Optimal Active Power Loss with Feeder Routing Collaborate Distributed Generation Allocation and Sizing in Smart Grid Distribution
Phatcharasak Phawanaphinyo, Narongdech Keeratipranon, Chaiyaporn Khemapatapan
Available Online January 2017.
- https://doi.org/10.2991/icefs-17.2017.48How to use a DOI?
- Minimal active power loss, Backward Forward Sweep Method, Harmony Search Algorithm, Artificial Bee Colony Algorithm, Particle Swarm Optimization Algorithm
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/icefs-17.2017.48 ID - Phawanaphinyo2017/01 ER -