Coordinated operation framework for multi-integrated energy systems with electricity-carbon interaction based on Nash-Stackelberg-Nash game and distributionally robust chance-constraints

With gradual deepening of coupling between electricity market and carbon market, and advancement of energy technology, interest coupling between multi-integrated energy systems (MIES) and multi-prosumers (MP) has become increasingly close. At same time, output of renewable energy (RE) within system is uncertain. Therefore, it is urgently necessary to establish scheduling framework that can coordinate MIES and MP to effectively address uncertainty of RE output and achieve collaborative operation. For this purpose, this paper proposes three-layer game distributionally robust chance-constrained (DRCC) scheduling strategy of MIES electricity-carbon interaction Nash-Stackelberg-Nash (N-S-N). Firstly, Nash game of electricity between MP, Stackelberg game between MP and IES, and Nash game of electricity-carbon interaction between MIES are constructed by using game theory. Then, three-layer MIES N-S-N game model is constructed to precisely describe interaction characteristics between MIES and MP. Based on this, uncertainty of RE output is characterized by using rectangular information fuzzy set, and generalized DRCC model is established. Coupling this model with N-S-N three-layer game model, N-S-N three-layer game DRCC framework is proposed. Furthermore, Stackelberg game between IES and MP is handled by applying Karush-Kuhn-Tucker conditions and McCormick envelope method. DRCC is reformulated as second-order cone programming problem that is easy to solve through Conditional Value at Risk (CVaR). Nesterov-accelerated prediction-correction alternating direction method of multipliers (NAPC-ADMM) is adopted to determine optimal interaction volumes between distributed decision-making MIES. Finally, case analysis verified effectiveness of proposed method.