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Proceedings Paper

Capacity and reliability analyses with applications to power quality
Author(s): Mohammad Azam; Fang Tu; Yuri Shlapak; Thiagalingam Kirubarajan; Krishna R. Pattipati; Rajaiah Karanam
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Paper Abstract

The deregulation of energy markets, the ongoing advances in communication networks, the proliferation of intelligent metering and protective power devices, and the standardization of software/hardware interfaces are creating a dramatic shift in the way facilities acquire and utilize information about their power usage. The currently available power management systems gather a vast amount of information in the form of power usage, voltages, currents, and their time-dependent waveforms from a variety of devices (for example, circuit breakers, transformers, energy and power quality meters, protective relays, programmable logic controllers, motor control centers). What is lacking is an information processing and decision support infrastructure to harness this voluminous information into usable operational and management knowledge to handle the health of their equipment and power quality, minimize downtime and outages, and to optimize operations to improve productivity. This paper considers the problem of evaluating the capacity and reliability analyses of power systems with very high availability requirements (e.g., systems providing energy to data centers and communication networks with desired availability of up to 0.9999999). The real-time capacity and margin analysis helps operators to plan for additional loads and to schedule repair/replacement activities. The reliability analysis, based on computationally efficient sum of disjoint products, enables analysts to decide the optimum levels of redundancy, aids operators in prioritizing the maintenance options for a given budget and monitoring the system for capacity margin. The resulting analytical and software tool is demonstrated on a sample data center.

Paper Details

Date Published: 20 July 2001
PDF: 12 pages
Proc. SPIE 4389, Component and Systems Diagnostics, Prognosis, and Health Management, (20 July 2001); doi: 10.1117/12.434255
Show Author Affiliations
Mohammad Azam, Univ. of Connecticut (United States)
Fang Tu, Univ. of Connecticut (United States)
Yuri Shlapak, Univ. of Connecticut (United States)
Thiagalingam Kirubarajan, Univ. of Connecticut (Canada)
Krishna R. Pattipati, Univ. of Connecticut (United States)
Rajaiah Karanam, General Electric Co. (United States)

Published in SPIE Proceedings Vol. 4389:
Component and Systems Diagnostics, Prognosis, and Health Management
Peter K. Willett; Thiagalingam Kirubarajan, Editor(s)

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