Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment
Integrated energy systems (IESs) represent a promising energy supply model within the energy internet. However, multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning, affecting the cost, efficiency, and environmental perform...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2021-04-01
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| Series: | Global Energy Interconnection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096511721000451 |
| _version_ | 1818575289150603264 |
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| author | Chengzhou Li Yongping Yang Zhuo Wang Ningling Wang Ligang Wang Zhiping Yang |
| author_facet | Chengzhou Li Yongping Yang Zhuo Wang Ningling Wang Ligang Wang Zhiping Yang |
| author_sort | Chengzhou Li |
| collection | DOAJ |
| description | Integrated energy systems (IESs) represent a promising energy supply model within the energy internet. However, multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning, affecting the cost, efficiency, and environmental performance of IES. A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES. An extended energy hub model is introduced based on the “node of energy hub” concept by decomposing the IES into different types of energy equipment. Subsequently, a planning method is applied as a two-level optimization framework—the upper level is used to identify the type and size of the component, while the bottom level is used to optimize the operation strategy based on a typical day analysis method. The planning problem is solved using a two-stage evolutionary algorithm, combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver, to minimize the lifetime cost of the IES. Finally, the feasibility of the proposed planning method is demonstrated using a case study. The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were $4.26 million and $4.15 million, respectively, in the case study. Moreover, ignoring the variation in component characteristics in the design stage resulted in an additional 11.57% expenditure due to an energy efficiency reduction under the off-design conditions. |
| first_indexed | 2024-12-15T00:38:18Z |
| format | Article |
| id | doaj.art-f7a77a782bc44bceb9d5fd0ee1b79937 |
| institution | Directory Open Access Journal |
| issn | 2096-5117 |
| language | English |
| last_indexed | 2024-12-15T00:38:18Z |
| publishDate | 2021-04-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Global Energy Interconnection |
| spelling | doaj.art-f7a77a782bc44bceb9d5fd0ee1b799372022-12-21T22:41:44ZengKeAi Communications Co., Ltd.Global Energy Interconnection2096-51172021-04-0142169183Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipmentChengzhou Li0Yongping Yang1Zhuo Wang2Ningling Wang3Ligang Wang4Zhiping Yang5National Research Center for Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing 102206, P.R. China; Industrial Process and Energy Systems Engineering, Swiss Federal Institute of Technology in Lausanne (EPFL), SwitzerlandNational Research Center for Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing 102206, P.R. China; Innovation Research Institute of Energy and Power, North China Electric Power University, Beijing 102206, P.R. ChinaNational Research Center for Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing 102206, P.R. ChinaNational Research Center for Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing 102206, P.R. ChinaInnovation Research Institute of Energy and Power, North China Electric Power University, Beijing 102206, P.R. ChinaNational Research Center for Thermal Power Engineering and Technology Research Center, North China Electric Power University, Beijing 102206, P.R. ChinaIntegrated energy systems (IESs) represent a promising energy supply model within the energy internet. However, multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning, affecting the cost, efficiency, and environmental performance of IES. A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES. An extended energy hub model is introduced based on the “node of energy hub” concept by decomposing the IES into different types of energy equipment. Subsequently, a planning method is applied as a two-level optimization framework—the upper level is used to identify the type and size of the component, while the bottom level is used to optimize the operation strategy based on a typical day analysis method. The planning problem is solved using a two-stage evolutionary algorithm, combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver, to minimize the lifetime cost of the IES. Finally, the feasibility of the proposed planning method is demonstrated using a case study. The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were $4.26 million and $4.15 million, respectively, in the case study. Moreover, ignoring the variation in component characteristics in the design stage resulted in an additional 11.57% expenditure due to an energy efficiency reduction under the off-design conditions.http://www.sciencedirect.com/science/article/pii/S2096511721000451Energy hubIntegrated energy systemConfiguration planningPart-load characteristicsGenetic algorithm |
| spellingShingle | Chengzhou Li Yongping Yang Zhuo Wang Ningling Wang Ligang Wang Zhiping Yang Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment Global Energy Interconnection Energy hub Integrated energy system Configuration planning Part-load characteristics Genetic algorithm |
| title | Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment |
| title_full | Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment |
| title_fullStr | Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment |
| title_full_unstemmed | Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment |
| title_short | Energy hub-based optimal planning for integrated energy systems considering part-load characteristics and synergistic effect of equipment |
| title_sort | energy hub based optimal planning for integrated energy systems considering part load characteristics and synergistic effect of equipment |
| topic | Energy hub Integrated energy system Configuration planning Part-load characteristics Genetic algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2096511721000451 |
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