期刊
ENERGY REPORTS
卷 9, 期 -, 页码 790-798出版社
ELSEVIER
DOI: 10.1016/j.egyr.2022.11.099
关键词
Wind and Photovoltaic power consumption; Cost analysis; Deep peak shaving; Electricity price response; Chance-constrained programming
This paper constructs a wind-light-fire-storage joint optimal dispatching model based on electricity price response and uncertainty of wind and photovoltaic power. The model guides customers to change their electricity consumption habits through electricity price response and considers the impact of wind and photovoltaic output uncertainty on power grid peaking. Simulation in the modified IEEE30 node system verifies the feasibility and effectiveness of the model.
The high proportion of renewable energy connected to the power grid puts enormous pressure on the power system for peaking. To reduce the peak-to-valley load difference, reduce the abandoned wind and light rate, and improve the economy of power system peaking, this paper constructs a wind-light-fire-storage joint optimal dispatching model based on electricity price response and uncertainty of wind and photovoltaic power. First, the model adds electricity price response to guide customers to change their electricity consumption habits by adjusting electricity prices at different times, bringing economic benefits to customers while shifting part of the peak load to the trough to achieve the purpose of peak shaving and valley filling; Secondly, considering the impact of wind and photovoltaic output uncertainty on power grid peaking, chance-constrained programming is added to the model, which is based on the simulation method, using the Latin hypercube sampling method, eventually transformed into a mixed integer linear programming model for solution; Finally, simulation is carried out in the modified IEEE30 node system to verify the feasibility and effectiveness of the model. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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