An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster

Mansouri, Seyed Amir; Jordehi, Ahmad Rezaee; Marzband, Mousa; Tostado‐Véliz, Marcos; Jurado, Francisco; Aguado, José A.

doi:10.1016/j.apenergy.2022.120560

Cited by 92 publications

(24 citation statements)

References 50 publications

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“…In recent years, most scholars have conducted extensive research on the management models and optimal scheduling methods of Multi-energy system [13], such as powertransportation convergence systems [14][15][16] and multifunctional parks [17][18][19]. Reference [13] proposes an integrated energy collaborative management model based on demand response for residential, commercial and industrial Moreover, the optimal power flow constraint of network configuration and communication is added, and the cost of environmental carbon emission is considered.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Reference [13] proposes an integrated energy collaborative management model based on demand response for residential, commercial and industrial Moreover, the optimal power flow constraint of network configuration and communication is added, and the cost of environmental carbon emission is considered. Considering the active participation of smart buildings (SBs) and electric vehicle (EV) fleets in scheduling, reference [14] presents a nested framework for transmission system operator-distribution system operator (TSO-DSO) coordination under the influence of a high number of renewable technologies (RGs). To effectively model the energy interac-tions of different forms of energy in a multi-energy system, the concept of an energy hub (EH) was first introduced in 2007 [15].…”

Section: Literature Reviewmentioning

confidence: 99%

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A collaborative training approach for multi energy systems in low‐carbon parks accounting for response characteristics

Bao,

Sun,

Zheng

2023

IET Renewable Power Gen

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Existing researches lack systematic design of the operation mechanism and overall implementation process of park oriented multi‐state energy system; The existing researches on multi‐state energy systems ignored the dynamic response characteristics of load and the coupling effect of units considering the impact of carbon emissions, and did not go deep into the collaborative management of multiple multi state energy system parks. To this end, this paper first proposes a two‐stage multi‐energy system operation architecture for low carbon parks, and establishes a mathematical model considering carbon emissions, operating costs and other objectives. The response space of load is optimized by considering the dynamic interaction characteristics of load response and the coupling characteristics of unit operation. Then, considering the problems of data security and training efficiency, F‐DDPG technology is used to conduct collaborative training for multiple campus systems. Finally, an example is given to prove the effectiveness of the method, which is not only conducive to reducing the operating cost of the system and the carbon emissions on the supply side, but also improves the convergence of model training. In the case of collaborative training in multiple parks, the method in this paper converges faster and has better economic benefits.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A collaborative training approach for multi energy systems in low‐carbon parks accounting for response characteristics

Bao,

Sun,

Zheng

2023

IET Renewable Power Gen

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“…Hydrogen energy from PEMFCs offers a significant means to manage and balance power flows, as opposed to other renewable energy sources like solar and wind, which have intermittency issues, power balancing issues, and high maintenance costs [4]. In recent years, an increasing number of PEMFCs are getting connected to various electrical networks, with microgrid applications being one of the most rapid advancements [5]. The primary objective of PEMFCs is to provide support for the microgrid to compensate the power requirements of the electrical loads.…”

Section: Introductionmentioning

confidence: 99%

A High Voltage Gain Interleaved DC-DC Converter Integrated Fuel Cell for Power Quality Enhancement of Microgrid

et al. 2023

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Fuel cells have drawn a lot of interest in recent years as one of the most promising alternative green power sources in microgrid systems. The operating conditions and the integrated components greatly impact the quality of the fuel cell’s voltage. Energy management techniques are required in this regard to regulate the fuel cell’s power in a microgrid. The active/reactive power in the microgrid should be adjusted in line with US Energy Star’s regulations whereas the grid current needs to follow the standard set by IEEE 519 2014 to enhance the power quality of the electrical energy injected into the microgrid. Uncontrolled energy injection from the fuel cell can have serious impacts including superfluous energy demand, overloading, and power losses, especially in high power and medium voltage systems. Although fuel cells have many advantages, they cannot yet produce high voltages individually to compensate for the demand of a microgrid system. Due to these reasons, the fuel cell must be interfaced with a DC-DC converter. This research proposes a novel high voltage gain converter integrated 1.26 kW fuel cell for microgrid power management that can boost the fuel cell’s voltage up to 20 times. Due to this high voltage gain, the voltage and current ripple of the fuel cell is also reduced substantially. According to the analysis, the proposed converter demonstrated optimal performance when compared to the other converters due to its high voltage gain and extremely low voltage ripple. As a result, the harmonic profile of the microgrid current persists with a reduced THD of 3.22% and a very low voltage ripple of 4 V. To validate the converter’s performance, along with extensive simulation, a hardware prototype was also built. The voltage of the fuel cell is regulated using a simplified proportional integral controller. The operating principle of the converter integrated fuel cell along with its application in microgrid power management is demonstrated. A comparative analysis is also shown to verify how the proposed converter is improving the system’s performance when compared against other converters.

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“…In [25], day ahead scheduling model is developed for prosumers based on stochastic approach to address the uncertainties in the energy generation systems. In [26], a simultaneous management of different markets such as electricity, heat and hydrogen is developed using hierarchical decentralized framework whereas a two stage optimal scheduling framework for energy communities has been designed by authors in [27]. An interesting algorithm has been designed in [28] where 100% renewable energy communities having individual load controls with small generators.…”

Section: Introductionmentioning

confidence: 99%

A novel automated demand response control using fuzzy logic for islanded battery‐operated rural microgrids

Azeem

Memon

Baig

et al. 2023

IET Renewable Power Gen

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Islanded rural microgrid require continuous resource monitoring. Demand response schemes have been phenomenal in managing loads. However, urban demand response schemes are well equipped with market prices and peak time penalties to control deferrable loads. In rural microrids, regular loads such as fans, lights and water pumps are normally used that do not fall under category of deferrable loads. In addition, full liberty of utilizing regular load at any time, lack of awareness and no information of storage reserves make task of load management more complex. In this research fully automated two layered demand response scheme is designed for regular operating loads. The first layer control is load mode control. The mode of operation is decided on the state of charge (SoC) of battery. In second layer, fuzzy controller is designed on the consumer's routines, SoC and ambient temperature as membership function. Results are assessed in terms of consumers comfort and availablity of SoC. The load operation in automated demand response remained indentical to actual rutine operation as per consumer's desire with 5 to 7% deviation. In all modes of operation SoC levels remained 15% higher and heavy load operated 13.5% more compare to relevant study.

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An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster

Cited by 92 publications

References 50 publications

A collaborative training approach for multi energy systems in low‐carbon parks accounting for response characteristics

A collaborative training approach for multi energy systems in low‐carbon parks accounting for response characteristics

A High Voltage Gain Interleaved DC-DC Converter Integrated Fuel Cell for Power Quality Enhancement of Microgrid

A novel automated demand response control using fuzzy logic for islanded battery‐operated rural microgrids

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