State-of-the-Art Approach to Economic Load Dispatch on Nigerian HydroThermal Electric Power System: A Review

Abstract

The need to efficiently minimize the cost of power generation of fossil
fueled fired-plants is indeed a thing of great concern in grid energy
management. One way to achieve this is to optimally schedule the
power output of all the connected thermal plants on the system.
Recently, population-based artificial intelligence (AI) algorithms are
promising alternative means of addressing ELD problems as against
the conventional lambda iterative technique which had been
previously applied. The adoption of these AI techniques is largely due
to possession of good processing speed, mild computational
complexity coupled with less computational time. This paper therefore
presents various AI algorithms that had been used and identifies types
of ELD problems so far addressed. Based on the review, diverse
algorithms had been used to address convex ELD problem, however
scanty works have been referenced on non-convex ELD, even cases of
emission of gases, multiple fuel option, spinning reserve requirement
and ramp rate limit are yet to be researched on Nigerian hydrothermal plants. It was also observed that less attention has been
drawn to aspect of reactive power dispatch on Nigerian grid. It is
hoped that this review will be an eye opener to Nigerian researchers
as regards other aspects of ELD problems that had received less
attention.