Multi-time scale coordination of complementary resources for the provision of ancillary services

Abstract

This paper presents a predictive control scheme for coordinating a set of heterogeneous and complementary resources at different time scales for the provision of ancillary services. In particular, we combine building thermodynamics (slow), and energy storage systems (fast resources) to augment the flexibility that can be provided to the grid compared to the flexibility that any of these resources can provide individually. A multi-level control scheme based on data-based robust optimization methods is developed that enables heterogeneous resources at different time scales (slow and fast) to provide fast regulation services, especially a secondary frequency control (SFC) service. A data-based predictor is developed to forecast the future regulation signal, and is used to improve the performance of the controller in real-time operation. The proposed control method is used to conduct experiments, for nine consecutive days, demonstrating the provision of SFC service fully complying to the Swiss regulations, using a controllable building HVAC system on the EPFL campus and a grid connected energy storage system. The experimental results show that optimally combining such slow and fast resources can significantly augment the flexibility that can be provided to the grid. Moreover, by providing SFC service, the building can reduce its operational costs by up to 46% on average while maintaining a high level of occupant comfort. To the best of author's knowledge this work is the first experimental demonstration of coordinating heterogeneous demand-response to provide SFC service.

Data-driven methods for building control — A review and promising future directions

“…In the so called demand response (DR) scenario, power consumption is adjusted -not necessarily reduced -in real-time with the objective of contributing to the grid power balance [Yoon et al, 2014]. Due to their significant energy consumption in conjunction with their inherent large inertia, it has been shown that buildings are suitable candidates for this task [Fabietti et al, 2018b, Luc et al, 2018, Pallonetto et al, 2019. DR programs are furthermore expected to grow significantly in the next years (see e.g.…”

“…This in turn triggers time-dependent or demand-dependent electricity tariffs and a general rise of energy prices. We believe that the most systematic method to deal with these factors while minimizing operating is MPC rather than the previous alternatives (see [Fabietti et al, 2018b] for an example of a realistic DR thermal control study).…”

A Comparative Analysis of Two Pricing Mechanisms, MCP and PAB, in the Chinese Frequency Regulation Market

“…[23] incorporates wind power based on energy storage and proposes a real-time cooperative scheme for the joint participation of wind storage in the energy and ancillary services markets, taking advantage of their complementary nature and significantly increasing the overall revenue. The literature [24] proposes a predictive control scheme for coordinating the provision of ancillary services from heterogeneous complementary resources at different time scales. Additionally, the literature [25], thinking from the user side, proposes a two-way smart charging algorithm for electric vehicles considering user preferences, peer-to-peer power trading, and the provision of ancillary services to the grid.…”

A machine learning-based control strategy for improved performance of HVAC systems in providing large capacity of frequency regulation service

“…Among various types of demand resources, heating, ventilation and air-conditioning (HVAC) systems in buildings are one of the most promising sources to provide frequency regulation service [8]. The reasons are that they account for a large proportion of electric energy consumption [9,10], and because of thermal inertia of buildings and HVAC systems, they have great power use flexibility [11].…”