Markov Model and Game of Cooperation-based Storage Capacity Configuration for Multi-integrated Energy Systems

With the dual carbon goal, reasonable planning and configuration of the distributed energy storage among integrated energy parks to realize energy storage sharing would promote high consumption of renewable energy and improve system stability. Firstly, considering the uncertainty of renewable energy output in parks represented by the Markov states, a stochastic programming model of energy storage capacity configuration based on Markov model is established. Secondly, considering the energy trade between parks to reduce their own operating costs, a multi-objective model of energy storage capacity optimization configuration in interconnected multi-parks based on Nash bargaining is established with the objectives of minimum investment operating cost, minimum carbon emission penalty cost, minimum light abandonment penalty cost, and minimum inter-area trading cost in each park. Then, the nonconvex nonlinearization model is transformed into two subproblems and solved by alternating direction multiplier method and CONOPT solver. Finally, by analyzing the decision results under different modes and schemes, it is verified that the proposed model could rationally allocate the energy storage capacity and effectively reduce the cost, carbon emission and photovoltaic curtailment.