# Coordinated Dispatch of Multi-Energy Microgrids and Distribution Network with a Flexible Structure
## 1 Introduction
The MGs can provide the DN auxiliary service [25] to improve the power quality and voltage stability of the DN. Moreover, the MGs have better ability in accommodation of renewable energy and some low-carbon distributed power sources, increasing environmental benefits, and having a positive impact on the DN operation [26]. As two stakeholders, MGs and DN should have their own interests. To maximize their benefits with coordination, in [27] DN is equivalent to a coupled multi-microgrid system, using a decentralized observable Markov decision process with a dual multiplier based on Lagrangian relaxation. Some research not only considers the electric power in the MGs but also takes cooling and heating load into consideration. With the increasingly close coupling of various types of energy, the distribution and regulation of energy are more diversified, providing more choices for ensuring network operation security. CCHP-based MGs have greater flexibility in energy management due to its multi-energy coupling characteristics [28]. In [29], CCHP-based MGs and DN are regarded as two stakeholders, using the analytical target cascading algorithm (ATC) to achieve the optimization goals under the distributed controlling method. Nevertheless, the topology of the DN is not considered. Flexible topologies also have a crucial impact on reducing losses and improving the reliability of DN, which can be achieved through DN reconfiguration [30; 31; 32]. In summary, some of the main deficiencies of the above research can be generalized as follows:  
1. Many literatures only consider the optimal operation of the MG itself, but do not consider the working status of the DN connected to the MG, which will have a bad impact on the entire distribution system;2 Some other literature only considers the dispatch of electric loads when considering the optimal joint dispatching of the MG and the DN regardless of other types of loads;
3 A few works in the literature consider the joint dispatch of multi-energy MGs and the DN but do not consider the topology and power flow of the distribution network itself. Thus, to better study the operation of the MGs-integrated DN, a bi-level optimal dispatch method of multi-energy MGs and DN is proposed in this paper. The framework of the DN with the integration of the distributed generators (DG) and the MGs is shown in Figure 1. A particle swarm optimization (PSO) algorithm with mixed-integer linear programming (MILP) is used to solve the optimization of the bi-level problem. The advantages of the proposed model are as follows:  
1. Cooling and heating loads are taken into consideration, which will increase the complementary use of energy and more dispatch flexibility. 2. The load flow optimization problem of the DN under the integration of the multi-MGs is considered, the aim of which is to improve the operation conditions (minimize the power loss and voltage offset of the DN) and to make the model more accurate. 3. The DN reconfiguration is included in the proposed method to make further efforts to optimize the operation mode and the security of the DN under the integration of MGs and to improve control flexibility with limited control actions, which will also make the MGs sacrifice the minimum economic benefit under the framework of the coordinated dispatch method. The rest of the paper is organized as follows. Section 2 presents the mathematical model of MGs and DN. The form of the problem and the objective function are introduced in Section 3. Section 4 presents the solving method. Numerical results are given and analyzed in Section 5. Finally, the conclusion is presented in Section 6.