Recently, due to technology improvements and governmental incentives for using the green energies, Fuel Cell Power Plants (FCPPs) seem to be a promising approach for electricity generation. FCPPs, as Distributed Generation (DG) units, can be considered as Combined sources of Heat, Power, and Hydrogen (CHPH). CHPH operation of FCPPs improves system efficiency because of produced hydrogen which can be stored for future use of FCPPs or can be sold for profit. Using 2m + 1 Point Estimate Method (2m + 1 PEM), a probabilistic load flow approach is employed to model the uncertainties in electrical and thermal load demands, pressure of input oxygen and hydrogen importing to FCPPs, and temperature of FCPPs. Minimizing the operation costs of electrical energy generated by distribution substation and FCPPs, minimizing the voltage deviation, and minimizing total emissions produced by distribution substations and FCPPs are selected as objective functions. This paper just considers the placement of CHPH FCPPs without assuming the devices investment cost. A powerful optimization technique, theta-Self Adaptive Gravitational Search Algorithm (theta-SAGSA), is proposed to achieve the optimal places for FCPPs and daily optimal active powers of distribution substation and FCPPs. For solving the proposed multi-objective problem, this paper utilizes the Pareto Optimality idea to obtain a set of solutions in the multi-objective problem instead of a sole solution. The proposed method effectiveness is validated on a 69-bus distribution system. (C) 2012 Elsevier Ltd. All rights reserved.