Dr. METRO: a demand-responsive metro-train operation planning program [PDF]
WIT Transactions on The Built Environment, 2014 This paper introduces Dr.METRO, which is a demand responsive metro-train operation planning program. It involves several key functions for metrotrain operation planning such as the data handling of passenger traffic, demand forecasting, train scheduling and the sequencing of a train-set operation.
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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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Definition and evaluation of model-free coordination of electrical vehicle charging with reinforcement learning [PDF]
, 2020 Demand response (DR) becomes critical to manage the charging load of a growing electric vehicle (EV) deployment. Initial DR studies mainly adopt model predictive control, but models are largely uncertain for the EV scenario (e.g., customer behavior ...
Deleu, Johannes +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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Optimal Participation of DR Aggregators in Day-Ahead Energy and Demand Response Exchange Markets [PDF]
, 2014 Aggregating the Demand Response (DR) is approved as an effective solution to improve the participation of consumers to wholesale electricity markets. DR aggregator can negotiate the amount of collected DR of their customers with transmission system operator, distributors, and retailers in Demand Response eXchange (DRX) market, in addition to ...
Ehsan Heydarian-Forushani +3 more
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Aggregated effect of demand response on performance of future grid scenarios [PDF]
, 2015 Session 32 - Future power system infrastructure: no. 459750Conference Theme: Towards Future Power Systems and Emerging TechnologiesThe existing future grid (FG) feasibility studies have mostly considered simple balancing, but largely neglected network ...
Hill, DJ, Marzooghi, H, Verbic, G
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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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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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A survey of demand response adoption in retail stores DR control preferences, stakeholder engagement, and cross-national differences [PDF]
Energy Informatics, 2019 Abstract Retail stores can participate in demand response programs with the possibility of load shifting and building automation systems. Demand response activities in retail stores are influenced by various factors, such as business operations, company goals and policies, etc.
Zheng Ma +2 more
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Optimal bidding strategy for demand response aggregator in day-ahead markets via stochastic programming and robust optimization [PDF]
, 2015 This paper evaluates the optimal bidding strategy for demand response (DR) aggregator in day-ahead (DA) markets. Because of constraint of minimum power quantity requirement, small-sized customers have to become indirect participants of electricity ...
Wei, M, Zhong, J
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