A tradeoff between unit capacity and average production cost in spinning reserve optimization |
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| Affiliation: | 1. Key Laboratory of Power System Intelligent Dispatch and Control (Shandong University), Ministry of Education, Jinan 250061, China;2. School of EEE, Nanyang Technological University (NTU), 639798, Singapore;1. Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. Department of Electrical Engineering, Tianjin University, Tianjin 300072, China;3. China Electric Power Research Institute, Beijing 100192, China;4. Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK;1. School of Electrical Engineering, Northeast Electric Power University, Jilin, 132012, China;2. State Grid Chaoyang Power Supply Company, Chaoyang, 122000, China;1. School of Automation, Central South University, Changsha, China;2. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, and Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, China University of Geosciences (Wuhan), Wuhan, China;3. Siberian Branch of the Russian Academy of Sciences, Melentiev Energy Systems Institute, Irkutsk, Russia;1. Tianjin University, Tianjin 300072, China;2. Vrginia Polytechnic Institute and State University, Falls Church, VA 22043, USA;3. Nanyang Technological University, 639798, Singapore;4. Mississippi State University, Starkville, MS 39762, USA;5. Hydro-Quebec Research Institute, Varennes, QC J3X 1S1, Canada;6. National University of Singapore, 117575, Singapore;7. Virginia Tech, Blacksburg, VA 24061, USA;8. Universidad de Oviedo, Oviedo 33003, Spain;9. Skolkovo Institute of Science and Technology, Moscow 121205, Russian Federation |
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| Abstract: | In power systems the spinning reserve (SR) amount can be determined by deterministic or probabilistic techniques. Probabilistic techniques draw more attention since they can consider the economics and the stochastic nature of system behavior and component failures. In probabilistic techniques, the tradeoff between cost and reliability directly affects the SR deployment and it has been extensively analyzed. However, there is another tradeoff which reflects the compromise between the unit capacity and average production cost in the SR optimization problem. This tradeoff impacts the solution accuracy to a certain extent and influences the complexity of the model, and it has not been explicitly analyzed before. In this paper, a new SR optimization method is proposed in which the tradeoff between unit capacity and average production cost is well respected. The proposed method strikes a good balance between solution accuracy and computation efficiency and can obtain better results within a desirable run time compared with those of the previous methods. Besides, the proposed method can also be used to improve the solution of the reserve constrained unit commitment problem. It can lower the total cost by just redistributing the MW dispatch even when the SSR is fixed. The efficiency and validity of the proposed method are verified using the IEEE reliability test system. |
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| Keywords: | Expected energy not supplied (EENS) Spinning reserve (SR) System spinning reserve (SSR) Tradeoff Unit commitment (UC) |
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