Nash Differential Evolution (NashDE) Algorithm for WAMS Planning

Wide Area Monitoring System (WAMS) is an inevitable component in todays power system since a small catastrophe like fluctuations caused by the renewable energy sources, fast changing loads, electric vehicles, etc. will lead to the collapse of the whole system. This paper addresses the optimal planning of WAMS by Nash Differential Evolution (NashDE) Algorithm, in which the variables of the problem are clustered into number of clusters, and will evolve parallelly by Differential Evolution (DE) towards the global objective of the problem. For optimization problems which are based on the connectivity of variables involved as in most of the power system planning processes, the convergence speed will greatly improve if variables in a cluster are physically connected. Further, this will ensure global convergence of the problem. Hence, this paper proposes a NashDE algorithm in which the variables are clustered based on their connectivity. Markov Clustering Algorithm (MCL) is used for clustering the variables based on their connectivity. This is the first paper of such kind which addresses WAMS planning problem by Evolutionary Game Theory. Simulations are carried out for IEEE 14 and 30 bus test system using Python programming and the results are presented graphically.