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Li Yao
School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, People’s Republic of China

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Journal article
Published: 10 September 2019 in IFAC-PapersOnLine
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Multi-terminal VSC-HVDC (MTDC) is considered to be a attractive option for integrating wind energy from large-scale offshore wind farms. This paper proposes a distributionally robust economic dispatch model with considering the operation of MTDC. The power output of a wind farm is a random variable and assumed to follow an unknown probability distribution. The proposed model aims to seek the optimal economic dispatch decision under the worst-case probability distribution. Although the power equations for MTDC are nonlinear, we obtain a linear approximation by linearizing them around the nominal voltage. We propose a method to transform the proposed model to a linear model and it can be solved efficiently.

ACS Style

Li Yao; Xiuli Wang. Distributionally Robust Chance-constrained Economic Dispatch For Integrating Wind Energy Through Multi-terminal VSC-HVDC. IFAC-PapersOnLine 2019, 52, 159 -164.

AMA Style

Li Yao, Xiuli Wang. Distributionally Robust Chance-constrained Economic Dispatch For Integrating Wind Energy Through Multi-terminal VSC-HVDC. IFAC-PapersOnLine. 2019; 52 (4):159-164.

Chicago/Turabian Style

Li Yao; Xiuli Wang. 2019. "Distributionally Robust Chance-constrained Economic Dispatch For Integrating Wind Energy Through Multi-terminal VSC-HVDC." IFAC-PapersOnLine 52, no. 4: 159-164.

Journal article
Published: 24 October 2018 in Sustainability
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The requirement for energy sustainability drives the development of renewable energy technologies and gas-fired power generation. The increasing installation of gas-fired units significantly intensifies the interdependency between the electricity system and natural gas system. The joint scheduling of electricity and natural gas systems has become an attractive option for improving energy efficiency. This paper proposes a robust day-ahead scheduling model for electricity and natural gas system, which minimizes the total cost including fuel cost, spinning reserve cost and cost of operational risk while ensuring the feasibility for all scenarios within the uncertainty set. Different from the conventional robust optimization with predefined uncertainty set, a new approach with risk-averse adjustable uncertainty set is proposed in this paper to mitigate the conservatism. Furthermore, the Wasserstein–Moment metric is applied to construct ambiguity sets for computing operational risk. The proposed scheduling model is solved by the column-and-constraint generation method. The effectiveness of the proposed approach is tested on a 6-bus test system and a 118-bus system.

ACS Style

Li Yao; Xiuli Wang; Tao Qian; Shixiong Qi; Chengzhi Zhu. Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach. Sustainability 2018, 10, 3848 .

AMA Style

Li Yao, Xiuli Wang, Tao Qian, Shixiong Qi, Chengzhi Zhu. Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach. Sustainability. 2018; 10 (11):3848.

Chicago/Turabian Style

Li Yao; Xiuli Wang; Tao Qian; Shixiong Qi; Chengzhi Zhu. 2018. "Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach." Sustainability 10, no. 11: 3848.