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Power exchange network composed of ordinary houses equipped with photovoltaics (solar panel) units is considered to effectively use the unsteady and uncontrollable solar power. In the previous study, an optimal power transfer schedule with the least wasted power is obtained as an optimal solution of linear programming model under the given power generation and consumption amounts. The present study considers a trading market mediated by brokers with pricing strategy. The goal is to design the market which leads to the optimal transfer obtained by the mathematical model. Simulation results show that reinforcement learning is effective to acquire the pricing strategy even for the unsteady daily generation of the solar power.
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