• Energy Research

This paper presents a new soft switching (SS) multiphase interleaved boost converter (MIBC) consisting of three boost converters (BCs) that operate rapidly and efficiently to charge a lithium-ion battery for photovoltaic (PV) power system applications. This suggested converter can operate both active power switches at zero current switching (ZCS), and when switched off, it works at zero voltage switching (ZVS), which reduces switching losses and increases switching efficiency (SF). An interleaving structure is employed to decrease the conduction losses and reduce the input current ripple (ICR) and output voltage ripple (OVR) to increase the power rating. The suggested converter regulates the input and output power by modulating the phase shift in the pulse width modulation (PWM) technique using the maximum power point tracking (MPPT) algorithm via two closed feedback loops, one for a slower external loop and the other for a faster PWM control internal loop, similar to current mode control. The suggested converter has high voltage (HV) gain due to the coupled inductors (CIs), which act as a transformer. This magnetic design structure in both the steady-state and transient states also decreases the size and enhances the converter’s performance. Finally, the suggested converter was experimentally verified on a 285W prototype, and the maximum efficiency was found to be 98%, based on modeling and experimental data.

This paper presents a new soft switching (SS) multiphase interleaved boost converter (MIBC) consisting of three boost converters (BCs) that operate rapidly and efficiently to charge a lithium-ion battery for photovoltaic (PV) power system applications. This suggested converter can operate both active power switches at zero current switching (ZCS), and when switched off, it works at zero voltage switching (ZVS), which reduces switching losses and increases switching efficiency (SF). An interleaving structure is employed to decrease the conduction losses and reduce the input current ripple (ICR) and output voltage ripple (OVR) to increase the power rating. The suggested converter regulates the input and output power by modulating the phase shift in the pulse width modulation (PWM) technique using the maximum power point tracking (MPPT) algorithm via two closed feedback loops, one for a slower external loop and the other for a faster PWM control internal loop, similar to current mode control. The suggested converter has high voltage (HV) gain due to the coupled inductors (CIs), which act as a transformer. This magnetic design structure in both the steady-state and transient states also decreases the size and enhances the converter’s performance. Finally, the suggested converter was experimentally verified on a 285W prototype, and the maximum efficiency was found to be 98%, based on modeling and experimental data.

The integration of clean energy sources (CESs) into modern power systems has been studied using various power converter topologies. The challenges of integrating various CESs are facilitated by the proper design of multi-port power converter (MPPC) architecture. In this study, a brand-new two-stage MPPC is suggested as a solution to the intermittent nature and slow response (SR) of CESs. The suggested system combines a DC\DC and a DC\AC converter and storage unit, and the suggested circuit additionally incorporates a number of CESs (PV\wind\fuel cell (FC)). This article discusses the power management and control technique for an integrated four-port MPPC that links three input ports (PV, wind, and FC), a bidirectional battery port, and an isolated output port. One of the recent optimization techniques (Harris Hawk’s algorithm) is applied to optimize the system’s controller gains. By intelligently combining CESs with complementary characteristics, the adverse effects of intermittency are significantly mitigated, leading to an overall enhancement in system resilience and efficiency. Furthermore, integrating CESs with storage units not only addresses SR challenges but also effectively combats intermittent energy supply. The proposed system exhibits improved dynamic capabilities, allowing it to efficiently distribute excess energy to the load or absorb surplus energy from external sources. This dual functionality not only optimizes system operation but also contributes to a reduction in system size and cost, concurrently enhancing reliability. A comprehensive investigation into operational principles and meticulous design considerations are provided, elucidating the intricate mechanics of the suggested MPPC system. Employing MATLAB/Simulink, the proposed architecture and its control mechanisms undergo rigorous evaluation, affirming the feasibility and efficacy of this innovative system.

The integration of clean energy sources (CESs) into modern power systems has been studied using various power converter topologies. The challenges of integrating various CESs are facilitated by the proper design of multi-port power converter (MPPC) architecture. In this study, a brand-new two-stage MPPC is suggested as a solution to the intermittent nature and slow response (SR) of CESs. The suggested system combines a DC\DC and a DC\AC converter and storage unit, and the suggested circuit additionally incorporates a number of CESs (PV\wind\fuel cell (FC)). This article discusses the power management and control technique for an integrated four-port MPPC that links three input ports (PV, wind, and FC), a bidirectional battery port, and an isolated output port. One of the recent optimization techniques (Harris Hawk’s algorithm) is applied to optimize the system’s controller gains. By intelligently combining CESs with complementary characteristics, the adverse effects of intermittency are significantly mitigated, leading to an overall enhancement in system resilience and efficiency. Furthermore, integrating CESs with storage units not only addresses SR challenges but also effectively combats intermittent energy supply. The proposed system exhibits improved dynamic capabilities, allowing it to efficiently distribute excess energy to the load or absorb surplus energy from external sources. This dual functionality not only optimizes system operation but also contributes to a reduction in system size and cost, concurrently enhancing reliability. A comprehensive investigation into operational principles and meticulous design considerations are provided, elucidating the intricate mechanics of the suggested MPPC system. Employing MATLAB/Simulink, the proposed architecture and its control mechanisms undergo rigorous evaluation, affirming the feasibility and efficacy of this innovative system.

To avert climate change, there has been a rise in the usage of green energy sources that are also beneficial to the environment. To generate sustainable energy in a financially and technically efficient manner, our research attempts to close the gaps. The potential of green sources like photovoltaic (PV) and biomass for a rural community southwest of Sohag Al Gadida City, Sohag, Egypt, is examined in this research considering its techno-economic (TE) and eco-friendly feasibility. The HOMER Pro v3.14 package is used as a scaling and optimization instrument, to calculate the price of the PV/biomass setup and the size and characteristics of its parts. This is to estimate the corresponding electrical production and reduce the total annual cost for the customer. The suggested system structure is validated through the presentation of simulation outcomes and evaluations utilizing MATLAB/SIMULINK R2022a. In addition, a TE-environmental investigation of the optimized PV/biomass structure is performed. The optimum structure is carefully chosen from the best four configurations using the demand predilection by analogy to the perfect technique based on the generation cost, operation cost, energy production, and renewable fraction. The results also indicate that using hybrid PV/biomass is an attractive choice with the initial capital cost (ICC: USD 8.144), net present cost (NPC: USD 11,026), a low cost of energy (LCOE: 0.184 USD/kWh), and the high renewable fraction (RF: 99.9%) of the system. The annual CO2 emission performance of a PV/biomass system is much better than that of the grid alone and PV/diesel. This method might be applied in rural areas in other developing countries.

To avert climate change, there has been a rise in the usage of green energy sources that are also beneficial to the environment. To generate sustainable energy in a financially and technically efficient manner, our research attempts to close the gaps. The potential of green sources like photovoltaic (PV) and biomass for a rural community southwest of Sohag Al Gadida City, Sohag, Egypt, is examined in this research considering its techno-economic (TE) and eco-friendly feasibility. The HOMER Pro v3.14 package is used as a scaling and optimization instrument, to calculate the price of the PV/biomass setup and the size and characteristics of its parts. This is to estimate the corresponding electrical production and reduce the total annual cost for the customer. The suggested system structure is validated through the presentation of simulation outcomes and evaluations utilizing MATLAB/SIMULINK R2022a. In addition, a TE-environmental investigation of the optimized PV/biomass structure is performed. The optimum structure is carefully chosen from the best four configurations using the demand predilection by analogy to the perfect technique based on the generation cost, operation cost, energy production, and renewable fraction. The results also indicate that using hybrid PV/biomass is an attractive choice with the initial capital cost (ICC: USD 8.144), net present cost (NPC: USD 11,026), a low cost of energy (LCOE: 0.184 USD/kWh), and the high renewable fraction (RF: 99.9%) of the system. The annual CO2 emission performance of a PV/biomass system is much better than that of the grid alone and PV/diesel. This method might be applied in rural areas in other developing countries.

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS’s DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.

Solar energy, a prominent renewable resource, relies on photovoltaic systems (PVS) to capture energy efficiently. The challenge lies in maximizing power generation, which fluctuates due to changing environmental conditions like irradiance and temperature. Maximum Power Point Tracking (MPPT) techniques have been developed to optimize PVS output. Among these, the incremental conductance (INC) method is widely recognized. However, adapting INC to varying environmental conditions remains a challenge. This study introduces an innovative approach to adaptive MPPT for grid-connected PVS, enhancing classical INC by integrating a PID controller updated through a fuzzy self-tuning controller (INC-FST). INC-FST dynamically regulates the boost converter signal, connecting the PVS’s DC output to the grid-connected inverter. A comprehensive evaluation, comparing the proposed adaptive MPPT technique (INC-FST) with conventional MPPT methods such as INC, Perturb & Observe (P&O), and INC Fuzzy Logic (INC-FL), was conducted. Metrics assessed include current, voltage, efficiency, power, and DC bus voltage under different climate scenarios. The proposed MPPT-INC-FST algorithm demonstrated superior efficiency, achieving 99.80%, 99.76%, and 99.73% for three distinct climate scenarios. Furthermore, the comparative analysis highlighted its precision in terms of control indices, minimizing overshoot, reducing rise time, and maximizing PVS power output.