Power sharing operation optimization strategy accounting for multivariate uncertainty

Driven by the "dual-carbon" goal, the transition to a clean and low-carbon power system is imminent. In order to realize the cooperative optimization of multiple integrated energy systems (IESs), economic low-carbon operation, and reasonable distribution of benefits, this paper proposes a cooperative operation optimization strategy for multiple IESs considering multivariate uncertainties. Firstly, a cost model for each IES is constructed considering the uncertainties of market price and new energy output; then, a multi-IES cooperative operation optimization model is established based on the Nash negotiation theory, which is decomposed into a multi-IES coalition cost minimization subproblem and a benefit allocation subproblem based on asymmetric bargaining; then, the variable penalty parameter alternating directional multiplier method (ADMM) is adopted to solve the problem, in order to protect the privacy and improve the solving efficiency; finally, a multi-IES cooperative operation optimization strategy is proposed to achieve a reasonable allocation of benefits. Finally, an asymmetric bargaining method is proposed to quantify the contribution size of each participant with a nonlinear energy mapping function, and each IES negotiates based on the size of its electrical energy contribution in the cooperation to ensure the fair distribution of cooperative benefits. Case analysis shows that this method can improve the economic benefits of IESs, reduce carbon emissions, enhance the ability of IESs to cope with uncertain risks, and realize the fair and reasonable distribution of benefits.