Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach
Abstract Integrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run. A novel IGT&SP planning scheme is proposed to balance the planning cost, i.e. renewable energy sources (...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-10-01
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| Series: | IET Renewable Power Generation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rpg2.12859 |
| _version_ | 1797650322004377600 |
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| author | Lu Qiu Yangqing Dan Xukun Li Ye Cao |
| author_facet | Lu Qiu Yangqing Dan Xukun Li Ye Cao |
| author_sort | Lu Qiu |
| collection | DOAJ |
| description | Abstract Integrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run. A novel IGT&SP planning scheme is proposed to balance the planning cost, i.e. renewable energy sources (RESs) and energy storage systems, based on the distributionally ambiguity sets. A novel decision‐dependent ambiguity set is proposed to capture the relation between the uncertainties of RES output and long‐term planning. A two‐stage risk‐averse distributionally robust optimization is formulated, where the RESs, energy storage systems, and transmission line expansion are optimized in the first stage and a unit commitment problem is proposed in the second‐stage optimization to assess the performance of the expanded system. This problem is reformulated into a two‐stage optimization problem with complete mixed‐integer recourse, where the state variable is binary. A novel enhanced Benders decomposition algorithm is proposed to solve the IGT&SEP efficiently, where the cutting planes are generated by a primal‐dual relaxation of the recourse problem. Simulations are conducted on the modified IEEE‐30 test system and modified IEEE‐118 test system. Compared with adjustable robust optimization and L1‐norm Wasserstein distance‐based distributionally robust optimization, numerical results verify the effectiveness of the proposed IGT&SP, together with the solution algorithm. |
| first_indexed | 2024-03-11T15:58:36Z |
| format | Article |
| id | doaj.art-17dc6bd6ac084270a55ea790fc3ef869 |
| institution | Directory Open Access Journal |
| issn | 1752-1416 1752-1424 |
| language | English |
| last_indexed | 2024-03-11T15:58:36Z |
| publishDate | 2023-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Renewable Power Generation |
| spelling | doaj.art-17dc6bd6ac084270a55ea790fc3ef8692023-10-25T08:27:41ZengWileyIET Renewable Power Generation1752-14161752-14242023-10-0117143442345610.1049/rpg2.12859Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approachLu Qiu0Yangqing Dan1Xukun Li2Ye Cao3Economic Research Institute of State Grid Jinhua Power Supply Company Jinhua Zhejiang ChinaEconomic Research Institute of State Grid Zhejiang Electric Power Company Hangzhou Zhejiang ChinaSchool of Electronic and Information Engineering Xi'an Jiaotong University Xi'an Shaanxi ChinaSchool of Electronic and Information Engineering Xi'an Jiaotong University Xi'an Shaanxi ChinaAbstract Integrated generation, transmission, and storage expansion planning (IGT&SP) is the cornerstone to realize low‐carbon transition considering security constraints in the long run. A novel IGT&SP planning scheme is proposed to balance the planning cost, i.e. renewable energy sources (RESs) and energy storage systems, based on the distributionally ambiguity sets. A novel decision‐dependent ambiguity set is proposed to capture the relation between the uncertainties of RES output and long‐term planning. A two‐stage risk‐averse distributionally robust optimization is formulated, where the RESs, energy storage systems, and transmission line expansion are optimized in the first stage and a unit commitment problem is proposed in the second‐stage optimization to assess the performance of the expanded system. This problem is reformulated into a two‐stage optimization problem with complete mixed‐integer recourse, where the state variable is binary. A novel enhanced Benders decomposition algorithm is proposed to solve the IGT&SEP efficiently, where the cutting planes are generated by a primal‐dual relaxation of the recourse problem. Simulations are conducted on the modified IEEE‐30 test system and modified IEEE‐118 test system. Compared with adjustable robust optimization and L1‐norm Wasserstein distance‐based distributionally robust optimization, numerical results verify the effectiveness of the proposed IGT&SP, together with the solution algorithm.https://doi.org/10.1049/rpg2.12859power system operation and planningpower system planningpower system reliabilitypower transmission planning |
| spellingShingle | Lu Qiu Yangqing Dan Xukun Li Ye Cao Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach IET Renewable Power Generation power system operation and planning power system planning power system reliability power transmission planning |
| title | Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach |
| title_full | Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach |
| title_fullStr | Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach |
| title_full_unstemmed | Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach |
| title_short | Decision‐dependent distributionally robust integrated generation, transmission, and storage expansion planning: An enhanced Benders decomposition approach |
| title_sort | decision dependent distributionally robust integrated generation transmission and storage expansion planning an enhanced benders decomposition approach |
| topic | power system operation and planning power system planning power system reliability power transmission planning |
| url | https://doi.org/10.1049/rpg2.12859 |
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