Stochastic Scheduling of Integrated Energy Systems Considering Wind Power and Multienergy Loads Uncertainties
Publication: Journal of Energy Engineering
Volume 143, Issue 5
Abstract
This paper proposes a stochastic day-ahead scheduling framework for integrated energy systems (IES) considering uncertain wind power generation and multienergy loads. The structure and modeling of the IES consisting of electrical, natural gas, and heating networks are presented. The network constraints of the electricity network, natural gas network, and heating network are formulated and incorporated into the optimization model. Uncertainties of hourly wind power and multienergy loads are taken into account by creating multiple representative scenarios with different probabilities using Monte Carlo simulation. The stochastic scheduling model is formulated as a mixed integer linear programming (MILP) problem by linearizing the nonlinear constraints, with the objective function of minimizing the total expected operation cost. Numerical results validate the proposed model and demonstrate the impact of natural gas and heating network on IES operation.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (Nos. 51377016, 51477027, 51677022, 51607033, and 51607034).
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Published In
Journal of Energy Engineering
Volume 143 • Issue 5 • October 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Oct 27, 2016
Accepted: Feb 20, 2017
Published online: May 12, 2017
Published in print: Oct 1, 2017
Discussion open until: Oct 12, 2017
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