Optimal operation strategy for interconnected microgrids in market environment considering uncertainty
•Solved the optimal operation problem for IMS in market environment with uncertainty.•Established a hierarchical distributed framework for cloud-edge coordination.•Proposed a bi-level distributed optimization model with fair price mechanism.•Analytical target cascading and augment Lagrange method ar...
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| Published in: | Applied energy Vol. 275; p. 115336 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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01.10.2020
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| ISSN: | 0306-2619, 1872-9118 |
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| Abstract | •Solved the optimal operation problem for IMS in market environment with uncertainty.•Established a hierarchical distributed framework for cloud-edge coordination.•Proposed a bi-level distributed optimization model with fair price mechanism.•Analytical target cascading and augment Lagrange method are integrated.•The diagonal quadratic approximation is employed for parallel solution.
The interconnected microgrid system (IMS) is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. To optimally coordinate the operation of microgrids owned by different owners while considering uncertainties in market environment, a bi-level distributed optimized operation method for IMS with uncertainties is proposed in this paper. A hierarchical and distributed operational communication architecture of IMS is first established. A bi-level distributed optimization model was built for IMS, where at the upper level, the IMS operates purchase-sale mode or demand response mode with the distribution network operator and optimizes the trading power with microgrids to maximize revenue. At the lower level, the chance constraint programming is used to describe and deal with the uncertainty of renewable energy and loads and optimize the output and energy storage of distributed energy with the goal of minimum cost. The analytical target cascading and augmented Lagrange method are combined to decouple and reconstruct the bi-level model for distributed solution and establishing a fair price mechanism. The optimal solutions of the problem are obtained through parallel iteration, in which the price signal plays a coordinated role in the distributed iterative optimization process. Abundant case studies verify the advantages of the model and the performance of the proposed method. |
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| AbstractList | •Solved the optimal operation problem for IMS in market environment with uncertainty.•Established a hierarchical distributed framework for cloud-edge coordination.•Proposed a bi-level distributed optimization model with fair price mechanism.•Analytical target cascading and augment Lagrange method are integrated.•The diagonal quadratic approximation is employed for parallel solution.
The interconnected microgrid system (IMS) is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. To optimally coordinate the operation of microgrids owned by different owners while considering uncertainties in market environment, a bi-level distributed optimized operation method for IMS with uncertainties is proposed in this paper. A hierarchical and distributed operational communication architecture of IMS is first established. A bi-level distributed optimization model was built for IMS, where at the upper level, the IMS operates purchase-sale mode or demand response mode with the distribution network operator and optimizes the trading power with microgrids to maximize revenue. At the lower level, the chance constraint programming is used to describe and deal with the uncertainty of renewable energy and loads and optimize the output and energy storage of distributed energy with the goal of minimum cost. The analytical target cascading and augmented Lagrange method are combined to decouple and reconstruct the bi-level model for distributed solution and establishing a fair price mechanism. The optimal solutions of the problem are obtained through parallel iteration, in which the price signal plays a coordinated role in the distributed iterative optimization process. Abundant case studies verify the advantages of the model and the performance of the proposed method. The interconnected microgrid system (IMS) is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. To optimally coordinate the operation of microgrids owned by different owners while considering uncertainties in market environment, a bi-level distributed optimized operation method for IMS with uncertainties is proposed in this paper. A hierarchical and distributed operational communication architecture of IMS is first established. A bi-level distributed optimization model was built for IMS, where at the upper level, the IMS operates purchase-sale mode or demand response mode with the distribution network operator and optimizes the trading power with microgrids to maximize revenue. At the lower level, the chance constraint programming is used to describe and deal with the uncertainty of renewable energy and loads and optimize the output and energy storage of distributed energy with the goal of minimum cost. The analytical target cascading and augmented Lagrange method are combined to decouple and reconstruct the bi-level model for distributed solution and establishing a fair price mechanism. The optimal solutions of the problem are obtained through parallel iteration, in which the price signal plays a coordinated role in the distributed iterative optimization process. Abundant case studies verify the advantages of the model and the performance of the proposed method. |
| ArticleNumber | 115336 |
| Author | Wang, Chengshan Sun, Fangyuan Li, Shupeng Kong, Xiangyu Liu, Dehong |
| Author_xml | – sequence: 1 givenname: Xiangyu surname: Kong fullname: Kong, Xiangyu email: eekongxy@tju.edu.cn organization: Key Laboratory of Smart Grid of Ministry of Education (Tianjin University), Nankai District, Tianjin 300072, China – sequence: 2 givenname: Dehong surname: Liu fullname: Liu, Dehong email: Dekh_liu@tju.edu.cn organization: Key Laboratory of Smart Grid of Ministry of Education (Tianjin University), Nankai District, Tianjin 300072, China – sequence: 3 givenname: Chengshan surname: Wang fullname: Wang, Chengshan organization: Key Laboratory of Smart Grid of Ministry of Education (Tianjin University), Nankai District, Tianjin 300072, China – sequence: 4 givenname: Fangyuan surname: Sun fullname: Sun, Fangyuan organization: Key Laboratory of Smart Grid of Ministry of Education (Tianjin University), Nankai District, Tianjin 300072, China – sequence: 5 givenname: Shupeng surname: Li fullname: Li, Shupeng organization: Tianjin Electric Power Company Electric Power Science Research Institute, Tianjin, 300384, China |
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| Keywords | Uncertainty Bi-level energy dispatch Multi-microgrid system Decentralized framework Power Internet of things |
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