Paulo Sérgio Sausen

Monitoring in Industrial Systems Using Wireless Sensor Network With Dynamic Power Management

The advances in wireless communication, microelectronics, digital electronics, and highly integrated electronics and the increasing need for more efficient controlled electric systems make the development of monitoring and supervisory control tools the object of study of many researchers. This paper proposes a digital system for energy usage evaluation, condition monitoring, diagnosis, and supervisory control for electric systems applying wireless sensor networks (WSNs) with dynamic power management (DPM). The system is based on two hardware topologies responsible for signal acquisition, processing, and transmission: intelligent sensor modules (ISMs) and remote data acquisition units (RDAUs). The gateway function of the wired network is carried out by remote servers (RSs) based on the Soekris architecture, which is responsible for receiving the data collected and transmitting it to the supervisory controller (SC). To extend the WSN lifetime, sensor nodes implement a DPM protocol. The basic characteristics of the presented system are the following: 1) easy implementation; 2) low-cost implementation; 3) easy implementation of redundant routines (security); 4) portability/versatility; and 5) extended network lifetime.

Smart Grid Infrastructure Using a Hybrid Network Architecture

Smart grid can be defined as a modern electric power grid infrastructure for improved efficiency, reliability and safety, with smooth integration of renewable and alternative energy sources through automated control and modern communications technologies. The increase need for more effective power electrical systems control turned the development of smart grids, the main object of study for many researchers. This paper proposes a digital system for condition monitoring, diagnosis and supervisory control applied to smart grids. The system is based on hybrid network architecture (HNA), consisting of a wired infrastructure, a wireless sensor network (WSN), a power line communications (PLC) and a controller area network (CAN). The system is based on three hardware topologies: remote data acquisition units (RDAUs), intelligent sensors modules (ISMs) and a PLC modem. The basic characteristics are: a) easy/low cost implementation, b) easy to set up by user, c) easy implementation of redundant routines (security), d) portability/versatility, and e) open system. To validate the developed system, it was implanted in one underground electric substation power distribution, characterized as an extremely hostile environment for supervisory control applications. In this application, the main challenge is to establish a communication system installed inside the substation with the outside (operations center-OC) considering that there are not commercial solutions appropriate to solve completely this problem.

Broadcast routing in wireless sensor networks with dynamic power management and multi-coverage backbones

In a wireless sensor network (WSN), nodes are power constrained. As a consequence, protocols must be energy efficient to prolong the network lifetime while keeping some quality-of-service (QoS) requirements. In WSNs, most protocols resort to the broadcast of control messages like, for example, for the topology control (TC) of the network. On its turn, TC itself can be applied to improve the broadcast of data packets in the network, and because only a subset of nodes need to be active at any time, it is possible to extend the network lifetime. We investigate some alternatives to improve broadcasting in WSN for an extended network lifetime. This is accomplished in two ways. First, we adapt the dynamic power management with scheduled switching modes (DPM-SSM) technique to a blind flooding protocol (i.e., FLOOD). To capture the battery capacity recovery effect as a result of applying DPM, we consider a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). Second, we implement a multi-coverage TC solution for computing an energy efficient broadcast backbone. Extensive simulation results using the NS2 network simulator show that it is possible to extend the network lifetime while keeping good broadcasting performance.

Monitoring and Diagnosis in Industrial Systems Using Wireless Sensor Networks

Condition monitoring and diagnosis of industrial systems avoids unexpected failures and greatly improves system reliability and maintainability. Advances in wireless communication, microelectronics, digital electronics and highly integrated electronics in addition to the increasingly need for more efficient controlled electric systems, makes the development of monitoring and supervisory control tools object of study of many researchers. This paper proposes a digital system for energy usage evaluation, condition monitoring, diagnosis and supervisory control for electric systems applying wireless sensor networks (WSNs) connected to a wired infrastructure. The system is based on two hardware topologies responsible for the signal acquisition, processing and transmission: Intelligent Sensors Modules (ISMs) and Remote Data Acquisition Units (RDAUs). The gateway function of the wired network is carried out by Remote Servers (RSs) based on the AMD-Soekris NET4521 architecture, responsible for receiving the data collected and transmitting it to the Supervisory Controller (SCs) based on a PC Pentium IV architecture. The basic characteristics of the presented system are: (a) easy implementation, (b) low cost implementation, (c) easy implementation of redundant routines (security), and (d) portability/versatility.

Dynamic Power Management with Scheduled Switching Modes

A Wireless Sensor Network (WSN) comprises many sensor nodes each one containing a processing unit, one or more sensors, a power unit, and a radio for data communication. Nodes are power constrained, because they run on batteries which usually cannot be replaced due to the nature of the applications. We present a novel dynamic power management approach, named Dynamic Power Management with Scheduled Switching Modes (DPM-SSM), derived from a more realistic analysis of the battery capacity recovery effect and the switching energy. This was only possible thanks to the application of a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). We also devised a Hybrid Differential Petri Nets formalism to evaluate our power management solution. Preliminary results showed the potential for improving the battery lifetime by taking advantage of the battery recovery effect when a node transitions to a sleeping state mostly after packet transmissions. DPM-SSM provides several DPM modes which are triggered depending on the battery remaining capacity. Simulations results show that, depending on the scheduling approach, DPM-SSM can provide real battery power recovery without compromising the timeliness of the applications running on the sensor network.

Dynamic Power Management with Scheduled Switching Modes in Wireless Sensor Networks

A wireless sensor network (WSN) comprises many sensor nodes each one containing a processing unit, one or more sensors, a power unit, and a radio for data communication. Nodes are power constrained, because they run on batteries, that in many cases cannot be easily replaced. This paper presents a novel dynamic power management technique, named Dynamic Power Management with Scheduled Switching Modes (DPM-SSM), derived from a more realistic analysis of the battery capacity recovery effect and the switching energy. This was only possible thanks to the application of a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). Preliminary results showed the potential for improving the battery lifetime by taking advantage of the battery recovery effect when a node transitions to a sleeping state, and mostly when transitions are scheduled after packet transmissions. DPM-SSM provides several DPM modes which are triggered depending on the battery remaining capacity. Simulations results show that DPM-SSM can provide real battery power recovery without compromising the timeliness of the applications running on the wireless sensor network.

Smart distribution transformer applied to Smart Grids

Growing demand, requirements for power quality enhancement and distribution generation are increasing the complexity of distribution systems. In this scenario, voltage regulation of distribution networks also becomes more complex, especially in long distribution lines. In this paper, a smart distribution transformer is proposed, which employs an electronic on load tap changer with a bidirectional communication system. This system enables automatic voltage regulation, telemetry and remote control for power utilities, allowing its application in Smart Grids.

Applying dynamic power management with mode switching in wireless sensor networks

With the latest advances in wireless communication, new monitoring and supervisory control tools have been designed for industrial systems, avoiding unexpected failures and greatly improving system reliability and maintainability. Usually supervisory control for electric systems applies wireless sensor networks (WSN). WSN comprises many sensor nodes each one containing a processing unit, one or more sensors, a power unit, and a radio for data communication. Nodes are power constrained, because they run on batteries, that in many cases cannot be easily replaced. This paper presents the application of Dynamic Power Management with Mode Switching (DPM-MS) technique into Intelligent Sensor Modules (ISMs). Preliminary results showed the potential for improving the battery lifetime by taking advantage of the battery recovery effect when a node transitions to a sleeping state, and mostly when transitions are scheduled after packet transmissions. Performance results show that DPM-MS can provide real battery power recovery without compromising the timeliness of the applications running on the sensor network.

Bounded-distance multi-coverage backbones in wireless sensor networks

Topology control can improve the performance of Wireless Sensor Network (WSN) by allowing only a subset of nodes to be active at any time with guaranteed network coverage. We present the first centralized and distributed solutions for computing Bounded-Distance Multi-Coverage Backbones in WSNs. The solutions are based on the (k, r)-CDS problem from graph theory for computing backbones in which any regular node is covered by at least k backbone members within distance r, offering a variable degree of redundancy and reliability. Applications that require reliable data gathering with bounded-delays are the intended targets for such structures. Given that the centralized solution is unsuitable for WSNs, because of the incurred control overhead, it is used as a lower bound for evaluating the performance of the distributed solution. The distributed solution is source-based in the sense that usually the base-station (or sink) is the focus of attention in a WSN. The two approaches are evaluated through extensive simulations, and it is shown that even though the distributed solution builds larger backbones, it does not incur on much control overhead.

Acquisition and transmission data monitoring system applied to energy substation

The development, which took place in the digital electronics and telecommunications fields, among others, in addition to the necessity of a more effective control upon the electrical systems, more specifically, the energy substations, turned the development of supervisory control tools the main study object of many researchers. A project was presented to the Electrical Sector Technological Development and Research Program, aiming the development of a Substations Automation System. This on going project, supported by CEEE - Electrical Energy State Company, Rio Grande do Sul State, Brazil, exists since 2002. We present what has already been concluded in terms of data acquisition and transmission. Future works are going to present the Person-Machine Interface development, security procedures implementation as well as the actuation system and the realized tests including the whole system.