کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5770987 1629905 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Research papersStudy on optimization of the short-term operation of cascade hydropower stations by considering output error
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Research papersStudy on optimization of the short-term operation of cascade hydropower stations by considering output error
چکیده انگلیسی


- VAR was applied to the short-term reservoir optimal operation.
- A short-term reservoir optimal operation model by considering output error was proposed in this paper.
- EVT-GA was proposed to solve the model.
- The rationality and feasibility of the model was verified.

The study of reservoir deterministic optimal operation can improve the utilization rate of water resource and help the hydropower stations develop more reasonable power generation schedules. However, imprecise forecasting inflow may lead to output error and hinder implementation of power generation schedules. In this paper, output error generated by the uncertainty of the forecasting inflow was regarded as a variable to develop a short-term reservoir optimal operation model for reducing operation risk. To accomplish this, the concept of Value at Risk (VaR) was first applied to present the maximum possible loss of power generation schedules, and then an extreme value theory-genetic algorithm (EVT-GA) was proposed to solve the model. The cascade reservoirs of Yalong River Basin in China were selected as a case study to verify the model, according to the results, different assurance rates of schedules can be derived by the model which can present more flexible options for decision makers, and the highest assurance rate can reach 99%, which is much higher than that without considering output error, 48%. In addition, the model can greatly improve the power generation compared with the original reservoir operation scheme under the same confidence level and risk attitude. Therefore, the model proposed in this paper can significantly improve the effectiveness of power generation schedules and provide a more scientific reference for decision makers.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 549, June 2017, Pages 326-339
نویسندگان
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