Iterative Decomposition of Joint Chance Constraints in OPF
| Autor: | Gabriela Hug, Mengshuo Jia, Chen Shen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Wind power generation Computer science Energy Engineering and Power Technology Systems and Control (eess.SY) Iterative framework Electrical Engineering and Systems Science - Systems and Control Upper and lower bounds Test case Risk allocation FOS: Electrical engineering electronic engineering information engineering Resource management Electrical and Electronic Engineering Joint (audio engineering) |
| Zdroj: | IEEE Transactions on Power Systems. 36:4836-4839 |
| ISSN: | 1558-0679 0885-8950 |
| DOI: | 10.1109/tpwrs.2021.3072541 |
| Popis: | In chance-constrained OPF models, joint chance constraints (JCCs) offer a stronger guarantee on security compared to single chance constraints (SCCs). Using Boole's inequality or its improved versions to decompose JCCs into SCCs is popular, yet the conservativeness introduced is still significant. In this letter, a non-parametric iterative framework is proposed to achieve the decomposition of JCCs with negligible conservativeness. An adaptive risk allocation strategy is also proposed and embedded in the framework. Results on an IEEE test case show that the conservativeness using the framework is nearly eliminated, thereby reducing the generation cost considerably. |
| Databáze: | OpenAIRE |
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