Advances in wide area analytics in grid operations

Recent advances in Wide Area Monitoring Systems (WAMS) have allowed utilities world-wide to learn more about the fundamental characteristics of their transmission networks. This has enabled them to revise and improve their mitigation plans. Although no two systems are the same, lessons learned in one network are transferrable to others, allowing WAMS systems and applications to be more effectively deployed and used to improve system stability. In India, the network system comprises the synchronized Eastern, North-Eastern and Western regions (known as NEW), and the Southern region, which is connected asynchronously to the NEW system. The aim by 2014 is to connect all the regions synchronously to share one national frequency [1]. The synchronized network has both DC and AC inter-regional connections and is characterized by widely dispersed generation and load-rich areas, where weather and loading patterns differ greatly. Due to the concentration of generation in the eastern region and large load centres located in central and western regions, there is bulk power transmission from east to west over long distances. Growth of Independent Power Producers (IPPs) and increased renewable generation are changing these power flow patterns. Summer peak demand in the north creates a generation deficit, increasing stress on the system. This paper describes how existing WAMS can augment the existing SCADA-EMS systems to alert operators to increasingly stressed conditions in the network, like those that occurred prior to the blackout on 31^st July 2012, where 48 GW of load was lost. During this event, certain forced outages on account of high voltage had initially caused overloading of inter-regional tie-lines. Following a number of line trips, bulk power flow got redirected leading to large inter-regional power swings. A suitably configured wide area measurement system (WAMS) would have been useful in highlighting stressed regions of the network in real time as well as - ndicating and characterizing disturbances such as generation and load loss.