Abstract
A hybrid evolutionary approach is proposed to design off-grid electrification projects that require distributed generation (DG). The design of this type of systems can be considered as an NP-Hard combinatorial optimization problem; therefore, due to its complexity, the approach tackles the problem from two fronts: optimal network configuration and optimal placement of DG. The hybrid scheme is based on a particle swarm optimization technique (PSO) and a genetic algorithm (GA) improved with a heuristic mutation operator. The GA-PSO scheme permits finding the optimal network topology, the optimal number, and capacity of the generation units, as well as their best location. Furthermore, the algorithm must design the system under power quality requirements, network radiality, and geographical constraints. The approach uses GPS coordinates as input data and develops a network topology from scratch, driven by overall costs and power losses minimization. Finally, the proposed algorithm is described in detail and real applications are discussed, from which satisfactory results were obtained.
Highlights
The increasing penetration of distributed generation and renewable energy sources (RES) have brought new opportunities to improve electrical systems
(ii) Optimal placement of distributed generation: a particle swarm optimization technique (PSO) is used to find the optimal placement of DGs, minimizing power losses and quality issues; see Figure 1(c)
If ρi is the best position among all the particles this result is saved in σn, and the fitness of the group is established by fn (Gn) = f
Summary
The increasing penetration of distributed generation and renewable energy sources (RES) have brought new opportunities to improve electrical systems. Optimal placement and adequate size estimation of DGs, with a suitable network configuration, can improve an electrical system by reducing power losses, excessive generation, and overall costs. Unlike grid-connected systems, small isolated projects have more freedom to locate DGs in different points of the network, even small generation units can be installed at each house This implies a greater number of possible configurations, becoming a hard combinatorial optimization problem. Considering the aforementioned problem and the lack of investigation related to this type of optimization problems, a hybrid GA-PSO approach is proposed to design off-grid electrification projects, which require multiple placement of DGs. The GA-PSO scheme is based on optimal network reconfiguration and optimal placement of DGs. to prove the effectiveness of the proposed algorithm several experiments have been made on two real cases where distributed photovoltaic generation (DPG) has to be installed.
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