Optimal Placement And Sizing Of Distributed Generation Considering Costs Of Operation Planning

Loo, Soon Lii (2017) Optimal Placement And Sizing Of Distributed Generation Considering Costs Of Operation Planning. Project Report. UTeM, Melaka, Malaysia. (Submitted)

Text (24 Pages) Optimal Placement And Sizing Of Distributed Generation Considering Costs Of Operation Planning.pdf - Submitted Version Download (550kB)

Abstract

Distributed Generation (DG) can be defined as power generation at the distribution site or on-site generation. DG technology has been growing rapidly in industries as this technology can increase the overall efficiency to the power systems. The optimal placement and sizing of DG is vital as it significantly affects the distribution system. Improper placement and sizing can lead to power losses and interrupt the voltage profile of distribution systems. Studies have been done to solve the DG placement and sizing problem considering various factors and one of the common factor is minimising the power losses. However, it is not adequate by only considering the power losses, whereas, the costs of the generation, investment, maintenance and losses of the distribution system must be taken in consideration. Otherwise, it will create disadvantages after the installation of DG such as the system with DG is generating the same amount of energy but higher costs or losses compared to the conventional generation. In this research, DG chosen to be study is Photovoltaic (PV) type which are Monocrystalline and Thin-film. Costs of operation planning with respect to the power losses is considered which include the costs of investment, maintenance, power loss and generation are determine for optimal placement and sizing of DG. Proposed method algorithm Improved Gravitational Search Algorithm (IGSA) is used in the MATLAB environment to find the optimal placement and sizing of DG and is tested with the IEEE 34-bus system and IEEE 69-bus system. The performance of IGSA is then compared with Gravitational Search Algorithm (GSA) and Particle Swarm Optimisation (PSO) to find out which algorithm gives the best fitness value and convergence rate. Both Monocrystalline PV and Thin-film PV are compared based on the results obtained. The purpose of this report is to identify the operation planning cost based on the optimisation results and improves the optimal placement and sizing of DG in future, in order to provide maximum economical, technical, environmental benefits and increase the overall efficiency to the power system.

Actions (login required)

View Item