Affiliations: Department of Electrical and Computer Engineering, Safashahr Branch, Islamic Azad University, Safashahr, Iran
Correspondence:
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Corresponding author. Reza Khorramnia,Department of Electrical and Computer Engineering, Safashahr Branch, Islamic Azad University, Safashahr, Iran. Tel./Fax: +98 7133524523; r.k.safashahr@gmail.com
Abstract: In the modern power system analysis, the investigation on the impacts of growing wind power generation can be mentioned as an inseparable part of power grids. The development of wind-thermal coordination economic dispatch leads to an optimal dispatch scheme and a mature wind power efficiency. Adding further uncertainties to the study of power systems is one of the effects of intermittent nature of wind energy which is apart from random nature of realistic power grids. Now in order to inspect these uncertainties, an efficient probabilistic method is needed to comfort the issue. In this paper a novel optimization method based on Social Spider Optimization (SSO) is presented to meet large non-convex Economic Dispatch (ED) problems and uncertainties in the network caused by wind turbines, simultaneously. To provide a more realistic model, following constrains have been included in the proposed Probabilistic ED (PED) formulation: ramp rate limits, Prohibited Operating Zones (POZs), system spinning reserve, valve loading consequences, and multiple fuel choice. Unscented Transform (UT) approach is utilized in this paper to model the uncertainty in wind speed and thereupon solve the PED. In order to show the efficiency of the presented algorithm, it is successfully tested on different systems and compared with several of the most recently published ED methods.
Keywords: Probabilistic economic dispatch, social spider optimization, unscented transform
