Fast and Reliable Primary Frequency Reserves From Refrigerators with Decentralized Stochastic Control

Due to increasing shares of renewable energy sources, more frequency reserves are required to maintain power system stability. In this paper, we present a decentralized control scheme that allows a large aggregation of refrigerators to provide Primary Frequency Control (PFC) reserves to the grid based on local frequency measurements and without communication. The control is based on stochastic switching of refrigerators depending on the frequency deviation. We develop methods to account for typical lockout constraints of compressors and increased power consumption during the startup phase. In addition, we propose a procedure to dynamically reset the thermostat temperature limits in order to provide reliable PFC reserves, as well as a corrective temperature feedback loop to build robustness to biased frequency deviations. Furthermore, we introduce an additional randomization layer in the controller to account for thermostat resolution limitations, and finally, we modify the control design to account for refrigerator door openings. Extensive simulations with actual frequency signal data and with different aggregation sizes, load characteristics, and control parameters, demonstrate that the proposed controller outperforms a relevant state-of-the-art controller.Comment: 44 pages, 17 figures, 9 Tables, submitted to IEEE Transactions on Power System

An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †

The design and implementation of management policies for plug-in electric vehicles (PEVs) need to be supported by a holistic understanding of the functional processes, their complex interactions, and their response to various changes. Models developed to represent different functional processes and systems are seen as useful tools to support the related studies for different stakeholders in a tangible way. This paper presents an overview of modeling approaches applied to support aggregation-based management and integration of PEVs from the perspective of fleet operators and grid operators, respectively. We start by explaining a structured modeling approach, i.e., a flexible combination of process models and system models, applied to different management and integration studies. A state-of-the-art overview of modeling approaches applied to represent several key processes, such as charging management, and key systems, such as the PEV fleet, is then presented, along with a detailed description of different approaches. Finally, we discuss several considerations that need to be well understood during the modeling process in order to assist modelers and model users in the appropriate decisions of using existing, or developing their own, solutions for further applications

Compliance of Distribution System Reactive Flows with Transmission System Requirements

Transmission system operators (TSOs) often set requirements to distribution system operators (DSOs) regarding the exchange of reactive power on the interface between the two parts of the system they operate, typically High Voltage and Medium Voltage. The presence of increasing amounts of Distributed Energy Resources (DERs) at the distribution networks complicates the problem, but provides control opportunities in order to keep the exchange within the prescribed limits. Typical DER control methods, such as constant cosϕ or Q/V functions, cannot adequately address these limits, while power electronics interfaced DERs provide to DSOs reactive power control capabilities for complying more effectively with TSO requirements. This paper proposes an optimisation method to provide power set-points to DERs in order to control the hourly reactive power exchanges with the transmission network. The method is tested via simulations using real data from the distribution substation at the Sundom Smart Grid, in Finland, using the operating guidelines imposed by the Finnish TSO. Results show the advantages of the proposed method compared to traditional methods for reactive power compensation from DERs. The application of more advanced Model Predictive Control techniques is further explored.©2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Part of this work was carried out in the SolarX research project with financial support provided by Business Finland, 2019–2021 (grant No. 6844/31/2018).fi=vertaisarvioitu|en=peerReviewed