4.7 Article

Distributed Frequency Control via Randomized Response of Electric Vehicles in Power Grid

期刊

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 7, 期 1, 页码 312-324

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2015.2494504

关键词

Electric vehicle; renewable energy sources; distributed frequency control; randomized algorithm; optimization

向作者/读者索取更多资源

In this paper, we propose a new distributed frequency control scheme for electric vehicles (EVs) to help restore the power grid frequency upon a contingency of supply-demand imbalance. Under our scheme, each EV independently monitors the grid frequency at discrete times and responds by switching among its charging, idle, and discharging operational modes according to a simple threshold-based switching algorithm. To recover the grid frequency smoothly and prevent an undesired frequency overshoot/undershoot due to simultaneous response of EVs, we design the inter-response times of any EV to follow an exponentially distributed random variable with a certain mean value at each operational mode. To draw insights into the performance of our scheme, we characterize its impacts on the grid frequency in various aspects, including the mean and variance of the resulting grid frequency over time, the mean frequency recovery time, the average number of EV switching their modes, and the probability of frequency overshoot/undershoot. Accordingly, we formulate an optimization problem for the grid operator to minimize the expected cost of implementing our frequency control scheme by designing EVs' response rates subject to their requested incentive prices and the given grid performance guarantees. Finally, we validate our analysis via simulations on the IEEE 9-Bus test system and the Ireland power system, where it is observed that our frequency control scheme can be used as a reliable and cost-efficient alternative for the conventional primary reserve service.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据