Design and control approaches for energy harvesting wireless sensor networks

Wireless Networks are monitoring infrastructures composed of sensing (measuring), computing, and communication devices used to observe, supervise and monitor environmental phenomena. Energy Harvesting Wireless Sensor Networks (EH-WSN) have the additional feature to save energy from the environment in order to ensure long life autonomy of the entire network, without ideally the human intervention over long periods of time. The present work is aimed to address some of the most significant limitations of the actual EH-WSN, making a step forward the perpetual operation of EH-WSN. In this dissertation, design methodology and management policies are proposed to improve EH-WSN in terms of application performances, traffic congestion and energy efficiency. The study explicitly targets to energy-efficient affordable ways to develop more reliable and trustworthy EH-WSN, capable to ensure long life and desired performances. The presentation is organized into two macro sections, or Parts: the first one is dedicated to design the main EH-WSN hardware and software parameters that affect the energy efficiency of a sensor node, while in the second part three dynamic control strategies are proposed to outperform the EH-WSN in terms of energy efficiency, traffic congestion and application requirements

Evaluation of Energy Efficiency-Reconstruction Error Trade-Off in the Co-design of Compressive Sensing Techniques for Wireless Lossy Sensor Networks

In the recent years, the technological improvements on wireless sensor computational capability and versatility have caused a massive use of battery-supplied Wireless Sensor Network (WSN) in many different monitoring applications. The most relevant factors of reliability of such systems are related to the energetic autonomy and the accuracy of the sampled data delivered to the Fusion Center. These two factors are usually in trade off because a more reliable acquisition system requires more energy consumption and vice-versa. In this paper, we present a tool for the co-design of Compressive Sensing techniques to get the desired performance in terms of energy efficiency and reconstruction error. Preliminarily, we formulate a WSN model taking into account both node energy consumption and the traffic model. The effects of packet collision phenomena (that typically affect wireless communication) are also added to the traffic model. The provided WSN model is used to support a tool for the software co-design of parameters that are related to the compression method in order to fulfil given performance specifications on energetic autonomy or signal reconstruction error. To show the effectiveness of the proposed model and the feasibility of the co-design approach, the model is particularized to representative schemes of Compressive Sensing implemented over the network in the presence and in absence of packet loss. An example of software co-design aimed to improve both network autonomy and signal reconstruction error of the considered Compressive Sensing schemes is presented

A Two-Layer Controller Scheme for Efficient Signal Reconstruction and Lifetime Elongation in Wireless Sensor Networks

Abstract: Random sampling compressive sensing (RSCS) is a prominent compression algorithm suitable for wireless sensor network as it can significantly reduce the number of samples required for signal reconstruction. This improves the network lifetime, but can introduce uncertainty in the signal reconstruction. In this paper, we propose a two-layer controller that ensures efficient signal reconstruction (i.e., low level of reconstruction error) and high network lifetime. The proposed controller is composed of a global controller, developed at the fusion center layer, and two local controllers, implemented at each node layer. The former steers the RSCS reconstruction error to a desired value, while the latter are implemented to reduce the energy consumption of each node. A performance evaluation of the proposed scheme is carried out in terms of reconstruction error regulation and network lifetime. Simulation results show the effectiveness of the proposed scheme compared with two main strategies existing in the literature

Enhancing wireless networked monitoring system sustainability by multi-hop consensus algorithm

The widely studied consensus protocols have been increasingly used in industrial monitoring applications to support distributed process control. As the theoretical convergence rate covers vast interests in literature, techniques to speed up the convergence rate of consensus have been extensively explored, whereas their effects on the energetic consumption and on the sensor node technology have received a relatively lower attention. This work proposes to analyze jointly the energetic consumption and the consensus convergence rate in a Wireless Sensor Network scenario. Two different consensus techniques have been compared: the single-hop and the multi-hop algorithms. An environmental simulator has been built to validate the above techniques. Results show that multi-hop algorithm may be preferable to preserve the network lifetime, while the single-hop is more suitable in order to achieve higher speed of convergence

A design approach of the Solar Harvesting Control System for Wireless Sensor Node

In the last recent years the implementation of PV (PhotoVoltaic) solar harvesting maximum power point tracking (MPPT) systems has been widely investigated to achieve self-powered and fully autonomous wireless sensor networks (WSNs). In this context, this paper mainly aims to design an efficient and long-lived solar harvesting control system for sensor nodes. Specifically, a design approach of the overall solar harvesting control system, that is composed of PV source, controller, converter, and UltraCapacitor (UC), is provided in order to obtain the desired performance in terms of autonomy and efficiency. The methodology is based on the analytical derivation of system efficiency and takes into account design requirements. The approach is applied to the design of an harvesting control system supplying an off-the-shelf Texas Instruments eZ430. -. RF4500 mote. The prototype is realized and used to experimentally validate the approach by mean of out-door four days test. The experimental results show the effectiveness of the methodology to assess the required performance in terms of efficiency (about 0.86) and autonomy (four days)

An implementation of a smart maximum power point tracking controller to harvest renewable energy of wireless sensor nodes

In wireless sensor network (WSN) application one of the main requirement is the self-powered of the nodes. This is why it is increasing the use of renewable source (i.e. photovoltaic (PV)) for supplying power to WSN node. A Maximum Power Point Tracker (MPPT) controller circuit is required to be implemented in order to guarantee the maximum power efficiency of the system. Therefore, in the scenario of renewable energy harvesting, the consumption as well as the tracking performance of the MPPT controller represents a crucial point. The paper proposes a low power implementation of MPPT controller for WSN application. The proposed implementation scheme guarantees the maximum power point tracking performance requiring just 330 ??W of power consumption. An ultracapacitor as storage device has been used. The proposed scheme has been implemented and tested for a wireless pressure sensor node under typical both solar irradiance conditions

Adaptive FOCV-based Control Scheme to improve the MPP Tracking Performance: an experimental validation

Nowadays the photovoltaic (PV) is one of the most renewable source device used in the harvesting system to support the life time of stand alone devices like sensor node. One of the most diffused method to increase the PV efficiency is the Fractional Open-Circuit Voltage (FOCV) that allows the PV to work around its estimated Maximum Power Point (MPP). To increase the solar harvesting system efficiency both static (in terms of efficiency) and dynamic (in terms of MPP tracking responsiveness) performances are of crucial interest. Most of works in the literature focus on improving the static system performance by giving a more accurate MPP estimation. In this paper, it is proposed a FOCV-based algorithm to improve system dynamic performance in terms of MPP tracking performance and energy conveyed to the load under varying solar irradiance conditions. The MPP system dynamically adapts the MPP estimation to the solar irradiance condition by mean of a ”smart timer” circuitry that continuously adjusts the operative frequency of the sample and hold component. A detailed hardware implementation description of a smart timer as well as a related analytical analysis used for component design are presented. An experimental validation and a comparison of the proposed approach than the standard FOCV based method are carried out. The results show the effectiveness of the proposed scheme in improving dynamic system performance in terms of tracking performance and timeless to convey solar energy to the load storage component (i.e. ultracapacitor)

A PV Model-Based Design of a MPPT Controller for Energy Harvested Wireless Sensor Nodes

The contribute of this work is to propose a PV model-based design of a MPPT controller to harvest energy in a stand-alone wireless sensor node. Firstly a model identification of PV cell is carried out. Then the identified parameters are used to design the PV maximum power point tracker (MPPT) controller to continuously supply the wireless sensor node by a storage buffer. Additionally, the implementation of the proposed MPPT scheme is here presented. It has been implemented a rational energy management system, which uses an ultracapacitor as storage buffer, by increasing the autonomy of the system. The proposed scheme was realized and validated by outdoor tests under typical both solar and load absorption conditions