Abstract
The application of gas turbines and power to gas equipment deepens the coupling relationship between power systems and natural gas systems and provides a new way to absorb the uncertain wind power as well. The traditional stochastic optimization and robust optimization algorithms have some limitations and deficiencies in dealing with the uncertainty of wind power output. Therefore, we propose a robust stochastic optimization (RSO) model to solve the dynamic optimal power flow model for electricity-gas integrated energy systems (IES) considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance. Then, the Wasserstein ambiguity set is affined to the eventwise ambiguity set, and the proposed RSO model is transformed into a mixed-integer programming model, which can be solved rapidly and accurately using commercial solvers. Numerical results for EG-4 and EG-118 systems verify the rationality and effectiveness of the proposed model.
Highlights
With the development and practical application of the theory of the “integrated energy system (IES),” it has become a research upsurge to realize the mutual transformation of multienergy flows over the worldwide [1,2,3,4,5,6,7,8]
Is paper proposed an robust stochastic optimization (RSO) model to solve the dynamic optimal power flow model for electricity-gas integrated energy systems (IES) considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance and affined to the eventwise ambiguity set to solve. e main contributions are as follows: (1) e ambiguity set of wind power output is constructed based on Wasserstein distance and affined to the eventwise ambiguity set of the RSO model, which can be solved by commercial solvers such as CPLEX, GUROBI, and MOSEK
Influence of Different Wind Power Penetration Rates on the Results of the RSO Model. e challenge of wind power uncertainty to the electricity-gas IES is usually directly related to wind power penetration rate, and using different ambiguity sets to deal with the uncertainty of wind power output will obtain different results. us, in order to study the impact of the penetration rate of wind power generation on the operation of the electricity-gas IES, the operation results under different penetration rates in the two cases are calculated, respectively, which are shown in Table 1 and Figures 3–6
Summary
With the development and practical application of the theory of the “integrated energy system (IES),” it has become a research upsurge to realize the mutual transformation of multienergy flows over the worldwide [1,2,3,4,5,6,7,8]. DRO has different decision models and corresponding processing methods, which may lead to the model and solution only applicable to specific problems in the electricity-gas IES and lacking generality. Is paper proposed an RSO model to solve the dynamic optimal power flow model for electricity-gas IES considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance and affined to the eventwise ambiguity set to solve. (2) Aiming at the uncertainty of wind power output, Wasserstein ambiguity sets based on 1-norm and ∞−norm are constructed, respectively, to study the influence of wind power penetration, adjustment cost coefficient of wind units, and sample size on the operation of the electricity-gas IES.
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