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Day-ahead interval optimization for CCHP system considering uncertainty of wind power and PV

•A day-ahead interval optimization method for the CCHP system considering the uncertainty of wind power and PV is proposed.•The wind power and PV output are expressed in interval mathematics in the proposed model.•The model analyses the scheduling results of load demands and wind power, PV under fou...

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Bibliographic Details
Published in:International journal of electrical power & energy systems 2022-06, Vol.138, p.107895, Article 107895
Main Authors: Zeng, Linjun, Xu, Jiazhu, Wu, Min, Tang, Jiachang, Wu, Qiuwei, Wang, Qike, Fan, Guoqi
Format: Article
Language:English
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Summary:•A day-ahead interval optimization method for the CCHP system considering the uncertainty of wind power and PV is proposed.•The wind power and PV output are expressed in interval mathematics in the proposed model.•The model analyses the scheduling results of load demands and wind power, PV under four seasons.•The economy and environmental friendliness of the model are verified via interval optimization and robust optimization. To address the uncertainty of renewable energy and different load demands under different seasons in combined cooling, heating, and power (CCHP) system, a day-ahead interval scheduling optimization method is proposed for the CCHP system taking into account the uncertainty of wind power and photovoltaic (PV). Based on the interval theory, the uncertainty of wind power and PV are expressed by intervals. The total operating cost of carbon oxide emissions treatment cost and energy purchase cost is minimized as an objective function. A day-ahead interval optimization model of the CCHP system including wind power, PV, and energy storage is established considering different load demands in four seasons. The established nonlinear integer programming model is converted into the mixed-integer linear programming (MILP) model. The model is solved by interval linear programming. The CCHP system of a park is studied and compared with robust optimization. The simulation results verify the effectiveness of the method in this paper to achieve effective cooperative operation of the economy and environmental protection.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2021.107895