CSP clustering in unit commitment for power system production cost modeling

Abstract

The power system planning requires the simulation of unit commitment (UC) for long time periods up to multiple years or decades which is conducted with production cost modeling (PCM) and usually ends up solving a number of mixed integer programming problems. The development of concentrating solar power (CSP) raises the computational burden of PCM dramatically due to its complex structural and operational characteristics, small unit capacity and large unit number. To improve the PCM efficiency for power systems with large scale CSP generation, a CSP clustering method is proposed based on a novel CSP unit model where the startup and heat accumulation process is considered to simulate CSP operation properly and avoid infeasible operation schemes. In the CSP clustering method, a series of CSP units are modelled in clusters and the numerous binary variables are replaced by integer ones. The number of the variables can be greatly reduced and so is the problem scale. The case studies on the modified IEEE-RTS 1979 have verified the validity and effectiveness of the proposed model and method. The CSP clustering method well outperforms the aggregated unit model which is introduced for comparison. The solution time for the UC with CSP is dramatically reduced (even by 1–2 orders of magnitude) with high accuracy especially the generation cost whose deviation is usually below 0.1%. The proposed method shows great potential in power system planning and operation with large-scale CSP generation.