Power Manager with PID controller in Energy Harvesting Wireless Sensor Networks Trong Nhan LE ∗ , Olivier SENTIEYS ∗ , Olivier BERDER ∗ , Alain PEGATOQUET † and Cecile BELLEUDY † ∗ IRISA/INRIA, University of Rennes 1, 6 rue de Kerampont BP 80518 - 22305 Lannion Cedex, France † LEAT, University of Nice-Sophia Antipolis, CNRS 250, rue de Albert Einstein, 06560, Valbonne, France ∗ {trong-nhan.le, sentieys, oberder}@irisa.fr, † {alain.pegatoquet, belleudy}@unice.fr Abstract— System lifetime is the crucial problem of Wireless Sensor Networks (WSNs), and exploiting environmental energy provides a potential solution for this problem. When considering self-powered systems, the Power Manager (PM) plays an impor- tant role in energy harvesting WSNs. Instead of minimizing the consumption energy as in the case of battery powered systems, it makes the harvesting node converge to Energy Neutral Operation (ENO) to achieve a theoretically infinite lifetime and maximize the system performance. In this paper, a low complexity PM with a Proportional Integral Derivative (PID) controller is introduced. This PM monitors the buffered energy in the storage device and performs adaptation by changing the wake-up period of the wireless node. This shows the interest of our approach since the impractical monitoring harvested energy as well as consumed energy is not required as it is the case in other previously proposed techniques. Experimental results are performed on a real WSN platform with two solar cells in an indoor environment. The PID controller provides a practical strategy for long-term operations of the node in various environmental conditions. I. I NTRODUCTION Wireless Sensor Networks (WSNs) are widely used in moni- toring applications such as temperature sensing in smart build- ings, measuring tire pressure in automobiles, and structural- health monitoring. Wireless nodes are densely deployed in remote places to collect information from sensors and co- operatively transmit data to base stations via RF commu- nication. However, limited energy in batteries cannot meet long-term operation in such applications. Wireless sensor networks including energy harvesting can provide a solution to this problem by exploiting ambient energy sources. Several technologies have been developed for harvesting energy from surrounding such as solar, wind and vibration energy [1]. As the environmental energy can be scavenged for as long as desired, the system can theoretically reach an infinite lifetime. A WSN node usually includes a Power Manager (PM) whose aim is to adapt the power consumption of the node to its remaining energy capacity. In battery powered WSNs, the main goal of the PM is to minimize the energy consumption and therefore, to maximize the system lifetime. In energy harvesting WSNs, the PM adapts the consumed energy ac- cording to the energy harvested from environmental sources. For an autonomous system, the PM ensures that the consumed energy is always less than or equal to harvested energy for a long period. This leads to an Energy Neutral Operation (ENO) [2] with maximum performance in harvesting energy powered WSNs. [2] also provides basic studies of dynamic PM in energy harvesting WSNs. Time is divided into slots and, to the predicted energy harvesting, the duty cycle or the wake-up period of the wireless node is estimated at the beginning of each slot. An algorithm for dynamic adaptation depending on the harvested energy is proposed to maximize the average duty cycle. In [3], adapting duty cycle of a solar node is formulated as a Linear Program (LP) and is carried out periodically in each slot. Not only trade-offs between harvested energy and consumed energy, LP is capable of modeling a set of constraints and optimization objectives. For example, trade- offs between using local memory and communication are applied in [3]. However, the consumed energy is considered a constant value and needs to be characterized in these models. In [4], a new concept of energy neutrality, known as ENO- Max, is proposed. An adaptive controller is constructed for the node to minimize the cost function and satisfy the ENO- Max condition. The power manager only considers the battery level to adapt the duty cycle. Therefore, this approach does not need to characterize harvesting sources and consumed energy. However, the energy storage model based on battery level is only considered in the linear region of the rechargeable battery. Similarly to [4], a low complexity PM that only considers the available energy in the storage device is introduced in this paper 1 . The proposed PM does not require to monitor either harvested or consumed energy. Based on the principle of ENO, the PM adapts a harvesting node to sustainable operations with a PID controller. Using a super capacitor as the energy storage, this design takes advantage of a low complexity energy monitor since state of charge can be estimated through a measurement by the system of the voltage level of the capacitor. The rest of this paper is organized as follows. In Section II, the generic architecture of an energy harvesting WSN is presented. The PID controller and energy monitor for buffered energy are proposed in Section III, followed by the experimental results in Section IV. Finally, the paper ends with conclusions. II. GENERIC ARCHITECTURE OF THE PM The PM is considered as the core of the energy harvesting WSN node. It is embedded inside the digital part to control 1 This work is supported by the French National Research Agency (ANR) project GRECO bearing reference ANR-2010-SEGI-004-04. 2012 IEEE International Conference on Green Computing and Communications, Conference on Internet of Things, and Conference on Cyber, Physical and Social Computing 978-0-7695-4865-4/12 $26.00 © 2012 IEEE DOI 10.1109/GreenCom.2012.107 668