Comparison of Meta-Heuristic Algorithms for Solving Dominating Set Problems in WAMS Design

Wide area measurement system (WAMS) integrates new digital metering devices (e.g. PMUs), and modern and high speed communication systems to measure the parameters of the network in wide geographical area. In a WAMS, measuring devices like PMUs form a measurement infrastructure that gathers raw data from the grid, while a communication infrastructure should be implemented to transmit such data to the control center(s). Due to the importance of WAMS in the operation of smart grids and also the high price of its implementation, the design of WAMS has been one of the research fields of interest in recent years. As WAMS consists of two different infrastructures, i.e. measurement and communication, there are three different approaches to WAMS design: separated, sequential, and comprehensive. The comprehensive method means the simultaneous design of two WAMS infrastructures in the form of a general optimization problem, whose its complex network equivalent is finding the minimum connected dominant set (MCDS). In this paper, in order to compare the performance of meta-heuristic algorithms in comprehensive WAMS design (i.e., finding the MCDS for a power graph), a new algorithm based on the ant colony optimization and a pheromone modification technique is proposed. Through simulations for three IEEE test cases, we have shown that the proposed algorithm brings % 17-% 25 saving in the investment cost in comparison with previous algorithms.