Optimal Placement and Sizing of Distributed Generation for Power Loss Reduction Using Particle Swarm Optimization

Bhumkittipich, Krischonme; Phuangpornpitak, N.

doi:10.1016/j.egypro.2013.06.759

Cited by 79 publications

(52 citation statements)

References 3 publications

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“…To decide the optimal combination for HRES while minimizing LCE [17] Jul-07 An original hardware-in-the loop (HIL) solution Optimization of the frequency control mechanism of autonomous microgird with battery ESS [61] May-12 PSO Particle swarm optimization for designing Optimal design of LC filter and its controlling parameters in Autonomous and GridConnected Modes [41]; to reduce costs in planning with ε-constraint method [42] Mar-11; Jan-14 Particle swarm optimization for sizing To find optimal sites and corresponding sizes of renewable resources -to reduce the power loss in the radial distribution systems [45]; hybrid PSO with GSA for mutidistributed planning [90] Jul-05; Apr-13…”

Section: Methods Of Optimization Optimization Objectivesmentioning

confidence: 99%

“…Whereas, siting deals with the problem of the placement of these generators on the distribution bus (as long transmission is not characteristic of microgrids) so as to minimize the transmission losses and to deliver the maximum quality power to the load. Many research works have been done in this field by applying various optimization methods [45][46][47].…”

Section: Applications Of Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Optimization in microgrids with hybrid energy systems – A review

Fathima

Palanisamy

2015

Renewable and Sustainable Energy Reviews

551

214

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Section: Methods Of Optimization Optimization Objectivesmentioning

confidence: 99%

Section: Applications Of Optimizationmentioning

confidence: 99%

Optimization in microgrids with hybrid energy systems – A review

Fathima

Palanisamy

2015

Renewable and Sustainable Energy Reviews

551

214

View full text Add to dashboard Cite

“…The algorithm was successfully tested on a modified IEEE 14 bus test system. Bhumkittipich et al [32] used the Particle swarm optimization method to determine the place of distributed generation within the distribution network with the aim of active power losses reduction.…”

Section: Non-traditional Methods For Determining Optimal Location Andmentioning

confidence: 99%

Review of Non-Traditional Optimization Methods for Allocation of Distributed Generation and Energy Storage in Distribution System

Šipoš¹,

Klaić²,

Fekete³

et al. 2018

Teh. vjesn.

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Abstract:The integration of distributed energy sources transforms passive distributed grid, in which the energy flows only in one direction (from the source to the consumer), in an active one, in which energy flows in both directions. To maximize positive impacts, which distributed generation (DG) can provide to the distribution network, it is necessary to determine the optimal allocation of distributed generation. The optimal allocation can be determined by using the optimization method. There are two main categories: exact methods (traditional) and heuristic (non-traditional) methods. Exact methods search for global optimum while heuristic methods achieve satisfactory solutions with greater computation speed. This paper gives a brief review of non-traditional methods used for determining optimal location and optimal power of DG with the aim to reduce real power losses and to improve voltage characteristics. Also, there is a review of the application of those methods in determining the optimal power, optimal location and optimal cycle of charging/discharging of electrical energy storage systems.

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“…These constraints ensure that the algebraic sum of all incoming and outgoing power flow over Downloaded by [University of Tasmania] at 10:00 01 October 2015 the distribution system should be equal (Aman et al 2012;Bhumkittipich and Phuangpornpitak 2013); thus,…”

Section: Equality Constraintsmentioning

confidence: 99%

Genetic single objective optimisation for sizing and allocation of renewable DG systems

Hassan

Fahmy

Nafeh

et al. 2015

International Journal of Sustainable Energy

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The optimal design of renewable-based distributed generations (DGs) is a challenging issue in order to maximise their benefits and to overcome power quality problems. Therefore, this paper proposes a methodology for optimal allocation and sizing of renewable DG units to minimise total power losses over radial distribution systems. The planning problem is formulated as a single objective nonlinear mixed integer-constrained optimisation problem and is solved by using the augmented Lagrangian genetic algorithm (ALGA) by combining the objective function and the nonlinear constraints. In that case, the ALGA solves a sequence of sub-problems where the objective function penalises the constraints violation in order to obtain the best solution. The proposed technique is applied to IEEE radial test systems including 33-bus, 69-bus and 119-bus and is implemented with different scenarios including all possible combinations and various types of renewable DG units to prove the effectiveness of the proposed methodology.

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Optimal Placement and Sizing of Distributed Generation for Power Loss Reduction Using Particle Swarm Optimization

Cited by 79 publications

References 3 publications

Optimization in microgrids with hybrid energy systems – A review

Optimization in microgrids with hybrid energy systems – A review

Review of Non-Traditional Optimization Methods for Allocation of Distributed Generation and Energy Storage in Distribution System

Genetic single objective optimisation for sizing and allocation of renewable DG systems

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