Unit Commitment Accommodating Large Scale Green Power

• Published in: Applied sciences Vol. 9; no. 8; p. 1611
• Main Authors: Ju, Yuntao, Wang, Jiankai, Ge, Fuchao, Lin, Yi, Dong, Mingyu, Li, Dezhi, Shi, Kun, Zhang, Haibo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 18.04.2019
• Subjects: Clean energy; Clean technology; Electric power distribution; Energy resources; energy storage system; Gaussian mixture model; Green energy; Nuclear electric power generation; Nuclear energy; nuclear power generation; Nuclear power plants; Nuclear reactors; Objective function; Optimization; Peak load; Probability distribution; Pumped storage; Random variables; Schedules; Scheduling; Security; spinning reserve; Standard deviation; Thermal power; Unit commitment; Wind farms; Wind power; wind power generation; China
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app9081611

As more clean energy sources contribute to the electrical grid, the stress on generation scheduling for peak-shaving increases. This is a concern in several provinces of China that have many nuclear power plants, such as Guangdong and Fujian. Studies on the unit commitment (UC) problem involving the characteristics of both wind and nuclear generation are urgently needed. This paper first describes a model of nuclear power and wind power for the UC problem, and then establishes an objective function for the total cost of nuclear and thermal power units, including the cost of fuel, start-stop and peak-shaving. The operating constraints of multiple generation unit types, the security constraints of the transmission line, and the influence of non-gauss wind power uncertainty on the spinning reserve capacity of the system are considered. Meanwhile, a model of an energy storage system (ESS) is introduced to smooth the wind power uncertainty. Due to the prediction error of wind power, the spinning reserve capacity of the system will be affected by the uncertainty. Over-provisioning of spinning reserve capacity is avoided by introducing chance constraints. This is followed by the design of a UC model applied to different power sources, such as nuclear power, thermal power, uncertain wind power, and ESS. Finally, the feasibility of the UC model in the scheduling of a multi-type generation unit is verified by the modified IEEE RTS 24-bus system accommodating large scale green generation units.