Page 296 - Mathematical Models and Algorithms for Power System Optimization

288 Chapter 8

In the second scenario, the main reason is that the power system is a large interconnected
system with strong interaction; the impact of local disturbance will gradually spread to the rest
of the system after the first swing cycle, making the entire system oscillate. This type of
oscillation sometimes will be aggravated due to the absence of the system damping for various
reasons, resulting in some local generators’ loss of synchronism with the system. For instance,
if the stabilization measures taken at the point of failure are not reasonable (their strength or
switching time), these measures are used in the first swing cycle; in the later system oscillation,
the requirements for local stability will become unmatched with the one for overall stability;
thus, it is likely to aggravate the oscillation, resulting in system breakdown.
In view of the first scenario, to keep the system stable (once the fault is removed as quickly as
possible in the initial stage), the only feasible remedial measure to prevent the synchronous
generator from desynchronizing with the rest of the system within the first swing period is to
brake the synchronous generator as soon as possible, so as to absorb the excess energy obtained
during the fault and to avoid loss of synchronism in the first swing period, thus minimizing its
impact on the rest of the system.

In view of the second scenario, the local generator after the first swing period, as a result of
intense interaction among the parts of the system, the impact of local fault will spread to the
overall system, putting the system in danger of disconnection at any time due to its severe
oscillation, then it is still necessary to continue taking effective control measures in due time at
each part of the system. However, these stability measures should not only be favorable for
local stability but also promote overall stability.

Nevertheless, it is difficult to obtain all information of the system because the local parts in the
system provide only limited local information. Normally, it is very difficult to make a decision
and control in such a way as to realize the consistency between a local and overall stability goal
based only on local information.

8.2.2 Purposes of Introducing an Observation Decoupled State Space

To overcome the previously mentioned difficulties (the difficulty to obtain all information of
the system based on limited local information, and the difficulty to make decisions and controls
that harmonize local stability with global stability based on local information) and to make the
local stability control in line with the limited local information favorable to overall system
stability, it is required to decouple local information of the whole system and eliminate the
impact of the rest of the system on local information, so as to reach accordance between goals of
local and overall stability during local stability control in line with local decoupled observation
information.

This chapter attempts to achieve this purpose of decoupling by introducing a new state space,
that is, observation decoupled state space. The system state can be estimated by local