A sufficient stochastic framework to capture the uncertainty of load models in the management of distributed generations in power systems

Article type: Research Article

Authors: Zare, Alireza | Kavousi-Fard, Abdollah | Abbasi, Alireza | Kavousi-Fard, Farzaneh

Affiliations: Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran

Note: [] Corresponding author. Abdollah Kavousi-Fard, 1 Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran. Tel./Fax: +98 9356357770; E-mail: [email protected]

Abstract: With the high penetration of renewable power sources in the form of distributed generations (DGs), the amount of uncertainty in the power systems is increased greatly. This high uncertainty has affected most of the grid operation strategies including the optimal management of DGs. One significant source of uncertainty is the forecast error in the modeling of the future active and reactive load values. In order to deal with this problem, this paper suggests a new stochastic framework based on the scenario generation process and roulette wheel mechanism. This method converts the stochastic problem into a number of deterministic problems with different probabilities. Since the problem investigated is a complex nonlinear optimization problem, a sufficient optimization algorithm based on the bio-inspired krill herd algorithm is proposed to solve the problem effectively. The satisfying performance of the proposed method is examined on the IEEE standard test system.

Keywords: Uncertainty, Roulette Wheel Mechanism (RWM), krill herd algorithm, adaptive modification, Distributed Generation (DG)

DOI: 10.3233/IFS-141320

Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 447-456, 2015