Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications

Aljafari, Belqasem; Devarajan, Gunapriya; Subramani, Sivaranjani; Subramaniyaswamy, V.

doi:10.3390/su15129425

Cited by 6 publications

(2 citation statements)

References 59 publications

(69 reference statements)

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“…Assumptions: In this research, it is assumed that weather conditions for a short time horizon (three hours ahead) are known [43,68,69]. This assumption is made on the basis of the growing application of the Internet of Things (IoT) in buildings and the possibility of acquiring reasonably accurate weather predictions for a few hours ahead [70,71]. In addition, different prediction models have been recently developed based on machine learning algorithms and historical weather data, which can be used to provide reasonably accurate short-term weather predictions.…”

Section: Energyplus-matlab Co-simulation-optimization Platformmentioning

confidence: 99%

Model Predictive Control for Energy Optimization of HVAC Systems Using EnergyPlus and ACO Algorithm

Bamdad,

Mohammadzadeh,

Cholette

et al. 2023

Buildings

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The deployment of model-predictive control (MPC) for a building’s energy system is a challenging task due to high computational and modeling costs. In this study, an MPC controller based on EnergyPlus and MATLAB is developed, and its performance is evaluated through a case study in terms of energy savings, optimality of solutions, and computational time. The MPC determines the optimal setpoint trajectories of supply air temperature and chilled water temperature in a simulated office building. A comparison between MPC and rule-based control (RBC) strategies for three test days showed that the MPC achieved 49.7% daily peak load reduction and 17.6% building energy savings, which were doubled compared to RBC. The MPC optimization problem was solved multiple times using the Ant Colony Optimization (ACO) algorithm with different starting points. Results showed that ACO consistently delivered high-quality optimized control sequences, yielding less than a 1% difference in energy savings between the worst and best solutions across all three test days. Moreover, the computational time for solving the MPC problem and obtaining nearly optimal control sequences for a three-hour prediction horizon was observed to be around 22 min. Notably, reasonably good solutions were attained within 15 min by the ACO algorithm.

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Section: Energyplus-matlab Co-simulation-optimization Platformmentioning

confidence: 99%

Model Predictive Control for Energy Optimization of HVAC Systems Using EnergyPlus and ACO Algorithm

Bamdad,

Mohammadzadeh,

Cholette

et al. 2023

Buildings

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show abstract

“…Non-isolated DC–DC converters with high voltage gain are considered due to their boost capability, high efficiency, and proper voltage regulation. These converters are widely employed in many different applications, including DC nano grids 8 , electric vehicles 9 , photovoltaic (PV) systems 10 , and fuel cells (FC) 11 . The primary types of non-isolated DC–DC converters are cascaded converters, coupled inductor converters, switched capacitor converters, and interleaved converters.…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of an interleaved step-up DC–DC converter with enhanced characteristics

Hosseinpour,

Seifi,

Seifi

et al. 2024

Sci Rep

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In this paper, an interleaved DC–DC step-up converter with improved characteristics based on a voltage multiplier rectifier is presented. The proposed converter is presented and analyzed for two different operating duty regions including operating region 1 (0 < D ≤ 0.5), and operating region 2 (0.5 ≤ D < 1). This converter can be used in various applications such as energy storage, electric vehicles, and renewable energy systems. This converter is composed of two stages: an interleaved boost stage and a voltage multiplier rectifier stage, which collectively forms its general structure. The interleaved boost stage is a type of two-phase boost converter that transforms the input DC voltage into a high-frequency AC square waveform. This waveform can be readily filtered using smaller capacitors. The square-shaped voltage waveform from the interleaved boost stage is rectified and converted to a high DC voltage by the Voltage Multiplier Rectifier (VMR) stage. The operating regions, the evaluation of the steady-state condition, the voltage gain of the proposed converter's parasitic and ideal models as well as its losses and efficiency analysis have been evaluated. The proposed converter has an efficiency of 97% at the output power of 150 W. The proposed converter is simulated to convert a voltage of 25–159.5 V and to validate the mathematical relationships and simulation results, a laboratory prototype has been developed. The simulation and experimental results show the precision of the performance of the proposed interleaved boost converter.

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Selective harmonic elimination in Novel 27-level trinary DC source inverter using optimization algorithm for hybrid renewable energy sources

Revathi,

Deborah,

Balamurugan

2024

Electr Eng

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Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications

Cited by 6 publications

References 59 publications

Model Predictive Control for Energy Optimization of HVAC Systems Using EnergyPlus and ACO Algorithm

Model Predictive Control for Energy Optimization of HVAC Systems Using EnergyPlus and ACO Algorithm

Design and analysis of an interleaved step-up DC–DC converter with enhanced characteristics

Selective harmonic elimination in Novel 27-level trinary DC source inverter using optimization algorithm for hybrid renewable energy sources

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