Stochastic optimal planning of distribution system considering integrated photovoltaic-based dg and dstatcom under uncertainties of loads and solar irradiance

101Citations
Citations of this article
86Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Optimal planning of integration the Photovoltage Distributed Generation (PV-DG) and DSTATCOM is a crucial task due to the stochastic variations of PV output power and the load demand which are related to solar irradiance variations and the activities of the customers, respectively. In this article, the optimal planning problem of the PV-DG and DSTATCOM system is solved. The proposed model considers the uncertainties of the solar irradiance and the load demand for a multi-objective function, including the cost reduction, the voltage profile, and stability index improvement. Modified Ant Lion Optimizer (MALO) is proposed to enhance the basic ALO searching ability using two strategies. The first strategy is based on Levy Flight Distribution (LFD) to strengthen the exploration of the algorithm and avoid the premature of the basic ALO. In contrast, the second strategy is based on updating the solutions in a spiral orientation to improve the exploitation of the algorithm. The IEEE 69-bus and 118-bus radial distribution systems are used to demonstrate the effectiveness of the proposed method, and the yielded simulations are compared with the basic ALO and other well-known optimization techniques for power loss minimization under deterministic conditions. The simulation results demonstrate that the techno-economic benefits can be increased considerably by optimal inclusion of two PV-DGs and DSTATCOMs compared with a single system.

Cite

CITATION STYLE

APA

Oda, E. S., Hamed, A. M. A. E., Ali, A., Elbaset, A. A., Sattar, M. A. E., & Ebeed, M. (2021). Stochastic optimal planning of distribution system considering integrated photovoltaic-based dg and dstatcom under uncertainties of loads and solar irradiance. IEEE Access, 9, 26541–26555. https://doi.org/10.1109/ACCESS.2021.3058589

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free