Two-Timescale Multi-Objective Coordinated Volt/Var Optimization for Active Distribution Networks

Jin, Dan; Chiang, Hsiao‐Dong; Li, Peng

doi:10.1109/tpwrs.2019.2914923

Cited by 39 publications

(20 citation statements)

References 32 publications

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“…With the increasing number of RESs integrated into active distribution networks, the day-ahead VVC problem is converted from a deterministic optimization problem [8,9] to an uncertain one [10]. To address the uncertainty outputs of RESs, many methods [11][12][13]15,[16][17][18][19][20] have been proposed recently. They can be roughly categorized into two types: robust optimization [11,12] methods and stochastic optimization methods [13,[15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…The stochastic optimization methods [13,15,16] based on scenario generation and reduction technology are easier to find a feasible solution and be more practical. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…In Ref. [16], the Latin hypercube sampling method was applied to generate scenarios, and the affinity propagation (AP) clustering scheme was applied to identify the key scenarios for the scenario reduction.…”

Section: Introductionmentioning

confidence: 99%

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A Day-Ahead Chance Constrained Volt/Var Control Scheme With Renewable Energy Sources by Novel Scenario Generation Method in Active Distribution Networks

et al. 2021

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With the integration of huge renewable energy sources (RESs) into active distribution networks, how to address the uncertainty outputs of RESs for the day-ahead volt/var control (VVC) is a significant challenge. This paper presents a chance constrained mixed integer second order cone model to handle the nodal power uncertainties and nonlinear branch flow equations. A direct and fast scenario generation method is proposed by employing the group division method and the seven-step probability distribution model of RESs outputs. An efficient and accurate solution method which only uses few larger probability level scenarios instead of all reserved scenarios is also proposed. Numerical simulations on the IEEE 69 standard system show the superiority of the proposed algorithm over traditional Monte Carlo sampling (MCS)-based methods. , sh j u Continuous state variable on bus j at hour h of scenario s . Abbreviation RESs Renewable energy sources. VVC Volt/var control. MCS Monte Carlo sampling. OLTC On-load tap changer. MINLP Mixed integer nonlinear programming. CCP Chance constrained programming. SSC Switchable shunt capacitors. PV Photovoltaic. WTG Wind turbine generator.

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Section: Introductionmentioning

confidence: 99%

“…The stochastic optimization methods [13,15,16] based on scenario generation and reduction technology are easier to find a feasible solution and be more practical. Ref.…”

Section: Introductionmentioning

confidence: 99%

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A Day-Ahead Chance Constrained Volt/Var Control Scheme With Renewable Energy Sources by Novel Scenario Generation Method in Active Distribution Networks

et al. 2021

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“…A stochastic optimization [2] allows us to encompass the minimization of risks of failure at reasonable actuation prices. In the literature of distribution grid control algorithms, many papers which achieve volt/var stochastic optimization use scenarios or robust optimization in order to take uncertainties into account [3][4][5]. These papers do not require the probability density functions of the input variables; however, they provide little information about the stochastic properties of the voltages and powers inside the grid [6].…”

Section: Introductionmentioning

confidence: 99%

“…The paper [3] deals with the stochastic nature of the input variables using two time scales, the slow one encompassing capacitor banks and on load tap changer (OLTC) control, and the faster one dealing with reactive power reserves (DG control). However, the objectives and methods are quite different.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids

et al. 2019

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This paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.

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Integrated Energy System: A Low‐Carbon Future Enabler

Zhao¹,

Gu²,

Cao³

et al. 2022

The 4Ds of Energy Transition

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Two-Timescale Multi-Objective Coordinated Volt/Var Optimization for Active Distribution Networks

Cited by 39 publications

References 32 publications

A Day-Ahead Chance Constrained Volt/Var Control Scheme With Renewable Energy Sources by Novel Scenario Generation Method in Active Distribution Networks

A Day-Ahead Chance Constrained Volt/Var Control Scheme With Renewable Energy Sources by Novel Scenario Generation Method in Active Distribution Networks

Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids

Integrated Energy System: A Low‐Carbon Future Enabler

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