Probability-weighted robust optimization for distributed generation planning in microgrids
Distributed generation (DG) has been rapidly integrated into microgrids. However, uncertain power generation of intermittent DG such as wind turbines brings challenges to the DG planning problem. This paper proposes a novel probability-weighted robust optimization (PRO) method to allocate DG units i...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/10356/141505 |
| _version_ | 1811691415876403200 |
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| author | Zhang, Cuo Xu, Yan Dong, Zhao Yang |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Zhang, Cuo Xu, Yan Dong, Zhao Yang |
| author_sort | Zhang, Cuo |
| collection | NTU |
| description | Distributed generation (DG) has been rapidly integrated into microgrids. However, uncertain power generation of intermittent DG such as wind turbines brings challenges to the DG planning problem. This paper proposes a novel probability-weighted robust optimization (PRO) method to allocate DG units including microturbines and wind turbines in microgrids, aiming to maximize the total profit over a long-term planning horizon. First, probability-weighted uncertainty sets are proposed to model uncertainties including wind turbine output and load demand during a long-term planning horizon which can fully cover the uncertainty spectrum and accurately represent the uncertainty probability distribution. Then, the PRO method optimizes DG sizing and locating under the worst uncertainty cases considering their occurrence probabilities. Therefore, the planning decision is robust against any possible uncertainty realization. Besides, a modified column-and-constraint generation algorithm is developed to solve the PRO problem. Simulation results show that the DG planning obtained by the proposed method can achieve full operating robustness. |
| first_indexed | 2024-10-01T06:19:32Z |
| format | Journal Article |
| id | ntu-10356/141505 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:19:32Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1415052020-06-09T01:54:25Z Probability-weighted robust optimization for distributed generation planning in microgrids Zhang, Cuo Xu, Yan Dong, Zhao Yang School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Distributed Generation Planning Microgrids Distributed generation (DG) has been rapidly integrated into microgrids. However, uncertain power generation of intermittent DG such as wind turbines brings challenges to the DG planning problem. This paper proposes a novel probability-weighted robust optimization (PRO) method to allocate DG units including microturbines and wind turbines in microgrids, aiming to maximize the total profit over a long-term planning horizon. First, probability-weighted uncertainty sets are proposed to model uncertainties including wind turbine output and load demand during a long-term planning horizon which can fully cover the uncertainty spectrum and accurately represent the uncertainty probability distribution. Then, the PRO method optimizes DG sizing and locating under the worst uncertainty cases considering their occurrence probabilities. Therefore, the planning decision is robust against any possible uncertainty realization. Besides, a modified column-and-constraint generation algorithm is developed to solve the PRO problem. Simulation results show that the DG planning obtained by the proposed method can achieve full operating robustness. MOE (Min. of Education, S’pore) 2020-06-09T01:54:25Z 2020-06-09T01:54:25Z 2018 Journal Article Zhang, C., Xu, Y., & Dong, Z. Y. (2018). Probability-weighted robust optimization for distributed generation planning in microgrid. IEEE Transactions on Power Systems, 33(6), 7042-7051. doi:10.1109/TPWRS.2018.2849384 0885-8950 https://hdl.handle.net/10356/141505 10.1109/TPWRS.2018.2849384 2-s2.0-85048873552 6 33 7042 7051 en IEEE Transactions on Power Systems © 2018 IEEE. All rights reserved. |
| spellingShingle | Engineering::Electrical and electronic engineering Distributed Generation Planning Microgrids Zhang, Cuo Xu, Yan Dong, Zhao Yang Probability-weighted robust optimization for distributed generation planning in microgrids |
| title | Probability-weighted robust optimization for distributed generation planning in microgrids |
| title_full | Probability-weighted robust optimization for distributed generation planning in microgrids |
| title_fullStr | Probability-weighted robust optimization for distributed generation planning in microgrids |
| title_full_unstemmed | Probability-weighted robust optimization for distributed generation planning in microgrids |
| title_short | Probability-weighted robust optimization for distributed generation planning in microgrids |
| title_sort | probability weighted robust optimization for distributed generation planning in microgrids |
| topic | Engineering::Electrical and electronic engineering Distributed Generation Planning Microgrids |
| url | https://hdl.handle.net/10356/141505 |
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