State estimation in power distribution

Distribution network world over has been planned and designed with a fit and forget approach. Traditionally the feeder capacity is decided keeping future load growth into consideration. Because of this approach to distribution system, there is hardly any automation in place. The energy management system (EMS) in primary distribution substation (33 kV level) is lot simpler as far as the network computation functions are concerned.

However, the situation in the last decade has dramatically changed. A good proportion of generations are being added at this level. The demand characteristic is also changing with more electric vehicle charging stations being connected to the system. Such changes demand monitoring of the network for efficient operation and control of the network with high reliability. Some of the important network computation tools such as state estimation, optimal power flow will play a major role in this. The nature of the generation and demand are also intermittent requiring more stochastic approaches to network function.

The research undertaken by Dr Pal’s team focuses on modelling of unmetered demand as pseudo measurement for state estimation purpose, developing suitable algorithm for state estimation and selection of sensor location for real measurement. The research has been sponsored by UK Power Networks (earlier known as EDF Energy Network). The research outcome has influenced the network measurement principle of the sponsor. The research outcome have also been found useful by other network operator Scottish and Southern Energy and technology vendor SIEMENS.