Intelligent Based wind-solar Hybrid power Generation system for Rural Energy solution in Ethiopian In case: Kulumsa Village
Domain:
environment and energyRecord type:
paper
Creator:
Asn
Editor:
Kem
Publisher:
Nat
Host:
Electrical energy is a key factor for socio-economic development, improved health care and
living standards of human being. Moreover, the benefit is highly exceled if the electricity is
generated with Renewable Energy sources (RES). However, RES such as solar PV system have
low conversion efficiencies, but have high fabrication cost and are not reliable due to their
intermittent nature. Thus, an appropriate control system and a management strategy is required
to generate power at optimum efficiency and supply the loads. This thesis work presents the
intelligent based PV-Wind hybrid power generation system (IHPGS) with battery energy
storage system (ESS) in selected sites of rural areas. A power management algorithms based
on Artificial Intelligent Techniques (AITs) is proposed. To enhance efficiency and ensure
optimum power from RES, Adaptive Neural-Fuzzy Inference System (ANFIS) based
Maximum Power Point Tracking (MPPT) algorithm is employed for PV generation system
(PGS) and Fuzzy logic Controller (FLC) based MPPT for wind power generation system
(WGS). Moreover, this thesis work describes the implementation of Fuzzy controlled power
management system (FPMS) to manage the power flow to the system. Using metrological data
of the studied location, the developed system is tested and simulated in MATLAB-Simulink
under different scenarios. The obtained result show that the proposed algorithm can maximize
the conversion efficiency of both PV and WGS and ensures effective utilization of the
generated power. The total power generated from PGS without any controller is 59.7kW and
due to implementation of ANFIS MPPT for PGS is 86.6kW which is increased by 45.06% at
STC while power generated from WGS without MPPT is 5.582kW and with FLC based MPPT
controller is 6.488kW which shows the power generated is increased by a percentage of 16.23%
at wind speed of 7m/s and FPMS provides effective utilization and uninterruptible power to
the loads.
living standards of human being. Moreover, the benefit is highly exceled if the electricity is
generated with Renewable Energy sources (RES). However, RES such as solar PV system have
low conversion efficiencies, but have high fabrication cost and are not reliable due to their
intermittent nature. Thus, an appropriate control system and a management strategy is required
to generate power at optimum efficiency and supply the loads. This thesis work presents the
intelligent based PV-Wind hybrid power generation system (IHPGS) with battery energy
storage system (ESS) in selected sites of rural areas. A power management algorithms based
on Artificial Intelligent Techniques (AITs) is proposed. To enhance efficiency and ensure
optimum power from RES, Adaptive Neural-Fuzzy Inference System (ANFIS) based
Maximum Power Point Tracking (MPPT) algorithm is employed for PV generation system
(PGS) and Fuzzy logic Controller (FLC) based MPPT for wind power generation system
(WGS). Moreover, this thesis work describes the implementation of Fuzzy controlled power
management system (FPMS) to manage the power flow to the system. Using metrological data
of the studied location, the developed system is tested and simulated in MATLAB-Simulink
under different scenarios. The obtained result show that the proposed algorithm can maximize
the conversion efficiency of both PV and WGS and ensures effective utilization of the
generated power. The total power generated from PGS without any controller is 59.7kW and
due to implementation of ANFIS MPPT for PGS is 86.6kW which is increased by 45.06% at
STC while power generated from WGS without MPPT is 5.582kW and with FLC based MPPT
controller is 6.488kW which shows the power generated is increased by a percentage of 16.23%
at wind speed of 7m/s and FPMS provides effective utilization and uninterruptible power to
the loads.