Multi-stage stochastic dual dynamic programming to low-carbon economic dispatch for power systems with flexible carbon capture and storage devices

The carbon capture and storage (CCS) technique gains much attention due to its role in reducing CO2 emissions. By introducing flexible CCS devices into conventional power plants, the low-carbon economic operation of the power system can be achieved. However, the uncertainty of renewable energy makes it hard to obtain an optimal operation policy. First, the detailed model of CCS consisting of bypass venting stacks, solvent storage tanks, absorber, and stripper is described. Then, a low-carbon economic dispatch model of the power system with CCS is proposed to minimize the total operation and renewable energy abandonment penalty costs. Next, the problem is reformulated as multi-stage stochastic programming, and the stochastic dual dynamic programming (SDDP) method is applied to relieve the computation burden. To control the probability of stopping the algorithm prematurely, a new stopping criterion based on a two-sided hypothesis test is proposed. Finally, the effectiveness of the proposed model and the new stopping criterion is demonstrated by case studies on a practical power system. A low-carbon economic dispatch model of the power system with carbon capture and storage (CCS) is proposed to minimize the total operation and renewable energy abandon penalty costs. The basic formulation of SDDP and a new stopping criterion avoiding the premature convergence of the algorithm are studied.image