Heuristic optimization techniques for connecting renewable distributed generators on distribution grids

Tolba, Mohamed A.; Rezk, Hegazy; Al‐Dhaifallah, Mujahed; Eisa, Ayman A.

doi:10.1007/s00521-020-04812-y

Cited by 28 publications

(6 citation statements)

References 47 publications

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“…Furthermore, results from them were much better than those from other algorithms. Modified metaheuristic algorithms were also applied to reach better results than original ones such as hybrid CSA-ABCA [10], MTLOA [11], MABCA [12], and MOALO [13]. In this regard, hybrid method [14] and HOA [15] were also effective methods.…”

Section: Introductionmentioning

confidence: 99%

Finding Optimal Solutions for the Placement of Reactive and Active Power Generation Components in Distribution Networks Using a High-Performance Metaheuristic Algorithm

Kien

Tuyet

Phan

et al. 2022

International Transactions on Electrical Energy Systems

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This paper proposes a modified slime mold algorithm (MSMA) for finding optimal site and size of both photovoltaic generators (PGs) and shunt capacitors (SCs) in radial distribution power systems (RDPSs). The most suitable site together with the most effective size of PGs and SCs can reduce currents of conductors effectively, resulting in the significant reduction of active power loss on all conductors. MSMA and two other applied algorithms, slime mold algorithm (SMA) and equilibrium optimizer (EO), are implemented for three study cases of IEEE 33, 69, and 85 RDPSs including Case (1) place only PGs with both active and reactive power generations; Case (2) place both SCs and PGs with only active power generation; and Case (3) place both SCs and PGs with both active and reactive power generations. Comparisons with SMA and EO, MSMA can reach either the same loss or much smaller loss for study cases. Furthermore, MSMA also outperforms other previously published methods for the three study cases, and it can reach significantly smaller loss for the three cases by 1.5%, 30.55%, and 19.64% for system 1, 7.59%, 0.26%, and 0.32% for system 2, and 7.51%, 34.2%, and 22.65% for system 3. As comparing the loss among three study cases obtained by MSMA, Case 3 can reach less loss than Case 1 and Case 2 by 11.71% and 11.64% for system 1, 26.27% and 26.13% for system 2, and the same 26.6% for system 3. Thus, it is recommended that MSMA is the most effective algorithm and the placement of both SCs and PGs with active and reactive power generations is the most optimal.

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Section: Introductionmentioning

confidence: 99%

Finding Optimal Solutions for the Placement of Reactive and Active Power Generation Components in Distribution Networks Using a High-Performance Metaheuristic Algorithm

Kien

Tuyet

Phan

et al. 2022

International Transactions on Electrical Energy Systems

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“…Therefore, various DGs types are employed. These DGs can be classified based on their fuel energy into dispatchable and non-dispatchable units [11]. However, the inclusion of DGs in distribution systems raises the short circuit levels.…”

Section: Introductionmentioning

confidence: 99%

Effective Automation of Distribution Systems With Joint Integration of DGs/ SVCs Considering Reconfiguration Capability by Jellyfish Search Algorithm

et al. 2021

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Power system operators and planners have progressively shown an interest in maximizing distribution automation technologies. The automated distribution systems (ADS) provide the capability of efficient and reliable control which require an optimal operation strategy to control the status of the line switches and also dispatch the controllable devices. Therefore, this paper introduces an efficient and robust technique based on Jellyfish Search Algorithm (JFSA) for optimal Volt/VAr coordination in ADSs based on joint distribution system reconfiguration (DSR), distributed generation units (DGs) integration and Distribution static VAr compensators (SVCs) operation. The suggested technique is used for the dynamic operation of ADS in order to minimize losses and reduce emissions when considering regular daily loading conditions. The 33-bus and 69-bus delivery DSs have been subjected to a variety of scenarios. These situations are mostly concerned with achieving optimum distribution system operation and control, as well as validating the proposed methodology. Despite the problem's complexity, the proposed technique JFSA is shown to be the best solution in all of the cases considered. Furthermore, a comparison of the proposed JFSA with other similar approaches demonstrates its usefulness as a method to be used in modern ADS control centers.

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“…The increased interest in the integration of DGs into distribution networks is due to many reasons such as the dramatic growth in load demand, the desire to reduce pollution, and power market liberalization 10 . There are diverse DG types already implemented in the distribution networks, which can be classified into dispatchable and non‐dispatchable units according to their fuel 11 . Despite the advantages of DGs integration into distribution systems, this integration leads to an increase in the short circuit levels so that fault current limiters should be fitted in the network to sort out this issue 12 .…”

Section: Introductionmentioning

confidence: 99%

Optimal management of static volt‐ampere‐reactive devices and distributed generations with reconfiguration capability in active distribution networks

Shaheen

Elsayed

El‐Sehiemy

et al. 2021

Int Trans Electr Energ Syst

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Summary Recently, power system planners and operators are of interest to maximize distribution automation investments. Optimal operation of control centers of fully automated distribution systems enables it to control all switches as well as dispatching connected controllable apparatuses. Most previously enhanced distribution systems, which include additional enhancement apparatuses, such as distribution static VAr compensators, capacitor banks, and distributed generators, cannot take advantage of the features of these apparatuses because there is no efficient and reliable control. Accordingly, this article presents a robust and efficient technique using Manta ray foraging optimization algorithm (MRFOA) for optimal coordination and control of such apparatuses as well as distribution network reconfiguration simultaneously. The proposed procedure is employed for the dynamic operation of automated distribution systems, considering daily load variations, for losses minimization and emissions reduction with diverse cases of both the 33‐bus and 69‐bus distribution test systems. To manifest, these cases are developed to validate the proposed technique and to achieve optimum control and operation of the distribution systems. Despite the complexity of this problem, the proposed technique can achieve the optimal solution for the various considered cases. As well, the comparative assessment of the proposed MRFOA with relevant techniques demonstrates its effectiveness as an effective tool used in the control centers of modern automated distribution systems. One of the most complex challenges to distribution systems operators in the practical daily load variations is the control and optimal operation of the associated dispatchable enhancement apparatuses such as DGs and DSVCs. The DNR makes the utilization and control of such aforementioned enhancement apparatuses more feasible for distribution systems, but this is in return for increasing the complexity of the problem. Significant technical and environmental benefits have been achieved. Great power losses reduction (about 80%) and voltage enhancement are achieved using the MRFOA. In addition, the emission levels are kept at the lowest levels.

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Heuristic optimization techniques for connecting renewable distributed generators on distribution grids

Cited by 28 publications

References 47 publications

Finding Optimal Solutions for the Placement of Reactive and Active Power Generation Components in Distribution Networks Using a High-Performance Metaheuristic Algorithm

Finding Optimal Solutions for the Placement of Reactive and Active Power Generation Components in Distribution Networks Using a High-Performance Metaheuristic Algorithm

Effective Automation of Distribution Systems With Joint Integration of DGs/ SVCs Considering Reconfiguration Capability by Jellyfish Search Algorithm

Optimal management of static volt‐ampere‐reactive devices and distributed generations with reconfiguration capability in active distribution networks

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