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| Content Provider | ACM Digital Library |
|---|---|
| Author | Shenoy, Prashant Sitaraman, Ramesh Dalvi, Bhavana Lee, Stephen Mishra, Aditya Irwin, David Zhu, Ting |
| Abstract | Electricity generation combined with its transmission and distribution form the majority of an electric utility's recurring operating costs. These costs are determined, not only by the aggregate energy generated, but also by the maximum instantaneous peak power demand required over time. Prior work proposes using energy storage devices to reduce these costs by periodically releasing energy to lower the electric grid's peak demand. However, prior work generally considers only a single storage technology employed at a single level of the electric grid's hierarchy. In this paper, we examine the efficacy of employing different combinations of storage technologies at different levels of the grid's distribution hierarchy. We present an optimization framework for modeling the primary characteristics that dictate the lifetime cost of many prominent energy storage technologies. Our framework captures the important tradeoffs in placing different technologies at different levels of the distribution hierarchy with the goal of minimizing a utility's operating costs. We evaluate our framework using real smart meter data from 5000 customers of a local electric utility. We show that by employing hybrid storage technologies at multiple levels of the distribution hierarchy, utilities can reduce their daily operating costs due to distributing electricity by up to 12%. |
| Starting Page | 37 |
| Ending Page | 46 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450336093 |
| DOI | 10.1145/2768510.2768543 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-07-14 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Peak shaving Electricity Energy Battery Grid |
| Content Type | Text |
| Resource Type | Article |
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