Information Technology Reference
In-Depth Information
Keywords Generation scheduling
Unit commitment
Fuzzy-logic
Optimization
Production cost
1 Introduction
In recent decades, the demand for electricity has undergone an excessive increase
with the growth of industrialization. The power system is an interconnection of
generating units to load centers through high voltage electric transmission lines and
in general is mechanically controlled. It can be divided into three subsystems:
generation, transmission and distribution subsystems. Until recently all three sub-
systems were under supervision of one body within a certain geographical area
providing power at regulated rates (Mantawy et al.
1998
). Considering the recent
electrical network evolutions, the guarantee of stability and to ensure the service
continuity became currently the most interested subjects. In addition, these elec-
trical networks must be stable for all small variations as well as for several dis-
turbances cases which able to lead the system to a total voltage collapse (Abbassi
et al.
2012
; Moez et al.
2011
). Thus, different electrical network stability procedures
have been procured in order to found desired and acceptable voltage level at any
electrical network bus.
In order to provide cheaper electricity the deregulation of power system, which
will produce separate generation, transmission and distribution companies, is
already being performed. At the same time electric power demand continues to
grow and also building of the new generating units and transmission circuits is
becoming more dif
cult because of economic and environmental reasons. There-
fore, power utilities are forced to relay on utilization of existing generating units
and to load existing transmission lines close to their thermal limits. However,
stability has to be maintained at all times. Hence, in order to operate power system
effectively, without reduction in the system security and quality of supply, even in
the case of contingency conditions such as loss of transmission lines and/or gen-
erating units, which occur frequently, and will most probably occur at a higher
frequency under deregulation, a new control strategies need to be implemented.
As electrical systems have an important role in modern society, energy managers
are trying to ensure the proper functioning of generators while guaranteeing min-
imal cost. In this context, reliable power production is critical to the pro
tability of
electricity utilities. Power generators (units) need to be scheduled ef
ciently to meet
electricity demand. This dissertation develops a solution method to schedule units
for producing electricity while determining the estimated amount of surplus power
each unit should produce taking into consideration the stochasticity of the load and
its correlation structure (Attaviriyanupap et al.
2002
; Cheng et al.
2002
). This
scheduling problem is known as the unit commitment problem in the power
industry. Thus, solving Unit Commitment (UC) problem remains a challenge in
optimizing operational planning systems devoted for power production due to its
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