Optimal Combination and Sizing of a Stand–Alone Hybrid Energy System Using a Nomadic People Optimizer

In this work, the main objective is the provision of an electric supply to a residential complex located in a remote area in Iraq (Thi-Qar) that has no access to the electricity grid. This study relied on the Nomadic People Optimizer (NPO) for the tri-objective design of a stand-alone hybrid energy system (HES). The NPO algorithm comprises five main operators; these are the initial meeting, the semicircular tents distribution, the families searching, the transition of leadership, and the periodic meeting of the normal leaders. A HES optimized the electricity supply of a residential complex with 30 houses in Thi-Qar, which is located in southern Iraq at latitude 31.06
⁰
and longitude 46.26
⁰
. The objectives of this study are to minimize the total life cycle cost (LCCT), total dump energy (DE
_Total
), and total CO
₂
emissions (E
_CO2
T) for 25 years. The deployed algorithm was used to evaluate six different power source scenarios (PV/battery, wind turbine/battery, 20-split diesel generators, a single large diesel generator, and PV/wind turbine/diesel generator/battery) when diesel a generator covers a deficit of renewable energy sources (RESs) without charges to the batteries, and PV/wind turbine/diesel generator and battery when a diesel generator covers a deficit in the renewable energy sources (RESs) with charges to the batteries. The data used in this study, such as the wind speed, solar radiation, and temperature, were collected from weather forecasts in Thi-Qar every hour for a full year; the data load was collected from the Thi-Qar Electricity Distribution Directorate for the same housing complex and the same number of houses in an area equipped with electricity. Additionally, the prices of the system components, maintenance, and cost of fuel were collected from the Iraq market. From the obtained results, the PV/wind/large diesel generator/battery system when the diesel generator charges the batteries was found to be the most attractive scenario because it achieved a total life cycle cost (LCCT($)) of 1.6974×10
⁶
, cost of energy (COE($/kWh)) of 0.080495746, total dump energy (DE
_Total
(GWh)) of (3.5418), and total CO
₂
emission (E
_CO2
T (kg) of 2.957 x 10
⁶
.