Distributed optimization of station-network collaborative operation and alliance benefit allocation for integrated energy system
Shaomin Wang, Shaomin Wang, Shouxiang Wang, Shouxiang Wang, Qianyu Zhao, Xuan Wang, Zhuoran Lin
Abstract
With the increasingly urgent need to build a clean and efficient energy system, the interaction between energy station and networks is closer and the coupling relationship becomes more complex. To break energy barriers in independent solution of energy subsystems and solve the problem of privacy disclosure caused by centralized solution of integrated energy system, a distributed optimization of station-network collaborative operation and alliance benefit allocation for integrated energy system is provided. Firstly, a Nash bargaining model of multi-stakeholder cooperation is constructed based on cooperative game theory; Secondly, the nonconvex and nonlinear Nash bargaining model is equivalent converted into alliance economic optimization subproblem and energy transaction dynamic pricing subproblem for the convenience of solution; Thirdly, a distributed optimization architecture for subproblems is constructed based on alternating direction method of multipliers with an adaptive dynamic penalty factor updating strategy. Finally, the effectiveness of the proposed method is verified by a numerical example and the simulation results show that privacy information and independence in decision-making of each stakeholder are protected. The convergence speed and local refine search ability are improved by the adaptive dynamic penalty factor updating strategy. What’s more, more benefits are obtained than independent optimization, and higher satisfaction and richer information based on dynamic pricing are got than the widely used Shapley value, which is practical significance to improve the enthusiasm of all stakeholders to participate in energy trading and promote energy transformation.