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This research proposes a use of an agent-based intelligent simulator to numerically examine the influence of a transmission line limit on the dynamics of a wholesale power market. In the proposed simulator, all agents are equipped with learning capabilities. The power market is structured by multiple zones connected by transmission lines. The following business implications are found in this study. 1) The learning speed of reinforcement learning depends upon a dynamic change of market price. 2) The marketprice and volatility of electricity is increased by a line limit. The increase is influenced by not only a capacity limit but also a zone structure and an amount of demand. 3) The average price and volatility of electricity are influenced by the number of capacity-limited links. 4) There is no major difference between day-ahead (DA) and real-time (RT) markets in terms of the influence of a line limit. 5) There is a slightly increasing trend in average DA and RT market prices along with the percentage reduction of a current line limit.