Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty

• Published in: Applied energy 2016-04, Vol.167 (C), p.270-279
• Main Authors: Bai, Linquan, Li, Fangxing, Cui, Hantao, Jiang, Tao, Sun, Hongbin, Zhu, Jinxiang
• Format: Article
• Language: English
• Subjects: Coordinated operation; Demand response; Electricity; Energy management; Gas and electricity network; Integrated energy systems; Interval optimization; Intervals; Mathematical models; Natural gas; Networks; Optimization; Uncertainty; Wind power uncertainty
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2015.10.119

•The gas and electricity integrated energy system (IES) is modeled in detail.•A multi-period coordinated operating strategy of the IES is proposed.•Both of the electrical and gas network constraints are considered.•The wind power uncertainty is addressed by interval optimization.•A demand response model is incorporated into the optimization model. In the United States, natural gas-fired generators gained increasing popularity in recent years due to the low fuel cost and emission, as well as the proven large gas reserves. Consequently, the highly interdependency between the gas and electricity networks is needed to be considered in the system operation. To improve the overall system operation and optimize the energy flow, an interval optimization based coordinated operating strategy for the gas-electricity integrated energy system (IES) is proposed in this paper considering demand response and wind power uncertainty. In the proposed model, the gas and electricity infrastructures are modeled in detail and their operation constraints are fully considered, wherein the nonlinear characteristics are modeled including pipeline gas flow and compressors. Then a demand response program is incorporated into the optimization model and its effects on the IES operation are investigated. Based on interval mathematics, wind power uncertainty is represented as interval numbers instead of probability distributions. A case study is performed on a six-bus electricity network with a seven-node gas network to demonstrate the effectiveness of the proposed method; further, the IEEE 118-bus system coupling with a 14-node natural gas system is used to verify its applicability in practical bulk systems.