Abstract
In this paper, an optimal design of a microgrid including four houses in Dakhla city (Morocco) is proposed. To make this study comprehensive and applicable to any hybrid system, each house has a different configuration of renewable energies. The configurations of these four houses are PV/wind turbine (WT)/biomass/battery, PV/biomass, PV/diesel/battery, and WT/diesel/battery systems. The comparison factor among these configurations is the cost of energy (COE), comparative index, where the load is different in the four houses. Otherwise, the main objective function is the minimization of the net present cost (NPC), subject to several operating constraints, the power loss, the power generated by the renewable sources (renewable fraction), and the availability. This objective function is achieved using a developed optimization algorithm. The main contribution of this paper is to propose and apply a new optimization technique for the optimal design of a microgrid considering different economic and ecological aspects. The developed optimization algorithm is based on the hybridization of two metaheuristic algorithms, the invasive weed optimization (IWO) and backtracking search algorithm (BSA), with the aim of collecting the advantages of both. The proposed hybrid optimization algorithm (IWO/BSA) is compared with the original two optimization methods (IWO and BSA) as well as other well-known optimization methods. The results indicate that PV/biomass and PV/diesel/battery systems have the best energy cost using the proposed IWO/BSA algorithm with 0.1184 $/kWh and 0.1354 $/kWh, respectively. The best system based on its LCOE factor is the PV/biomass which represents an NPC of 124,689 $, the size of this system is 349.55 m2 of PV area and the capacity of the biomass is 18.99 ton/year. The PV/diesel/battery option has also good results, with a system NPC of 142,233 $, the size of this system is about 391.39 m2 of PV area, rated power of diesel generator about 0.55 kW, and a battery capacity of 12.97 kWh. Otherwise, the proposed IWO/BSA has the best convergence in all cases. It is observed that the wind turbine generates more dumped power, and the PV system is highly suitable for the studied area.
Highlights
Increasing power demand is a logical result of the significant increase in the world population and their energy consumption and industrialization growth
To confirm the suitability of the proposed invasive weed optimization (IWO)/backtracking search algorithm (BSA) in addressing the studied optimization problem, IWO/BSA, AEFA, grey wolf optimizer (GWO), BSA, and IWO are launched 100 times for each configuration and a statistical study is conducted based on a set of measures like the best minimum value of the fitness function
For an in-depth analysis of the obtained results and to ensure the analysis study, four indices are calculated, the net present cost (NPC), Levelized cost of energy (LCOE), loss of power supply probability (LPSP), and the availability
Summary
Increasing power demand is a logical result of the significant increase in the world population and their energy consumption and industrialization growth. Distributed systems-based-renewable energy resources appear as a practical solution compared with the traditional energy resources due to the advantages of using such renewable sources. A microgrid is a distribution system consisting of hybrid energy sources dedicated to meet a particular need for electrical energy. A microgrid can be isolated from the utility in most cases; otherwise, it can be connected to the network when the microgrid owner needs more power flexibility. The authors of [1] presented the major issues regarding the motivations and benefits of adopting hybrid renewable energy systems (HRES), mainly in sub-Sahara. Different renewable energy systems that can be adopted for HRES applications for both on-grid and off-grid consumers were proposed and discussed. Detailed design and modeling of an isolated HRES have been presented in [2], including traditional and renewable energy resources using meta-heuristic algorithms. Other pertinent review research, such as microgrid transactive energy [3], optimal smart energy coordination in the microgrid applications [4], multi-agent microgrid management system for single-board computers [5], and peer-to-peer energy trading in micro/mini-grids for local energy communities [6], statistical analysis of PV/wind HRES have been presented in [7]
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