A Complex Network-based Approach for Designing of Wide Area Measurement Systems in Smart Grids using Adam-Eve Like Genetic Algorithm

The wide area measurement system (WAMS) consists of two different measuring and communication infrastructures, which is respectively responsible for measuring power girds’ data in the wide area and sending and processing them in the control centers. The design of WAMS can include the design of each of its infrastructures or target both infrastructures at the same time, the latter has been known as the WAMS comprehensive design. The WAMS comprehensive design means the simultaneous placement of measurement components and its required communication, which is known as minimum connected dominating set (MCDS) problem in graph theory and is formulated in the form of an optimization problem. Solving such a complex optimization problem is often done with evolutionary algorithms (e.g. genetic algorithm and ant colony), and the speed and efficiency of finding the solution has always been a challenge. This research proposes an adaptive genetic algorithm known as the Adam and Eve algorithm, which has the ability to solve the MCDS problem that arises from the WAMS comprehensive design. Through simulation results for IEEE 1354 bus network, we demonstrate that proposed algorithm is well-tuned to solved MCDS related to the power graphs. It is 30% faster than simple genetic algorithm, handles large-scale problems effectively, and outperforms both simple genetic algorithm and ant colony algorithm within a given timeframe.