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SCIE Article [Excluded]A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach |
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Author | Lu, RZ; Hong, SH; Zhang, XF |
Corresponding Author Info | Prof. Hong, Seung HO |
Professor | |
shhong@hanyang.ac.kr | |
Document Type | |
Source | APPLIED ENERGY 2018,15, 220-230 |
Times Cited | Excluded |
External Information | https://www.sciencedirect.com/science/article/pii/S0306261918304112 |
Abstract | - 7¿ù/8¿ù 2020ºÎ·Î, ÀÌ ÀÎ¿ë ºóµµ°¡ ³ôÀº ³í¹®ÀÇ Àοë Ƚ¼ö°¡ ºÐ¾ß¿Í ÃâÆÇ ¿¬µµ¿¡ ´ëÇØ Engineering °ü·Ã Çмú ºÐ¾ß¿¡¼ »óÀ§ 1%¿¡ ¿Ã¶ú½À´Ï´Ù.
- JUN 2018 <Abstract> With the modern advanced information and communication technologies in smart grid systems, demand response (DR) has become an effective method for improving grid reliability and reducing energy costs due to the ability to react quickly to supply-demand mismatches by adjusting flexible loads on the demand side. This paper proposes a dynamic pricing DR algorithm for energy management in a hierarchical electricity market that considers both service provider¡¯s (SP) profit and customers¡¯ (CUs) costs. Reinforcement learning (RL) is used to illustrate the hierarchical decision-making framework, in which the dynamic pricing problem is formulated as a discrete finite Markov decision process (MDP), and Q-learning is adopted to solve this decision-making problem. Using RL, the SP can adaptively decide the retail electricity price during the on-line learning process where the uncertainty of CUs¡¯ load demand profiles and the flexibility of wholesale electricity prices are addressed. Simulation results show that this proposed DR algorithm, can promote SP profitability, reduce energy costs for CUs, balance energy supply and demand in the electricity market, and improve the reliability of electric power systems, which can be regarded as a win-win strategy for both SP and CUs. |
Web of Science Categories | Energy & Fuels; Engineering |
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Àüü Excluded ±âŸ |
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[Excluded]A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach Author(s) : Yu, M; Hong, SH Source : IEEE TRANSACTIONS ON SMART GRID 2016, 7, 879-888 Time Cited : Excluded |
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Author(s) : Lu, RZ; Hong, SH; Zhang, XF Source : APPLIED ENERGY 2018,15, 220-230 Time Cited : Excluded |
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Author(s) : Lu, Renzhi; Hong, Hong, Seung Ho; Source : APPLIED ENERGY 2019, 236, 937-949 Time Cited : Excluded |
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[Excluded] An Incentive-Based Demand Response (DR) Model Considering Composited DR Resources Author(s) : Yu, Mengmeng; Hong, Seung Ho; Ding, Yuemin; Ye, Xun Source : IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019, 66, 1488-1498 Time Cited : Excluded |
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Author(s) : Sridharan, Kishore; Jang, Eunyong; Park, Tae Joo Source : APPLIED CATALYSIS B-ENVIRONMENTAL 2013, 142, 718-728 Time Cited : Excluded |
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