当综合能源系统(integrated energy system, IES)的电、气、热系统分属不同的运营主体时，IES内部异质能之间的协调调度会导致各主体利益的严重冲突，不利于维系IES多能系统联合运行机制的稳定性，因此，需要解决IES内部多能系统协同运营定价机制、该机制下的IE内部多能系统协同优化调度，以及IE与配电网(active distribution network, ADN)联合运行优化调度等关键问题，以促进IES中高比例新能源的就地消纳，实现多主体利益共赢。为此，文中提出了IES内部多余电能有偿交易模式，即电力系统将剩余电能转化为气、热能，电力运营商据此制定售能价格，引导气、热公司优先购买，通过气、热时空迁移调节调度，促进新能源就地消纳。对此，文中构建了IES双层优化调度模型：外层，为ADN和IES之间的主从博弈模型，优化电网电价和IES电能交易量；内层，为电力运营商与气、热公司之间的主从博弈模型，优化电力运营商报价和气、热公司购能策略。采用粒子群优化( particle swarm optimization, PSO)算法和CPLEX求解器相结合求解，内、外双层模型交替迭代优化，获得ADN最优购售电价策略及电、气、热各主体最优能量调度策略，并通过多场景算例，对比验证了文中方法的有效性。
英文摘要:
When the electricity, gas and heat systems of integrated energy system (IES) belong to different operating subjects, the coordination and scheduling of heterogeneous energy within IES will lead to serious conflicts of interests among various subjects, which is not conducive to maintaining the stability of the joint operation mechanism of IES multi-energy system. Therefore, it is necessary to solve the key problems, such as the collaborative operation pricing mechanism of IES internal multi-energy system, the collaborative optimization scheduling of IES internal multi-energy system under this mechanism, and the joint operation optimization scheduling between IES and active distribution network (ADN), so as to promote the local consumption of high proportion of new energy in IES and accomplish the win-win interests of multiple subjects. For this reason, this paper proposes a paid transaction mode of surplus electric energy within IES, that is, the power system converts the surplus electric energy into gas and heat energy, which will be the basis that the electric power operator formulates the energy sales, and then guides the gas and heat operators to purchase. All of above is to achieve the aim of promoting the local consumption of new energy through the regulation and scheduling of gas and heat space-time migration. In this regard, this paper constructs an IES double-layer optimal scheduling model: the outer layer is a master-slave game model between ADN and IES, which optimizes the electricity price and IES electric transaction volume；the inner layer is the master-slave game model between the electric power operator and the gas and heat operators, which optimizes the bidding strategy of the electric power operator and the energy purchase strategy of the gas and heat operators. Finally, the PSO algorithm and CPLEX solver are combined to solve the problem, and the internal and external double-layer models are alternately iteratively optimized to obtain the optimal purchase and sale price strategy of ADN and the optimal energy scheduling strategy of electricity, gas and heat. Meanwhile, the effectiveness of the proposed method is verified by multi-scenario examples.