Distributed MPC Strategies With Application to Power System Automatic Generation Control

Venkat, Aswin N.; Hiskens, Ian A.; Rawlings, James B.; Wright, Stephen J.

doi:10.1109/tcst.2008.919414

Cited by 699 publications

(472 citation statements)

References 25 publications

Supporting

Mentioning

460

Contrasting

Unclassified

Order By: Relevance

“…MPC is a model-based control strategy that uses a prediction of the system response to establish an appropriate control action [51,52]. This strategy makes an explicit use of a mathematical model of the process to generate a sequence of future actions within a finite prediction horizon.…”

Section: Model Predictive Control (Mpc)mentioning

confidence: 99%

“…Additionally, decentralized and distributed MPC configurations have become a growing research field. Distributed MPC has been studied for different applications including control and coordination of power systems [52,64] and urban traffic control [65]. Decentralized and distributed MPC strategies have also been studied in water related applications such as level control in tanks [66] and coordination in water supply networks [67,68,69].…”

Section: Model Predictive Control (Mpc)mentioning

confidence: 99%

See 1 more Smart Citation

Modeling and real-time control of urban drainage systems: A review

Garcia¹,

Barreiro-Gómez

Escobar³

et al. 2015

Advances in Water Resources

197

113

View full text Add to dashboard Cite

Urban drainage systems (UDS) may be considered large-scale systems given their large number of associated states and decision actions, making challenging their real-time control (RTC) design. Moreover, the complexity of the dynamics of the UDS makes necessary the development of strategies for the control design. This paper reviews and discusses several techniques and strategies commonly used for the control of UDS. Moreover, the models to describe, simulate, and control the transport of wastewater in UDS are also reviewed.

show abstract

Section: Model Predictive Control (Mpc)mentioning

confidence: 99%

Section: Model Predictive Control (Mpc)mentioning

confidence: 99%

Modeling and real-time control of urban drainage systems: A review

Garcia¹,

Barreiro-Gómez

Escobar³

et al. 2015

Advances in Water Resources

197

113

View full text Add to dashboard Cite

show abstract

“…In addition, recent works on the topic include as significant examples [2], [3], [4], [10], [13], [5], [7], [8]. While many applications can be considered, such as the control of power networks [6] or electrical vehicle charging control [9], this article concentrates its attention on the control of water delivery canals. Besides its socioeconomic impact, this problem raises interesting control problems that have been addressed by distributed predictive control [14], [15], [11], as well as with other approaches.…”

Section: A Motivation and Reviewmentioning

confidence: 99%

D-ADMM based distributed MPC with input-output models

Costa

Lemos

Mota

2014

2014 IEEE Conference on Control Applications (CCA)

View full text Add to dashboard Cite

Abstract-This article presents a distributed model predictive controller (MPC) based on linear models that use input/output plant data and D-ADMM optimization. The use of input/output models has the advantage of not requiring a Kalman filter to estimate the plant state. The D-ADMM algorithm solves the optimization problem associated to a cost function that is the sum of the control agents private costs, being a modification of the Alternating Direction of Multipliers (ADMM) algorithm that requires no central node and implies a significant reduction in the communication among adjacent nodes. The distributed MPC is obtained for the special case of a linear graph. An application to distributed control of a water delivery canal is presented to illustrate the algorithm.

show abstract

“…A distributed MPC framework for the LFC system has been proposed in [11]. In [12] and [13], the design and application of functional and robust multivariable MPC for the power system LFC have been performed.…”

Section: Introductionmentioning

confidence: 99%

Multivariable predictive control considering time delay for load-frequency control in multi-area power systems

Daniar

Shiroei

Aazami

2016

Archives of Control Sciences

View full text Add to dashboard Cite

In this paper, a multivariable model based predictive control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area interconnected power system. The proposed controller is designed to consider time delay, generation rate constraint and multivariable nature of the LFC system, simultaneously. A new formulation of the MPC is presented to compensate time delay. The generation rate constraint is considered by employing a constrained MPC and economic allocation of the generation is further guaranteed by an innovative modification in the predictive control objective function. The effectiveness of proposed scheme is verified through time-based simulations on the standard 39-bus test system and the responses are then compared with the proportional-integral controller. The evaluation of the results reveals that the proposed control scheme offers satisfactory performance with fast responses.

show abstract

Distributed MPC Strategies With Application to Power System Automatic Generation Control

Cited by 699 publications

References 25 publications

Modeling and real-time control of urban drainage systems: A review

Modeling and real-time control of urban drainage systems: A review

D-ADMM based distributed MPC with input-output models

Multivariable predictive control considering time delay for load-frequency control in multi-area power systems

Contact Info

Product

Resources

About