Journal of Terahertz Science and Electronic Information Technology , Volume. 21, Issue 1, 112(2023)
Reinforcement Learning-based Optimizing Dynamic Pricing algorithm in smart grid
Dynamic pricing is one of the most effective ways to encourage customers to change their consumption pattern. Therefore, Reinforcement Learning-based Optimizing Dynamic Pricing(RLODP) algorithm is proposed for energy management in a hierarchical electricity market by considering both service provider's profit and customers' costs. Using Reinforcement Learning, the SP can adaptively determine the retail electricity price. Dynamic pricing problem is formulated as a discrete finite Markov Decision Process(MDP), and Q-learning is adopted to solve this decision-making problem. Simulation results show that the RLODP algorithm can reduce energy costs for customers, balance the energy supply and the demands in the electricity market.
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CAO Jun, SUN Yingying, ZHAO Hang. Reinforcement Learning-based Optimizing Dynamic Pricing algorithm in smart grid[J]. Journal of Terahertz Science and Electronic Information Technology , 2023, 21(1): 112
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Received: Apr. 28, 2020
Accepted: --
Published Online: Mar. 14, 2023
The Author Email: Jun CAO (huxyu_82@sohu.com)