Proposal and Experimental Verification of Distribution Voltage Estimation and Control Method using Measured Data from IT Switches

Hanai, Yuji; Hayashi, Yasuhiro; Matsuki, Junya; Kurihara, Masanori

doi:10.1541/ieejpes.130.859

Cited by 22 publications

(18 citation statements)

References 11 publications

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“…R is the maximum nodal number in section 1 ~ section r. (6) where m is the node number in section 1 ~ section s and AF m p V , is the nodal voltage calculated by linear interpolation using the voltage value measured at adjacent switches after the 1 st ~ (X-1) th switches are reclosed.…”

Section: B Procedures Of the Proposed Das For Service Restorationmentioning

confidence: 99%

Distribution automation system for service restoration involving simultaneous disconnection and reconnection of distributed generators

Kawano

Fujimoto

Wakao

et al. 2015

2015 IEEE Eindhoven PowerTech

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This paper presents a distribution automation system (DAS) for service restoration in the distribution network with photovoltaic (PV) generator systems, which are disconnected simultaneously after a fault and subsequently reconnected after service restoration. Because the reverse power flow of PVs affects voltage in the distribution system, voltage dips and surges occur during the service restoration. However, current DAS do not control voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) during the service restoration. The proposed DAS estimates the voltage in a distribution network considering the simultaneous disconnection of PVs by performing power flow calculations, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage deviation. The voltage after the disconnection of PVs is calculated by estimating the PV output utilizing square kilometer solar radiation data calculated using satellite image data in real time.Index Terms--distribution automation system, simultaneous disconnection and reconnection of DGs, solar radiation, voltage control I.

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Section: B Procedures Of the Proposed Das For Service Restorationmentioning

confidence: 99%

Distribution automation system for service restoration involving simultaneous disconnection and reconnection of distributed generators

Kawano

Fujimoto

Wakao

et al. 2015

2015 IEEE Eindhoven PowerTech

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“…On the other hand, state estimation methods focused on distribution systems are studied recently as a fundamental technology to improve online monitoring and control in next-generation distribution automation systems that can handle introduction of renewable energies into distribution systems, increasing deregulation of power industry, and other factors. [3][4][5][6][7][8][9][10][11][12][13][14][15] Conventional techniques of state estimation for distribution systems can be divided into statistical methods [3][4][5]8 and load adjustment methods. 3,6,7 Both approaches use least squares based on the Newton method, sensitivity-based algorithms, and so on, assuming that functions of interest are continuous and differentiable.…”

Section: Introductionmentioning

confidence: 99%

“…However, models of real equipment in distribution systems include nonlinear elements, and power flow equations are not necessarily differentiable or continuous, 16 so that derivatives and sensibility cannot be used. In addition, section switches provided with sensors are introduced into distribution systems in Japan, and using these sensor data for state estimation is considered, 9,10 but errors sneak in estimation by least squares when measured results are corrupted by faults of measuring devices or communication failures, and so on.…”

Section: Introductionmentioning

confidence: 99%

Differential Evolutionary Particle Swarm Optimization for Load Adjustment Distribution State Estimation using Correntropy

Iwata

Fukuyama

2018

IEEJ Trans. PE

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This paper proposes differential evolutionary particle swarm optimization (DEEPSO) for load adjustment distribution state estimation (DSE) using correntropy. Practical equipment in distribution systems causes nonlinear characteristics in an objective function and evolutionary computation methods have been applied to DSE so far. This paper applies DEEPSO in order to improve estimation equality. Minimization of sum of square errors by the least squares method has a problem when outliers exit in measured values. Quality of estimated results is largely affected by the outliers using the least squares method, while correntropy has a possibility not to be affected by the outliers. The proposed method is applied to a typical distribution system. The results indicate that the proposed DEEPSO-based method can improve estimation results compared with conventional particle swarm optimization (PSO) and hybrid PSO-based method, and the correntropy-based proposed method can estimate distribution system conditions more accurately than the conventional least squares method. K E Y W O R D Scorrentropy, differential evolutionary particle swarm optimization, distribution system, load adjustment distribution state estimation Electr Eng Jpn. 2018;205:11-21.

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“…On the other hand, existing section switches on medium-voltage lines are being replaced with SSS (Section Switchgear with Sensors) that can measure voltage, current, and power factor. With such information, reports on monitoring [10][11][12] and operation [13][14][15] of power systems have been created. For example, in literature [11], sensor data are used for the online estimation of PV output and load in sections between SSS to determine the actual load required for fault recovery in a power distribution system.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in literature [11], sensor data are used for the online estimation of PV output and load in sections between SSS to determine the actual load required for fault recovery in a power distribution system. Voltage management techniques using sensor information were proposed [13][14][15]. Specifically, in literature [13], voltage profiles are estimated using sensor information in combination with metaheuristics (PSO: Particle Swarm Optimization), and thus obtained results are utilized in LRT tap position control.…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Estimation Method of Reactive Power Controlled by PCS using Measurement Data of Switchgears with Sensors

Koide

Tsuji

Oyama

et al. 2017

Electrical Engineering Japan

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SUMMARY It becomes an important issue to maintain voltage profile within the allowable range in distribution systems with a large number of distributed generators (DGs), such as Photovoltaic (PV). Although reactive power control by power conditioning system (PCS) is effective to mitigate the voltage increase, there is a possibility that active power curtailment is needed to provide enough amount of reactive power due to current limitation. Here, it is expected that the active power curtailment can be avoided if a cooperative voltage control between load ratio tap controller (LRT) and PCS is realized. To this end, system operators have to know the amount of reactive power controlled by PCS. Hence, in this paper, we developed a new state estimation method of the reactive power using the measurement data obtained by the switchgears with sensors. In addition, a probabilistic approach was applied because an accurate estimation is theoretically impossible only by using the limited number of measurement data. The proposed method was tested in a hierarchic distribution system model and its effectiveness was shown through simulations.

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Proposal and Experimental Verification of Distribution Voltage Estimation and Control Method using Measured Data from IT Switches

Cited by 22 publications

References 11 publications

Distribution automation system for service restoration involving simultaneous disconnection and reconnection of distributed generators

Distribution automation system for service restoration involving simultaneous disconnection and reconnection of distributed generators

Differential Evolutionary Particle Swarm Optimization for Load Adjustment Distribution State Estimation using Correntropy

A Probabilistic Estimation Method of Reactive Power Controlled by PCS using Measurement Data of Switchgears with Sensors

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