The power supply in remote areas has been usually provided by thermal power plants, usually diesel
generators. Recently the use of renewable resources to generate electricity and protect the environment
increased rapidly. Hybrid power systems may c
onstitute the most economical solution in many
applications in the near future, especially for electrification remote area.
Hybrid systems by definition contain a two sources or more of power generation (or storing) to supply
electricity to the loads. These sources may be pure traditional, traditional and renewable, or may be
renewable only.
This paper describes a case study for a remote area. It shows importance of using the hybrid system to
electrify a remote area. The suggested hybrid system consists of wind turbine, PV, traditional generator,
and batteries to supply a load (72 kWh/d). A real wind data related to Alsukhna near Homs is used. We
perform a technical and economical analysis using Homer to determine the optimal design of a hybrid
System for a Reliable Load Supply in Remote Area with least cost.
This study has reached to that ANN (5-9-1) (five neurons in input
layer_nine neurons in hidden layer _ one neuron in output layer) is the
optimum artificial network that hybrid system has reached to it with
mean squared error equals (1*10^-4) (0.7
m3/sec), where this software
has summed up millions of experiments in one step and in limited time, it
has also given a zero value of a number of network connections, such as
some connections related of relative humidity input because of the lake
of impact this parameter on the runoff when other parameters are
avaliable.
This study recommend to use this technique in forecasting of
evaporation and other climatic elements.
