4.8 Article

Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power

期刊

APPLIED ENERGY
卷 275, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2020.115357

关键词

Day-ahead stochastic scheduling of IEHS; Unit commitment; Reserve; Gaussian Mixture model; Gibbs sampling; Spatial-temporal correlation of wind power

资金

  1. Innovationsfonden through the project Using flexible district heating with heat pumps for integrated electricity and heat dispatch with renewables (HEAT4RES)
  2. MOST China [2018YFE0106600]

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Using the improved flexibility from the district heating system with multiple flexible devices is an effective solution to ensure the cost-effective and secure operation of the integrated energy system with high penetration of renewables. This paper exploits the improved flexibility of the integrated electricity and heat systems by using reserves from multiple flexible devices to accommodate more wind power and reduce operational costs. A two-stage stochastic optimal dispatching scheme is proposed for the integrated electricity and heat system considering both power networks and heat pipelines, and reserves from the condensing combined heat and power units, heat pumps, electric boilers, and heat storage tanks. The proposed scheme balances the power and heat sectors both in the day-ahead and real-time stages with the synergy of different flexible devices and linkage for each device in the two stages. A scenario generation method considering spatial-temporal correlation is proposed to provide reasonable wind power profiles for the two-stage dispatch scheme. The Gaussian mixture model and exponential function are used to construct the spatial and temporal correlation, respectively, and the Gibbs sampling is utilized to reduce the sampling complexity. The case studies were conducted on a 6-bus integrated electricity and heat system and a practical integrated energy system in Northern China. The results show that utilizing the scenario set with spatial-temporal correlation and improved flexibility can effectively reduce the operational cost and wind power curtailment.

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