Fully Distributed Risk-based Robust Reserve Scheduling for Bulk Hybrid AC-DC Systems

To enhance the cost-effectiveness of bulk hybrid AC-DC power systems and promote wind consumption, this paper proposes a two-stage risk-based robust reserve scheduling (RRRS) model. Different from traditional robust optimization, the proposed model applies an adjustable uncertainty set rather than a fixed one. Thereby, the operational risk is optimized together with the dispatch schedules, with a reasonable admissible region of wind power obtained correspondingly. In addition, both the operational base point and adjustment capacity of tie-lines are optimized in the RRRS model, which enables reserve sharing among the connected areas to handle the significant wind uncertainties. Based on the alternating direction method of multipliers (ADMM), a fully distributed framework is presented to solve the RRRS model in a distributed way. A dynamic penalty factor adjustment strategy (DPA) is also developed and applied to enhance its convergence properties. Since only limited information needs to be exchanged during the solution process, the communication burden is reduced and regional information is protected. Case studies on the 2-area 12-bus system and 3-area 354-bus system illustrate the effectiveness of the proposed model and approach.