology

A Flyback converter is a simple switch-mode power supply that can be used to generate a DC output from either an AC or DC input. The converter switch is the most critical part of any converter. The voltage stress across the switch is a... more

descriptionView Paper arrow_downwardDownload

Analysis of SEPIC for PV-Applications using PI Controller and Current Mode Control

by Revanth Kumar s

2023

1821 Abstract—A SEPIC (single-Ended Primary Inductor Converter) DC-DC converter is capable of operating in either step-up or step-down mode and widely used in battery-operated equipment. This paper presents two various closed loop... more

descriptionView Paper arrow_downwardDownload

Fault analysis in grid-connected solar photovoltaic systems based on multi-objective grey wolf optimisation

by Indonesian Journal of Electrical Engineering and Computer Science

2023, The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

The renewable energy resources depend on environmental concerns. Photovoltaic (PV) systems are an interesting form of renewable energy resource. The two main problems associated with PV systems are nonuniformity of irradiation and... more

descriptionView Paper arrow_downwardDownload

Assessment of a single-phase single-stage grid-connected photovoltaic system

by Indonesian Journal of Electrical Engineering and Computer Science

2023, The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

A grid-connected photovoltaic (GCPV) system plays an important role in the development of green technology. However, generated photovoltaic (PV) power that is injected into the grid causes instability in the grid system. Previous studies... more

descriptionView Paper arrow_downwardDownload

Periodic Perturbation Method for Controlling Chaos for a Positive Output DC-DC Luo Converter

by Tole Sutikno

2023, International Journal of Power Electronics and Drive Systems (IJPEDS)

A simple, non-feedback method of controlling chaos is implemented for a DC-DC converter. The weak periodic perturbation (WPP) is the control technique applied to stabilize an unstable orbit in a current-mode controlled Positive Output Luo... more

descriptionView Paper arrow_downwardDownload

RBFNN Machine Learning BASED BLDC Motor Driven PVFed Electric Vehicle

by Dr.V BALAJI

2023, nternational Journal of Scientific Research and Engineering Development

This paper presents a Radial Basis Function Neural Network (RBFNN) based MPPT(Maximum Power Point Tracking) algorithm. This algorithm is implemented in Sensor less Permanent magnet Brushless DC Motor for driving an electric vehicle. In... more

descriptionView Paper arrow_downwardDownload

MAXIMUM POWER TRACKING BY ANN FOR LUO CONVERTER IN GRID-CONNECTED PHOTOVOLTAIC SYSTEMS

by Dr.V BALAJI

2023

In this study, a maximum power point tracking controller based on ANN has been constructed. The ANN tracker calculates the voltages and currents necessary for a solar PV array to provide its maximum power under conditions of fluctuating... more

descriptionView Paper arrow_downwardDownload

Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system

by Indonesian Journal of Electrical Engineering and Computer Science

2023, The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting... more

descriptionView Paper arrow_downwardDownload

Analysis of a Bidirectional DC-DC Converter with High Voltage Gain

by Mahdi Salimi

2023, Bulletin of Electrical Engineering and Informatics

A novel bidirectional DC-DC converter with high conversion ratio is proposed in this paper. The proposed converter uses the three windings coupled-inductor to achieved high voltage conversion ratio. The primary side consist of a winding... more

descriptionView Paper arrow_downwardDownload

Novel three‐level T‐type isolated bidirectional DC–DC converter

by Onur Demirel

2023, IET Power Electronics

This study presents a novel three-level T-type isolated bidirectional DC-DC converter (3LTT-IBDC) for bidirectional DC power transfer. Owing to of the T-type structure of the proposed converter it has less number of switches and thus,... more

descriptionView Paper arrow_downwardDownload

Investigation of voltage regulation in grid–connected PV system

by Soumen Gorai

2023, Indonesian Journal of Electrical Engineering and Computer Science

In the present scenario the power demand on the load side is increasing day by day, so to balance the power demand and power supply various renewable energy comes to picture as the additional source of electricity generation. The power... more

descriptionView Paper arrow_downwardDownload

Preliminary design report for the power distribution block Project

by Pedro Cobos

2023

This document reports the preliminary design of the Power Distribution Unit (PDU) of the NEWTON instrument. The PDU supplies energy to the Control Unit (CU) and the Sensor Unit (SU) and it is composed by two different blocks, the power... more

descriptionView Paper arrow_downwardDownload

Preliminary design report for the power distribution block Project

by Marina Pérez

2023

This document reports the preliminary design of the Power Distribution Unit (PDU) of the NEWTON instrument. The PDU supplies energy to the Control Unit (CU) and the Sensor Unit (SU) and it is composed by two different blocks, the power... more

descriptionView Paper arrow_downwardDownload

Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system

by Sivkumar Mishra

2023, Indonesian Journal of Electrical Engineering and Computer Science

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting... more

descriptionView Paper arrow_downwardDownload

Modelling and Simulation of MPPT Based Solar Photovoltaic System for Voltage Lift LUO Converter

by FOREX Publication

2023, IJEER

Several maximum PowerPoint tracking techniques have been proposed to achieve optimal matching between solar photovoltaic arrays to load for extracting maximum available power from photovoltaic source. These techniques differ in terms of... more

descriptionView Paper arrow_downwardDownload

Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system

by Sivkumar Mishra

2023, Indonesian Journal of Electrical Engineering and Computer Science

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting... more

descriptionView Paper arrow_downwardDownload

Perturb and observe maximum power point tracking approach for microgrid linked photovoltaic system

by Kshirod Kumar Rout

2023, Indonesian Journal of Electrical Engineering and Computer Science

This paper develops a maximum power point tracking (MPPT) approach for a microgrid-linked solar photovoltaic (PV) system based on the concept of a perturb and observe (P&O) approach. It is an iterative algorithm that requires a starting... more

descriptionView Paper arrow_downwardDownload

Artificial intelligent controller-based energy management system for grid integration of PV and energy storage devices

by durga prasad ananthu

2023, Indonesian Journal of Electrical Engineering and Computer Science

In the modern world, photovoltaic (PV) energy generation is becoming more prevalent and cost-effective. To address climate change, many countries have prioritised photovoltaics and made significant investments in energy generation.... more

Figure 1. ANFIS maximum power point tracking of 100 kW PV simulation model Table 2. Battery parameters

Figure 2. PV system’s ANFIS (a) MPPT, (b) training data, and (c) inference rules 2.1. ANFIS based grid integration of PV and battery management system As depicted in Figure 1, a three-phase distribution line of 400 V and 50 Hz was employed in the grid integration of a 100kW photovoltaic simulation model. The 100 kW MPPT controller can be connected to the ANHIS algorithm via a 3-phase inverter. A voltage source converter (VSC) was utilised to regulate the three- phase converter that was linked to the grid. This VSC controller consists of a phase lock loop, a voltage regulator, and a current regulator. With the help of this controller, the inverter linked to the network can match the frequency and voltage of the network, facilitating photovoltaic model that are synced with the power grid. The VSC monitor collects data on three-phase voltage and grid current on a regular basis and feeds it into a phase interlock loop that locks the frequency. A voltage regulator is required to maintain the inverter's voltage stable when it is linked to the three-phase network and synchronised with the distribution network. The current controller regulates the natural and reactive power flows in the 3-phase inverter. The controller regulates currents in the three-phase inverter's direct axis Id and quadrant axis Iq. Finally, phase width modulation is used to produce the switching pulses of the grid-connected 3-ph inverter. In this article, a bidirectional DC-DC converter (BDC) is used to transfer electricity from solar (PV) to battery and from battery to load.

Figure 3. ANFIS-BEMS’s (a) training data and (b) test data Figure 4 illustrates the ANFIS validation data and ANFIS rules for BEMS. For the ANFIS BMS, a test error of 0.071552 is shown in Figure 4(a). The ANFIS network produced an inevitably formed membership function of input and output, which was then cross-pending, rules-based battery management, as illustrated in Figure 4(b). BMS ANFIS rules are; i) If (inputl=inlmf1), so (output=outlmf1) (1), ii) If (input 1=in1 mf2), so (output=out1mf2) (1), and iii) If (input1=in1 mf3), so (output=out!mf3) (1).

Figure 4. ANFIS (a) validation data and (b) rules for BEMS

Figure 5. Photovoltaic energy at higher than load (battery under SoC) and lower than load (battery under SoD) demand, the battery begins to degrade in 0 to 1 second (assuming a 75 percent starting battery capacity). The battery starts charging when the PV generates 50 kW for 1 to 2 seconds and 75 kW for 2 to 3 seconds, as shown in Figure 6. Figure 7 shows the load voltage and current waveforms, as well as the distribution grid. The standard consumer load's grid current and voltage are 15 Amps and 380 volts. Furthermore, as seen Figure 8, the coordinated utility grid power quality was investigated utilising total harmonic distortion (THD) for the voltage and current profiles (given as 3.45% and 1.73% respectively).

Figure 6. SoC of battery at variable PV power and constant load

Figure 7. Distribution grid V and I & V, and I, waveforms

Figure 9. Architecture of (a) MLP network and (b) Proposed MFNN for Photovoltaic MPPT system An artificial neural network (ANN) is a type of artificial intelligence that consists of a collection of interlinked basic units called neurons. Essentially, each neuron represents a mapping, particularly one with several inputs and only one output. The neuron's output is a function of the neuron's inputs as a whole. Neurons utilise activation functions in the output of their neuronal outputs. The sign for a single neuron displays the number of arrows emanating from the neuron's sole output, which can be applied to othe neurons. Perceptron is a term for a network design that simply includes the input and output layers. There is no intermediary layer between the input and output layers in a perceptron. Input and output have a linear relationship. The weighted sums of signals delivered from the input to the output indicate the direct interaction between the two levels. Multi-layer perceptrons (MLP) are neural networks that have many layers between input and output. Feedforward neural network (FFNN) are another name for MLP networks in neural network modelling (NNM). FFNN's network has a "hidden layer," which serves as an additional layer of the network. The hidden layer receives the weighted signal from the input layer. The buried layer neurons receive the signals from the inputs. The underlying layer has an activation function that processes signals that enter the buried neurons. Because hidden layer activation functions are nonlinear, they can be employed as transfer functions. The output layer receives the weighted total of the hidden layer's neuron outputs. On its path to the output layer, the activation function across this layer processes the incoming signal. Figure 9 depicts the architecture of MLP neural network and proposed MFNN-MPPT system.

Figure 10. Proposed MFNN (a) Best validation performance and (b) Solar mppt’s gradient, mean and validation Figure 10 illustrates the proposed MFNN validation performance and solar mppt’s gradient, mean and validation results. The MPPT algorithm was generated using more than 1000 epochs of training data. As be shown in Figure 10(a), the proposed MNFF has the best driving performance of 4.5066e-13 and Figure 10(b) shows the suggested MNFF's gradient analysis, Mu, and validation check. In the end, Figure 11 shows the predicted network regression value.

Figure 11. Proposed MPPT algorithm training, validation analysis, test and overall performance

Figure 12. 100 kW PV system’s (a) MFNN-MPPT Simulink model and (b) PV output power Vs. MPPT power at various irradiances The constructed current regulator algorithm has been implemented in the proposed PV-connected inverter for synchronising into the electrical grid. Figure 16 shows the simulation results of the proposed system. According to Figure 16(a), the simulation results are analysed under varying solar power and at constant load power (Battery under the SoC and SoD shown). Voltage and current waveforms of the solar system and the electricity grid are shown in Figure 16(b). Figure 17 depicts the 3-phase THD of PCC voltage and current waveforms and the values are given in Table 3.

Figure 13. MFNN PV power output at (a) MPPT and (b) proposed algorithm’s converter output power

Figure 14. Grid connected solar (PV) and BMS simulation model

Figure 16. Simulation results of (a) battery SoC, SoD at variable solar power and constant load and (b) distributed grid voltage and current waveform

Figure 17. THD level at (a) load voltage and (b) load current

Table 3. Total harmonic distortion values Indonesian J Elec Eng & Comp Sci, Vol. 26, No. 2, May 2022: 617-628

descriptionView Paper arrow_downwardDownload

Modelling and Analysis of Non-ideal Two stage Lift Luo Converter with Positive Output

by FOREX Publication and

2022, IJEER

High power applications such as motor drive control requires a higher voltage level of the DC-DC power converter fed from low-level DC input sources. For increasing the output voltage, a gain of the converter is increased using the pump... more

Figure 3: NI- CTSLLC torr equivalent circuit Operation of NI-CTSLLC during switch-OFF condition is shown in fig. 3. Voltage across the capacitor C; reverse biases the diode D;. Voltage on the input side, inductor V1; and voltage across the capacitor C; forward biases the diode D2 and charges the first stage lift circuit capacitor C2 to V1. First stage lift circuit voltage V; and voltage across inductor L2 forward biases the diode D4 and charges the capacitor C4 Voltage across the capacitor C3 reverse biases the diode D3. In OFF- state Diode Ds is reverse biased by the voltage across the inductor L2, which is greater than the diode Ds anode voltage. During ton the voltage across the capacitor C; is charged to t supply voltage Vin and the voltage across the capacitor C, equal to 10.02 V at the steady state condition as shown in t fig 4. During tor state, the capacitor C2 is charged to the voltage equal to Vin + Viit+Vci. As shown in fig 4 the voltage across t! capacitor C2 at steady state is equal to 33.87V. Capacitor C3 charged to the first stage output voltage equal to the voltage across the capacitor C2. From the fig 4, at steady state t voltage across the capacitor C3 is equal to 32.43 V during t During torr, the energy stored in the inductor L2 and C3, charges the capacitor C4 to (Vi + Vri2+ Vc3). So the voltage across t he iS he he iS ne ons ne capacitor C4 is equal to 105.54V at steady state condition, which is also equal to the output voltage Vo. Ripple in the output voltage of CTSSLLC is shown in the fig 5. From the fig 5, it is inferred that the maximum peak to peak ripple voltage is equal to 10 mV and the ripple factor is equal to .0009% which is very

much less than the standard value of 1%, so the output voltage is a stiffed DC voltage. Figure 4: Voltage waveforms across the capacitors C1, C2, C3 and

Figure 6: Output voltage of CTSLLC with variation in duty ratio

Figure 7: Output voltage of CTSLLC with variation in the load resistance

Turn- OFF equivalent state equations for the second stage lift circuit are Turn-OFF equivalent state equations for the first stage lift circuit are

Output voltage equation matrix form at Turn - ON condition

Figure. 8 Step response comparisons of I-CTSLLC and NI-CTSLLC Figure. 9 Frequency response comparisons of I-CTSLLC and NI- CTSLLC

The gain and phase margin of the NI-CTSLLC are 2.05 dB at phase crossover frequency equals to 652 rad/s and 24° at gain cross over frequency equals to 465 rad/s. For I- CTSLLC gain margin GM is -5.9 dB at 790 rad/s and phase margin PM is 0.549° at 674 rad/s. Since, the two margins are positive in the NI-CTSLLC the system is stable.

Figure.10 Output voltage comparisons of Luo and CTSLLC Figure 10 shows the output voltage comparison of super lift Luo and CTSSLLC for different ratio with the input voltage fixed to 12 V. From the comparison it is inferred that for 0.5 duty ratio the super-lift Luo converter output voltage is equal to 36 V. And CTSSLLC output voltage is equal to 108 V.

Table 2: Output voltage comparisons of the NI- CTSLLC and I- CTSLLC at steady state

descriptionView Paper arrow_downwardDownload

Investigation of Power Quality Improvement in Super Lift Luo Converter

by Naga Priya

2022, International Journal of Power Electronics and Drive Systems (IJPEDS)

This paper presents the improved single phase AC-DC super lift Luo converter for enhancing quality of power by mitigating the issues. The proposed converter is used for output voltage control, power factor improvement and reduced source... more

descriptionView Paper arrow_downwardDownload

ZVS Boost Converter with A Flyback Snubber Circuit

by Suraj Damodaran

2022

Power semiconductors are the heart of power electronics equipment. Snubbers are circuits which are placed across semiconductor devices for protection and to improve performance.In this paper, several passive and active snubbers associated... more

descriptionView Paper arrow_downwardDownload

Grey wolf optimization-recurrent neural network based maximum power point tracking for photovoltaic application

by Indonesian Journal of Electrical Engineering and Computer Science

2022, Indonesian Journal of Electrical Engineering and Computer Science

To increase the photovoltaic (PV) power-generation conversion, maximum power point tracking (MPPT) is the primary concern. This works explains about the grey wolf optimization (GWO-RNN)-based hybrid MPPT method to get quick and maximum... more

descriptionView Paper arrow_downwardDownload

Articles for Common Nouns

by Geetanjali S. Masamaddi

2022

In today's' vitality power industries Boost converters highly required to convert the normal power into improvised power. Normally vitality converters struggled with voltage pressure over the power electronics switching nature and... more

descriptionView Paper arrow_downwardDownload

Implementation of Snubber Circuits in a PV-Based Off-Grid Electric Vehicle Charging Station—Comparative Case Studies

by Krishnamachar Prasad

2022, Energies

With the penetration of electric vehicles (EVs), there have been paradigm shifts in the transportation sector. EVs are ideally considered to be clean and eco-friendly, but they can overload the existing grid infrastructure and... more

descriptionView Paper arrow_downwardDownload