Abstract
Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.
Highlights
Distribution power systems usually are radial networks with different branches and concentrated loads at different points or buses
A- VALIDATION OF Ecosystem-based Optimization (EAEO) USING STANDARD BENCHMARK FUNCTIONS The accuracy and reliability of the proposed EAEO is validated through its application for solving ten different standard benchmark functions
The results obtained by the application of EAEO are compared with those obtained by the conventional artificial ecosystem-based optimization (AEO)
Summary
Distribution power systems usually are radial networks with different branches and concentrated loads at different points or buses. The PSO algorithm has been applied in [33] for multiple DG placement with UPF in distribution systems for the objective of total power losses reduction. The authors of [36] tried to minimize the system losses by applying the analytical approach of enhanced analytical (EA) with the integration of the optimal power flow (OPF) to allocate different DG units with UPF and Optimal-PF. In [12], a hybrid of ant colony optimization (ACO) and artificial bee colony optimization (ABC) has been applied for the DG allocation problem in the distribution system for minimizing the total power losses. An effective version of AEO, EAEO, is proposed and both are applied to solve the problem of the optimal size and location of the DG units in distribution systems.
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