Reliability enhancement and voltage profile improvement of distribution network using optimal capacity allocation and placement of distributed energy resources

Agajie, Takele Ferede; Khan, B. Zorina; Guerrero, Josep M.; Mahela, Om Prakash

doi:10.1016/j.compeleceng.2021.107295

Cited by 26 publications

(7 citation statements)

References 18 publications

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“…To achieve this objective, integrating suitable DGUs can be a highly effective solution. To enhance the voltage profiles of each bus in the network, the calculation of AVDI can be employed using Equation (3). It is important to note that reducing AVDI will lead to an improvement in the voltage profiles of the buses [22] …”

Section: Problem Formulationmentioning

confidence: 99%

“…It compensates for the lagging reactive demand generated due to transformers or motors connected in the system or loads with low power factor (PF). The SCUs when connected in the DSN reduce the series impedance, thereby reducing the voltage drop and losses, and consequently, PF and power system stability limits improve [3]. However, the placement and sizing of SCUs should be properly selected since wrong placement and size may lead to the condition of voltage swell and consequences may drag the system into instability conditions.…”

Section: Introductionmentioning

confidence: 99%

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Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Mehroliya,

Arya

2023

Comp Applic In Engineering

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In the transmission and distribution networks, both active and reactive power play significant roles. While active power does the beneficial work, reactive power maintains the voltage that necessitates management from a system reliability perspective. The voltage variation from the nominal range may result in unintentional operation and early component failure. To maximize the amount of real power that can be transported over the power‐transmitting media, the system must also control reactive power flow. In a three‐phase unbalanced distribution system reinforced with distributed generator units (DGUs) and shunt capacitor units (SCUs), this paper suggests a teaching learning‐based optimization (TLBO) approach to be applied to combinatorial problems for simultaneous reduction of real power loss and net reactive power flow, enhance voltage stability index (VSI) and minimize aggregated voltage deviation index. A multiobjective formulation based on TLBO has been implemented to choose the ideal sizes and placements of DGUs and SCUs in large distribution networks. The case studies have been carried out on an IEEE 33‐bus standard system and a large 123‐bus unbalanced system. The analysis of the IEEE 33‐ and 123‐bus test systems reveals the economic efficiency of the suggested TLBO algorithm. Notably, by applying DG and capacitor simultaneously in the 33‐bus system, a significant reduction of 59.35%, 55.05%, and 50.76% (phases a, b, and c), and for the 123‐bus system, a significant reduction of 43.65%, 19%, and 48.65% (phases a, b, and c) in total active power losses have been achieved. The results suggest that the proposed method renders significant improvement in voltage stability and reduces power losses concerning the base case for both test systems.

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Mehroliya,

Arya

2023

Comp Applic In Engineering

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“…Customers rely on a constant and stable supply of electricity. However, the increasing integration of new technologies such as DER is negatively impacting performance metrics, leaving customers vulnerable to more frequent power outages [26]. Improvements in the observability of conventional electrical features for power system analysis and the identification of DER in LV distribution networks provide DNOs enhanced monitoring of this section of the electrical system.…”

Section: Social Contributionsmentioning

confidence: 99%

Impact Assessment of NILM Methods for an Enhanced Observability of Low Voltage Distribution Networks

Jaramillo

Lopez‐Lorente

Brogan³

et al. 2022

2022 IEEE International Smart Cities Conference (ISC2)

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“…DG side restoration with technical considerations, such a DG failure, load demand and DG output time-dependent patterns are taken into account. The optimal placement of distributed energy resources (DERs) to enhance reliability and improve the voltage profile of distribution network is studied in [12]. A renewable DG allocation planning algorithm is proposed in [13] to determine the optimum locations and sizes of DG units in distribution network for reliability improvement and loss reduction.…”

Section: Introductionmentioning

confidence: 99%

Planning of Distributed Generation Resources to Simultaneously Improve Reliability and Resilience of Distribution Network

Ghanbarimasir

Yousefi

Noori

et al. 2023

Preprint

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In this paper, a novel optimization framework is proposed for the assessment of distribution network reliability and resilience via distributed generation (DG) placement. In this regard, a stochastic multi-objective optimization model is introduced that utilizes optimal allocation of DG units along with an optimal service restoration strategy by using the network’s embedded remote-control switches. The model minimizes distribution network outage costs due to both reliability contingencies and resilience events while keeping DG investment costs minimum. The optimal service restoration problem is formulated as a mixed-integer linear programming (MILP) model that satisfies network technical constraints. In order to capture the uncertain nature of fault contingencies, two different scenario sets are generated. Historical data of the network’s fault-rates, and the failure probability functions of network components obtained from Monte Carlo simulation (MSC), are used for reliability and resilience scenarios, respectively. The non-dominated sorting genetic algorithm (NSGA-II) approach is applied to solve the model which provides a Pareto-optimum solution pool. A fuzzy decision-making logic tool is then applied to assist the network planners in opting the final solution from the Pareto-front. The proposed model is tested on IEEE 33-bus system and the simulation results show the effectiveness of the model.

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Reliability enhancement and voltage profile improvement of distribution network using optimal capacity allocation and placement of distributed energy resources

Cited by 26 publications

References 18 publications

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Impact Assessment of NILM Methods for an Enhanced Observability of Low Voltage Distribution Networks

Planning of Distributed Generation Resources to Simultaneously Improve Reliability and Resilience of Distribution Network

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