Development of Optimal Electricity Management Systems to Minimize Resources andLosses using Particle Swarm Optimization Techniques: A Case Study for UDUS

Abstract

Hybrid energy systems (HESs), have played an important role as clean and efficient
source of electricity generation. HESs are often formulated as an optimization problem
which is solved mostly using metaheuristics techniques. The conventional objective
function is based on levelized cost of energy (LCOE), the lowest loss of power supply
probability (LPSP), and the maximum renewable factor (REF) as indices. This paper
proposed an enhanced objective function based on additional index known as Lost Load
Dump Load Index (LLDLI), which helps in finding optimal solution to HES deployment.
Usmanu Danfodiyo University Sokoto (UDUS), Nigeria is used as case study, Particle
swamp optimization (PSO)is used to solve the optimization problem in MATLAB/Simulink
for its early convergence. With the proposed method, an optimal solution for the
allocation of HES resources is achieved with minimum LCOE, LPSP, and LLDL indices
that are equal to 1.21$/kWh and 0.04%, and 0.05%respectively against conventional PSO
of The minimum parameters come out to be 1.3$/kWh for LCOE, 0.06% for LPSP, 0.09I.