A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy. (15th August 2018)

• Record Type: Journal Article
• Authors: Wei, Congying; Xu, Jian; Liao, Siyang; Sun, Yuanzhang; Jiang, Yibo; Ke, Deping; Zhang, Zhen; Wang, Jing
• Is Part Of: Applied energy. Volume 224(2018)
• Page Start: 659
• Page End: 670
• Publication Date: 2018-08-15
• Subjects: Virtual power plant -- Distributed energy resource -- Thermostatically controlled loads -- A bi-level scheduling -- Forecast error; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2018.05.032
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Thermostatically controlled loads are scheduled to decrease imbalanced power of virtual power plant. Proportion static and dynamic aggregation not affected by parameters heterogeneity are proposed. A bi-level optimal scheduling model and its two-step simplified algorithm are established. The performance is verified under different regulating ranges, heterogeneity and forecast errors. Abstract: With the penetration of renewable energy increasing, the power system requires higher flexibility of power regulation. Virtual power plants can aggregate distributed flexible loads to improve the utilization of distributed renewable energy. In this paper, a bi-level scheduling model for virtual power plants with a large number of distributed thermostatically controlled loads and intermittent renewable energy is established to reduce the net exchange power deviation caused by the forecast error of renewable energy. The upper level optimizes the exchange power curve and reduces the imbalance costs in intraday, while the lower level tracks the optimized power curve in real-time to complete the regulation target. Static and dynamic aggregation method reflecting the regulation characteristics of aggregated thermostatically controlled loads is proposed and applied in lower/upper level, respectively. In addition, a two-step simplified strategy is proposed to solve the mixed integer nonlinear programming in upper level. Simulation results show that the proposed method can reduce the maximum imbalance power, and it is not affected by parameters heterogeneity, which is suitable for virtual power plants with diversified users.