Optimal Capacity Planning of Distributed Generators | An Unbalanced Multi-phase Optimal Power Flow based Approach for MV/LV Distribution Networks

Adnan Anwar (u. a.)

ISBN 10: 3659593737 / ISBN 13: 9783659593734

Published by LAP LAMBERT Academic Publishing, 2014

About this Item

Optimal Capacity Planning of Distributed Generators | An Unbalanced Multi-phase Optimal Power Flow based Approach for MV/LV Distribution Networks | Adnan Anwar (u. a.) | Taschenbuch | 160 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659593734 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 105066967

Bibliographic Details

• Title: Optimal Capacity Planning of Distributed Generators | An Unbalanced Multi-phase Optimal Power Flow based Approach for MV/LV Distribution Networks
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2014
• Language: English
• ISBN 10: 3659593737
• ISBN 13: 9783659593734
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 11D millimeters 220 millimeters width by 150 millimeters height by 11 millimeters depth
• Weight: 256 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

In this book, a method based on a sensitivity analysis and quadratic curve-fitting technique for power loss reduction in a low-voltage distribution area is proposed. For determining the optimum generation capacity of multiple DG units, a new methodology based on an unbalanced multi-phase optimal power flow (UM-OPF) is also presented. During the formulation of the UM-OPF, an optimisation algorithm is developed in Matlab and the unbalanced multi-phase power flow is solved using the Electric Power Research Institute’s (EPRI) software OpenDSS. To ensure a global minimum loss profile, adaptive weight particle swarm optimisation (AW-PSO) algorithm is used which shows better convergence profile compared with basic PSO algorithm. Validation of the proposed methodologies is also conducted using an exhaustive search algorithm. The results obtained from the proposed methods show that significant loss reduction is possible using multiple optimum sized DG units. To determine the optimum DG capacity, with varying generation and load, a cost minimisation planning methodology is also proposed. During the planning process, different DG technologies are considered.

About the Author

Adnan Anwar received his Master by Research degree from the UNSW Australia. He joined the University of Asia Pacific (UAP) as a lecturer in 2009. Currently, he is working as a postgraduate researcher in UNSW Australia. He has also worked with National ICT Australia (NICTA).