HIES: Cases for hydrogen energy and I-Energy

Lü, Yang; Xie, Pengli; Zhang, Ronghui; Cheng, Yang; Cai, Bowen; Wang, Rongben

doi:10.1016/j.ijhydene.2019.03.056

Cited by 8 publications

(3 citation statements)

References 87 publications

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“…Several issues confront the Deep Q-Network (DQN) algorithm in cogeneration scheduling: complexity, computing demands, data requirements, model complexity, algorithm tuning, exploration vs exploitation, policy generalization, safety, and dependability. The energy conversion form in Figure 1 is analyzed, and it is proposed that the 80-kWh energy of traditional thermal power units can only produce 28 kWh of electrical energy [12]. The 100-kWh energy of the cogeneration unit can obtain 28 kWh of electric energy and 63 kWh of heat energy.…”

Section: Related Workmentioning

confidence: 99%

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The Optimal Dispatching Strategy of Cogeneration Based on Deep Q-Network (DQN) Algorithm

Zhang,

Fu,

Yao

2024

Sci. Tech. Energ. Transition

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This work expands on previous research to offer a state-of-the-art approach for optimizing the dispatching of cogeneration systems, given the limitations faced by conventional coal-fired cogeneration units and the increasing environmental standards. Acknowledging the constraints of flexibility in winter heating, the study aims to improve unit coal use optimization and lower emissions. The paper presents a novel optimization approach for distributing electricity and heat in cogeneration units, utilizing the Deep Q-Network (DQN) algorithm. The suggested approach reduces operating expenses and improves system dependability using a sixth-order function fitting and fuzzy set space division. The study's results indicate a significant 8.96% increase in performance, demonstrating the effectiveness of the DQN-based strategy in enabling cost-effective scheduling in cogeneration systems. This research offers a road towards sustainable and effective energy use and contributes to the development of cogeneration technology. It also has potential applications in natural energy systems.

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Section: Related Workmentioning

confidence: 99%

“…Generally, the heating cannot be continued but can only be interrupted. The impact of environmental temperature and boiler pressure is relatively apparent, and the heating quality is low [9]. China's industrial enterprises (smelting, steel, paper making, textile, etc.)…”

mentioning

confidence: 99%

The Optimal Dispatching Strategy of Cogeneration Based on Deep Q-Network (DQN) Algorithm

Zhang,

Fu,

Yao

2024

Sci. Tech. Energ. Transition

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“…A household energy management system was implemented and processed using a predictive control model in [20]. A comprehensive review of studies on hydrogen energy was presented in [21].…”

Section: Introductionmentioning

confidence: 99%

A Survey of Hydrogen Energy and I-Energy Applications: Household Intelligent Electrical Power Systems

Sami

2020

IEEE Access

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The authors would like to thank the DSR technical and financial support. ABSTRACT I-energy and its applications used in the smart grid are chosen as attractive research issues due to their widespread applications in the smart home. In this vein, the optimization of energy demand in smart home appliances, in a smart grid, is considered the main challenge faced by power companies during peak periods regarding its considerable effect on the global power system stabilities. Therefore, this paper aims to show explicitly the performance of smart grid on electricity and hydrogen applications with reused communication methods. To facilitate the understanding of the communication-reused methods in the smart grid, several components are identified and presented in terms of improvements, benefits and lack of features. In the smart grid, most innovation communications are being used as wireline and wireless bundle, where the main features are aggregated. Indeed, reducing consumers' electricity bills in smart home electrical systems relies on increasing the relationship between the highest energy demand and annual energy use. The most appropriate research has been reviewed on optimization approaches discussing the smart home electric system. The examined methods are categorized into trustworthy and metaheuristic algorithms. INDEX TERMS Smart home, I-energy concept, hydrogen-renewable energy system, smart meter, smart grid, risk management, demand-side management, AMI.

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Entropy analysis of hydrogen production in electrolytic processes

Chmielniak

Remiorz

2020

Energy

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HIES: Cases for hydrogen energy and I-Energy

Cited by 8 publications

References 87 publications

The Optimal Dispatching Strategy of Cogeneration Based on Deep Q-Network (DQN) Algorithm

The Optimal Dispatching Strategy of Cogeneration Based on Deep Q-Network (DQN) Algorithm

A Survey of Hydrogen Energy and I-Energy Applications: Household Intelligent Electrical Power Systems

Entropy analysis of hydrogen production in electrolytic processes

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