Optimal Wind-Solar Capacity Allocation With Coordination of Dynamic Regulation of Hydropower and Energy Intensive Controllable Load

• Published in: IEEE access Vol. 8; pp. 110129 - 110139
• Main Authors: Yang, Hongming, Yu, Qian, Liu, Junpeng, Jia, Youwei, Yang, Guangya, Ackom, Emmanuel, Dong, Zhao Yang
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Alternative energy; Bi-level capacity allocation; Cost function; dynamic regulation; energy intensive controllable load; Fluctuations; Hybrid systems; Hydroelectric power; Hydroelectric power generation; Hydroelectric power stations; hydropower; Load modeling; Operating costs; Optimization; Regulation; Renewable energy; Renewable resources; Resource management; source-load tracking; Tracking; Wind; Wind power generation
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3001666

With the increasing penetration of renewable energy, it becomes challenging to smoothen highly fluctuant and intermittent power output only through the conventional thermal units. In this paper, by exploiting the dynamic regulating ability of hydropower and energy intensive controllable load to reduce the power output uncertainties, an optimal wind-solar capacity allocation method is proposed. The power regulation characteristics of hydropower stations based on hydraulic head and energy intensive controllable load based on complex production process are modelled. A bi-level (including planning and operation layers) optimization model for wind-solar capacity allocation is proposed, which is subject to the system dynamic regulation constraints. In the planning layer, a cost function model is constructed to minimize the investment and operational cost of the hybrid system with wind-solar, hydropower and energy intensive load. In the operation layer, a coordinated optimal dispatching scheme is proposed to minimize the dynamic source-load tracking coefficient. Finally, case studies on Hunan province China are carried out through four scenarios of various combinations of energy intensive controllable load, system regulation ability and source-load tracking coefficient. The results show the proposed method that taken all of these into account provides better performance in adapting to the power fluctuations, which improves the capacity allocation accuracy of renewable energy and decreases their curtailed amount.