Data Privacy for the Grid: Toward a Data Privacy Standard for Inverter-Based and Distributed Energy Resources

被引：1

作者：

Currie, Robert ^{[1
]}

Peisert, Sean ^{[2
]}

Scaglione, Anna ^{[3
]}

Shumavon, Aram ^{[1
]}

Ravi, Nikhil ^{[3
]}

机构：

[1] Kevala Inc, San Francisco, CA 94133 USA

[2] Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA

[3] Cornell Univ, New York, NY 10044 USA

来源：

IEEE POWER & ENERGY MAGAZINE | 2023年 / 21卷 / 05期

关键词：

Data privacy; Contingency management; Planning; Distributed power generation; Behavioral sciences; Asset management; Reliability; Power distribution control; Power distribution planning; Power grids;

D O I：

10.1109/MPE.2023.3288595

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The traditional approach to planning the distribution grid has focused on reliability in the context of gradual and reasonably predictable load growth. Forecasts of load growth, combined with asset management practices, were used by system planners to identify upgrades to the system to maintain or improve reliability. The decisions, typically based within load flow analysis tools, included considerations about contingency scenarios and corporate forecasts (i.e., top-down predictions at a summary level of what would happen in a particular area that could impact load growth and behavior). Today, this traditional approach no longer fits all purposes.

引用

页码：48 / 57

页数：10