Results 21 to 30 of about 127,999 (165)
Dynamic Pricing Based on Demand Response Using Actor–Critic Agent Reinforcement Learning
Energies, 2023 Eco-friendly technologies for sustainable energy development require the efficient utilization of energy resources. Real-time pricing (RTP), also known as dynamic pricing, offers advantages over other pricing systems by enabling demand response (DR ...
Ahmed Ismail, Mustafa Baysal
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Demand Response: Moving beyond the Technical and Physical Context of Buildings
Proceedings, 2019 This paper discussed the demonstration experiences from an EU funded H2020 project called “Demand Response in Blocks of Buildings” (DR-BOB).
Sylvia Breukers, Tracey Crosbie
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Demand Response in Buildings: A Comprehensive Overview of Current Trends, Approaches, and Strategies
Buildings, 2023 Power grids in the 21st century face unprecedented challenges, including the urgent need to combat pollution, mitigate climate change, manage dwindling fossil fuel reserves, integrate renewable energy sources, and meet greater energy demand due to higher
Ruzica Jurjevic, Tea Zakula
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Reinforcement Learning-Based Pricing and Incentive Strategy for Demand Response in Smart Grids
Energies, 2023 International agreements support the modernization of electricity networks and renewable energy resources (RES). However, these RES affect market prices due to resource variability (e.g., solar).
Eduardo J. Salazar +2 more
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A reinforcement learning-based demand response strategy designed from the Aggregator’s perspective
Frontiers in Energy Research, 2022 The demand response (DR) program is a promising way to increase the ability to balance both supply and demand, optimizing the economic efficiency of the overall system. This study focuses on the DR participation strategy in terms of aggregators who offer
Seongmun Oh +4 more
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Energies, 2018 It has been four years since the introduction of the Demand Response (DR) market in Korea. Although the DR market has been steadily increasing resource capacity and payments for demand resources, it cannot efficiently utilize DR resources under the ...
Seungmi Lee, Jinho Kim
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, 2022 As the rise in electricity rises, it creates a need for more flexibility on the power grid. Utility companies have begun to give more attention to Demand Response (DR) programs. These programs are essential in assisting with the growing demand for energy
Stotts, Austin
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Demand Response Strategy of Energy Prosumer Based on Robust Optimization Through Aggregator
IEEE Access, 2020 In this article, the optimal operation strategy for the aggregator to participate in demand response (DR) market is proposed. First, on the day before the occurrence of DR, Customer Baseline Load (CBL)-based load forecasting is performed using historical
Minsu Park, Jihoan Lee, Dong-Jun Won
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Electric Water Heater Modeling, DR Approaches Analysis and Study of Consumer Comfort for Demand Response [PDF]
, 2019 With the smart energy management system household residential appliances is able to participate in the demand response events. To reduce peak load demand and complexities in the local infrastructure DR can play an important role now a days.
Ahmed +5 more
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, 2023 Accurate prediction of renewable energy generation acts as a critical role which not only provides short-term power generation in the future, but also facilitates scheduling and pre-configuration of energy storage systems.
Zheng, Xidong +9 more
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