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[HTML][HTML] A review on energy hubs: Models, methods, classification, applications, and future trends
Increasing environmental concerns, scarcity of fossil fuel resources, and uncontrolled
demand growth have led to upgrading and restructuring existing energy systems …
demand growth have led to upgrading and restructuring existing energy systems …
Review of optimization methods for energy hub planning, operation, trading, and control
The increasing concerns with adverse environmental issues have led to the proliferation of
renewable energy resources (RESs), which have been expanded more recently to multi …
renewable energy resources (RESs), which have been expanded more recently to multi …
Optimal planning for electricity-hydrogen integrated energy system considering power to hydrogen and heat and seasonal storage
For the future development of an integrated energy system (IES) with ultra-high penetration
of renewable energy, a planning model for an electricity-hydrogen integrated energy system …
of renewable energy, a planning model for an electricity-hydrogen integrated energy system …
A cooperative transactive multi-carrier energy control mechanism with P2P energy+ reserve trading using Nash bargaining game theory under renewables uncertainty
Abstract Transactive Energy Control (TEC) as a market-based control is a critical notion for
scheduling Multi-Carrier Energy Systems (MCESs) in local networks and forming an Energy …
scheduling Multi-Carrier Energy Systems (MCESs) in local networks and forming an Energy …
Bi-level mixed-integer planning for electricity-hydrogen integrated energy system considering levelized cost of hydrogen
Hydrogen is regarded as secondary energy that is perfectly complementary to electricity
owing to its friendly storage characteristics and can play a vital role in the future low-carbon …
owing to its friendly storage characteristics and can play a vital role in the future low-carbon …
A novel model-free deep reinforcement learning framework for energy management of a PV integrated energy hub
This paper utilizes a fully model-free and data-driven deep reinforcement learning (DRL)
framework to develop an intelligent controller that can exploit information to optimally …
framework to develop an intelligent controller that can exploit information to optimally …
Optimal operation of energy hubs considering uncertainties and different time resolutions
This article presents a robust chance-constrained optimization framework for the optimal
operation management of an energy hub (EH) in the presence of electrical, heating, and …
operation management of an energy hub (EH) in the presence of electrical, heating, and …
Two-stage distributionally robust optimization for energy hub systems
Energy hub system (EHS) incorporating multiple energy carriers, storage, and renewables
can efficiently coordinate various energy resources to optimally satisfy energy demand …
can efficiently coordinate various energy resources to optimally satisfy energy demand …
Strategic operation of a virtual energy hub with the provision of advanced ancillary services in industrial parks
Coordinated operation of several industrial energy hubs (IEHs) to realize local energy
management concepts at strategic points like industrial parks has attracted the attention of …
management concepts at strategic points like industrial parks has attracted the attention of …
[HTML][HTML] Data-driven-based distributionally robust optimization approach for a virtual power plant considering the responsiveness of electric vehicles and Ladder-type …
Y Chen, Y Niu, C Qu, M Du, J Wang - … Journal of Electrical Power & Energy …, 2024 - Elsevier
To encourage the utilization of decentralized renewable energy systems, a data-driven-
based distributionally robust optimization (DRO) model is proposed for a virtual power plant …
based distributionally robust optimization (DRO) model is proposed for a virtual power plant …