An Optimal Scheduling Method for Source-Load-Storage Systems Considering Carbon Trading Cost and Forecast Uncertainty

Currently, the new energy is developing rapidly. Medium- and long-term energy and power plans have either been introduced or are expected to be implemented in various places. These plans aim to coordinate the specific construction of the undeveloped source-storage resources with the load demand, improve the new energy consumption rate, and reduce operating costs. Fully combined with various time scales under the power resources planning objectives and future load demand forecasts, a system is developed with the objective of minimizing the total operating costs by introducing fuzzy chance constraints. For planning resources, the coordinated operation of source-load-storage resources is simulated. Taking 2025 and 2030 as the medium- to long-term time nodes, the analysis is conducted from two aspects: the confidence setting and multi-scenarios of the resource allocation scheme. The main study reveals that the model can serve as an effective reference tool for setting the future standby capacity and other indicators. From the perspective of economy and green low-carbon goals, the scale of wind power put into operation should be controlled properly to achieve a balance between economy and green. Our study provides valuable configuration reference from the perspectives of hydropower, thermal power, wind power, and storage power for various regions.