虚拟发电厂
调度(生产过程)
计算机科学
电力系统
经济调度
时间范围
数学优化
风力发电
软件部署
可再生能源
分布式发电
需求响应
电力系统仿真
分布式计算
工程类
功率(物理)
电
物理
电气工程
操作系统
量子力学
数学
作者
James Naughton,Wenhua Han,Michael Cantoni,Pierluigi Mancarella
出处
期刊:IEEE Transactions on Power Systems
[Institute of Electrical and Electronics Engineers]
日期:2021-09-01
卷期号:36 (5): 3960-3972
被引量:57
标识
DOI:10.1109/tpwrs.2021.3062582
摘要
Market and network integration of distributed energy resources can be facilitated by their coordination within a virtual power plant (VPP). However, VPP operation subject to network limits and different market and physical uncertainties is a challenging task. This paper introduces a framework that co-optimizes the VPP provision of multiple market (e.g., energy, reserve), system (e.g., fast frequency response, inertia, upstream reactive power), and local network (e.g., voltage support) services with the aim of maximizing its revenue. To ensure problem tractability, while accommodating the uncertain nature of market prices, local demand, and renewable output and while operating within local network constraints, the framework is broken down into three sequentially coordinated optimization problems. Specifically, a scenario-based robust optimization for day-ahead resource scheduling, with linearized power flows, and two receding horizon optimizations for close-to-real-time dispatch, with a more accurate second-order cone relaxation of the power flows. The results from a real Australian case study demonstrate how the framework enables effective deployment of VPP flexibility to maximize its multi-service value stack, within an uncertain operating environment, and within technical limits.
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