Evaluation of hydrogen storage technology in risk-constrained stochastic scheduling of multi-carrier energy systems considering power,gas and heating network constraints |
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| Affiliation: | 1. Dept. of Architectural Engineering, Pennsylvania State Univ., 104 Engineering Unit A, University Park, PA, 16802, USA;2. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;3. Faculty of Engineering and Environment, Northumbria University, Newcastle Upon Tyne, NE1 8ST, UK;4. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam;1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;2. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam;3. Department of Architectural Engineering, Pennsylvania State University, Pennsylvania, USA;4. Department of Energy Technology, Aalborg University, 9220, Aalborg East, Denmark;5. Penn State Erie, The Behrend College, Erie, PA, 16563, USA;6. Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran;1. Dept. of Architectural Engineering, Pennsylvania State Univ, 104 Engineering Unit A, University Park, PA 16802.2, United States;2. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;2. Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam;3. Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle, England, United Kingdom;4. Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia;5. Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark;1. Institute of Intellectual Finance, Yango University, Fuzhou 350015, China;2. Department of Agriculture, Jouybar Branch, Islamic Azad University, Jouybar, Iran;3. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;4. Faculty of Social Sciences and Humanities, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;5. Tyumen Industrial University, Russia;6. Department of Mechanical Engineering, Tabriz University, Iran;7. Department of Electrical Engineering, University of Bonab, Bonab, Iran;1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran;2. Department of Electrical Engineering, University of Bonab, Bonab, Iran |
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| Abstract: | The operation of energy systems considering a multi-carrier scheme takes several advantages of economical, environmental, and technical aspects by utilizing alternative options is supplying different kinds of loads such as heat, gas, and power. This study aims to evaluate the influence of power to hydrogen conversion capability and hydrogen storage technology in energy systems with gas, power, and heat carriers concerning risk analysis. Accordingly, conditional value at risk (CVaR)-based stochastic method is adopted for investigating the uncertainty associated with wind power production. Hydrogen storage system, which can convert power to hydrogen in off-peak hours and to feed generators to produce power at on-peak time intervals, is studied as an effective solution to mitigate the wind power curtailment because of high penetration of wind turbines in electricity networks. Besides, the effect constraints associated with gas and district heating network on the operation of the multi-carrier energy systems has been investigated. A gas-fired combined heat and power (CHP) plant and hydrogen storage are considered as the interconnections among power, gas and heat systems. The proposed framework is implemented on a system to verify the effectiveness of the model. The obtained results show the effectiveness of the model in terms of handling the risks associated with multi-carrier system parameters as well as dealing with the penetration of renewable resources. |
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| Keywords: | Hydrogen storage technology Multi-carrier system Risk analysis Renewable energy sources Stochastic scheduling |
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