Advanced building blocks of power converters for renewable energy based distributed generators

2011 ◽  
Author(s):  
Riming Shao ◽  
Mary Kaye ◽  
Liuchen Chang
Keyword(s):  
Renewable Energy ◽  
Power Converters ◽  
Building Blocks ◽  
Distributed Generators

scholarly journals Power Converters in Power Electronics: Current Research Trends

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 654
Author(s):  
Minh-Khai Nguyen
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Power Electronics ◽  
Electric Vehicles ◽  
Power Converters ◽  
Energy Systems ◽  
Research Trends ◽  
Pulsed Power ◽  
Renewable Energy Systems

In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical [...]

The Controller Parameters Optimization for Droop Controlled Distributed Generators in Microgrid

2014 ◽  
Vol 672-674 ◽  
pp. 1329-1335 ◽  
Author(s):  
Zhong Wen Li ◽  
Chuan Zhi Zang ◽  
Peng Zeng ◽  
Hai Bin Yu ◽  
He Peng Li
Keyword(s):  
Renewable Energy ◽  
High Speed ◽  
Control Method ◽  
Energy Resource ◽  
Parameters Optimization ◽  
Stable Operation ◽  
Simulation Studies ◽  
Distributed Generators ◽  
Pi Controllers ◽  
Circulating Currents

Microgrids are attracting a great deal of attention as integrated renewable energy resource can benefit both the utility and the customers. The droop-control method is popular for the microgrid stable operation as it avoids circulating currents among the converters without using any critical communication between them. The distributed generators should have high speed to follow the reference given by the droop controller, otherwise the system will fluctuate and even black out. Renewable energy powered Distributed Generators (DGs) are mostly inverter-interfaced and controlled by PI controllers. The Particle Swarm Optimization (PSO) was used to optimize the PI parameters with the objective of high tracking speed of the Inverter-interfaced DGs. Simulation studies in Matlab demonstrate the effectiveness of the optimized control parameters.

scholarly journals ARTIFICIAL INTELLIGENCEINTERVENTION TO URBAN BUILDING RENEWABLE ENERGY MODELING INTERVENTION FOR ROBUST FLEXIBLE COMMUNITIES

2021 ◽  
Vol 9 (03) ◽  
pp. 314-321
Author(s):  
Sammar Z. Allam
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Power Plants ◽  
Energy Use ◽  
Model Simulation ◽  
Renewable Energy Sources ◽  
Energy Generation ◽  
Building Blocks ◽  
Positive Energy ◽  
Use Pattern

This research coveys a comparative analysis between Urban Building energy model (UBEM) generated by scholar, researchers, and professional in academia and industry while highlighting the reliable main components to manifest a successful and reliable UBEM technologies. Nevertheless, it consolidates distributed generation on building blocks rather than a whole district relying on renewable energy sources. It guides engineers through energy system model simulation on Openmodelica platform to feed green sustained communities. Moreover, energy use-pattern is mapped and analyzed by internet of things (IOT) technologies to fine-tune energy uses and refine use-pattern. Demonstrating artificial Intelligence (AI) algorithmto predict energy consumption can reflect on the amount of energy required for storage to cover energy needs. AI shapes a robust positive energy district (PED) through storinggenerated renewable solar or bio-energy to cover predicted energy use-pattern.Distributed -power-plant stations capacity to cover clusters using AI in predicting energy consumption consolidates on-site energy generation recommended by multiple International rating systems. AI-based Energy management plan guide engineers and planners to design distributed-power-plants of energy generation capacity lies between the actual energy need and a predicted scenario.

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