Short‐term operational planning framework for virtual power plants with high renewable penetrations. Issue 5 (1st May 2016)

• Record Type: Journal Article
• Authors: Luo, Fengji; Dong, Zhao Yang; Meng, Ke; Qiu, Jing; Yang, Jiajia; Wong, Kit Po
• Is Part Of: IET renewable power generation. Volume 10:Issue 5(2016)
• Page Start: 623
• Page End: 633
• Publication Date: 2016-05-01
• Subjects: power markets -- predictive control -- stochastic processes -- minimisation -- power generation planning -- power generation control -- power generation economics -- power generation dispatch; short‐term operational planning framework -- virtual power plants -- high renewable penetrations -- VPP -- stochastic bidding model -- energy market -- expected economic profit maximisation -- model predictive control‐based dispatch model -- MPC‐based dispatch model -- actual energy output minimisation -- contracted energy minimisation; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2015.0358
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : This study proposes a two‐stage operational planning framework for the short‐term operation of the virtual power plant (VPP). In the first stage, a stochastic bidding model is proposed for the VPP to optimise the bids in the energy market, with the objective to maximise its expected economic profit. The imbalance costs of the VPP are considered in the bidding model. In the second stage, a model predictive control (MPC)‐based dispatch model is proposed to optimise the real‐time control actions. In the real‐time dispatch model, the real‐time information of the resources is continuously updated, and the deviations between the actual energy output and the contracted energy over the MPC control horizon are minimised. The simulation results prove the efficiencies of the proposed method.