Decentralized control of smart grid with fixed and moving loads

Khayyer, Pardis; Özgüner, Ü.

doi:10.1109/peci.2013.6506037

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…Moreover, mobile loads such as plug-in hybrid electric vehicles represent stochastic loads for the system. 2 In order to compensate the impacts of such transient resources and loads, storage units can be utilized in power systems. Battery banks, flywheels, superconductivity magnetic energy storages, and compressed air energy storages are the main types of short and long-term energy balancing systems used in power system design.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, the dynamics of a wind turbine is affected by the intermittent nature of such energy sources. Moreover, mobile loads such as plug‐in hybrid electric vehicles represent stochastic loads for the system 2 . In order to compensate the impacts of such transient resources and loads, storage units can be utilized in power systems.…”

Section: Introductionmentioning

confidence: 99%

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Optimal decentralized control of a wind turbine and diesel generator system

Shojaee

Azizi

2021

Optim Control Appl Methods

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This article presents a decentralized optimal controller design technique for the frequency and power control of a coupled wind turbine and diesel generator. The decentralized controller consists of two proportional‐integral (PI)‐lead controllers which are designed and optimized simultaneously using a quasi‐Newton based optimization technique, namely, Davidon–Fletcher–Powell algorithm. The optimal PI‐lead controllers are designed in such a way that there are no communication links between them. Simulation results show the superior performance of the proposed controller with a lower order structure compared to the benchmark decentralized linear‐quadratic Gaussian integral controllers of orders 4 and 11. It is also shown that the proposed controller demonstrates an effective performance in damping the disturbances from load and wind power, as well as a robust performance against the parameter changes of the power system.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal decentralized control of a wind turbine and diesel generator system

Shojaee

Azizi

2021

Optim Control Appl Methods

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“…[1], [2], [3], and references therein. The developed qc-MPC is suitable to the decentralized control of interconnected systems rationalized by its engagement with the global information in the design phase.…”

Section: Introductionmentioning

confidence: 99%

Application of quadratically-constrained model predictive control in power systems

Tran

Foo

Ling

et al. 2014

2014 13th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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Simulations for the quadratically-constrained model predictive control (qc-MPC) with power system linear models are studied in this work. In qc-MPC, the optimization is imposed with two additional constraints to achieve the closed-loop system stability and the recursive-feasibility simultaneously. Instead of engaging the traditional terminal constraint for MPC, both constraints in qc-MPC are imposed on the first control vector of the MPC control sequence. As a result, qc-MPC has the potential for further extension to the control of network centric power systems. The algorithm of qc-MPC has been developed in a previous paper. Here, simulation studies with small-signal linear models of three typical power systems are presented to demonstrate its efficacy. We also develop a computational strategy for the decentralized static state-feedback control using the same quadratic dissipativity constraint as of the qc-MPC. Only state constraints are considered in the state feedback design. A comparison is then provided in the simulation study of qc-MPC relatively to the constrained-state feedback control. 193We36.5

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“…The Kalman filters are designed for modeling of noise and interconnected system parameter variations. The main parameter variation is considered as the load imposed by moving PHEVs on the power grid (Tuffner, Kintner-Meyer, 2011), (Kintner-Meyer, Nguyen, Jin, Balducci, Secrest, 2010), (Khayyer, Ozguner, 2013). The estimation technique is used in solving the problem of frequency control of a large-scale interconnected power system.…”

Section: Introductionmentioning

confidence: 99%