Abstract

Power systems with a high level of renewable energy penetration face challenges due to the inherent properties of some renewable energy sources, such as their variability and uncertainty. These systems require reliable technologies capable of handling large ramps and flexibility needs. Concentrating Solar Power (CSP) has been identified as one solution, which has been researched and implemented in several countries. This paper presents a novel analysis and evaluation of the impacts of choosing an inadequate representation of CSP technology in power system planning tools. The current state of CSP in power system expansion planning in the literature is examined, providing a classification for the modeling of investment and operation of CSP plants. Based on a proposed analysis framework, different models and configurations for CSP plants are evaluated and applied to a 5-bus test system. One of the key findings is that the selected model highly impacts the computational effort (150% more processing time), the quality of the planning decision (14% more overall costs), and the total emissions (up to 52% more emissions). A storage-based model proves to be the most suitable option, considering the operation and investment costs, as well as computational burden. The selected model achieves a 1% error compared to the results obtained with a reference model, while also requiring 40% less computation effort. The proposed framework can be applied to other power system structures by choosing the best suited CSP modeling.