EcoFlex DC-DC Converter Optimization Using a Stochastic-Heap Hybrid Optimizer and IoT Technology | Chapter 12 | Research and Developments in Engineering Research Vol. 7

The climbing need for energy-efficient capacity electronics in Internet of Things (IoT)-authorized devices requires the invention of advanced optimization methods. The EcoFlex DC-DC converter, a new energy-effective solution, is received in this chapter, in addition to a proposal for its growth using an IoT-integrated theory of probability-heap hybrid optimizer (SHHO). The main aims are to produce an eco-friendly DC-DC preacher, an IoT-based switching control bettering, and a low-capacity converter. The widespread use of Internet of Things (IoT) designs in recent years has raised demand for power electronics schemes that meet networked intelligent maneuvers' varied and changing strength requirements. Innovative power administration systems that can affect a balance between energy frugality, agility, and environmental knowledge are urgently needed as IoT uses continue to evolve. A prospective solution to these questions is the EcoFlex DC-DC converter, which this stage covers. It is meant to maximize strength use while allowing for the vacillating load requirements of IoT-enabled supplies. The Stochastic-Heap Hybrid Optimizer (SHHO), which combines the benefits of guessed exploration accompanying heap-based exploitation, is used to reach this. Improving the EcoFlex DC-DC converter's effectiveness is the basic goal of this work. The SHHO optimizes the EcoFlex preacher's settings to obtain high energy effectiveness, which lowers total energy payments and promotes tenable operation. The chapter's second aim is to use IoT technologies to reinforce EcoFlex converter control.In this book chapter, investigators and engineers may test the EcoFlex converter's potential as a high-efficiency power management alternative for the developing IoT system countryside. These results and conclusions prepare the way for further investigation into optimizing power camcorders and support the growth of environmentally friendly and strength-efficient IoT ploys.

Author(s) Details:

Praveen Mande,
Department of EECE, GITAM University, Vishakhapatnam, India.

Budidi Udaya Kumar,
Department of EECE, GITAM University, Vishakhapatnam, India.

S. V. Bharath Kumar Reddy,
Department of EECE, GITAM University, Vishakhapatnam, India.

Sreenivasulu Ummadisetty,
Department of EECE, GITAM University, Vishakhapatnam, India.

I. E. S. Naidu,
Department of EECE, GITAM University, Vishakhapatnam, India.

Please see the link here: https://stm.bookpi.org/RADER-V7/article/view/11712

Stochastic-Heap Hybrid Optimizer (SHHO) and Control Strategies for AC to DC Converters in IoT Applications | Chapter 11 | Research and Developments in Engineering Research Vol. 7

The rebellious effects of the Internet of Things (IoT) on tool interaction and communication have happened in significant development in the adoption of IoT-based requests. Effective power source exercise is crucial in IoT uses, especially in settings accompanying constrained strength resources. AC to DC converters plays a crucial part in the present position by converting interspersing current into direct current. This conversion procedure helps to increase strength efficiency and create it easier to include energy from undepletable source sources. The Stochastic-Heap Hybrid Optimizer (SHHO) is a finish that may be used to help the energy efficiency and control plans of AC to DC converters in Internet of Things (IoT) applications. As submitted, the SHHO method combines guessed search methods accompanying a heap-based addition strategy to efficiently investigate the solution room. SHHO successfully overcomes the local optima question by using the capacities of randomization and prioritization, leading to revised convergence and greater acting. This chapter still comprehensively resolves several AC-to-DC converter control algorithms that concede possibility be used in IoT plans. The solutions include containing, procedures like Proportional-Integral-Derivative (PID) control, Maximum Power Point Tracking (MPPT), and Pulse Width Modulation (PWM). These control methods' examination and contrasting shed light on their distinct benefits and restraints in diverse IoT backgrounds. Additionally, this chapter explores the troubles encountered when SHHO (Solar Hybrid Home Optimisation) is linked with IoT-located AC-to-DC converters. Real-time operation, fittings limits, and communication limits are all part of these difficulties. The authors further discuss useful implementation issues and focal point prospective applications place SHHO might considerably increase performance and energy adeptness. To verify the productiveness of the suggested SHHO and control means, extensive simulations and experimental tests are completed activity in typical IoT positions. According to the findings, SHHO performs better than usual optimization systems in terms of influence, dependability, and flexibility. The Stochastic-Heap Hybrid Optimizer and control arrangements for AC to DC converters are thoroughly checked in this book chapter for use in Internet of Things uses. The approaches and conclusions argued in this information improve the development of strength-efficient IoT wholes. This development sets the stage for the next smart and tenable IoT deployments.

Author(s) Details:

I. E. S. Naidu,
Department of EECE, GITAM University, Vishakhapatnam, India.

Praveen Mande,
Department of EECE, GITAM University, Vishakhapatnam, India.

Budidi Udaya Kumar ,
Department of EECE, GITAM University, Vishakhapatnam, India.

S. V. Bharath Kumar Reddy,
Department of EECE, GITAM University, Vishakhapatnam, India.

Sreenivasulu Ummadisetty,
Department of EECE, GITAM University, Vishakhapatnam, India.

Please see the link here: https://stm.bookpi.org/RADER-V7/article/view/11711