Multi-Power Coordinated Optimization Operation Strategy Considering Conditional Value at Risk

Abstract

In order to achieve carbon peaking and carbon neutrality goals, the power system presents the trend of extensive access of multiple power sources. A multi-power coordination bi-level optimal operation model was proposed. In the upper level model, photovoltaic, gas turbine, energy storage and other power sources were aggregated into the virtual power plant, and the overall dispatching cost of virtual power plant was minimized through optimization. In addition, the conditional value at risk theory was adopted to measure the risks in view of the uncertainty of photovoltaic output. The lower level model was the system clearing model, which took the minimum total cost of the system as the optimization objective. It can consider the virtual power plant, thermal power units and diesel units to participate in the bidding, and output the actual bidding capacity of the virtual power plant back to the upper level, so that the virtual power plant can adjust the power output according to the actual bidding capacity. In order to solve the constructed model, Karush-Kuhn-Tucker (KKT) condition and strong duality theory were used to transform the bi-level model into a single-level model. Finally, an example was given to verify the validity of the model, the results show that the coordinated operation of multiple power sources can effectively reduce the operating cost of the system and improve the consumption rate of renewable energy.

Keywords

• virtual power plant
• multi-power optimization
• bi-level model
• conditional value at risk