**1. Introduction**

With the increasingly serious energy crisis and environmental problems, the traditional distributed energy system is gradually being replaced by the integrated energy system, which will become the first choice for the future energy system [1]. The combined cooling, heating, and power (CCHP) system is a typical integrated energy system, and the use of this operating structure can improve the energy utilization efficiency of the system to more than 85% [2]. Heat storage devices can improve the utilization rate of waste heat [3]. Adding renewable energy generation methods, such as photovoltaic power generation and wind power generation, to the traditional CCHP system can improve the environmental protection of the CCHP system and reduce the dependence of the system on non-renewable energy. Increasing the use of clean energy helps reduce carbon emissions [4]. Rising wind power penetration can threaten the stability of the power system [5]. Compared to wind power, photovoltaic power is highly predictable and stable [6,7]. The introduction of photovoltaic/thermal systems can reduce pollutant gas emissions of the combined heat and power system and improve economic efficiency [8]. However, due to the influence of weather factors by temperature, solar irradiance, wind speed, etc., CCHP systems with renewable energy generation methods have uncertainty in electricity production, which

**Citation:** Ning, N.; Liu, Y.-W.; Yang, H.-Y.; Li, L.-L. Design and Optimization of Combined Cooling, Heating, and Power Microgrid with Energy Storage Station Service. *Symmetry* **2022**, *14*, 791. https:// doi.org/10.3390/sym14040791

Academic Editor: Peng-Yeng Yin

Received: 24 March 2022 Accepted: 9 April 2022 Published: 11 April 2022

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will increase the dependence on the grid [9]. The addition of energy storage batteries can alleviate the pressure on the grid [10]. The way that the user installs energy storage batteries in the CCHP system alone will increase the economic cost of the system, and it will also have little effect on reducing the system's dependence on the grid. Therefore, the research on the construction method and capacity configuration of energy storage devices is of grea<sup>t</sup> value [11]. There are many variables and constraints involved in the CCHP system, and the uncertainty of the load will also affect the optimal configuration and operation of the system. Consequently, it is relatively difficult to determine the optimal operation of the CCHP system [12,13]. The reasonable construction method of energy storage devices and the optimal configuration of the CCHP system can help the further promotion and application of integrated energy systems.

The various devices in the CCHP system determine how the energy is converted. Currently, CCHP systems are mainly divided into two categories: CCHP systems without energy storage equipment and CCHP systems of self-built energy storage equipment by users themselves [14,15]. Both types of CCHP systems can meet the needs of users, but they also have their own problems. During the peak periods of electricity consumption, CCHP systems without energy storage equipment can only be supplemented by the power grid, which increases the power supply pressure of the power grid [16]. Although the CCHP system of self-built energy storage equipment can reduce the dependence of the system on the power grid, the economic cost of the system itself will increase, and the optimization of the entire system will become more complex [17]. By combining the characteristics of the two systems, this study proposes a multi-microgrid operation method based on energy storage station (ESS) services. Operators establish ESS and take advantage of the scale effects of ESS to serve CCHP systems with different load requirements. While reducing the investment cost of the CCHP system, ESS can make profits by charging electricity service fees, so as to achieve a win-win effect between ESS and CCHP systems. Dealing with the coordinated operation between ESS and CCHP systems is a typical system optimization configuration problem.

Methods for optimal system configuration typically include mathematical programming and intelligent optimization algorithms [18]. Intelligent optimization algorithms can solve objective functions quickly and accurately without changing the system model [19]. Intelligent optimization algorithms have greater advantages in dealing with multi-variable, multi-constraint, and nonlinear problems such as system optimization configuration. In previous studies, classical and emerging algorithms, such as particle swarm optimization (PSO), genetic algorithm (GA), and salp swarm algorithm (SSA), have been applied to the optimal configuration of CCHP systems and achieved considerable results [20–22]. The aquila optimizer (AO) algorithm is a heuristic intelligent optimization algorithm proposed in 2021. Its performance is superior to the traditional PSO algorithm, GA, and novel algorithms such as SSA [23]. Similar to other intelligent optimization algorithms, the AO algorithm also has the problem of slow convergence and tendency to fall into local extremes when dealing with complex problems, so the AO algorithm needs to be improved [24]. The chaos strategy increases the randomness of individuals during the initialization stage, the mutation strategy increases the diversity of the population during the iteration, and the levy flight strategy can prevent individuals from falling into local extremes [25,26]. Therefore, by introducing the above strategies, the improved aquila optimizer (IAO) algorithm is proposed. In this study, the IAO algorithm is applied as the optimization algorithm, and the comparison results are better than those of the compared algorithms.

In this study, we analyze the form of energy storage battery configuration of traditional CCHP system and innovatively propose a storage battery configuration scheme. By introducing the improved strategies into the original AO algorithm, the IAO algorithm is proposed and used for the optimal configuration of the CCHP microgrid model. The addition of photovoltaic power generation equipment improves the sustainability and environmental friendliness of the CCHP microgrid. The proposed method reduces the

power supply pressure of the grid, improves the profits of operators, and is conducive to promoting the development of clean energy, alleviating the energy crisis.

The research hypothesis of this study is to reduce the economic cost and exhaust emissions of the CCHP system through optimizing the configuration of the CCHP multimicrogrid system based on ESS service. Through the establishment of ESS by operators, the dependence of the CCHP system on the grid decreases, and the operator makes a profit by providing electrical energy services to the CCHP system. The main work and contributions of this study can be summarized as follows: (1) establishing an optimal configuration model symmetrically considering the economic and environmental benefits of ESS and the CCHP system; (2) proposing the IAO algorithm for optimal system configuration based on the AO algorithm; (3) the proposed algorithm has better optimization performance compared to the original AO algorithm; (4) reducing the dependence of the CCHP system on the grid by establishing ESS; (5) a new energy storage configuration scheme is proposed, which is beneficial to the economic and environmental protection and stable operation of the CCHP system.

The rest of this study is organized as follows: Section 2 briefly analyzes the literature related to the design and optimal configuration of CCHP systems. Section 3 describes the system model proposed in this study. Section 4 describes the original algorithm and the improvement process. Section 5 conducts an actual case study. Section 6 discusses the implications of this study. Finally, conclusions are provided.
