Determining Optimal Forming of Flexible Microgrids in the Presence of Demand Response in Smart Distribution Systems

Mohsenzadeh, Amin; Pang, Chengzong; Haghifam, Mahmoud‐Reza

doi:10.1109/jsyst.2017.2739640

Cited by 38 publications

(22 citation statements)

References 34 publications

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“…3, is divided into multiple microgrids. Parameters in (7) are set as ( = 1, = 0). The chosen values for the weights in (1) are 1 = 2 = 0.5.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…As shown in (7), the objective function 3 to be minimized is the weighted summation of 1 and (1 − 2 ). The values of the weights and determine whether 3 targets the microgrid adequacy, microgrid islanding success, or a combination of both.…”

Section: Combining Objectivesmentioning

confidence: 99%

“…The microgrid success indicator 2 gives the probability of having successful islands taking into consideration the power requirements and the voltage limits of the microgrids. The parameters in (7) are set as ( = 0, = 1). Table IV shows the optimal switch locations, the corresponding values of success indicators F2, as well as the corresponding values of 1−F 2 .…”

Section: B Application Of the Islanding Success Probability Objectivmentioning

confidence: 99%

“…8 shows the optimal infrastructure when partitioning the modified system into six microgrids with maximized selfadequacy and islanding success probability. In this case, the virtual cut set lines (indicated in bold in Table XI) are (13,20,7,41,59). The corresponding value of the combined objective function 3 is 57.05 pu with microgrids islanding success indicator 2 of 94.2% and power mismatch 1 of 51.32 pu.…”

Section: E Comparison With Other Microgrid Design Objectivesmentioning

confidence: 99%

See 3 more Smart Citations

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

Osama

Zobaa

Abdelaziz

2020

IEEE Systems Journal

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This paper proposes a novel methodology for the optimal design of microgrids in distribution systems with multiple distributed generation units. Following the IEEE Standard 1547.4-2011, the operation and control of large distribution networks can be enhanced by dividing these networks into multiple virtual microgrids. The proposed planning framework incorporates the necessary conditions for microgrids to operate efficiently in gridconnected operating mode and successfully during islanding. To obtain a robust design, the clustering process considers three objectives: maximizing the self-adequacy of the designed microgrids, maximizing microgrid islanding success probability, and a combination of both targets. For this purpose, the PG&E distribution system with 69 buses is selected as a test case. Backtracking search optimization algorithm, a probabilistic load flow approach, and graph-based theories are used to accomplish this research. Simulation results demonstrate the effectiveness of combining the self-adequacy and the islanding success probability objectives in the clustering process. Compared with other strategies present in the previous literature, the proposed framework results in more self-sufficient and successful islands assessed in terms of active and reactive power adequacy as well as voltage constraints. Next, the effects of increased penetration level of distributed generation units and installation of both distributed energy storage units and distributed reactive sources on the design process are examined. Finally, comparison with other microgrid design objectives applied in previous researches reveals that the resultant design is sensitive to the system's reliability, security, and economic requirements.

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“…3, is divided into multiple microgrids. Parameters in (7) are set as ( = 1, = 0). The chosen values for the weights in (1) are 1 = 2 = 0.5.…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Combining Objectivesmentioning

confidence: 99%

Section: B Application Of the Islanding Success Probability Objectivmentioning

confidence: 99%

Section: E Comparison With Other Microgrid Design Objectivesmentioning

confidence: 99%

See 2 more Smart Citations

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

Osama

Zobaa

Abdelaziz

2020

IEEE Systems Journal

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show abstract

“…They are power distribution systems, which have capability of operating in standalone or grid connected mode. They can operate as DC, AC or hybrid power system structures, in which many renewable and non-renewable sources and some sorts of loads can be found [9][10][11][12]. However, NGs have lower power and simpler control.…”

Section: Introductionmentioning

confidence: 99%

Realising full‐selective sources contribution in AC nano‐grids

Samet

Kazemzadeh

Ghanbari

2020

IET Energy Systems Integration

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In addition to conventional load side and source side management techniques, some approaches for management of local resources have been proposed for networks in recent years. For a load section including several loads and local sources, there is no approach in which full-selective contribution of the sources has taken into account. This study deals with a fullselective method for realising different desirable contributions of the local sources in a AC nano-grid. The full-selective contribution for active and reactive powers delivery is achieved using an electric power hub (EPH) and an efficient algorithm, both suggested in this work. The EPH composed of some power control units, by which one can share each load between the sources, desirably. The performance of the approach is evaluated in different conditions using some simulations in Matlab/ Simulink.

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Evaluating the Impact of Demand Response in Planning Micro-grids Considering Uncertainties

Thang

Trung

2020

Advances in Engineering Research and Application

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Determining Optimal Forming of Flexible Microgrids in the Presence of Demand Response in Smart Distribution Systems

Cited by 38 publications

References 34 publications

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

Realising full‐selective sources contribution in AC nano‐grids

Evaluating the Impact of Demand Response in Planning Micro-grids Considering Uncertainties

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