Affiliations: Department of Electrical Engineering, Sarvestan Branch, Islamic Azad University, Sarvestan, Iran | Bahonar Technical College Affiliated to Technical and Vocational University, Shiraz, Iran
Note: [] Corresponding author. Mohammad-Reza Akbari-Zadeh, Bahonar Technical College Affiliated to Technical and Vocational University, Shiraz, Iran. Tel./Fax: +98 7115643674; E-mail: M.akbari.rec@gmail.com
Abstract: In this paper, a novel two-stage modification firefly Optimization algorithm (MFA) is proposed for the placement of Proton Exchange Membrane Fuel Cell Power Plants (PEM-FCPP) in distribution systems. FCPPs, as Distributed Generation (DG) units, can be taken into account as combined sources of Heat, Power, and Hydrogen (CHPH). The overall system efficiency can be improved by CHPH operation of FCPPs. Also, it will produce hydrogen which can be stored for the future use of FCPPs or can be sold to make a profit. The objective functions under investigation consist of the operating costs of electrical energy generation of distribution substations and FCPPs, the voltage deviation and the total emission. In this paper, only the placement of CHPH FCPPs is considered while investment cost of devices is not considered. Owing to the different, non-commensurable and nonlinear objectives, using conventional single-objective approaches makes difficulties to solve the problem. Other than that, the placement of FCPP in distribution systems is a mixed integer problem. Therefore, in order to overcome these problems, the firefly algorithm is utilized. In addition, a new two-stage modification is employed to search the problem area globally. Due to the multi-objective characteristic of the optimization, implementing the proposed MFA leads to obtain a set of solution in the problem instead of only one. The proposed algorithm is tested on a 69-bus distribution system to validate the effectiveness and impressiveness of the approach.
Keywords: Fuel cell power plant (FCPP), combined heat, power and hydrogen (CHPH), multi-objective optimization, distributed generation (DG)
