Conference Paper

Wide area monitoring in power systems using cellular neural networks

Real-Time Power & Intell. Syst. Lab., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
DOI: 10.1109/CIASG.2011.5953343 Conference: Computational Intelligence Applications In Smart Grid (CIASG), 2011 IEEE Symposium on
Source: IEEE Xplore

ABSTRACT The demand of power and the size and complexity of the power system is increasing. Wide area monitoring and control is an integral part in transitioning from the traditional power system to a Smart Grid. However, wide area monitoring becomes challenging as the size of the electric power grid, and consequently the number of components to be monitored, grows. Wide area monitor (WAM) designed using feed-forward and feedback neural network architectures do not scale up to handle the growing complexity of the Smart Grid. In this paper, cellular neural network (CNN) is presented as a way to provide scalability in the development of a WAM for Smart Grid. The CNN based WAM is compared with multilayer perceptrons (MLP) based WAM on two different power systems. The results show that the CNN has better or comparable performance with, and scales up much better than, MLP.

1 Follower
 · 
122 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: It is envisioned that home networks will shift from current machine-to-human communications to the machine-to-machine paradigm with the rapid penetration of embedded devices in home surroundings. In this article, we first identify the fundamental challenges in home M2M networks. Then we present the architecture of home M2M networks decomposed into three subareas depending on the radio service ranges and potential applications. Finally, we focus on QoS management in home M2M networks, considering the increasing number of multimedia devices and growing visual requirements in a home area. Three standards for multimedia sharing and their QoS architectures are outlined. Cross-layer joint admission and rate control design is reported for QoS-aware multimedia sharing. This proposed strategy is aware of the QoS requirements and resilience of multimedia services. Illustrative results indicate that the joint design is able to intelligently allocate radio bandwidth based on QoS demands in resource-constrained home M2M networks.
    IEEE Communications Magazine 04/2011; 49:44-52. DOI:10.1109/MCOM.2011.5741145 · 4.46 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: An efficient dependable smart power grid relies on the secure real-time data collection and transmission service provided by a monitoring system. In such a system, the measuring units, such as phasor measurement units (PMUs) and smart meters (SMs), are critical. These measuring equipments function as sensors in the smart grid. Data exchanges between these sensors and the central controller are protected by various security protocols. These protocols usually contain computationally intensive cryptographic algorithms that cause heavy energy overhead to the sensor nodes. Since PMUs and SMs are mostly energy-constrained, the problem of how to ensure the secure communication with minimum energy cost becomes a critical issue for the functionality of the whole smart grid. In this article, we focus on the low power secure communication of the PMUs and SMs. We take two wireless sensor platforms as examples to experimentally investigate the approaches and principles of reconciling the two conflicting system requirements¿communication security and low energy consumptions. The proposed methods are general ones and applicable to other energyconstrained yet security sensitive systems.
    IEEE Communications Magazine 05/2012; 50(5):142-149. DOI:10.1109/MCOM.2012.6194395 · 4.46 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A fundamental component of a smart grid is transmission and distribution system monitoring and control. Accurate load, power flow and voltage estimation is required for real time generation capacity dispatching and congestion management in wide area power systems or in networks with distributed generation. In electrical networks, bus voltage levels, load, generation and branch power flows are interdependent, and ones can be determined if others are known. This is a problem that can be solved using the approximation capabilities of artificial neural networks (ANNs). This paper explores the possibility of replacing the classic estimation algorithms in voltage and power flow estimation with ANN approaches, using available data from the Romanian power system.
    2014 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM); 05/2014

Preview

Download
16 Downloads
Available from