An Improved Hybrid Optimization Algorithm for Multimodal Benchmark Function for Hybrid PV/WT/ESS

Abba Muhammad Adua, I. I. Alabi, I. A. Araga, Tajudeen Danjuma, Umar Muhammed Jajere, Abubakar Usman Sadik, Yau Alhaji Samaila

Abstract


The adoption of Renewable Energy Systems (RES) has taken a centre stage in recent years due to depletion in fossil energy resources, climate change, absence of electric energy supply to remote locations and the high connection cost due to long distance. Despite the abovementioned challenges, the implementation of RES is quite slow in many countries, due to its high capital cost and uncertainties. A more promising RES is the hybrid power system. This system incorporates multiple RES which increases the system reliability, minimizes the system cost and excess energy produced when optimally sized. Therefore, this work considered an optimized techno economic design of a standalone PV/Wind/Battery RES for power generation considering coordinate (13.0931◦N, 7.2248◦E) of Jibia Katsina state Nigeria, using Smell Agent Optimization (GWO) simulation software and Improved Hybrid Particle Swarm Optimization Graywolf Optimization Optimization (PSO-GWO) Algorithm. The simulation was carried out in three scenarios namely; PV/Battery, Wind/Battery, and PV/Wind/Battery. The Levelized Cost of Energy (LCOE) obtained from GWO were found to be ₦44.14/kWhr, ₦29.63/kWhr and ₦29.48/kWhr respectively, and that obtained from SAO were found to be ₦15.57/kWhr, ₦19.38/kWhr and ₦12.53/kWhr respectively. The Loss of Power Supply Probability (LPSP) obtained from SAO were found to be 0.0328%, 0.0021%, and 0.0137% respectively, while that of PSO-GWO were found to be 0.000236%, 0.000236%, and 0.000184% respectively, The Excess Energy (ExE) produced from GWO simulation were found to be 4,238kW, 7,710kW, and 3,523kW, respectively while that obtained from ISAO were 12.66297kW, 17.150kW, and 205.5742kW respectively. The result of PSO-GWO shows significant reduction in LCOE, LPSP and ExE, as compared to the GWO.


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