Optimal operation for active management of distribution system with distributed generation

Rugthaicharoencheep, N.; Lantharthong, T.; Auchariyamet, S.

doi:10.1109/iccep.2011.6036381

Cited by 5 publications

(11 citation statements)

References 13 publications

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“…Moreover, the versatility and simple applicability of using the PSO algorithm to calculate DG units OPF with Newton–Raphson (NR) seems to converge well in the performed studies [76]. The objective function, which minimizes the total cost of the power produced by the DG units with the DN active management, provides the optimal energy distribution among the DGs [31]. The single and multiple ODGA objective functions and algorithms were compared to decrease the total system losses, operating costs, and voltage fluctuations of RDN.…”

Section: Optimization Methods For Dg Integrationmentioning

confidence: 99%

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A comprehensive review of recent advances in optimal allocation methods for distributed renewable generation

Tercan,

Demirci,

Unutmaz

et al. 2023

IET Renewable Power Gen

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Distributed generation (DG) has a key role in enlarging the implementation of renewable energy resources (RES). However, the intermittent and uncontrollable nature of RES can lead to several severe power quality‐related issues. Therefore, many efforts have been made to overcome these issues by optimizing DG sizes and locations. Hence, optimal DG allocation (ODGA) is significant for DG performance and provides advantages to the power system, such as improved power quality, voltage stability, reliability, and profitability. This study reviews recent ODGA studies eliminating the main DG integration problems. Often used ODGA methods have been categorized, and the main differences have been discussed, giving the details of features of optimization methods such as convergence performance and computational burden. A deep analysis for categorizing the objectives of ODGA has been done. In addition, optimization methods applied in ODGA studies have been presented by comparing the superiorities of algorithms and validated test network models. The objectives and significant findings of the ODGA applications are summarized with the advantages and disadvantages. It can be concluded that ODGA has a critical role in RES integration on the DG side and in reducing carbon emissions. This paper leads and provides a perspective for researchers working on recent ODGA methods.

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Section: Optimization Methods For Dg Integrationmentioning

confidence: 99%

“…It also determines distributed renewable generation (DRG) allocation by optimizing the energy losses. It may also minimize the total active power loss through reactive power control [31].…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review of recent advances in optimal allocation methods for distributed renewable generation

Tercan,

Demirci,

Unutmaz

et al. 2023

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Subsequently, six variables of real power (P) and reactive power (Q) are generated randomly. These variables P 1 , P 2 , P 3 assigned as real and reactive power generation of MDGs. The random generated number of real power (P) is between 1MW to 2MW and random generated number of reactive power (Q) is between 0Mvar to 1.5Mvar.…”

Section: Initializationmentioning

confidence: 99%

“…Distribute generation (DG) is a generation of electricity that normally located at the distribution network. This DG acts as auxiliary power sources, which associated to the grid at different places and basically satisfy the load demand that is required [1][2][3]. Nowadays, DG is vital with a specific end goal to secure and supply the power to the customer, deregulation of power market, decrease environment control and increase the power reliability [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

et al. 2019

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This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

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“…Salama [2] in their paper have presented an overview of the revolutionary techniques of implementing DGs, which in turn change operation of electric power systems along with their types and operating technologies. N. Rugthaicharoencheep and S. Auchariyamet [3] have discussed the benefits and drawbacks of DG on distribution systems. Duong Quoc Hung and Nadarajah Mithulananthan [4] used a better analytical technique for recognition of the optimal location and best power factor for integrating multiple DGs to reduce system losses in wide-ranging primary distribution systems.…”

Section: Introductionmentioning

confidence: 99%

Archives of Electrical Engineering

Kumar,

Bilgundi,

Pradeepa

2019

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High distribution system power-losses are predominantly due to lack of investments in R&D for improving the efficiency of the system and improper planning during installation. Outcomes of this are un-designed extensions of the distributing power lines, the burden on the system components like transformers and overhead (OH) lines/conductors and deficient reactive power supply leading to drop in a system voltage. Distributed generation affects the line power flow and voltage levels on the system equipment. These impacts of distributed generation (DG) may be to improve system efficiency or reduce it depending on the operating environment/conditions of the distribution system and allocation of capacitors. For this purpose, allocating of distributed generation optimally for a given radial distribution system can be useful for the system outlining and improve efficiency. In this paper, a new method is used for optimally allocating the DG units in the radial distribution system to curtail distribution system losses and improve voltage profile. Also, the variation in active power load in the system is considered for effective utilization of DG units. To evidence the effectiveness of the proposed algorithm, computer simulations are carried out in MATLAB software on the IEEE-33 bus system and Vastare practical 116 bus system.

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Optimal operation for active management of distribution system with distributed generation

Cited by 5 publications

References 13 publications

A comprehensive review of recent advances in optimal allocation methods for distributed renewable generation

A comprehensive review of recent advances in optimal allocation methods for distributed renewable generation

Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

Archives of Electrical Engineering

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