Stochastic-Heap Hybrid Optimizer (SHHO) and Control Strategies for AC to DC Converters in IoT Applications

Abstract

The revolutionary effects of the Internet of Things (IoT) on device interaction and communication have resulted in significant growth in the adoption of IoT-based applications. Effective power source utilization is crucial in IoT applications, especially in settings with constrained energy resources. AC to DC converters plays a crucial role in the present situation by converting alternating current into direct current. This conversion procedure helps to increase energy efficiency and makes it easier to include renewable energy sources. The Stochastic-Heap Hybrid Optimizer (SHHO) is a tool that may be used to improve the energy efficiency and control methods of AC to DC converters in Internet of Things (IoT) applications. As suggested, the SHHO method combines stochastic search methods with a heap-based optimization strategy to efficiently explore the solution space. SHHO successfully overcomes the local optima problem by using the powers of randomization and prioritization, leading to improved convergence and greater performance. This chapter also comprehensively analyzes several AC-to-DC converter control algorithms that may be used in IoT systems. The solutions include among other things, procedures like Proportional-Integral-Derivative (PID) control, Maximum Power Point Tracking (MPPT), and Pulse Width Modulation (PWM). These control systems' examination and comparison shed light on their distinct benefits and limitations in diverse IoT settings. Additionally, this chapter explores the difficulties encountered when SHHO (Solar Hybrid Home Optimisation) is combined with IoT-based AC-to-DC converters. Real-time operation, hardware limits, and communication restrictions are all part of these difficulties. The authors also discuss practical implementation issues and highlight prospective applications where SHHO might significantly increase performance and energy efficiency. To verify the efficacy of the suggested SHHO and control mechanisms, extensive simulations and experimental tests are carried out in typical IoT situations. According to the findings, SHHO performs better than traditional optimization methods in terms of effectiveness, dependability, and flexibility. The Stochastic-Heap Hybrid Optimizer and control methods for AC to DC converters are thoroughly examined in this book chapter for use in Internet of Things applications. The approaches and conclusions discussed in this publication improve the development of energy-efficient IoT systems. This development sets the stage for the next smart and sustainable IoT deployments.