Abstract
Recently, as many researchers introduced various methods and factors for distributed renewable energy resources and energy storage systems to the grid, the need for verification on their performance and effect to the grid is emerging. So, in this paper, we predict system marginal price (SMP) by using long short-term memory (LSTM) based on empirical data published by the Korea Power Exchange and the Korea Meteorological Administration. After then, this paper suggests an optimal energy storage system (ESS) operation strategy based on the predicted data and the dynamic programming (DP) algorithm. To verify the impact of the proposed operation strategy on power grid, a grid fault is simulated through OpenDSS to consider the power system reliability. As a result, the proposed algorithm was able to interpret the effect on the system when the ESS operator shows selfish behaviors to the system.
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