An IGDT/Scenario based stochastic model for an energy hub considering hydrogen energy and electric vehicles: A case study of Qeshm Island, Iran

Kafaei, Mostafa; Sedighizadeh, Davoud; Sedighizadeh, Mostafa; Fini, Alireza Sheikhi

doi:10.1016/j.ijepes.2021.107477

Cited by 32 publications

(15 citation statements)

References 44 publications

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“…In another study [151], energy management of a residential energy hub integrated with EVs and solar systems (solar photovoltaic and solar collector), has been accomplished with the aim of operational costs minimization, in which flexible power and thermal loads have been considered. In [152], EVs, fuel cells, hydrogen tanks, and renewable energy sources have been integrated with an energy hub related to a smart commercial building, where seawater desalination units were considered flexible loads. Moreover, in [153], electricity, thermal, and cooling loads have been considered as load demands of an energy hub, including EVs, combined heat and power units, and electrical, thermal, and cooling storage.…”

Section: Energy Hubs (Multi-carrier Energy Systems)mentioning

confidence: 99%

A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges

Sadeghian

Oshnoei

Mohammadi‐Ivatloo

et al. 2022

Journal of Energy Storage

162

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Section: Energy Hubs (Multi-carrier Energy Systems)mentioning

confidence: 99%

A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges

Sadeghian

Oshnoei

Mohammadi‐Ivatloo

et al. 2022

Journal of Energy Storage

162

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“…Quantum Particle Swarm Optimization (QPSO) is adopted in the paper to solve the problem and find the minimum overall cost burden of the EH. ermal power is utilized in [26] to produce electricity by adopting an Organic Rankine Cycle (ORC). Also, a seawater desalination (SWD) unit with Reverse Osmosis (RO) technology is used as a flexible load.…”

Section: Introductionmentioning

confidence: 99%

“…(i) In a few pieces of research such as [16,20,24,[26][27][28], models of EVs in the energy hub have been considered. Note, however, that EVs have the potential to reduce pollution, and they are also able to enhance system flexibility with RES accessibility, so it is anticipated that their presence in the hub will be certain in the coming years.…”

Section: Introductionmentioning

confidence: 99%

Participation of Energy Storage-Based Flexible Hubs in Day-Ahead Reserve Regulation and Energy Markets Based on a Coordinated Energy Management Strategy

Kazemi

Salehpour

Shahbaazy

et al. 2022

International Transactions on Electrical Energy Systems

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In order to increase energy efficiency, the energy hub is considered as a form of aggregator and coordinator of various resources and storage. With the optimal performance of resources and storage generators based on a proper energy management system, it is expected that hubs can gain financial benefits from energy markets and ancillary services. So, the paper presents the participation of networked energy hubs in day-ahead (DA) reserve regulation and energy markets, where the hub operator incorporates a coordinated energy management (CEM) strategy to manage power sources and energy storage devices within the hub. Hence, this problem maximizes the total profit of hubs in the DA energy and up and down reserve markets. Also, the problem is constrained by optimal power flow (OPF) constraints in gas, electricity, and thermal networks, reserve limits, and hub constraints, including the model of the combined heat and power (CHP), renewable energy source (RES), electrical/thermal storage, parking lots of electric vehicles (EVs), and boiler. Following that, a linear format is obtained for the nonlinear equation using traditional linearization methods so that an optimal solution is found in less time considering less computational error. Eventually, a standard case system is used to test the strategy, and thus, the capabilities of the approach are investigated. The obtained findings validate the potential of the proposed design in enhancing the economic situation of power sources and storage in hub form, which can enhance operation indices by optimal management of the hub so that the energy management of resources and storage in the form of a hub based on CEM compared to their independent management plan has been able to increase the profit of these elements in energy and up and down reserve markets by about 17%, 28%, and 15%, respectively. Regarding technical indices of energy networks, the proposed scheme by creating low energy losses in the gas network and providing pressure drop, overvoltage, and overtemperature within their permissible limits succeeded in reducing the energy losses in electricity and heat networks by about 83% and 38%, respectively, compared to power flow studies. Also, in these conditions, it has reduced the maximum voltage and temperature drop by 45% and 39%, respectively.

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“…To demonstrate the efficiency of our tool, we then apply it to a case study regarding electric vehicles (EVs). EVs were chosen as a guiding example for our technique as there is a demonstrated need and interest in scenario generation [31][32][33]. In particular, the scenarios covered by our case study include key themes about EVs, such as adoption [34][35][36], regulation and policy incentives [37][38][39], and technological enablers [40,41].…”

Section: Introductionmentioning

confidence: 99%

Automatically Generating Scenarios from a Text Corpus: A Case Study on Electric Vehicles

2022

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Creating ‘what-if’ scenarios to estimate possible futures is a key component of decision-making processes. However, this activity is labor intensive as it is primarily done manually by subject-matter experts who start by identifying relevant themes and their interconnections to build models, and then craft diverse and meaningful stories as scenarios to run on these models. Previous works have shown that text mining could automate the model-building aspect, for example, by using topic modeling to extract themes from a large corpus and employing variations of association rule mining to connect them in quantitative ways. In this paper, we propose to further automate the process of scenario generation by guiding pre-trained deep neural networks (i.e., BERT) through simulated conversations to extract a model from a corpus. Our case study on electric vehicles shows that our approach yields similar results to previous work while almost eliminating the need for manual involvement in model building, thus focusing human expertise on the final stage of crafting compelling scenarios. Specifically, by using the same corpus as a previous study on electric vehicles, we show that the model created here either performs similarly to the previous study when there is a consensus in the literature, or differs by highlighting important gaps on domains such as government deregulation.

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An IGDT/Scenario based stochastic model for an energy hub considering hydrogen energy and electric vehicles: A case study of Qeshm Island, Iran

Cited by 32 publications

References 44 publications

A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges

A comprehensive review on electric vehicles smart charging: Solutions, strategies, technologies, and challenges

Participation of Energy Storage-Based Flexible Hubs in Day-Ahead Reserve Regulation and Energy Markets Based on a Coordinated Energy Management Strategy

Automatically Generating Scenarios from a Text Corpus: A Case Study on Electric Vehicles

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