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Proceedings Paper

An operational power management method for the grid containing renewable power systems utilizing short-term weather and load forecasting data
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Paper Abstract

This paper addresses the problems associated with power management of the grid containing renewable power systems and proposes a method for enhancing its operational power management. Since renewable energy provides uncertain and uncontrollable energy resources, the renewable power systems can only generate irregular power. This power irregularity creates problems affecting the grid power management process and influencing the parallel operations of conventional power plants on the grid. To demonstrate this power management method for this type of grid, weatherdependent wind and photovoltaic power systems are chosen an example. This study also deals with other uncertain quantities which are system loads. In this example, the management method is based on adapting short-term weather and load forecasting data. The new load demand curve (NLDC) can be produced by merging the loads with the power generated from the renewable power systems. The NLDC is used for setting the loads for the baseload power plants and knowing when other plants are needed to increase or decrease their supplies to the grid. This will decrease the irregularity behavior effects of the renewable power system and at the same time will enhance the smoothing of the power management for the grid. The aim of this paper is to show the use of the weather and load forecasting data to achieve the optimum operational power management of the grid contains renewable power systems. An illustrative example of such a power system is presented and verified by simulation.

Paper Details

Date Published: 19 April 2013
PDF: 4 pages
Proc. SPIE 8692, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013, 86924O (19 April 2013); doi: 10.1117/12.2012127
Show Author Affiliations
Fadhil T. Aula, Univ. of Oklahoma (United States)
Samuel C. Lee, Univ. of Oklahoma (United States)


Published in SPIE Proceedings Vol. 8692:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2013
Jerome Peter Lynch; Chung-Bang Yun; Kon-Well Wang, Editor(s)

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