TY  - JOUR
T1  - Optimum Power Production of Small Hydropower Plant (SHP) using
Firefly Algorithm (FA) in Himreen Lake Dam (HLD), Eastern Iraq
AU - Hammid, Ali Thaeer AU - Sulaiman, Mohd Herwan Bin AU - Kadhim, Atheer Ahmed 
JO  - Research Journal of Applied Sciences
VL  - 12
IS  - 10
SP  - 455
EP  - 466
PY  - 2017
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2017.455.466
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2017.455.466
KW  - Himreen Lake Dam
KW  -small hydropower plants
KW  -particle swarm optimization
KW  -firefly algorithm
KW  -swarm intelligence
KW  -power production optimization
AB  - In developing countries, the amount of electrical power production is lower than the request of power
or load. Therefore, sustaining the stability of optimum power production system becomes a problem.
Sometimes, the development of the correct quantity of load demand is necessary in order to keep the system
of power production steady. Thus, the addition of Kaplan turbine into Small Hydropower Plant (SHP) is verified
to explore its applicability. This study focuses on the improvement of optimization model by applying particle
swarm optimization and firefly algorithm methods in order to get a stable power production utility at its maximum
level. Furthermore, it investigates on the minimization of utility loss in power production from the hydropower
systemn which is done by optimizing the variables of operation control in the hydropower plant at Lake
Himreen-Diyala Dam. The variables mentioned are net turbine head, rate of water flow and power production
which had been gathered in the data during a research throughout a 10 years period. Moreover, this study
investigates the uncertainties of input and output operation of small hydropower plant, the designing of the
entire 3570 experiments and the data collected from the observation on the performance of the nonlinear plant
model. The results obtained from these two methods, namely Firefly Algorithm (FA) and Particle Swarm
Optimization (PSO) are compared. The inferences for general comparisons are created through several behavior
indicators. The behavior indicators illustrate that FA’s performance is better than PSO’s performance in some
fields. At the end, the results show the strength of FA as well as its efficiency and superiority.
ER  -