Page 233 - Mathematical Models and Algorithms for Power System Optimization

Optimization Method for Load Frequency Feed Forward Control 225

In Section 7.3, an identification method is used to build the model of load disturbances of the
power system based on time series ananlysis, in which the process to identify the order of model
and the method to estimate parameters are given.

In Section 7.4, the power system equivalent model is constructed; blocks (govermor, prime
mover, generator) of power plant are taken into consideration except for the excitation because
only the small disturbance of the load is considered.

In Section 7.5, hierarchical decomposition principles are utilized to construct all levels of state
estimators to estimate or track the disturbances. A hierarchical estimator and a central predictor
are constructed according to the decomposition and aggregation principle. In both local and
central estimators, the Kalman filters are used to filtrate the random load fluctuations. The
central estimator (combined with load prediction model) can provide system relative speed and
load prediction based on the on-line measurements of power and frequency.
In Section 7.6, to compensate for the load error prediction, a load frequency controller,
called an error predication compensator, is derived via the invariance principle.
Both the absolute compensator for the thermal unit and the approximate one for
the hydro unit give much better performance than the conventional integral load
frequency controller.

Section 7.7 settles the transformation methods among mathematical models required for
identification, estimation, and control, including the transformation of difference equation
into differential equation, the transformation of differential transfer function into difference
transfer function, in which proposes a series of new transformation methods of practical
significance.

Section 7.8 illustrates the results of simulation on a simple two-unit system and a more
complicated five-unit system by the digital simulation of load frequency control based on
stochastic tracking, which proves that the control method proposed in this chapter is feasible.
The tracking control simulation test more realistically reflects the whole system control
process. The proposed load frequency controller can effectively control different types of
disturbances in the power system, with better performance than the widely used integral
feedback controllers.

7.2 Basic Ideas of Modeling

It is well known that the various control objects of the power system are widely distributed. It is
obviously uneconomical and unreasonable to realize a large amount of information exchange
among various control objects. Moreover, the linear optimal controller is only optimal for some
special type of load disturbance. Because load disturbance of the power system is a kind of