Distribution Network Operation Under Uncertainty Using Information Gap Decision Theory

O'Connell, Alison; Soroudi, Alireza; Keane, Andrew

doi:10.1109/tsg.2016.2601120

Cited by 25 publications

(19 citation statements)

References 27 publications

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“…2 and [2]. The merit function φ(Υ) is provided in (4). ζ ≥ 1 is a penalty parameter that weights constraint satisfaction against objective minimization.…”

Section: B Solution Methodologymentioning

confidence: 99%

“…Moreover, during the next day, the operator is able to further reduce the system cost by readjusting the schedule of the DCDs based on the uncertainties already revealed. The main focus of [4] was on presenting a comprehensive framework for uncertainty handling in an unbalanced three-phase system based on information gap decision theory. A day-ahead scheduling was solved for DCAs.…”

Section: A Literature Reviewmentioning

confidence: 99%

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Strategic Scheduling of Discrete Control Devices in Active Distribution Systems

Nouri

Soroudi

Keane

2020

IEEE Trans. Power Delivery

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The frequent actuation of discrete control devices (DCDs), e.g., on-load tap changers, drastically reduces their lifetime. This, in turn, imposes a huge replacement cost. Simultaneous scheduling of these DCDs and continuous control devices, e.g., distributed energy resources, is imperative for reducing the operating cost. This also increases the lifetime of DCDs and helps to avoid the sub-optimal/infeasible solutions. Considering the high cost of discrete control actions (DCAs), they may never be justified against the other options in a short scheduling horizon (SH). With a longer SH, their benefits over a long period justify DCAs. However, a shorter SH helps to hedge against the risk impelled by uncertainties. Here, the system future is modeled as a set of multi-period scenarios. The operator exploits a long SH, but solely applies the decisions made for the first period and waits for updated data to make the next decisions. This enables cost reduction by strategically applying DCAs prior to the time that they are inevitable, while avoiding them when unneeded. The proposed branch-and-cut-based solution methodology accurately deals with DCAs while applying some expediting heuristics. During the branching process, a globally convergent trust region algorithm solves the integer relaxed problems. BC Branch and cut CB Capacitor bank DCA Discrete controllable action DCC Discrete control cost DCD Discrete controllable device DER Distributed energy resource DSP Distribution scheduling problem LP Linear programming MILP Mixed integer linear programming MINLP Mixed integer nonlinear programming NLP Nonlinear programming OC Operation cost OLTC On load tap changer PDF Probability density function RES Renewable energy sources RHC Receding horizon control SH Scheduling horizon SOCP Second-order cone programming SVR Static voltage regulator SA Solution approaches A. Nouri (alireza.nouri@ucd.ie), A. Soroudi (alireza.soroudi@ucd.ie) and A. Keane (andrew.keane@ucd.ie) are with the

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“…2 and [2]. The merit function φ(Υ) is provided in (4). ζ ≥ 1 is a penalty parameter that weights constraint satisfaction against objective minimization.…”

Section: B Solution Methodologymentioning

confidence: 99%

Section: A Literature Reviewmentioning

confidence: 99%

Strategic Scheduling of Discrete Control Devices in Active Distribution Systems

Nouri

Soroudi

Keane

2020

IEEE Trans. Power Delivery

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“…It is clear that IGDT is an effective risk management tool with high robustness and low computational burden and is effective with limited data. IGDT does not need information about detailed uncertainties sets, membership functions, or probability distributions functions …”

Section: Robust Igdt‐based Model Descriptionmentioning

confidence: 99%

“…IGDT does not need information about detailed uncertainties sets, membership functions, or probability distributions functions. 46 Suppose a general form of an optimization problem as follows:…”

Section: Robust Igdt-based Model Descriptionmentioning

confidence: 99%

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Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Samimi

Rezaei

2019

Int Trans Electr Energ Syst

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Summary Distributed energy resources (DERs) are main components for smart distribution networks (SDNs). Generally, energy and reactive power dispatch scheduling problems are managed separately in SDNs. In this paper, a robust simultaneous active/reactive scheduling framework is presented for SDNs. In order to handle the uncertainties of wind power generation, upstream grid prices, and load demand forecasting in a robust framework, information gap decision theory (IGDT) technique is proposed. The proposed robust model considers the minimization of the energy and reactive power cost, carbon taxes of CO2 emission of all distributed resources along with the cost of implementation of demand response program. Numerical results based on a 22‐bus distribution system validate the effectiveness of the proposed method from determining boundaries of uncertainties viewpoint. The obtained results verify that through the proposed IGDT‐based model, the distribution system operator (DSO) can effectively schedule the all DERs while considering the possibility of problem with a specific uncertainty budget.

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Risk Averse Energy Management for Grid Connected Microgrid Using Information Gap Decision Theory

Rawat¹,

Niazi²

2019

Intelligent Computing Techniques for Smart Energy Systems

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Distribution Network Operation Under Uncertainty Using Information Gap Decision Theory

Cited by 25 publications

References 27 publications

Strategic Scheduling of Discrete Control Devices in Active Distribution Systems

Strategic Scheduling of Discrete Control Devices in Active Distribution Systems

Robust optimal energy and reactive power management in smart distribution networks: An info‐gap multi‐objective approach

Risk Averse Energy Management for Grid Connected Microgrid Using Information Gap Decision Theory

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