Effectiveness of updating the parameters of the Volt-VAR control depending on the PV penetration rate and weather conditions

Takasawa, Yuta; Akagi, Satoru; Yoshizawa, Shinya; Ishii, Hideo; Hayashi, Yasuhiro

doi:10.1109/isgt-asia.2017.8378328

Cited by 16 publications

(19 citation statements)

References 13 publications

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“…Fig. 5 shows a generic VVC that provides reactive power (Qs,i) according to the voltage at the point of common coupling (V(t)) as detailed in (1) [22], [26], [33], [48]. When the voltage exceeds an upper level, the PV system prevents further voltage increase by absorbing reactive power.…”

Section: B Smart Inverter Vvcmentioning

confidence: 99%

“…The VVC needed to support the voltage of the distribution system was obtained in [21] by changing the parameters of each function related to the VVC; however, no formal optimization was conducted, and multiple PV systems were evaluated using daily data and the same VVC. The effects of VVC parameters according to PV penetration and weather conditions have been evaluated [22], but the method of updating parameters had practical limitations. A method for preventing overvoltage in distribution test systems was experimentally validated in [23]; however, there were no details regarding the VVC settings for system performance improvement.…”

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confidence: 99%

“…3 Performance is only evaluated in default setting ( [16], [17], [20], [21], [24], [26], [27], [32], [33], [36]- [40] [18], [20]- [22], [25], [26], [29]- [31], [40], [42])…”

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Optimal Volt–Var Curve Setting of a Smart Inverter for Improving Its Performance in a Distribution System

2020

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We propose an algorithm to set the parameters of volt-var curves to improve the performance of distributed generation. Specifically, we optimally set the volt-var curves of the smart inverter for proper control of the distributed generation output. To improve the overall distribution system performance, we consider the minimization of voltage deviation, system loss, and peak of reactive power in an objective function, thereby providing optimal volt-var curve parameters. The proposed algorithm overcomes various limitations of existing studies. First, we use distribution system factors in a multiobjective optimization function to adjust volt-var curve parameters that deviate from the default settings. Second, we consider the service transformers that affect the system voltage according to the photovoltaic generation output in the test model during optimization. Third, we analyze the system improvement according to the number of parameters to be optimized. Fourth, we analyze the implementation of the optimized volt-var curve according to the practical periods when the smart inverter settings can be updated. Fifth, we evaluate different suitable voltvar curves for multiple photovoltaic generators grouped using clustering. Using the proposed algorithm, the distribution system operator can set the optimal volt-var curve according to the system conditions and requirements. We conducted simulations of the proposed method using OpenDSS, a quasistatic time-series simulation, on a test model reflecting the characteristics of a South Korean distribution system. The simulation results confirm that the overall system performance increases when the optimal volt-var curve settings obtained from the proposed algorithm are used. INDEX TERMS Distribution system, parameter optimization, smart inverter, volt-var curve. NOMENCLATURE i Bus index t Time (h) (year: 8760 h; spring: 2208 h; summer: 2208 h, fall: 2184 h; winter: 2160 h) vvnew Parameter (gene) for newly updated volt-var curve (Vvv2, Vvv3, Qvv1, Qvv4) vvcon Conventional volt-var curve parameter in Fig. 5 Pt(vv) System loss at time t according to volt-var curve parameter Vref Reference voltage, 22.9 kV, 1.00 pu ω Weight for system factor (voltage deviation, system loss, peak of reactive power) Vi,t Voltage of bus i at time t according volt-var curve parameter δVi,t(vv) − , () , voltage deviation index of bus i at time t Qi(vv) Reactive power output at smart inverter of bus i according to volt-var curve parameter Nconst Constraint condition ωc Penalty coefficient PFc Constraint weight E Disjoint subset of input pattern l Clusters index k Number of clusters Si Set of points belonging to cluster i µi Center of cluster i O• Objective function I. INTRODUCTION

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Section: B Smart Inverter Vvcmentioning

confidence: 99%

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Optimal Volt–Var Curve Setting of a Smart Inverter for Improving Its Performance in a Distribution System

2020

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“…By the word, proper settings of Volt‐Var and Volt‐Watt vary with distribution network configuration and with insolation and load conditions . In future, one can expect using communication functions of smart inverters to flexibly update settings in response to system conditions.…”

Section: Introductionmentioning

confidence: 99%

“…17 By the word, proper settings of Volt-Var and Volt-Watt vary with distribution network configuration and with insolation and load conditions. 21 In future, one can expect using communication functions of smart inverters to flexibly update settings in response to system conditions. For example, one can think of seasonal and daily updates, weather-and load-dependent updates, or individual settings depending on the installation location of smart inverters.…”

Section: Introductionmentioning

confidence: 99%

Determination method of Volt‐Var and Volt‐Watt curve for smart inverters applying optimization of active/reactive power allocation for each inverter

Yamane

Orihara

Iioka

et al. 2019

Electrical Engineering Japan

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In recent years, the smart inverter that is an advanced inverter has been investigated as a solution to voltage problem in the distribution network in which a lot of photovoltaic(PV)s are introduced Among multiple functions of the smart inverter, voltage‐reactive power control (Volt‐Var) and voltage‐active power control (Volt‐Watt) have been attracted attention because of their effectiveness. However, the problem is how to determine optimal curves setting of Volt‐Var and Volt‐Watt. In this paper, we suggest the determination method of optimal Volt‐Var and Volt‐Watt curves, and verify the effectiveness of the optimal curves on distribution network.

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A Decentralized Voltage Regulation Scheme Using Improved Volt‐Var Function of PV Smart Inverter

Xie,

Kaneko,

Hayashi

2024

IEEJ Transactions Elec Engng

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With the growing distributed PV installation rate in distribution systems, voltage regulation difficulties such as local voltage violations and fluctuations have become common. To solve the voltage regulation problems, the local voltage regulation method using volt‐var (VV) function is effective for its high regulation speed, high accuracy, and flexibility. However, there are still hurdles on real application, such as parameter setting difficulties, insufficient voltage fluctuation mitigation effect, and unfairness of reactive power generation between PV customers. To further improve the VV function, this paper proposes a PID closed‐loop based VV function and mode‐switching function of PV smart inverter (SI). To validate the proposed methods, numerical simulations were conducted using a 6‐feeder distribution system model based on the JST‐CREST 126 distribution feeder model. According to the simulation result, the proposed method can better mitigate the local voltage violation compared to basic VV function based on the VV curve, also improve the fairness between PV customers, while the total reactive power generation and tap operations increases for the aim of more adequate voltage regulation. © 2024 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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Effectiveness of updating the parameters of the Volt-VAR control depending on the PV penetration rate and weather conditions

Cited by 16 publications

References 13 publications

Optimal Volt–Var Curve Setting of a Smart Inverter for Improving Its Performance in a Distribution System

Optimal Volt–Var Curve Setting of a Smart Inverter for Improving Its Performance in a Distribution System

Determination method of Volt‐Var and Volt‐Watt curve for smart inverters applying optimization of active/reactive power allocation for each inverter

A Decentralized Voltage Regulation Scheme Using Improved Volt‐Var Function of PV Smart Inverter

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