The multi-energy system is a promising energy-efficient technology to supply electric and thermal energy to end-users simultaneously, which can realize the energy cascade utilization. However, it is challenging to optimize the operation of multi-energy systems due to their inherent structural complexity, as well as the highly coupled nature of multiple energy flows and the uncertainty of renewable energy generation. This paper proposed a collaborative demand-controlled operation strategy for a multi-energy system, which consists of an upper-level model and a lower-level model. In the upper-level model, a robust linear optimization method is adopted to optimize the system operation in a day-ahead stage. In the lowerlevel model, a stochastic rolling optimization method is applied to achieve a dynamic adjustment to cope with the fluctuation in both renewable electricity generation and electric load. The multiple energy demandcontrolled strategy is also applied in the optimal operation strategy to achieve load shifting and to create flexibility in energy demand despite the "source-load" imbalance power fluctuation. A case study is carried out and simulation results verify the effectiveness and correctness of the proposed model of the coordinated operation framework.INDEX TERMS Multi-energy system; robust linear optimization; indoor temperature control; demand response; optimal operation This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

A multi-energy system can supply both electric and thermal energy simultaneously to the end-users to achieve a high energy use-efficiency. However conventional operational strategies for multienergy systems, in the existing works, do not consider renewable energy generation plants and CCHP plants as belonging to different interests. To cope with this problem, this article studies a cooperative operation framework model for a Wind-Solar-CCHP Multi-energy system. Instead of the conventional noncooperative solution-based method, the optimal operation scheduling problem of a multi-energy system is described as an optimization problem of Nash Bargaining. Then the optimization problem of Nash Bargaining for the multi-energy system decomposed into two subproblems: social welfare maximization problem (P1) and energy trading payment problem (P2). The optimal energy transaction profiles can be obtained by solving the P1 problem and the problem of payment of energy trading between PV, WT plant agents and the CCHP plant agent can be obtained by solving the P2 problem. Both problems P1 and P2 can be formulated into mixed-integer linear programming problems and solved by the alternating directional multiplier method. Numerical studies demonstrate the correctness and effectiveness of the proposed cooperative operation framework and distributed algorithm for solving the two subproblems. Moreover, the bargaining-based cooperative operation method can further induce the multi-energy system to improve the operating profit with the reduced feed-in tariff of distributed generation.

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