Probabilistic Estimation of Distribution Network Performance With Respect to Voltage Sags and Interruptions Considering Network Protection Setting—Part I: The Methodology

Cebrian, Juan Carlos; Kagan, Nelson; Milanović, Jovica V.

doi:10.1109/tpwrd.2016.2633518

Cited by 33 publications

(30 citation statements)

References 14 publications

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“…This result is used for the subsequent calculations involved in the evaluation of CET. To identify the sensitive bus a method of sag score and energy index (EI) is used, which is given in Equations and

italicSag italicScore = 1 - \frac{1}{3} ((), U_{A} + U_{B} + U_{C})

italicEI = D_{ms} ((), {(1 - U_{A})}^{α} + {(1 - U_{B})}^{α} + {(1 - U_{C})}^{α})

…”

Section: Resultsmentioning

confidence: 99%

“…To identify the sensitive bus a method of sag score and energy index (EI) is used, which is given in Equations (24) and (25). 26…”

Section: Resultsmentioning

confidence: 99%

“…Whenever sag points fall in region 2, equipment may, or may not trip depending upon the tolerance level of the equipment which is given in Table . When sag points fall in the region 2C and 2A, equipment may trip depending upon the voltage sag severity and duration, respectively . As voltage sag points are scattered randomly, a probabilistic technique is used to evaluate the equipment trip.…”

Section: Number Of Equipment and Process Trip Evaluation Techniquementioning

confidence: 99%

“…When sag points fall in the region 2C and 2A, equipment may trip depending upon the voltage sag severity and duration, respectively. 22,[24][25][26] As voltage sag points are scattered randomly, a probabilistic technique is used to evaluate the equipment trip. In this work, the uniform exponential probability distribution function is used, which is defined based on the region in Equation (1) and (2).…”

Section: The Mathematical Formulation For Determining the Number Ofmentioning

confidence: 99%

See 3 more Smart Citations

A probabilistic approach for assessment of financial loss due to equipment outage caused by voltage sag using cost matrix

Behera

Banik

Nandi

et al. 2020

Int Trans Electr Energ Syst

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Summary In the industrial sector, poor power quality (PQ) can malfunction or shut down the processes or equipment, which leads to excessive loss in revenue. During a visit to a chemical industry, it has been observed that equipment ceases operation frequently due to PQ issues, which hinders the completion of consignment within the stipulated time. It has made the industrial authority to feel the need for quantifying the loss of economy due to frequent equipment trip to provide proper immunity to the system against PQ issues. This paper deals with the assessment of financial losses in industrial loads due to voltage sag. Analytical methods considering Monte Carlo simulation technique is implemented for the evaluation of voltage sag due to the occurrence of symmetrical and unsymmetrical faults. Depending on the characteristics of sensitive equipment towards voltage sag, the process trips were evaluated using probabilistic methods for a chemical industry's distribution system. In this paper, a concept of sag score is used to find out the most sensitive buses for the evaluation of the cost of the equipment trip. An energy index is given for the industrial system to find out how much energy is being unused during a voltage sag event. Factors like variable cost, restart cost and hidden cost are influenced by the tripping of sensitive equipment due to voltage sag. The data are collected from the industrial personnel for the evaluation of the proposed methodology.

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italicSag italicScore = 1 - \frac{1}{3} ((), U_{A} + U_{B} + U_{C})

italicEI = D_{ms} ((), {(1 - U_{A})}^{α} + {(1 - U_{B})}^{α} + {(1 - U_{C})}^{α})

…”

Section: Resultsmentioning

confidence: 99%

“…To identify the sensitive bus a method of sag score and energy index (EI) is used, which is given in Equations (24) and (25). 26…”

Section: Resultsmentioning

confidence: 99%

Section: Number Of Equipment and Process Trip Evaluation Techniquementioning

confidence: 99%

Section: The Mathematical Formulation For Determining the Number Ofmentioning

confidence: 99%

See 2 more Smart Citations

A probabilistic approach for assessment of financial loss due to equipment outage caused by voltage sag using cost matrix

Behera

Banik

Nandi

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…Upon the occurrence of a fault in the network, root mean square voltage magnitude drops below the nominal voltage, thus leading to voltage sag. Both temporary and permanent faults cause the voltage sag until the responsible protection device operates [14]. The severity of voltage sag depends on fault location, fault impedance, fault-clearing time, sensitivity of customer equipment/process, moment of occurrence of sag event, etc.…”

Section: Quantification Of Reliability Eventsmentioning

confidence: 99%

Utilizing Energy Storage for Reliability Solutions in Active Distribution Systems

2019

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Stochastic failures in a distribution network result in different reliability events, such as voltage sags and momentary and sustained interruptions, causing significant financial losses for many customers. Strategic utilization of energy storage system (ESS) can help mitigate these reliability events. This paper investigates the role of ESS toward providing reliability solutions in the context of an active distribution system. In this regard, scenario-based probabilistic modeling of reliability event mitigation with the ESS is presented, which is integrated into the reliability evaluation framework. The proposed approach is efficient in assessing reliability solutions with ESS considering storage technology type, power/energy rating, hardware availability, presence of other distributed energy resources, etc. A range of case studies is conducted to evaluate mitigation of reliability events at a different level of the distribution system. Valuable insights into the efficient utilization of ESS are provided based on findings. also being utilized to mitigate different reliability events. DERs can help reduce the impact of sag event by injecting an additional reactive power in case of voltage dips during system contingencies [7]. The energy storage installed at customer premises can override short-and long-duration reliability events [8,9]. Microgrid, which consists of controllable loads and DERs integrated at the point of common coupling (PCC) of distribution network, operates in isolated mode during utility supply disturbances (sags and interruptions), thereby protecting critical load against reliability events [7,10]. DERs that are not part of such microgrids and integrated along a distribution feeder can also operate in an islanded mode to reduce long-duration outages [11].Various aspects of utilization of ESS and other distributed energy resources to mitigate different reliability events have been explored in the existing literature. Reference [3] provides an analytic method to assess the contribution of energy storage and a backup generator to reduce the impact of sustained outages. A new method of protecting sensitive load against momentary interruptions using inverter-coupled ESS is developed in Reference [9]. The potential of sodium-sulfur batteries to protect customer devices/processes are investigated in Reference [8]. Authors in Reference [7] have discussed the role of DG in the mitigation of reliability events with the microgrid-like operation and an additional current injection method. References [5,6] have presented methodologies to model the contribution of power electronic-based devices to lower the impact of voltage sag on an individual load point and overall network. A Monte Carlo simulation-based approach is developed to quantify the role of ESS in reducing sustained outages experienced by customers in Reference [11]. The impact of intermittent renewable energy resources on the distribution network and the use of energy storage to mitigate this issue have been explored in Reference [12]. Authors i...

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Stochastic investment model for custom Voltage‐Sag‐Preventing service considering service price and punitive damages of contract

Zhou

et al. 2019

IEEJ Transactions Elec Engng

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Custom power quality (PQ) plays a significant part in improving PQ in distribution networks and hedging economic losses for power‐quality‐sensitive electricity users. In an electricity market with multiple power companies competing with each other, for a power company, providing custom PQ with proper service prices becomes a key element to maximize its total economic profit and improve competitiveness. In this work, with a focus on the voltage sag (VS) problem, a stochastic investment model for installing voltage‐sag‐preventing equipment is proposed. First, basic cost–benefit models are established from the perspectives of power companies and electricity users. Then, considering uncertainties in providing power with an expected number of voltage sags resulting from equipment failure and so on, proper pricing mechanisms and punitive damages of service contracts are analyzed accordingly. With each mechanism, the stochastic investment decision‐making model is formulated with the goal of maximizing a power company's economic profit during the life cycle of voltage‐sag‐preventing equipment. The influences of different factors on the economic benefits of the investment are analyzed in a case study, including the compensation coefficient, investment cost, and failure uncertainties, providing a reference for decision‐making for investment in and possible pricing of custom VS services. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Probabilistic Estimation of Distribution Network Performance With Respect to Voltage Sags and Interruptions Considering Network Protection Setting—Part I: The Methodology

Cited by 33 publications

References 14 publications

A probabilistic approach for assessment of financial loss due to equipment outage caused by voltage sag using cost matrix

A probabilistic approach for assessment of financial loss due to equipment outage caused by voltage sag using cost matrix

Utilizing Energy Storage for Reliability Solutions in Active Distribution Systems

Stochastic investment model for custom Voltage‐Sag‐Preventing service considering service price and punitive damages of contract

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