Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm

Candelo-Becerra, John E.; Riaño, Helman Enrique Hernández

doi:10.15446/dyna.v82n192.48573

Cited by 12 publications

(5 citation statements)

References 24 publications

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“…Karatepe et al 25 used an optimal power flow‐based approach to minimize loss and improve the voltage. Candelo‐Becerra et al, 26 Devabalaji et al, 27 Injeti et al, 28 used the Bat algorithm to minimize power loss. In Reference 18, the proposed method starts by selecting candidate buses to install the DG units on the system, prioritizing buses that are sensitive to voltage profile, and improving the voltage stability margin.…”

Section: Introductionmentioning

confidence: 99%

Distributed wind and solar power for grid sustainability and emission reduction

Noorollahi

Kalantari

Saifoddin

et al. 2021

Env Prog and Sustain Energy

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This article intends to maximize the amount of solar and wind power produced while minimizing the tested network's annual energy loss. It also wants to improve the voltage profile and reduce the dependence on the upstream network. Two types of distributed generation sources, that is, wind DGs and solar DGs, are investigated. In this article, the network loads vary according to the local consumption pattern. This research shows that the optimal utilizing of solar and wind distributed generation sources causes energy loss to decrease by about 43% and 94%, respectively. Besides, the grid will receive 1109.49 GWh of energy from the upstream power grid without distributed generation sources. In contrast, solar and wind generation sources receive only 801.47 and 125.84 GWh, respectively. Additionally, in solar and wind scenarios, micro‐grid sends 71.62 and 102.42 GWh energy to the upstream network. Also, by calculating the emission reduction, it was observed that by installing 465.45 MW of the wind turbine units in the area under consideration, the country's CO2 equivalent is reduced by 754,586 tons, and the country's primary energy is reduced by 263,916 TOE.

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Section: Introductionmentioning

confidence: 99%

Distributed wind and solar power for grid sustainability and emission reduction

Noorollahi

Kalantari

Saifoddin

et al. 2021

Env Prog and Sustain Energy

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“…DG placement strategies aim to maximize the utilization of these clean energy sources by locating generators in areas with abundant and consistent renewable resources. This reduces greenhouse gas emissions and contributes to a more environmentally friendly and sustainable energy mix [10].…”

Section: Integration Of Renewable Resourcesmentioning

confidence: 99%

Integration of Energy Storage Systems in Radial Distribution Networks for Enhanced Reliability and Efficiency

2024

Acta Energetica

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The increasing demand for electrical energy, coupled with the global push for sustainability, has necessitated a transformative shift in power distribution systems. Distributed generation (DG) sources, often based on renewable energy technologies, are being integrated into radial distribution systems to enhance resilience, reduce losses, and promote green energy. This study presents a comprehensive numerical simulation and design approach to identify the optimal placement of DG sources within radial distribution networks. The proposed methodology begins by characterizing the existing distribution system, considering load profiles, fault analysis, and network topology. Through advanced load flow analysis and optimization algorithms, potential locations for DG sources are identified. The optimal size and type of DG units (e.g., solar photovoltaic, wind turbines, or microturbines) are determined to maximize system performance while adhering to technical constraints and economic considerations. Incorporating real-world data and weather patterns, the simulation evaluates the impact of DG integration on voltage profiles, power losses, and system reliability. Different scenarios are assessed to account for varying load conditions and generation outputs. Furthermore, this research addresses the challenges of grid stability and protection coordination in the presence of DG units, ensuring that the distribution system remains robust against faults and disturbances. The outcomes of this study offer valuable insights into the effective deployment of DG sources in radial distribution systems. By optimizing their placement, utilities and stakeholders can enhance grid resilience, reduce carbon emissions, and harness the benefits of renewable energy sources. The results also provide a foundation for decision-makers to make informed investments in sustainable energy infrastructure. In conclusion, this research contributes to the ongoing efforts to transform http://actaenergetica.org traditional radial distribution systems into modern, adaptive, and eco-friendly grids by leveraging numerical simulations and design techniques for the optimal integration of distributed generation sources.

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“…The algorithm mimics the echolocation behaviour of micro‐bats . The performance of SBA in the optimisation of distributed generations' placement and sizing with load enhancement in a radial distribution systems is investigated in Yammani et al In Candelo‐Becerra and Hernández‐Riaño, the optimal sizes, numbers, and locations of DGs in radial DNS are achieved with the use of bat algorithm. A hybrid of SBA and loss sensitivity factor (LSF) is proposed for finding optimal sizes and locations of capacitor banks respectively.…”

Section: Optimisation Algorithms For Dg Allocation Planningmentioning

confidence: 99%

Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

2020

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Summary Integrating renewable energy hybrid distributed generation (REHDG) into distribution network systems (DNSs) has become increasingly important because of various technical, economic, and environmental advantages accruing from it. However, the output power of REHDGs from photovoltaic (PV) and wind is highly variable because of its dependency on intermittent parameters such as solar irradiance, temperature, and wind speed. Such variability of generated power from large‐scale REHDGs or load introduces small signal instabilities (oscillations). Meanwhile, different locations of integration and sizes of REHDGs in the DNS affect the system oscillation modes by either improving or depriving the small‐signal stability (SSS) of the network. Consequently, a significant number of research has been conducted on the planning of optimal allocation of REHDGs in DNS. In this regard, this paper reviews the existing planning models, optimisation techniques, and resources' uncertainty modelling employed in REHDGs allocations in terms of their capability in obtaining optimal solutions and enhancing SSS of the system. Planning models with optimisation algorithms are evaluated for modelling renewable resource uncertainties and curtailing SSS variables. Research works on planning of optimal allocation of these generations attain minimum cost, but were unable to satisfy the SSS requirements of the system. The existing models for the planning and design of optimal timing, sizing, and placement of REHDGs will need to be improved to optimally allocate REHDGs and satisfy the SSS of the DNS after the integration.

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Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm

Cited by 12 publications

References 24 publications

Distributed wind and solar power for grid sustainability and emission reduction

Distributed wind and solar power for grid sustainability and emission reduction

Integration of Energy Storage Systems in Radial Distribution Networks for Enhanced Reliability and Efficiency

Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

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