A robust optimization approach for integrated community energy system in energy and ancillary service markets

被引:150
作者
Zhou, Yizhou [1 ]
Wei, Zhinong [1 ]
Sun, Guoqiang [1 ]
Cheung, Kwok W. [2 ]
Zang, Haixiang [1 ]
Chen, Sheng [1 ]
机构
[1] Hohai Univ, Coll Energy & Elect Engn, Nanjing 210098, Jiangsu, Peoples R China
[2] GE Grid Solut, Redmond, WA 98052 USA
基金
美国国家科学基金会;
关键词
Integrated community energy system; Uncertainty; Robust optimization; Energy market; Ancillary service market; Gaussian process; VIRTUAL POWER-PLANT; SPINNING RESERVE MARKETS; JOINT ENERGY; WIND POWER; SUPPLY-SYSTEMS; MANAGEMENT; OPERATION; PRICE; STORAGE; TRENDS;
D O I
10.1016/j.energy.2018.01.078
中图分类号
O414.1 [热力学];
学科分类号
摘要
Distributed energy resources within local energy systems can be reorganized into a single entity, namely, into an integrated community energy system. This integration provides adequate scale to participate in wholesale markets. This paper proposes a day-ahead scheduling strategy for the integrated community energy system in a joint energy and ancillary service markets. The uncertainty of energy market prices, ancillary service market prices, wind power, and photovoltaic power are taken into account. The proposed integrated community energy system organizes combined cooling, heating, and power systems in different areas, and aggregates diverse distributed energy resources. Meanwhile, regulation up, regulation down, spinning, and non-spinning reserves are simultaneously employed in the proposed model. The robust optimization approach is adopted to handle uncertainty, and confidence intervals of uncertain parameters are predicted by a Gaussian process method. Finally, simulations of a real regional multi energy system demonstrate the effectiveness and applicability of the proposed model. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 15
页数:15
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