This paper provides a comprehensive review of the maximum power point tracking (MPPT) techniques applied to photovoltaic (PV) power system available until January, 2012. A good number of publications report on different MPPT techniques for a PV system together with implementation. But, confusion lies while selecting a MPPT as every technique has its own merits and demerits. Hence, a proper review of these techniques is essential. Unfortunately, very few attempts have been made in this regard, excepting two latest reviews on MPPT [Salas, 2006], [Esram and Chapman, 2007]. Since, MPPT is an essential part of a PV system, extensive research has been revealed in recent years in this field and many new techniques have been reported to the list since then. In this paper, a detailed description and then classification of the MPPT techniques have made based on features, such as number of control variables involved, types of control strategies employed, types of circuitry used suitably for PV system and practical/commercial applications. This paper is intended to serve as a convenient reference for future MPPT users in PV systems.

A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems

Thin-film electronics in its myriad forms has underpinned much of the technological innovation in the fields of displays, sensors, and energy conversion over the past four decades. This technology also forms the basis of flexible electronics. Here we review the current status of flexible electronics and attempt to predict the future promise of these pervading technologies in healthcare, environmental monitoring, displays and human-machine interactivity, energy conversion, management and storage, and communication and wireless networks.

Flexible Electronics: The Next Ubiquitous Platform

With the recent growth in sustainable HCI, now is a good time to map out the approaches being taken and the intellectual commitments that underlie the area, to allow for community discussion about where the field should go. Here, we provide an empirical analysis of how sustainable HCI is defining itself as a research field. Based on a corpus of published works, we identify (1) established genres in the area, (2) key unrecognized intellectual differences, and (3) emerging issues, including urgent avenues for further exploration, opportunities for interdisciplinary engagement, and key topics for debate.

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Mapping the landscape of sustainable HCI

An automated irrigation system was developed to optimize water use for agricultural crops. The system has a distributed wireless network of soil-moisture and temperature sensors placed in the root zone of the plants. In addition, a gateway unit handles sensor information, triggers actuators, and transmits data to a web application. An algorithm was developed with threshold values of temperature and soil moisture that was programmed into a microcontroller-based gateway to control water quantity. The system was powered by photovoltaic panels and had a duplex communication link based on a cellular-Internet interface that allowed for data inspection and irrigation scheduling to be programmed through a web page. The automated system was tested in a sage crop field for 136 days and water savings of up to 90% compared with traditional irrigation practices of the agricultural zone were achieved. Three replicas of the automated system have been used successfully in other places for 18 months. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas.

Automated Irrigation System Using a Wireless Sensor Network and GPRS Module

Wireless sensor networks (WSNs) research has pre-dominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial research efforts have been spent on designing energy-efficient networking protocols to maximize the lifetime of WSNs. However, there are emerging WSN applications where sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Examples include in-situ environmental/habitat monitoring and structural health monitoring of critical infrastructures and buildings, where batteries are hard (or impossible) to replace/recharge. Lately, an alternative to powering WSNs is being actively studied, which is to convert the ambient energy from the environment into electricity to power the sensor nodes. While renewable energy technology is not new (e.g., solar and wind) the systems in use are far too large for WSNs. Those small enough for use in wireless sensors are most likely able to provide only enough energy to power sensors sporadically and not continuously. Sensor nodes need to exploit the sporadic availability of energy to quickly sense and transmit the data. This paper surveys related research and discusses the challenges of designing networking protocols for such WSNs powered by ambient energy harvesting.

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Wireless sensor networks powered by ambient energy harvesting (WSN-HEAP) - Survey and challenges

This paper describes a new maximum-power-point-tracking (MPPT) method focused on low-power (<; 1 W) photovoltaic (PV) panels. The static and dynamic performance is theoretically analyzed, and design criteria are provided. A prototype was implemented with a 500-mW PV panel, a commercial boost converter, and low-power components for the MPPT controller. Laboratory measurements were performed to assess the effectiveness of the proposed method. Tracking efficiency was higher than 99.6%. The overall efficiency was higher than 92% for a PV panel power higher than 100 mW. This is, in part, feasible due to the low power consumption of the MPPT controller, which was kept lower than 350 μW. The time response of the tracking circuit was tested to be around 1 s. Field measurements showed energy gains higher than 10.3% with respect to a direct-coupled solution for an ambient temperature of 26°C. Higher gains are expected for lower temperatures.

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A New MPPT Method for Low-Power Solar Energy Harvesting

Current commercial autonomous sensors are mainly powered by primary batteries. Batteries need to be replaced and hence can become the largest and most expensive part of the system. On the other hand, our environment is full of waste and unused energy such as that coming from the sun or mechanical vibrations. As a result, commercial energy harvesters are increasingly available to power autonomous sensors. This work presents and analyses commercial energy harvesters currently available. First, environmental energy sources are classified and described. Then, energy harvesting principles are described and some guidelines are given to calculate the maximum power consumption allowed and the energy storage capacity required for the autonomous sensor. Finally, commercial energy harvesters are evaluated to determine their capability to power a commercial autonomous sensor in some given circumstances.

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A Review of Commercial Energy Harvesters for Autonomous Sensors

This paper proposes a closed-loop maximum power point tracker (MPPT) for subwatt photovoltaic (PV) panels used in wireless sensor networks. Both high power efficiency and low circuit complexity are achieved. A microcontroller (μC) driven by a fast clock was used to implement an MPPT algorithm with a low processing time. This leads to a maximum central-processing-unit duty cycle of 6% and frees the μC to be used in the remaining tasks of the autonomous sensor, such as sensing, processing, and transmitting data. In order to reduce power consumption, dynamic power management techniques were applied, which implied the use of predictive algorithms. In addition, the measurement and acquisition of the output current and voltage of the PV panel, which increase circuit complexity, was avoided. Experimental measurements showed power consumptions of the MPPT controller as low as 52 μW for a 2.7-mW PV power and up to 388 μW for a 94.4-mW PV power. Tracking efficiency was higher than 99.4%. The overall efficiency was higher than 90% for a PV panel power higher than 20 mW. Field measurements showed an energy gain 15.7% higher than that of a direct-coupled solution.

A Closed-Loop Maximum Power Point Tracker for Subwatt Photovoltaic Panels

Wireless sensor networks (WSNs) are increasingly used in many fields. Still, power supply of the nodes remains a challenge. Primary batteries are mainly used but energy harvesting offers an alternative, although not free of problems. This paper compares the use of primary batteries against solar cells. Basic principles are first enunciated, then generic design examples are presented and finally actual deployed nodes of a WSN are illustrated.

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Powering wireless sensor nodes: Primary batteries versus energy harvesting

The sensor nodes of wireless sensor networks remain inactive most of the time to achieve longer runtimes. Power is mainly provided by batteries, which are either primary or secondary. Because of its internal impedance, a significant voltage drop can appear across the battery terminals at the activation time of the node, thus preventing the extraction of all the energy from the battery. Additionally, internal losses can also be significant. Consequently, the runtime is reduced. The addition of a supercapacitor in parallel with the battery, thus forming a hybrid-storage device, has been proposed under pulsed loads to increase the power capabilities and reduce both the voltage drop and the internal losses at the battery. However, this strategy has not yet thoroughly been analyzed and tested in low-power wireless sensor nodes. This paper presents a comprehensive theoretical analysis that extends previous works found in the literature and provides design guidelines for choosing the appropriate supercapacitor. The analysis is supported by extensive experimental results. Two low-capacity (< 200 mAh) batteries were tested together with their hybrid-storage unit counterparts when using an electronic load as a pulsed current sink. The hybrid-storage units always achieved a higher runtime. One of the batteries was also tested using a sensor node. The runtime extension was 16% and 33% when connecting the hybrid-storage unit directly and through a dc-dc switching regulator to the sensor node, respectively.

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Maria Teresa Penella

Papers

A New MPPT Method for Low-Power Solar Energy Harvesting

A Review of Commercial Energy Harvesters for Autonomous Sensors

A Closed-Loop Maximum Power Point Tracker for Subwatt Photovoltaic Panels

Powering wireless sensor nodes: Primary batteries versus energy harvesting

Runtime Extension of Low-Power Wireless Sensor Nodes Using Hybrid-Storage Units