Optimal Active Power Loss with Feeder Routing Collaborate Distributed Generation Allocation and Sizing in Smart Grid Distribution

DOI

10.2991/icefs-17.2017.48How to use a DOI?

Keywords

Minimal active power loss, Backward Forward Sweep Method, Harmony Search Algorithm, Artificial Bee Colony Algorithm, Particle Swarm Optimization Algorithm

Abstract

The Smart Grid (SG) has widely supported the electric power from the Distributed Generation (DG). It becomes a practical standard to generate the electric power from a renewable energy into the distribution system to compensate for the power demand, especially in the peak time. However, the advancement of the SG continuing with the classical problem of active power loss as the traditional grid. This research aims to solve the active power loss problem by analyzing the elements and study to solve, in the scope of the organization that provides the electrical power. In order to solve the problem, the solutions can be achieved by feeder routing with adjusting cost Dijkstra's algorithm, afterward decided the allocation and sizing of DG by using the Evolutionary Computing (EC) which are Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) algorithms. The experiment evaluates the performance of the algorithm using power flow analysis, Backward/ Forward Sweep Method, on the IEEE 33-bus system. From the experimental result, the PSO provides the best performance. The overall active power loss in the case 3 DGs was reduced from 202.67 to 52.29 kW, representing 74.20% reduction.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Phatcharasak Phawanaphinyo
AU  - Narongdech Keeratipranon
AU  - Chaiyaporn Khemapatapan
PY  - 2017/01
DA  - 2017/01
TI  - Optimal Active Power Loss with Feeder Routing Collaborate Distributed Generation Allocation and Sizing in Smart Grid Distribution
BT  - Proceedings of the 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)
PB  - Atlantis Press
SP  - 387
EP  - 392
SN  - 2352-5428
UR  - https://doi.org/10.2991/icefs-17.2017.48
DO  - 10.2991/icefs-17.2017.48
ID  - Phawanaphinyo2017/01
ER  -