Self-intelligent active management system for electrical distribution networks with photovoltaic systems

The amount of small-scaled renewable energy sources, such as photovoltaic systems and small wind turbines, is anticipated to increase on the low-voltage distribution networks, in order to reduce the greenhouse gas emissions. However, the growth of the renewable energy sources on the network may result in the voltage rise and voltage unbalance, hence leading to the deterioration of the network efficiency, overloading of the transformers, nuisance tripping of the protection system and malfunction of the customers´ equipment. To ensure an effective operation of the distribution network with the increased penetration of renewable energy sources, a self-intelligent active management system is developed and installed on the network, to mitigate voltage rise and voltage unbalance. This paper gives an overview of an experimental set up of the low voltage network and the active management system at Universiti Tunku Abdul Rahman in Malaysia. Experimental results are presented in this paper to illustrate the effectiveness of the proposed self intelligent active management system (SAMS) in mitigating voltage rise and voltage unbalance under intermittent PV output power penetration.