Comprehensive mixed‐integer linear programming model for distribution system reconfiguration considering DGs

Teshome, Dawit Fekadu; Lian, Kuo Lung

doi:10.1049/iet-gtd.2018.5242

Cited by 21 publications

(9 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[2] A SOCP model for DSR considering reliability indices [4] Linear formulation of DG hosting considering DG curtailment [5] Dynamic reconfiguration [17] Radiality constraints for networks containing several buses without load and generation [15] Minimal spanning tree based on dual graph theory [ [101] Integration of switching cost, power losses, and uncertainties of wind, solar and biomass DG units [104] Voltage security and radiality improvements in deregulated electricity markets via DSR [105] Simultaneous DSR and capacitor placement [106] Distributed generation [107] Simultaneous online distribution lines and capacitor switching in active smart grids [108] Annual investment return [109] Simultaneous DSR and DG allocation [110] Effect of load and distributed generation variability on DSR in smart grids [112] Distribution system expansion planning using network reconfiguration [113] Voltage and reactive power control devices in presence of DG [115] N−1 security criterion [116] Reliability enhancement [118] Loadability maximization [119] Load type impact on DSR [120] A MILP model for DSR in presence of DG [121] Effect of network reconfiguration on DG hosting improvement [122] Binary convex model for DSR [123] Protective devices [124] Smart agents and load priority [126] Reliability formulation in DSR using minimal cut sets theory [127] Weibull-Markov stochastic-based model for simultaneous DSR and capacitor placement [128] Comprehensive MILP model for DSR in presence of DG [130] Statistic DR in simultaneous network reconfiguration and expansion planning [131] Use of flexible DC power flow controller in DSR [132] Energy storage systems in DSR [133] According to Table 8, it can be seen that loss reduction via DSR has been always important for researchers and it consists a great...…”

Section: Innovations References Solution Methodsmentioning

confidence: 99%

“…In [130], a comprehensive MILP model was presented for SDSR problem in presence of DG, by embedding exact network losses in power flow equations instead of considering losses as estimated power injections at each node. Furthermore, in [131], it was shown that simultaneous network reconfiguration and expansion planning in presence of DR reduces the expansion costs more efficiently compared to when only network expansion planning is performed.…”

Section: Literature Classification Based On Objective Functionsmentioning

confidence: 99%

See 1 more Smart Citation

Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification

Mahdavi

Alhelou²,

Hatziargyriou

et al. 2021

IEEE Access

View full text Add to dashboard Cite

Distribution systems play an important role, delivering the electric power of generation system to individual consumers. Distribution system reconfiguration (DSR) is a large-scale combinatorial optimization problem. For the last 45 years, the DSR problem has been widely studied; nowadays, DSR, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a literary framework for DSR specialists. A categorization of solution methods, case studies, and novelties of the most relevant works regarding DSR are provided. In order to establish a complete background, not only traditional approaches, but also those involving uncertainty, reliability, electricity market, power quality, distributed generation, capacitor placement, and switching time in DSR are highlighted. This framework can help researches to improve previous formulations and methods and can propose more efficient models to better exploit the existing infrastructure. INDEX TERMSDistributed generation, literary framework, network reconfiguration, power distribution systems, uncertainty. NOMENCLATURE Abbreviations used throughout the manuscript are reproduced below for quick reference. 1 AACO Adaptive ant colony optimization. AC Alternating current. ACO Ant colony optimization. ADC Automated distribution control. ADP Approximated dynamic programming. AENS Average energy not supplied. AGA Adoptive genetic algorithm. AIS Artificial immune system. AMPL A mathematical modeling language. ANN Artificial neural network. APSO Adaptive particle swarm optimization. ASIFI Average system interruption frequency index.

show abstract

Section: Innovations References Solution Methodsmentioning

confidence: 99%

Section: Literature Classification Based On Objective Functionsmentioning

confidence: 99%

Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification

Mahdavi

Alhelou²,

Hatziargyriou

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The DSR problem with DGs was presented in [22,23] to minimize real power loss and improve voltage profile. In [24], the authors employed a DSR model for the network losses in MIP formulation while DG locations and sizes are simultaneously optimized. The studies in [6] developed a model for the optimal siting and sizing of ESSs embedding network reconfiguration.…”

Section: Introductionmentioning

confidence: 99%

“…,10-11, 14-15, 16-17, 19-20, 24-25, 26-27, 30-31, 31-32 DG parameters. ,[10][11][14][15][16][17][19][20][24][25][26][27][30][31][31][32]…”

mentioning

confidence: 99%

A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming

et al. 2020

View full text Add to dashboard Cite

Widely used distribution generations (DGs) and energy storage systems (ESSs) enable a distribution system to have a more flexible fault reconfiguration capability. In order to enhance the service reliability and the benefit of distribution networks with DGs and ESSs, this paper proposes a novel distribution system reconfiguration (DSR) model including DGs and ESSs. Meanwhile, the impact of sectionalizing switches and tie switches on reliability is considered. The concept of “boundary switch” is introduced for quantifying the customer interruption duration. The DSR model is presented to minimize the sum of the customer interruption cost, the operation cost of switches, and the depreciation cost of DGs and ESSs. Furthermore, the proposed model is converted into a mixed-integer linear programming, which can be efficiently solved by commercial solvers. Finally, the validity and efficiency of the proposed DSR model are verified by a modified IEEE 33-bus system and a modified PG&E69-bus network. The obtained results indicate the advantages of DGs and ESSs in reducing outage time, and suggest that the types and locations of SSs have great effects on the resulting benefit of DGs and ESSs.

show abstract

“…Some modified methods [5]- [10] have been proposed to improve the power flow calculation in distribution networks, but none of them have got rid of the iterative calculation. Furthermore, the planning [11], optimization [12] and reconfiguration [13] of distribution networks become more complex because of the nonlinear power flow equations.…”

Section: Introductionmentioning

confidence: 99%

Linear Power Flow Calculation of Distribution Networks With Distributed Generation

Liu

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

To address the shortcomings of the existing linear power flow calculation methods for distribution networks with low versatility and calculation accuracy, a linear power flow calculation method considering distributed generation (DG) is proposed. According to the characteristics of distribution networks and using the Taylor series expansion technology, the nonlinear terms of the basic power flow equation are linearized. The reactive power generated by the non-PV type DG is simplified to a quadratic function of the voltage amplitude. Then, combined with linear approximation and the simplified DG calculation model, the basic power flow equation is simplified into a linear form. Based on the linear power flow equation, a linear power flow calculation method for distribution networks with DG is proposed. The proposed method, which considers various types of DG, has a strong versatility. Finally, the calculation results of typical test systems show that compared with the existing linear power flow calculation methods, the proposed method has a higher calculation accuracy and more versatility and can be used for rapid analysis of distribution networks.INDEX TERMS Distribution networks, distributed generation, linear power flow, Taylor series.

show abstract

Comprehensive mixed‐integer linear programming model for distribution system reconfiguration considering DGs

Cited by 21 publications

References 33 publications

Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification

Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification

A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming

Linear Power Flow Calculation of Distribution Networks With Distributed Generation

Contact Info

Product

Resources

About