Scheduling of combined electric-heating system based on multi-objective two-stage stochastic programming method

Summary: Aiming at the problem that the electric-heat integrated energy system is difficult to dispatch effectively due to the randomness and volatility of wind power output, a cost minimization andA multi-objective two-stage stochastic programming method with the goal of minimising wind abandonment(multi-objective and two-stage stochastic programming,MOTSP), where a two-stage randomThe planning model conducts modeling analysis on the cost minimization part. The first stage takes the start-up and stop cost of thermal power units as the scheduling target, and the second stage takes the unit operating cost as the scheduling target.Finally, a multi-objective algorithm is usedNSGA-ⅡThe screening mechanism of the solution in the solution solves the stochastic programming problem.The method uses Gaussian distribution to describe the load and wind power prediction error to solve the uncertainty of wind power output, uses the Monte Carlo method to generate random scenarios, and uses the reverse reduction technique to reduce the scenarios.The simulation results show that the proposed MOTSP algorithm is better than the solution set of many other intelligent algorithmsMore uniform and wider, with better convergence, minimizes wind curtailment and minimizes unit operating costs.