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

Zhou, Yizhou, Wei, Zhinong, Sun, Guoqiang, Cheung, Kwok W., Zang, Haixiang, Chen, Sheng
Energy 2018 v.148 pp. 1-15
confidence interval, cooling, energy, market prices, markets, models, solar energy, spinning, uncertainty, wholesale marketing, wind power
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.