Experimental implementation of frequency regulation services using commercial buildings

Fabietti, Luca; Gorecki, Tomasz T.; Qureshi, Faran A.; Bitlislioğlu, Altuğ; Lymperopoulos, Ioannis; Jones, Colin N.

doi:10.1109/ptc.2017.7980924

Cited by 14 publications

(22 citation statements)

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“…They consist of a regulation signal which allows a slower response than PFC, and which has a low energy content, meaning that its implementation should not result in a higher or lower energy consumption. Authors in [13] use electric heaters to participate in the SFC market in Switzerland with a twostage and multi-stage stochastic optimization. Authors in [6] investigated the potential of using the fan power to provide SFC and conclude that the fan power can be offered as reserve without loosing any comfort.…”

Section: B Literature Reviewmentioning

confidence: 99%

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Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

Bittel

Jones

Parisio

2018

2018 IEEE Conference on Decision and Control (CDC)

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Flexibility, particularly in terms of reserve services, is an essential requirement of power systems with high penetration of renewable electrical generation, which can reduce undesirable curtailment and enable higher integration of clean electrical power from renewable generation. Reserve services are related to additional active power sources available to the grid operator in the form of either increased generation or demand reduction. There is increasing evidence that commercial buildings can provide such reserves. In this paper we present a Model Predictive Control approach to optimization of flexibility afforded by commercial buildings for the provision of reserve services, in particular for Short-Term Operating Reserve from the National Grid in the United Kingdom. This reserve scheme is only required during selected hours of the day and involves turning down consumption for a few hours at the request of the National Grid with a slow response time (≤ 5 minutes). Commercial buildings equipped with heat pumps and backup gas boilers are considered. The proposed robust Model Predictive Control framework enables commercial buildings to provide Short-Term Operating Reserve without compromising the comfort of the occupants. Simulation are performed with a high-fidelity building model derived from Energy Plus through the software OpenBuild including real market data. Results show that a commercial building can provide Short-Term Operating Reserve and yield an economic benefit in a robust manner, without violating the indoor comfort of occupants. CONFIDENTIAL. Limited circulation. For review only.

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Section: B Literature Reviewmentioning

confidence: 99%

“…Once the STOR reserves have been obtained by solving Problem (33), and MPC controller is designed to enable the building to commit to those reserves in case of a STOR call from NG. The computed reserves Then the set of feasible inputs (32) is: (10), (12), (13), (14), (19),…”

Section: F Mpc Formulationmentioning

confidence: 99%

Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

Bittel

Jones

Parisio

2018

2018 IEEE Conference on Decision and Control (CDC)

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“…Due to the fact that the signal a is revealed as time progresses, both the Due to the infinite dimensionality of the decision space (policies), the problem as it is posed now cannot be solved. A scenario-based two-stage approximation scheme, similar to the one proposed in [23], is presented in Section 4.1.3 together with a specific form of the cost function J, and an explicit expression for the intraday policy, πP (a).…”

Section: Local Control and Measurementsmentioning

confidence: 99%

“…where a j are the previously observed AGC signal scenarios. [23] discusses the implications of the choice of Ξ in detail. The key idea is that, thanks to the statistical consistency of the AGC signal, if the controller is designed against past recorded instances of the AGC it should also be robust to future realizations.…”

Section: Uncertainty Set Constructionmentioning

confidence: 99%

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

et al. 2018

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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.

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“…The high-level MPC solves a centralised problem considering an averaged thermal model of the building, whilst the lowlevel MPC controllers minimise the local energy use based on the cooling duties sent by the high-level MPC. Some studies have demonstrated the potential benefits of MPC frameworks also for buildings-to-grid applications, in particular for frequency service provision of HVAC systems (e.g., [14], [15], [16]). There are a few studies showing promising results in reducing costs and peak power of centralised MPC schemes for residential buildings including heat pumps [17], [18], which however simply model the thermal building dynamics considering one aggregated thermal zone.…”

Section: Introductionmentioning

confidence: 99%

Distributed model predictive control for building energy systems in distribution grids

Krämer

Jambagi

Cheng

2017

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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Demand side management is widely acknowledged as an important source of flexibility and then an essential element to balance supply and demand more effectively. A fundamental challenge is to enable buildings to participate in demand side services without violating indoor comfort. In this paper, we present a distributed Model Predictive Control (MPC) approach to demand side management in buildings. The proposed MPC scheme encompasses heating/cooling systems, onsite generation and storage technologies, which are integrated into a unified management framework along with standard objectives (e.g., heating/cooling). The distributed algorithm, based on an active-set method, allows adjustments of multiple setpoints and enables the building to participate in balancing programs while minimising the energy use without violating the indoor comfort. Numerical results with real data from one university building show the promising performance and computational tractability of the proposed approach, which can enable practical implementations on building platforms. CONFIDENTIAL. Limited circulation. For review only.

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Experimental implementation of frequency regulation services using commercial buildings

Cited by 14 publications

References 0 publications

Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

Use of Model Predictive Control for Short-Term Operating Reserve Using Commercial Buildings in the United Kingdom Context

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

Distributed model predictive control for building energy systems in distribution grids

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