Publication: Optimal location and sizing determination of distributed generation for loss minimization and voltage stability improvement using immune evolutionary programming
Date
2017
Authors
Sharifah Munirah Mahmor
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Distributed generation (DG) in a power system is real power generation near the point of consumption. DG units can be fossil fuel generators like coal power plant or renewable sources like solar photovoltaic, wind turbine, etc. Normally, DG units generate small amount of electric power compared to the conventional generating units like coal power plants, large hydro stations, etc. This is why they are located near to consumers. In future ahead, the quantity of DG units connected to power systems grid has increased dramatically due to the deregulation by the governments. Many countries have started to reduce their dependency on fossil fuel generating units as they want to reduce the carbon emission produced from the electric power generation. It is important to ensure the optimal location and suitable size for DG units to be installed at power system grids. Otherwise, the connection may disturb the power system stability and security. The power injected to a system must be balanced with the power absorbed by the system. In order to find the appropriate placing and sizing of DG units in a power system, a project proposed to implement a hybrid optimization technique termed as immune evolutionary programming (IEP) in DG installation. Three DG units with different sizes have been installed in the IEEE 26- bus test system. And three cases have been introduced to study the performance of IEP algorithm. The difference between these three cases is at their load level. Case I has no load increment, Case II has 50 % load increment and Case III has 100% load increment. Voltage steadiness is also included in order to find a solution to DG installation issues. It is ensured that the voltage at all buses in the 26-bus system is within the allowable range (0.95 p.u. to 1.05 p.u.) after the DG units are installed. Furthermore, the power factor also maintained to be 0.85 p.u. It is found that the IEP algorithm effectively solved the DG installation problem for the all three cases.
Keywords:
Distributed Generation (DG), Evolutionary Programming (EP), Artificial Immune System (AIS), total loss minimization, voltage stability control.
Description
TK1006.S52 2017
Keywords
Distributed generation of electric power , Electric power system stability