An Optimal Accommodation of Distributed Generation in Power Distribution Systems

Babu, B. Kiran; Sydulu, M.

doi:10.1109/npsc.2018.8771743

Cited by 1 publication

(3 citation statements)

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“…Optimal emplacement and sizing of DG units in TPDN have been addressed by several academic/scientific researchers through distinct approaches. The state‐of‐the‐art methods may be classified into four categories: (a) Analytical Expressions (AEs), (b) Numerical Methods (NMs), (c) Meta‐heuristic Methods (MMs), and (d) Analytical Expressions + Meta‐heuristic Methods (AEMMs) . Analytical Expressions (AEs) : These methods use the AEs to find either DG location or DG size, and using search technique its corresponding optimal DG size or optimal location will be identified.…”

Section: Introductionmentioning

confidence: 99%

“…Meta‐heuristic Methods (MMs) : The MM algorithms initiate the optimisation process with a set of random candidate solutions and improve them over the course of iterations. To improve the quality of solutions, authors have proposed various meta‐heuristics techniques to the multi‐objective problem of the power distribution network.…”

Section: Introductionmentioning

confidence: 99%

“…A shuffled Bat algorithm has been introduced to address the OADG problem by considering loss minimisation, voltage profile improvement, and line flow capacity as multi‐objectives. A tri‐objective function that includes minimisation of network losses, better voltage profile, and improvement of the voltage stability has been solved with help of GA‐PSO, quasi‐oppositional teaching learning‐based optimisation (QOTLBO), comprehensive teaching learning‐based optimisation (CTLBO), improved elephant herding optimisation (IEHO), and multi‐verse optimisation (MVO) algorithm . A chaotic artificial bee colony (CABC) algorithm has been utilised to minimise the real and reactive power loss, improve the VSI, minimisation of MVA capacity index, minimisation of maximum voltage drop, and minimisation of DG power resources cost.…”

Section: Introductionmentioning

confidence: 99%

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A solution to multi‐objective optimal accommodation of distributed generation problem of power distribution networks: An analytical approach

Babu

Sydulu

2019

Int Trans Electr Energ Syst

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Summary Distributed generation (DG) technologies are considered an integral part of power distribution networks. The desired performance of power distribution networks can be obtained through the optimal accommodation of DG units. This paper proposes an analytical method called Branch Loss Bus Injection Index (BLBII) to solve the multi‐objective optimal accommodation of distributed generation (MO‐OADG) problem of power distribution networks. Four objectives were considered in the optimisation model: energy loss minimisation, overall bus voltage deviation minimisation, overall voltage stability margin maximisation, and energy not served (ENS) minimisation. A multiple criteria decision‐making method such as the analytical hierarchy process is employed to optimise the weight coefficients of the individual objectives as the optimisation problem is solved based on the weighted‐sum method. The proposed method is demonstrated on benchmark radial power distribution networks of IEEE 33‐bus and INDIAN 85‐bus. The applicability of the proposed BLBII has been validated, and results are presented.

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