energies
Article
Aggregation of Radial Distribution System Bus with
Volt-Var Control
Hiroshi Kikusato * , Taha Selim Ustun , Dai Orihara , Jun Hashimoto and Kenji Otani
Citation: Kikusato, H.; Ustun, T.S.;
Orihara, D.; Hashimoto, J.; Otani, K.
Aggregation of Radial Distribution
System Bus with Volt-Var Control.
Energies 2021, 14, 5390. https://
doi.org/10.3390/en14175390
Academic Editors: Pavlos S.
Georgilakis and Marco Pau
Received: 9 June 2021
Accepted: 27 August 2021
Published: 30 August 2021
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4.0/).
Fukushima Renewable Energy Institute, AIST (FREA), 2-2-9 Machiikedai, Koriyama 963-0298, Japan;
selim.ustun@aist.go.jp (T.S.U.); orihara.dai@aist.go.jp (D.O.); j.hashimoto@aist.go.jp (J.H.);
k.otani@aist.go.jp (K.O.)
* Correspondence: hiroshi-kikusato@aist.go.jp; Tel.: +81-29-861-8168
Abstract: The high penetration of the distributed energy resources (DERs) encourages themselves to
implement grid-supporting functions, such as volt-var control. The quasi-static time-series (QSTS)
simulation is an essential technique to evaluate the impact of active DERs on the grid. Meanwhile, the
increase of complexity on the circuit model causes a heavy computational burden of QSTS simulation.
Although circuit reduction methods have been proposed, there have been few methods that can
appropriately handle the distribution system (DS) with multiple voltage control devices, such as
DERs implementing volt-var control. To address the remaining issues, this paper proposes an offline
bus aggregation method for DS with volt-var control. The method determines the volt-var curve
for the aggregated bus on the basis of historical data to reduce error in the aggregated model, and
its offline process solves the computational convergence issue concerned in the online one. The
effectiveness of the proposed method is validated in the simulation using a Japanese low-voltage
DS model. The simulation results show that the proposed method can reduce the voltage error and
computational time. Furthermore, the versatility of the proposed method is verified to show the
performance does not heavily depend on how to select historical data for model-building.
Keywords: advanced inverter; distribution system; IEC 61850-90-7; IEEE 1547; photovoltaic; power
system modeling; power system analysis; reactive power control; voltage regulation
1. Introduction
Continued cost reduction and policy support are driving the sustained uptake of wind
power and solar photovoltaic (PV) across the world [1]. With the increased integration of
the distributed energy resources (DERs) to power systems, the required capabilities of them
have also changed. Earlier, it was required that DERs did not actively regulate voltage and
shall trip on abnormal voltage/frequency [2]. Recently, requirements were revised so that
they are capable of actively regulating voltage/frequency and shall ride through abnormal
volt-age/frequency [3]. Such migration in the power system makes it challenging and
important to understand the interaction between the power system and DERs.
In the DSs, many solutions have been proposed to mitigate the voltage rises, as well
as to maximize the captured energy by the DERs. As solutions on the supply side, on-
load tap changers (OLTCs) and their control schemes have been improved [4,5]. While
on the demand side, various DER management methods are proposed [6,7]. Voltage-
reactive power (volt-var) control by inverters of DERs is a reasonable solution to which
DERs themselves, the cause of the issue, can contribute [8,9]. Since these methods will be
eventually integrated to the same DS, coordinating them must be studied [10,11].
Quasi-static time-series (QSTS) analysis is essential to analyze the DSs with high
penetrations of DERs for developing the above-mentioned solutions [12]. This solves a
series of sequential steady-state power flow. Each time-step of the calculation is solved
to rely on the information from the previous time-step solution [13]. Due to the features
of QSTS analysis, as the number of buses, components, and a calculation time-step of the
Energies 2021, 14, 5390. https://doi.org/10.3390/en14175390 https://www.mdpi.com/journal/energies