| Autor: |
Huidong Wang, Yunpeng Fang, Xiaoyan Zhang, Zhihui Dong, Xiaoling Yu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Energy Reports, Vol 8, Iss , Pp 252-264 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2352-4847 |
| DOI: |
10.1016/j.egyr.2022.10.289 |
| Popis: |
The traditional robust optimization algorithm can only provide the scheduling plan in the worst case, but due to the time coupling constraints such as climbing and energy storage SOC(State of Charge) constraints, it is difficult to provide an adjustment scheme for intra-day scheduling plan. In the first stage, the upper and lower bounds of equipment output are taken as decision variables, and the cumulative change of load is introduced to deal with the constraint of demand response, so as to form the economic operation domain of the park. The Column-and-Constraint generation method (CCG) is used to solve the three-layer optimization problem, and the scheduling plan and optimal operating domain in the worst case are obtained. The intra-day scheduling can be adjusted arbitrarily according to the new energy output within the interval. Carbon transaction cost is included in the goal function to account for reduced carbon emissions. Simultaneously, to take use of the benefits of flexible adjustment, FM income is incorporated into the goal function, and the charging and discharging behavior of energy storage is defined by optimizing calculations based on real-time capacity prices during daily scheduling. The calculation results show that the proposed robust optimization algorithm based on economic operation domain can be regarded as an extension of the traditional robust algorithm. Besides, the total cost can be reduced and the economy can be improved by adjusting the scheduling scheme according to the new energy output in real time under the premise of ensuring the time coupling constraint. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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