Medium access control for thermal energy harvesting in advanced metering infrastructures

Abstract

In this paper we investigate the feasibility of powering wireless metering devices, namely heat cost allocators, by thermal energy harvested from radiators. The goal is to take a first step toward the realization of Energy-Harvesting Advanced Metering Infrastructures (EH-AMIs). While traditional batterypowered devices have a limited amount of energy, energy harvesting can potentially provide an infinite amount of energy for continuous operating lifetimes, thus reducing the cost involved in installation and maintenance. The contribution of this work is twofold. First, we experimentally identify the potential energy that can be harvested from Low Surface Temperature (LST) radiators. The experiments are based on a developed EnergyHarvesting Heat Cost Allocator (EH-HCA) prototype. On the basis of this measured power budget, we model and analytically compare the currently used Medium Access Control (MAC) scheme of an industrial case study (IMR+) to a MAC scheme specifically designed for energy harvesting systems (ODMAC).Our analytical comparison shows the efficiency of the latter, as well as its ability to adapt to harvested ambient energy.

Quality of service optimization in solar cells-based energy harvesting wireless sensor networks

“…ODMAC adjusts individually the duty cycle of each node, to the level that the energy consumed is at the same level of the energy harvested, thus maintaining it at state energy neutral. [36] is a first attempt to approach the energy harvesting WSNs in the metering industry by using the harvested thermal energy from radiators to power the nodes of the network (meters). Several are the contributions of this work: 1) to measure the energy harvested from the heat of a radiator, for which they developed a real prototype; 2) to compare analytically the default ALOHA-based MAC protocol typically used in the metering industry (IMR+) against ODMAC, the MAC scheme specifically designed for energy harvesting WSNs.…”

“…Each sensor has a different opportunity for scavenging and different scheduling plans with a consumption and a quality associated to its service level. Differently to the works presented by other authors to provide energy-neutral operation in energy harvesting WSNs [7,15,25,26,36], our focus is to maximize the quality of the applications executed on each node of the network, where quality is a wider concept than the performance network, for which we provide a variety of scheduling plans that can be dynamically selected for execution.…”

CRC Error Correction in IoT Applications

“…Table II summarises Based on the presented analysis, it can be concluded that the maximum number of iterations in the case of ADMM could be configured to match the application requirements. For applications where data is transmitted only occasionally, such as smart metering systems where a single packet is sent once in 24 hours [23], T max can be set to a value much larger than 1000, potentially increasing the probability of packet correction. 1 The projection algorithm implementation for the ADMM decoder was taken from [22].…”

A survey on ambient energy sources and harvesting methods for structural health monitoring applications

“…However, TEGs have a low conversion efficiency under small temperature changes, and they are difficult to combine with MEMS technologies due to their construction and size. 7,8 A commercial TEG was reported in previous works, [53][54][55][56] as shown in Figure 8(a). Losada et al 56 demonstrated a wireless sensor device powered by a TEG for infrastructure health monitoring applications.…”

“…Peak power (20 mW) was generated at temperature gradient of 20 K. A TEG-based multiple sensor node for an aircraft health monitoring system was presented in previous works. 55,56 Continuous power of 200 mW was generated by the TEG under normal working conditions, as shown in Figure 8(b).…”