A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks

Pesaran, H A Mahmoud; Nazari-Heris, Morteza; Mohammadi‐Ivatloo, Behnam; Seyedi, Heresh

doi:10.1016/j.energy.2020.118218

Cited by 86 publications

(48 citation statements)

References 48 publications

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“…The authors in [19] used quantum-inspired particle swarm optimization (Q-PSO) for the optimal allocation of distributed generation units. In [20], a hybrid genetic particle swarm optimization algorithm for the optimal allocation of distributed generation was developed. This paper aimed to reduce active and reactive power losses and voltage regulations in the system.…”

Section: Meta-innovative Methodsmentioning

confidence: 99%

A Novel Analytical Approach for Optimal Placement and Sizing of Distributed Generations in Radial Electrical Energy Distribution Systems

et al. 2021

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Considering the strong influence of distributed generation (DG) in electric distribution systems and its impact on network voltage losses and stability, a new challenge has appeared for such systems. In this study, a novel analytical algorithm is proposed to distinguish the optimal location and size of DGs in radial distribution networks based on a new combined index (CI) to reduce active power losses and improve system voltage profiles. To obtain the CI, active power losses and voltage stability indexes were used in the proposed approach. The CI index with sensitivity analysis was effective in decreasing power losses and improving voltage stability. Optimal DG size was determined based on a search algorithm to reduce active power losses. The considered scheme was examined through IEEE 12-bus and 33-bus radial distribution test systems (RDTS), and the obtained results were compared and validated in comparison with other available methods. The results and analysis verified the effectiveness of the proposed algorithm in reducing power losses and improving the distribution system voltage profiles by determining the appropriate location and optimal DG size. In IEEE 12 and 33 bus networks, the minimum voltage increased from 0.9434 p.u and 0.9039 p.u to 0.9907 p.u and 0.9402 p.u, respectively. Additionally, the annual cost of energy losses decreased by 78.23% and 64.37%, respectively.

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Section: Meta-innovative Methodsmentioning

confidence: 99%

A Novel Analytical Approach for Optimal Placement and Sizing of Distributed Generations in Radial Electrical Energy Distribution Systems

et al. 2021

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“…A distributed generation (DG) is a group of electrical distributed energy resources (DER) and energy storage activities operated by a range of small, grid-connected, or distribution system-connected devices [32,33].…”

Section: Dg •mentioning

confidence: 99%

DC Communities: Transformative Building Blocks of the Emerging Energy Infrastructure

2021

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Serious environmental concerns call for revolutionary solutions to cope with the harmful effects of the conventional energy landscape. Therefore, residential and commercial customers require cleaner and more reliable energy sources as they become more dependent on energy for daily and critical needs. In this case, transitioning to a cleaner energy economy is of paramount importance for both the environment and the utilities as well as the end-users. The desired transformation will require the deployment of massive amounts of clean energy sources. Many of these resources, such as solar photovoltaic (PV), provide electricity in the form of direct current (DC) that enables the return of DC grids to the electric power arena. The electric system has slowly transitioned to DC, mainly on the demand side. In recent years, modern electronic devices, lighting systems, and an increased number of appliances (≈22% of the residential and commercial loads) have adopted DC systems. Studies suggest that DC loads would account for more than 50% of the available loads in the next few years. Furthermore, the growing proliferation of electric vehicles influx is another example of a successful DC application. From this perspective, the viability of returning to the DC distribution system in the form of DC community grids is explored. We start by defining the DC community grid, which is followed by introducing the benefits of adopting DC at the distribution level. Finally, a summarizing outlook of successful pilot cases, projections of DC community deployment, barriers and concerns, strategies to address barriers and concerns, and suggestions for future research directions are presented. This perspective could shed new light on the building blocks of the transformed energy landscape for various stakeholders.

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“…Ganguly and Samajpati [53] utilized this method to control DGs' optimal management after connecting to the Network. Hybrid algorithms, such as a combined bee swarm and genetic algorithm for DG allocation developed by Mahmoud et al [54], have also been utilized in the specialized literature to enhance voltage control and decrease active and reactive power losses in the distribution network. GAMS software has also been used to propose and solve algebraic natural mathematical models [55].…”

Section: Introductionmentioning

confidence: 99%

Research on power system transient stability with wind generation integration under fault condition to achieve economic benefits

Mastoi

Tahir

Usman

et al. 2021

IET Power Electronics

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For a few decades, electric power growth and demand have increased globally. To fulfil this demand, distribution generators (DGs) have been installed in the power system. To get numerous benefits such as comprising reduction of power losses, improvement of (voltage, current, rpm) transient stability, leads to economic benefits. DGs integration in the distribution power system (DPS) was reported as an optimal generator placement (OGP) problem to maximize these benefits. This paper performs wind turbine (WT) integration while considering the internal generator's (rpm) transient stability under fault conditions. A power loss index (PLI) method is implemented to select potential candidate buses for generator placement. A self‐sorting analytical approach (SSA) is also used to determine the optimal bus and WT size. The IEEE 14‐bus DPS is used as the OGP test system to demonstrate the proposed method's effectiveness in terms of power losses reduction, system transient stability, and economic benefits. The IEEE 14 Bus system was considered using MATLAB with a 3.2 GHz processor to perform the said approach. WT integration suggested in case‐2 results in a 65.80% power losses reduction, which leads to a 60.88% enhancement of economic benefits of the DPS.

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A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks

Cited by 86 publications

References 48 publications

A Novel Analytical Approach for Optimal Placement and Sizing of Distributed Generations in Radial Electrical Energy Distribution Systems

A Novel Analytical Approach for Optimal Placement and Sizing of Distributed Generations in Radial Electrical Energy Distribution Systems

DC Communities: Transformative Building Blocks of the Emerging Energy Infrastructure

Research on power system transient stability with wind generation integration under fault condition to achieve economic benefits

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