Firm and Non-Firm Wind Generation Planning Considering Distribution Network Sterilization

Džamarija, Mario; Keane, Andrew

doi:10.1109/tsg.2013.2263676

Cited by 7 publications

(4 citation statements)

References 22 publications

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“…Nonlinear programming (NLP) is used for this class of optimization problem, since the ac power flow equations are nonlinear. The MPOPF planning model, presented in this section, enhances the planning model in [9] and [10], by including the DCC, DVC, that operate independent of each other, a number of demand-generation scenarios and on-load tap-changing (OLTC) transformers.…”

Section: Planning Methodologymentioning

confidence: 99%

“…Therefore, the thermal loading of a branch br, i.e., line or transformer, is constrained by its ampacity Re 2 i br,m + Im 2 i br,m ≤ i max br 2 , ∀br ∈ BR. (9) Although the generator's DCC is autonomous, i.e., it is independent of the other generators' export paths, or their active power dispatch, the following should be noted: the thermal loading measurements, fed back to the DCC, are not strictly local, since they are taken along the generator's export path.…”

Section: E Decentralized Active Power Curtailment Control and Thermamentioning

confidence: 99%

“…Linear programming is often preferred, over other techniques, due to its robustness and simple implementation, and it has also been applied for DG siting and sizing [6]. AC optimal power flow (OPF) is used for solving a wide range of power system optimization problems, including the optimal DG allocation [7], [9], [10], [15], [16].…”

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confidence: 99%

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Autonomous Curtailment Control in Distributed Generation Planning

Džamarija

Keane

2016

IEEE Trans. Smart Grid

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While enabling prominent growth of renewablebased distributed generation (DG) and matching energy harvesting, nonfirm connection policy requires accompanying active and reactive power dispatch control. Centralized control often implies comprehensive communication infrastructure and notable capital investment. Hence, DG planning models tailored for decentralized management of thermal and voltage constraints are found wanting. This paper presents a DG planning methodology, which successfully incorporates a new decentralized active power curtailment control and also includes decentralized voltage control. It optimizes autonomous control settings for each generator individually, such that the net energy export from the distribution to transmission level, per unit of installed capacity, is maximized. Comparative time series analysis validates the methodology.Index Terms-Distributed generation (DG), network planning, optimal power flow (OPF), power curtailment control.

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Section: Planning Methodologymentioning

confidence: 99%

Section: E Decentralized Active Power Curtailment Control and Thermamentioning

confidence: 99%

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Autonomous Curtailment Control in Distributed Generation Planning

Džamarija

Keane

2016

IEEE Trans. Smart Grid

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“…DGs, controllable loads, and on load tap changers (OLTCsΨ, are considered in the operation stage. Dzamarija and Keane [15] present the mathematical formulations of reactive power capabilities for the firm and non-firm wind generations, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%