A Nobel LLDI Index for Optimal Deployment of RERs Based HES: A Case Study for UDUS

Nasiru Abubakar¹ , Barau Inuwa² , Zahraddin Umar Dahiru³

Section:Research Paper, Product Type: Journal-Paper
Vol.11 , Issue.3 , pp.1-10, Sep-2024

Online published on Sep 30, 2024

Copyright © Nasiru Abubakar, Inuwa Barau Inuwa, Zahraddin Umar Dahiru . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Renewable energy resources (RERs) especially of Wind energy and PV system (together with battery storage system BSS) plays a key role in mitigating carbon emission by deploying and integrating the RERs as hybrid energy system (HES) to existing conventional power system. To ensure reliable and efficient energy solutions of the HES, the deployment is mostly formulated as multi objective optimization problem. To enhanced the optimal capacity deployment of RERs devices, an improved objective function based on proposed lost load dump load index (LLDLI) is proposed. Solution of the optimization problem for the proposed using particle swamp optimization (PSO) in MATLAB/Simulink shows that the convergence rate of the proposed method is faster than the conventional method, thus indicating that the proposed method is more efficient and requires less iteration count to converge to optimal solution. In addition, the case study of Usmanu Danfodiyo University Sokoto (UDUS), Nigeria distribution system which is used as the test system shows that system supply reliability increased by 17.5% for the HES, the deployment and operational cost is minimized by 35% while the contribution of the of the RERs in the HES system is significantly increased to 40%, while significantly minimizing power losses. Conclusively, the proposed method is more robust and efficient for the deployment of HES system to existing power distribution system

Key-Words / Index Term :
RERs, Wind energy, PV system, BSS, HES PSO, LLDI

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