Multi-Objective Optimization of a Hybrid Nanogrid/Microgrid: Application to Desert Camps in Hafr Al-Batin

Abstract

This paper presents an optimal design for a nanogrid/microgrid for desert camps in the city of Hafr Al-Batin in Saudi Arabia. The camps were designed to operate as separate nanogrids or to operate as an interconnected microgrid. The hybrid nanogrid/microgrid considered in this paper consists of a solar system, storage batteries, diesel generators, inverter, and load components. To offer the designer/operator various choices, the problem was formulated as a multi-objective optimization problem considering two objective functions, namely: the cost of electricity (COE) and the loss of power supply probability (LPSP). Furthermore, various component models were implemented, which offer a variety of equipment compilation possibilities. The formulated problem was then solved using the multi-objective evolutionary algorithm, based on both dominance and decomposition (MOEA/DD). Two cases were investigated corresponding to the two proposed modes of operation, i.e., nanogrid operation mode and microgrid operation mode. The microgrid was designed considering the interconnection of four nanogrids. The obtained Pareto front (PF) was reported for each case and the solutions forming this front were discussed. Based on this investigation, the designer/operator can select the most appropriate solution from the available set of solutions using his experience and other factors, e.g., budget, availability of equipment and customer-specific requirements. Furthermore, to assess the quality of the solutions found using the MOEA/DD, three different methods were used, and their results compared with the MOEA/DD. It was found that the MOEA/DD obtained better results (nondominated solutions), especially for the microgrid operation mode.

Techno-economic optimization for isolated hybrid PV/wind/battery/diesel generator microgrid using improved salp swarm algorithm

“…The required number of BESU that must be connected in parallel, , is calculated by dividing the total required capacity of BESU, , by the capacity of a single battery, , as shown below 41 : …”

“…In addition, the number of BESU that must be connected in series, , is calculated using and , the voltages for the DC bus system and the BESU, in volt (V), respectively 41 : …”

“…Finally, the total number of BESU, , is determined by the product of and , as illustrated below 41 : …”

“…Accordingly, the total cost of the BESU, , assuming represents the cost of a single battery, will be as follows 41 : …”

Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings

“…The type of source is common for both topologies in most instances, as a DC source is mostly utilised for the majority of applications. Despite that fuel cells and diesel generators have been reported in a nanogrid setting [8,9], the most favourable sources are battery energy storage systems (BESS) for storage, as well as PVs small-scale wind turbines for generation. Wind turbines usually output AC due to the use of induction motors, however, its output power is converted to DC, as its voltage and frequency are unregulated.…”