Dynamic locational marginal prices based zonal division in large-scale regional electricity markets

Price indicators are considered as the core of optimal allocation of resources in electricity markets. Zonal pricing can provide more flexible price signals than nodal pricing and uniform pricing, and a reasonable division of the energy market into zones is essential. In this paper, a topology based K-means clustering algorithm is developed which starts from calculating the locational marginal prices (LMPs) for a certain period of time as the characteristic values of buses and then clusters the buses characterized by similar dynamic LMPs into zones while taking the system's topology into account. Finally, the methodology is applied to IEEE-118 bus system and a realistic regional power system and the simulation results show that the developed aggregation method is effective and practical.