With the gradual depletion of traditional primary energy, various forms of renewable energy have been widely used [1
]. As the penetration rate of renewable energy gradually increases, the distribution networks (DNs) transform into active networks, the characteristics of which are that control and dispatch are distributed, power flows are bidirectional [2
]. Microgrids (MGs) are presented to connect to DNs in response to the growing power supply security issues, as well as considering the economics of energy, cleanliness and various ancillary services [3
]. With the maturity of distributed power sources and energy storage technology, multi-MGs’ access to distribution networks gradually become the mainstream. As a controllable integrated unit of distributed power supply, energy storage device and user load, the MG can be flexibly controlled and managed and can run in grid-connected or island mode. It is of considerable significance to increase the economic and environmental benefits of the power system.
The traditional research of MGs mainly concentrates on the utilization of electric power. With the introduction of the concept of energy internet and the development of communication technology, the barriers between various forms of energy are being broken [5
]. The multi-energy systems integrate multiple types of energy, such as natural gas, coal, petroleum, and renewable power sources, which are highly coupled with production, transmission, and management. Combined cooling, heating and power (CCHP) technology is widely used in small and medium-sized MGs, which leads to new challenges for optimized dispatch of MGs [7
Much effort has been focused on the optimal dispatch of the MGs [11
]. Wang Chengshan proposes a general modeling method using an energy bus to describe the injection of different forms of energy in [12
]. To minimize fuel costs, Seon-Ju uses the direct search method to tackle the economic problem considering load and DG constraints [11
]. Chunyang Liu develops a mixed-integer linear programming (MILP) dispatch model of MGs considering the lifetime of the battery under the weighted Wh throughput method [13
]. For multi-energy microgrids, operating modes proceed following the electric load (FEL), following the thermal load (FTL) and optimal economic dispatch, etc. [14
]. Li Lin proposes an economic dispatch method of CCHP-based multi-microgrids considering the power interaction [15
]. Liu N proposes an energy sharing strategy, which let CHP units to break the limit of working modes [16
]. Bui, V develops an internal trading method with barter trading, which can reduce the power trading with the external system [17
]. For stochastic operation [18
], Li Yong proposes a low carbon micro integrated electric power, natural gas, and heat delivery system, considering uncertainties of renewable power and demand under the scenario-based method in [18
]. A hierarchical energy management strategy is presented in [19
] to establish an efficient framework for MGs considering the uncertainty of power interaction among MGs. In [20
], a joint-dispatch method of reserve and energy is presented for the study of CCHP MGs considering the thermal dynamics of buildings and forecast errors of renewable power. When considering demand response [21
], Rakipour establishes an energy hub with multi-energy flow considering uncertainties of renewable power and different degrees of demand response of cooling and electric load to maximize income in [21
]. In [22
], a mechanism of bi-transaction mode between CCHP-based-MG and a load aggregator including pricing strategy and a two-stage optimization model is introduced to achieve integrated demand response.
As renewable power sources, MGs, distributed energy storage systems, and controllable loads are connected to the DN, power quality monitoring [23
] and optimal dispatch [24
] of the DN has become increasingly important. There are also many types of research on the coordinate dispatch of the DN and MGs [25
]. 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
In summary, some of the main deficiencies of the above research can be generalized as follows:
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;
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;
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:
Cooling and heating loads are taken into consideration, which will increase the complementary use of energy and more dispatch flexibility.
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.
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. Numeral results are given and analyzed in Section 5
. Finally, the conclusion is presented in Section 6