Modeling and Optimisation of a Solar Energy Harvesting System for Wireless Sensor Network Nodes

Abstract

The Wireless Sensor Networks (WSN) are the basic building blocks of today’s modern internet of Things (IoT) infrastructure in smart buildings, smart parking, and smart cities. The WSN nodes suffer from a major design constraint in that their battery energy is limited and can only work for a few days depending upon the duty cycle of operation. The main contribution of this research article is to propose an efficient solar energy harvesting solution to the limited battery energy problem of WSN nodes by utilizing ambient solar photovoltaic energy. Ideally, the Optimized Solar Energy Harvesting Wireless Sensor Network (SEH-WSN) nodes should operate for an infinite network lifetime (in years). In this paper, we propose a novel and efficient solar energy harvesting system with pulse width modulation (PWM) and maximum power point tracking (MPPT) for WSN nodes. The research focus is to increase the overall harvesting system efficiency, which further depends upon solar panel efficiency, PWM efficiency, and MPPT efficiency. Several models for solar energy harvester system have been designed and iterative simulations were performed in MATLAB/SIMULINK for solar powered DC-DC converters with PWM and MPPT to achieve optimum results. From the simulation results, it is shown that our designed solar energy harvesting system has 87% efficiency using PWM control and 96% efficiency ( η s y s ) by using the MPPT control technique. Finally, an experiment for PWM controlled SEH-WSN is performed using Scientech 2311 WSN trainer kit and a Generic LM2575 DC-DC buck converter based solar energy harvesting module for validation of simulation results.

Powering the Environmental Internet of Things

“…Some studies have shown that modelling algorithms can be refined to optimise this technique in practice. This has allowed for the creation of MPPT systems with very low energy consumption, which maximise the active time of photovoltaic cells [29], and also systems that are heavily optimised for IoT applications [30].…”

Special Issue: Wireless Sensor and Actuator Networks for Smart Cities

“…The articles that appear in this Special Issue form a diverse collection of topics studied under the scope of WSANs for smart cities. These include low-cost IoT implementation for smart-village settings [1], smart parking systems exploiting WSNs [2], Machine-To-Machine (M2M) Networking over LTE for smart-city services [3], WSN-driven smart waste-management systems for sustainable cities [4], user-support systems with wearable sensors and cameras [5], a SmartInsoles Cyber-Physical System (CPS) for mobile gait analysis [6], energy-harvesting systems for WSNs [7], and IoT for WSNs in smart cities [8].…”

“…The ubiquity of smart-city services can only be ensured with the significantly increased lifetime of sensors and WSNs. The authors of Reference [7] propose an efficient solar-energy-harvesting system with pulse-width modulation (PWM) and maximum power-point tracking (MPPT) to sustain the batteries of WSN nodes. Following the design of several models for a solar-energy harvester system, the authors run a series of simulations for solar powered DC-DC converters with PWM and MPPT to obtain optimum results.…”

Optimal Routing for Time-Driven EH-WSN under Regular Energy Sources

“…In contrast, low-level models are highly implementation-dependent and hence tightly associated with specific architectures. Low-level modeling relies on equivalent circuits of the integrated components, which are then combined into a system model to accurately describe the behavior of a given hardware architecture [ 26 , 27 , 28 ]. These low-level models can be implemented via specialized simulation software environments, like SPICE [ 29 ] or Simulink (a visual programming tool for model-based design that supports automatic code generation in Matlab), or directly executed by using EH-WSN-oriented simulation tools, like GreenCastalia [ 30 ], SolarCastalia [ 31 ], SensEH [ 32 ] and others, which already include an energy module that integrates the energy-harvesting, rechargeable battery and energy consumption models.…”