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This paper proposes an integration of renewable energy sources based on a modular multi-input bidirectional DC/DC buck-boost converter. The proposed four-port converter is realized with a reduced component count and simplified control strategy, which makes the converter more reliable and cost-effective. Also, this converter exhibits bidirectional power flow functionality, making it suitable for charging the battery during regenerative braking of an electric vehicle or hybrid electric vehicle. Photovoltaic (PV) panel, battery, and ultra-capacitor are the three different energy sources for the suggested topology. Dynamic modeling is derived, and the steady-state performance of the converter is well analyzed in the MATLAB/Simulink platform. Experimental results obtained from a 100 W prototype model validate the performance of the proposed four-port bidirectional buck/boost (FPB3C) DC/DC converter.

The demand for renewable energy-based Electric Vehicle (EV) charging infrastructure is increasing in recent years. Solar PV based EV charging method is preferred as it has simple energy harvesting technique. The PV system is an uncertain power source, where the power generation is varied with respect to the availability of sunlight. So, that the charging station requires a backup power supply for the uninterrupted charging. For the integrated power sources, the charging station requires a simple and efficient conversion unit for the DC/AC/DC conversion. In this work, a modified Z-source inverter (MZSI) is developed for the multiport EV charger using PV and grid. The proposed MZSI is connected between the input and output sides to boost the voltage as per the demand at the battery side. In order to connect many battery units with the charger, the capacitors used in the MZSI are split as per the required number of charging ports. This developed converter topology operates the systems in four different modes like PV-Grid, PV-battery, grid-battery, and battery-grid. The performance of this proposed work has been validated in MATLAB/Simulink® and in the experimental setup. The experimental setup has been developed with two charging ports for obtaining 250W at each charger end which cumulatively produces 500W output across both chargers with an efficiency of 90.18%. [ABSTRACT FROM AUTHOR]

The Electric Vehicle (EV) landscape has witnessed unprecedented growth in recent years. The integration of EVs into the grid has increased the demand for power while maintaining the grid's balance and efficiency. Demand Side Management (DSM) plays a pivotal role in this system, ensuring that the grid can accommodate the additional load demand without compromising stability or necessitating costly infrastructure upgrades. In this work, a DSM algorithm has been developed with appropriate objective functions and necessary constraints, including the EV load, distributed generation from Solar Photo Voltaic (PV), and Battery Energy Storage Systems. The objective functions are constructed using various optimization strategies, such as the Bat Optimization Algorithm (BOA), African Vulture Optimization (AVOA), Cuckoo Search Algorithm, Chaotic Harris Hawk Optimization (CHHO), Chaotic-based Interactive Autodidact School (CIAS) algorithm, and Slime Mould Algorithm (SMA). This algorithm-based DSM method is simulated using MATLAB/Simulink in different cases and loads, such as residential and Information Technology (IT) sector loads. The results show that the peak load has been reduced from 4.5 MW to 2.6 MW, and the minimum load has been raised from 0.5 MW to 1.2 MW, successfully reducing the gap between peak and low points. Additionally, the performance of each algorithm was compared in terms of the difference between peak and valley points, computation time, and convergence rate to achieve the best fitness value. [ABSTRACT FROM AUTHOR]

The occurrence of faults in electrical distribution networks is a significant concern due to the potential damage to electrical equipment, system instability, and the disruption of reliable energy. Detecting faults in a timely and accurate manner is crucial, especially in complex underground distribution networks with branches, non-homogeneous cables, and various loads. The inherent complexity of such networks poses challenges in pinpointing faulty sections, necessitating specialized detection methods. This research focuses on utilizing the k-Nearest Neighbors (k-NN) algorithm for detecting faulty sections in an underground distribution network. Practical data, obtained from Tenaga Nasional Berhad Malaysia (TNB), including measurements of current swell and voltage sags for 17 network sections, was used to calculate the Euclidean Distance. Given that 70% of faults in the distribution network are attributed to Single Line to Ground Fault (SLGF), this study specifically targets this fault type. Additionally, various fault resistances were tested to observe the k-NN algorithm's performance. The results indicate that the k-NN algorithm successfully detected faulty sections, demonstrating effectiveness across different fault resistances and ranks. This research contributes valuable insights into improving fault detection mechanisms in underground distribution networks. [ABSTRACT FROM AUTHOR]

The demand for electric vehicles (EVs) has increased dramatically in recent years, making it increasingly challenging to keep up with the demand for charging infrastructure. However, conventional power converters (DC–DC converters) have drawbacks such as a high component count, low voltage gain, low efficiency, and high cost. A new DC–DC multiport converter has been proposed to address these challenges by hybridizing a Super-lift Luo and Boost Converter (SLBC) with Photovoltaic (PV) and battery sources as dual inputs. The proposed Dual-Input Dual-Output (DIDO) converter offers significant advantages by super-lifting the input voltage while producing two step-up voltages, one by the Luo converter and another by the Boost converter. The SLBC uses simple structures without any additional electric circuits or transformers to generate high voltage gain and high power efficiency. To evaluate the performance of the proposed SLBC, the converter operation has been analyzed under steady-state and Continuous Current Mode conditions, and a comparison with other similar configurations has been conducted to demonstrate its benefits. Simulation and experimental results have shown that the proposed SLBC offers a considerable reduction in conduction losses compared to other SLBC converters in similar situations. Furthermore, the SLBC system provides 1.2 kW output at the charger side with 94.8% efficiency, making it a viable option for powering various EV components, including the charger, motor, lighting, and audio system, with variable voltages. [ABSTRACT FROM AUTHOR]

This paper covers the self‐sharing analysis of dc‐dc nonisolated converters with input parallel–output parallel (IPOP) configuration and operating in discontinuous conduction mode (DCM). The main contribution of the proposed system is its capability of providing self‐sharing of the currents on both sides of each individual converter, without average current sharing control, even in the face of parametric variations. This self‐balance only occurs for DCM. When the addressed converters operate in continuous conduction mode (CCM), the self‐sharing does not occur naturally under parametric differences among them, requiring the use of additional control loops. The use of self‐sharing converters in nonisolated converters simplifies the control system, it makes the modular solution being attractive for many applications, and it increases the power range that the DCM converters may be applied. This paper brings the theoretical study of self‐sharing of the current mechanism to six basic nonisolated converters operating in DCM. The self‐sharing is verified by experimental results, which are obtained from three modules of dc‐dc SEPIC converters. Both converters were designed to operate with 200‐V input voltage, 125‐V output voltage, 1500‐W rated power (500 W each module), and switching frequency at 30 kHz. [ABSTRACT FROM AUTHOR]