Optimal sitting and sizing of renewable distributed generations in distribution networks using a hybrid PSOGSA optimization algorithm

Tolba, Mohamed A.; Tulsky, Vladimir N.; Diab, Ahmed A. Zaki

doi:10.1109/eeeic.2017.7977441

Cited by 23 publications

(12 citation statements)

References 12 publications

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“…Although the result obtained is encouraging, if network reconfiguration was undertaken after integrating distributed generations into the existing distribution system, the power losses might be significantly minimized. The author of [14] focuses on the optimum sizing of distributed generation using particle swarm optimization to increase distribution network performance. By minimizing active power loss and improving the voltage profile of each bus in the system, optimal location and sizing play a significant role in enhancing system efficiency.…”

Section: Related Workmentioning

confidence: 99%

Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning

et al. 2022

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Electrical energy is critical to a country’s socioeconomic progress. Distribution system expansion planning addresses the services that must be installed for the distribution networks to meet the expected load need, while also meeting different operational and technical limitations. The incorporation of distributed generation sources (DGs) alters the operating characteristics of modern power systems, resulting in major economic and technical benefits, such as simplified distribution network expansion planning, lower power losses, and improved voltage profile. Thus, in this study, an analytical method is used to design the expansion planning of the Addis North distribution network considering the integration of optimal sizes of distributed generations for the projected demand growths. To evaluate the capability of the existing Addis North distribution network and its capability to supply reliable power considering future expansion, the load demand forecast for the years 2020–2030 is done using the least square method. The performance evaluation of the existing and the upgraded network considering the existing and forecasted load demand for the years 2030 is done using ETAP software. Accordingly, the results revealed that the existing networks cannot meet the existing load demand of the town, with major problems of increased power loss and a reduced voltage profile. To mitigate this problem, the Addis North feeder-1 distribution network is upgraded and for each study case, the balanced and positive sequence load flow analysis was executed and the maximum total real and reactive power losses were found at bus 29. The result shows that the upgraded network of bus 29 was the optimal location of DG and its size was 9.93 MW. After the optimal size of DG was placed at this bus, the real and reactive power losses of the upgraded networks were 0.2939 MW and 0.219 MVAr, respectively. At bus 29 the maximum power losses reduction and voltage profile improvements were found. The active and reactive power losses were minimized by 21.285% and 19.633% respectively and the voltage profiles were improved by 8.78%. Thus, in the predicted year 2030, DG power sources could cover 61.12% of the feeder-1 power requirements.

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Section: Related Workmentioning

confidence: 99%

Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning

et al. 2022

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“…Such hybrid methods include combining optimization and evaluation methods to improve the performance by iterations 156 . Besides, meta‐heuristic algorithms show high‐level availability in combining with other meta‐heuristic algorithms to complement one another, such as GA‐PSO 159,164 and PSO‐GSA 166 . They have been proven to show higher robustness and quality compared with individual methods.…”

Section: Algorithmsmentioning

confidence: 99%

Modelling, applications, and evaluations of optimal sizing and placement of distributed generations: A critical state‐of‐the‐art survey

Yang

Chen

et al. 2020

Int J Energy Res

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Summary Distributed generation (DG) has attracted significant attention due to its great potential for enhancing economical and technical performance of power systems and reducing dependence on fossil fuels. Optimal sizing and placement are critical for stimulating such potential, about which a considerable number of models and algorithms have been proposed in past literature. This paper attempts to undertake a comprehensive review on optimal sizing and placement of DG via a systematic methodology procedure, including definition and classifications of DG, modelling and problem formulation with different technical and economic criteria, and summary of optimization algorithms. Common features and distinctive characteristics of both models and methods are identified, followed by evaluations and comparisons based on their practical performance in various test systems. Selection of DG techniques with respect to application scenarios, indispensable and optional considerations in DG planning models, and pros and cons of algorithms are listed in tables for a clearer understanding. Lastly, a total of 107 algorithms are addressed, which are classified into five categories. Particular, hybrid methods can deal with complex engineering problems with multiple objective functions and constraints most effectively and robustly. Future research trends are also highlighted with the aim of providing a comprehensive and state‐of‐the‐art survey for researchers, engineers, and other stakeholders.

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“…An efficient and standard power flow method is required for real-time applications such as switching, planning, load shading, and optimization of network. Load flow analysis of radial feeders is done using the Backward/Forward Sweep (BFS) algorithm [15].…”

Section: Formulation Of Objective Problemmentioning

confidence: 99%

Photovoltaic Generation Integration with Radial Feeders Using GA and GIS

Getie

Gessesse

Workneh

2020

International Journal of Photoenergy

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The electric power generated from different electricity sources are not used efficiently by end users in the world. This is due to the loss of power supplied in the case of electricity transmission and distribution to residential, commercial, and industrial loads. Even if the loss of power in the power system cannot be avoided 100%, it should be reduced to the minimum optimal value. The loss of power in the radial feeders can be minimized using an optimally allocated photovoltaic (PV) generation system by considering the information of geography, solar irradiance of the site, and space availability, which should not have shadow from large buildings and trees. The PV generation system eliminates the problem of power demand by enhancing the capacity of the power network as well as by reducing the depletion and consumption of fossil fuel resources. To reduce power loss and improve system loading capacity for demand response, the integration and finding the optimal place of photovoltaic generation take high concern from power system operators and technicians. The optimal allocation of PV has been done using the Genetic Algorithm (GA) for optimization of a multiobjective function with different constraints. The main objective of this paper is to minimize the power loss of the radial distribution networks by maintaining the phase voltage of the load in balance and improving the drop in voltage along the phase. So, GA is used to determine the best location and capacity of PV generation that can reduce the loss of power in the system. The IEEE-33 bus system is used to test the proposed method. Generally, using the GA and GIS methods results in a high accuracy for optimal placement of PV generation in the IEEE-33 bus radial feeder and enables to reduce the loss of power during transmission and distribution by maintaining the power quality for consumers.

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Optimal sitting and sizing of renewable distributed generations in distribution networks using a hybrid PSOGSA optimization algorithm

Cited by 23 publications

References 12 publications

Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning

Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning

Modelling, applications, and evaluations of optimal sizing and placement of distributed generations: A critical state‐of‐the‐art survey

Photovoltaic Generation Integration with Radial Feeders Using GA and GIS

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