Sustainable Assessment of Hybrid Renewable Energy Systems Using Modern Optimization Algorithms for Off-Grid Rural Electrification
SSRN, ISSN: 1556-5068
2022
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Article Description
Exploitation of renewable hybrid energy systems is fast becoming an option to resolve the intermittent problems confronting renewable electricity from solar photovoltaic (PV) and wind turbine (WT). Energy from Biogas Power (BP) plant and Battery Storage (BS) system have also been used to support the dependability of electricity supply to off-grid rural communities. Implementation of hybrid energy systems require that techno-economic investigation be conducted to determine the optimal technical configuration and suitable economic cost of the systems. Modern algorithms of Flower Pollination Algorithm (FPA), Ant Colony Optimization (ACO), and Particle Swarm Optimization were used in this paper to perform the optimal sizing for the minimization of the Net Present Cost (NPC) with the most economical Cost of Energy (COE) at the point of meeting the load demand of a case study rural community. Results obtained proved that FPA is the most effective algorithm with the shortest time of execution to perform the objective tasks set by the design of the study. Four different scenarios of hybrid power systems comprising PV/WT/BS, PV/BP/BS, WT/BP/BS and PV/WT/BP/BS were investigated in the framework. Compared with PSO and ACO, the results obtained revealed that FPA meaningfully provides an optimal PV/BP/BS hybrid system with the least COE of 0.121$/kWh, NPC of $81506.34 and 0.02% Deficit Power Supply Probability (DPSP). The sensitive analysis conducted on decreasing battery efficiency of 10% resulted in approximately 4% increase in the NPC of the most economical hybrid PV/BP/BS for the lead-acid battery technology selected.
Bibliographic Details
Elsevier BV
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