Decoupled Reference Governors for Multi-Input Multi-Output Systems

Liu, Yudan; Osorio, Joycer; Ossareh, lIanaid

doi:10.1109/cdc.2018.8619592

Cited by 11 publications

(13 citation statements)

References 49 publications

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“…NIST is developing an Adaptive Reference Governor (RG) scheme to assist in distributed control of constrained DERs. The Reference Governor [85][86][87][88][89][90][91][92][93][94][95] is a control strategy that predicts the evolution of the system state to enforce pre-specified constraints on the inputs, states or the outputs of a system. The Reference Governor does this by modifying the reference to a pre-stabilized, closed-loop control system such that the system states and inputs belong to the Maximal Admissible Set (MAS).…”

Section: Composition and Constraint Enforcementmentioning

confidence: 99%

Validation capabilities of the NIST campus power system to evaluate distributed control of grid-edge distributed energy resources

Anand¹,

Ehsan²,

Freiheit³

et al. 2021

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This report outlines National Institute of Standards and Technology (NIST)'s validation tools developed to help address the smart grid's emergent needs and complement research and standards coordination efforts. Rapid advances have enabled an opportunity for the grid to autonomously and simultaneously control generation, balance load, and regulate power quality. The grid will need this coordinated control to regulate power and voltage in realtime, to meet fast-changing power demands, especially with increasing distributed energy resources. To do this, the grid needs measurements from across the distribution network to accurately assess demand and prevent negative impact of variable grid-edge generation. Additionally, such a coordinated control system depends on a new operating paradigm with two-way information flows between domains of the grid. The different operational domains and the information flows between them are outlined in the NIST Framework and Roadmap of Smart Grid Interoperability Standards, Release 4.0 [1].The coordinated control mentioned above requires improved observability of the state of distributed resources and depends on marshalling increasingly decentralized control systems. To implement such a system and meet system level performance objectives, distribution system operators (DSOs) need an understanding of the bandwidth, security and integrity considerations while also ensuring reliability at the grid's edges. Industry is also concerned with how to represent uncertainties like latency and cyber-vulnerabilities in a complex cyber-physical system. Additionally, industry is concerned that standards are focused more on devices than on coordinated control systems.Thus, this report presents an overview of a data acquistion and control system designed by NIST as a validation tool and deployed on the NIST campus in Gaithersburg, MD. This system is comprised of interoperating computing resources, cybersecurity infrastructure, communication links and data interfaces to both take measurements and to transmit control inputs to commonly used distribution system control components. An important proof of concept included in the aforementioned validation system is a data pipeline optimized to stream data from a 5 MW PV inverter and multiple sources of synchronized phasor data. This pipeline utilizes industry standard information modeling and communication standards with the intent of being compatible with industry standard testing equipment. This capability demonstrates how DSOs could test current standards against functionality -such as phasor based control of distribution circuits.

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Section: Composition and Constraint Enforcementmentioning

confidence: 99%

Validation capabilities of the NIST campus power system to evaluate distributed control of grid-edge distributed energy resources

Anand¹,

Ehsan²,

Freiheit³

et al. 2021

View full text Add to dashboard Cite

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“…x(t) tion, which combines the Decoupled Reference Governor scheme [15] and PRG theory. Detailed information will be explained in Section 7.…”

Section: Referencementioning

confidence: 99%

“…An explicit algorithm, similar to the one in SRG [15], can be developed to solve this LP efficiently (see Section 5 for details). The PRG solves the above LP at every time step to compute κ, updates v N (t) using ( 14), and applies the first element of v N (t) to the system G. Note that the variables in the LP in (15) at time step t are v N (t−1), r N (t), and x(t).…”

Section: Preview Reference Governors (Prg) For Singleinput Systemsmentioning

confidence: 99%

“…However, we do not use generic LP solvers to solve them. Instead, we use the Algorithm presented in [15] to solve the LPs in SRG and Algorithm 1 below to solve the LPs in PRG. The LPs in Multi-N PRG can be solved using a similar algorithm.…”

Section: Computational Considerationsmentioning

confidence: 99%

“…Obviously, v N (0)'s given by standard PRG and robust PRG (discussed in previous paragraph) will be equal to r N (0) (i.e., v N (0) = (0,0.5)) since r N (0) is in both MASs (red and green regions in Figure 8). In the next time step (t = 1), if κ = 1, v N (1) given by standard PRG (i.e., (15)) is a convex combination between the delay version of v N (0) (i.e., (0.5,0.5)) and r N (1). For robust PRG, v N (1) is a convex combination between Āv N (0) = (0.45,0.45) and r N (1).…”

Section: Prg For Systems With Uncertain Preview Informationmentioning

confidence: 99%

See 2 more Smart Citations

Preview Reference Governors: A Constraint Management Technique for Systems With Preview Information

Liu

Ossareh

2021

Preprint

Self Cite

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This paper presents a constraint management strategy based on Scalar Reference Governors (SRG) to enforce output, state, and control constraints while taking into account the preview information of the reference and/or disturbances signals.The strategy, referred to as the Preview Reference Governor (PRG), can outperform SRG while maintaining the highlyattractive computational benefits of SRG. However, as it is shown, the performance of PRG may suffer if large preview horizons are used. An extension of PRG, referred to as Multi-horizon PRG, is proposed to remedy this issue. Quantitative comparisons between SRG, PRG, and Multi-horizon PRG on a one-link robot arm example are presented to illustrate their performance and computation time. Furthermore, extensions of PRG are presented to handle systems with disturbance preview and multi-input systems. The robustness of PRG to parametric uncertainties and inaccurate preview information is also explored.

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Decoupled reference governors: a constraint management technique for MIMO systems

Liu

Osorio²,

Ossareh

2021

International Journal of Control

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Decoupled Reference Governors for Multi-Input Multi-Output Systems

Cited by 11 publications

References 49 publications

Validation capabilities of the NIST campus power system to evaluate distributed control of grid-edge distributed energy resources

Validation capabilities of the NIST campus power system to evaluate distributed control of grid-edge distributed energy resources

Preview Reference Governors: A Constraint Management Technique for Systems With Preview Information

Decoupled reference governors: a constraint management technique for MIMO systems

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