A bi-level optimal scheduling model for new-type power systems integrating large-scale renewable energy

Abstract

Abstract The construction of a new type of power system is a key way to achieve the goal of ‘carbon peaking and carbon neutrality’. In the process of developing renewable energy, large-scale wind and photovoltaic power systems replace conventional units, which will have an impact on the stability of the power grid. To eliminate these concerns, this paper proposes a bi-level optimal scheduling model for new-type power systems. The upper level aims to minimize fluctuation of net load, with the consideration of demand response, to smooth the load curve. The lower level takes the minimum operating cost of the new-type power system as the objective function and the most economical scheduling strategy is established. To deal with the uncertainty of renewable energy integrated within the system, the lower model is transformed into a two-stage robust optimization model and solved by applying a column-and-constraint generation method. Finally, a regional power system is selected to conduct a case study comprising 760 MW thermal power, 50 MW·h energy storage, 200 MW wind turbine and 150 MW photovoltaic power. The results show that the constructed two-stage robust optimization model is conducive to establishing the most economical scheduling scheme of the system with an uncertain budget and the minimum operation cost is $45,9031. In addition, demand response and energy storage can reduce peak-to-valley differences in the power system.