Retail dynamic pricing strategy design considering the fluctuations in day-ahead market using integrated demand response

[1]  Kaile Zhou,et al.  Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices , 2020 .

[2]  S. Fathi,et al.  A bi-level model for strategic bidding of a price-maker retailer with flexible demands in day-ahead electricity market , 2020, International Journal of Electrical Power & Energy Systems.

[3]  Dan Wang,et al.  Dynamic pricing in electricity and natural gas distribution networks: An EPEC model , 2020 .

[4]  Kody M. Powell,et al.  Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles , 2020 .

[5]  Daniel C. Matisoff,et al.  A review of barriers in implementing dynamic electricity pricing to achieve cost-causality , 2020, Environmental Research Letters.

[6]  F. Sheidaei,et al.  Multi-stage stochastic framework for energy management of virtual power plants considering electric vehicles and demand response programs , 2020 .

[7]  Narayana Prasad Padhy,et al.  Real-Time Bilevel Energy Management of Smart Residential Apartment Building , 2020, IEEE Transactions on Industrial Informatics.

[8]  Young-Jin Kim,et al.  Retail electricity pricing via online-learning of data-driven demand response of HVAC systems , 2020 .

[9]  W Wim Zeiler,et al.  Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration , 2020 .

[10]  Josep M. Guerrero,et al.  Stochastic Risk-Constrained Scheduling of Renewable-Powered Autonomous Microgrids With Demand Response Actions: Reliability and Economic Implications , 2020, IEEE Transactions on Industry Applications.

[11]  Andrea Michiorri,et al.  Optimal Participation of Residential Aggregators in Energy and Local Flexibility Markets , 2020, IEEE Transactions on Smart Grid.

[12]  Philipp Grünewald,et al.  Cluster analysis and prediction of residential peak demand profiles using occupant activity data , 2020, Applied Energy.

[13]  S. Limmer,et al.  Peak load reduction through dynamic pricing for electric vehicle charging , 2019 .

[14]  Rana Rahim,et al.  A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids , 2019, International Transactions on Electrical Energy Systems.

[15]  Jiang Lin,et al.  Challenges and strategies for electricity market transition in China , 2019, Energy Policy.

[16]  Shengwei Wang,et al.  Game theory based interactive demand side management responding to dynamic pricing in price-based demand response of smart grids , 2019, Applied Energy.

[17]  Abhijit Gosavi,et al.  A data-driven methodology for dynamic pricing and demand response in electric power networks , 2019, Electric Power Systems Research.

[18]  M. Frondel,et al.  Heterogeneity in the price response of residential electricity demand: A dynamic approach for Germany , 2019, Resource and Energy Economics.

[19]  Mohammed Hassan Ahmed,et al.  Optimization modeling for dynamic price based demand response in microgrids , 2019 .

[20]  A. Chagas,et al.  Estimation of elasticities for electricity demand in Brazilian households and policy implications , 2019, Energy Policy.

[21]  Yuping Lu,et al.  Optimal design and operation of multi-energy system with load aggregator considering nodal energy prices , 2019, Applied Energy.

[22]  Kazem Zare,et al.  Optimal performance of CCHP based microgrid considering environmental issue in the presence of real time demand response , 2019, Sustainable Cities and Society.

[23]  Amir Hossein Sharifi,et al.  Energy management of smart homes equipped with energy storage systems considering the PAR index based on real-time pricing , 2019, Sustainable Cities and Society.

[24]  Heresh Seyedi,et al.  Real-time price-based demand response model for combined heat and power systems , 2019, Energy.

[25]  Iain MacGill,et al.  Appliance level data analysis of summer demand reduction potential from residential air conditioner control , 2019, Applied Energy.

[26]  Pierre Pinson,et al.  Peer-to-peer and community-based markets: A comprehensive review , 2018, Renewable and Sustainable Energy Reviews.

[27]  Vasco Brummer.  Community energy – benefits and barriers: A comparative literature review of Community Energy in the UK, Germany and the USA, the benefits it provides for society and the barriers it faces , 2018, Renewable and Sustainable Energy Reviews.

[28]  Goutam Dutta,et al.  A two-part dynamic pricing policy for household electricity consumption scheduling with minimized expenditure , 2018, International Journal of Electrical Power & Energy Systems.

[29]  Eberhard Waffenschmidt,et al.  Interactive Robust Model for Energy Service Providers Integrating Demand Response Programs in Wholesale Markets , 2018, IEEE Transactions on Smart Grid.

[30]  Antonio J. Conejo,et al.  Rethinking restructured electricity market design: Lessons learned and future needs , 2018, International Journal of Electrical Power & Energy Systems.

[31]  Zhinong Wei,et al.  A robust optimization approach for integrated community energy system in energy and ancillary service markets , 2018 .

[32]  Changhui Yang,et al.  Residential electricity pricing in China: The context of price-based demand response , 2018 .

[33]  Josep M. Guerrero,et al.  Dynamic Pricing: An Efficient Solution for True Demand Response Enabling , 2017 .

[34]  Yan Gao,et al.  Real-time pricing scheme based on Stackelberg game in smart grid with multiple power retailers , 2017, Neurocomputing.

[35]  Josep M. Guerrero,et al.  Economic demand response model in liberalised electricity markets with respect to flexibility of consumers , 2017 .

[36]  Dipti Srinivasan,et al.  Game-Theory based dynamic pricing strategies for demand side management in smart grids , 2017 .

[37]  Yong-Hyuk Kim,et al.  Effective scheduling of residential energy storage systems under dynamic pricing , 2016 .

[38]  Seung Ho Hong,et al.  A Real-Time Demand-Response Algorithm for Smart Grids: A Stackelberg Game Approach , 2016, IEEE Transactions on Smart Grid.

[39]  Fabio Massaro,et al.  Real-time pricing for aggregates energy resources in the Italian energy market , 2015 .

[40]  Masood Parvania,et al.  Incorporating Two-Part Real-Time Pricing Scheme into Distribution System Operation , 2014, 2014 IEEE Electrical Power and Energy Conference.

[41]  Tian Xia,et al.  Estimation of demand response to energy price signals in energy consumption behaviour in Beijing, China , 2014 .

[42]  Elisabeth Dütschke,et al.  Dynamic electricity pricing - Which programs do consumers prefer? , 2013 .

[43]  M. Abedi,et al.  A risk-considered stochastic home load management under real-time electricity prices , 2013, 2013 12th International Conference on Environment and Electrical Engineering.

[44]  Wenxian Yang,et al.  A Statistical Demand-Price Model With Its Application in Optimal Real-Time Price , 2012, IEEE Transactions on Smart Grid.

[45]  M. Parsa Moghaddam,et al.  Modeling and prioritizing demand response programs in power markets , 2010 .

[46]  Y. Z. Li,et al.  Effect of inter-temporal factors on the real time pricing of electricity , 1993 .