Large-scale hydropower system optimization using dynamic programming and object-oriented programming : the case of the Northeast China Power Grid
This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques ar...
| Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 68(2013), 11 vom: 11., Seite 2458-67 |
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| Auteur principal: | |
| Autres auteurs: | , , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2013
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| Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't |
| Résumé: | This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results |
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| Description: | Date Completed 18.03.2014 Date Revised 16.12.2013 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |
| DOI: | 10.2166/wst.2013.528 |