Nowadays electrical power systems in Thailand are restructuring and privatizing for better services and reducing monopoly. Therefore reliability-worth assessment has to be accurately evaluated and inserted in the electricity tariff for compensating customers in case a power interruption occurs [1]-[5], [8]. Reliability and quality of service have been a fundamental requirement factor of a power system. Electric utility providers need to improve power system performance with low cost and high level of reliability to meet customer satisfaction and increase business competitiveness. In addition, most electric utility providers have to minimize any expense as a way to prepare against market competition after entering privatization restructuring [1], [6], Therefore, an unmanned substation approach is a potential approach for reducing operation cost, while satisfying system requirements such reliability and quality of service. Electric utility providers have to effectively allocate distributed control centers (DCCs) and provide standby switching operators to monitor and control all unmanned substations of each DCC. This research paper proposes an efficient technique to optimize locations of DCCs and unmanned substations as clients of each DCC considering minimum outage cost especially from corrective operations with severe traffic jam when necessary to travel from a DCC to its failed unmanned substation. At the stage of DCC planning, the location of DCCs are determined based on actual collected data [9] including importance of each unmanned substation load, interruption rate of each unmanned substation, distance of an unmanned substation from its DCC, and types of substation equipments. This is our research approach where Genetic Algorithm technique [7] is applied for the problem solving under system design constraints.