# Configuration Optimization of Mobile Photovoltaic-Diesel-Storage Microgrid System Based on CPS-MOEA
## 1 Introduction  
As fossil fuels are increasingly consumed on a global scale, there is growing attention to the development and utilization of renewable energy sources. Consequently, microgrid systems incorporating renewable energy have begun to receive extensive research. A hybrid energy system refers to a microgrid system that incorporates both traditional fossil fuels and renewable energy sources. However, due to the characteristics of renewable energy, such as intermittency and instability, renewable energy sources often have varying outputs depending on the weather, season, time of day, and other factors. A combination of RE technologies yielded fewer emissions than one kind alone [1]. As a result, the generation of power in a hybrid energy system is somewhat random and unpredictable, making it a challenging aspect of research. The increasing capacity for renewable generation has strongly increased the level of uncertainty in the system, making the Unit Commitment model a large-scale, non-convex, uncertain program [2]. By modeling the uncertainty of renewable power generation with probabilistic constraints, a practical multi-objective optimal scheduling model of grid-connected MGs is proposed for minimizing the operating costs and improving the user experience based on chance-constrained programming (CCP) [3]. To address the uncertainty problem, researchers [4] have presented AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. Current studies on hybrid energy microgrids primarily focus on single-objective functions such as cost reduction and extended power supply duration. [PERSON] hasproposed an energy management optimization model that takes into account the mobile energy storage characteristics of electric vehicles. The objective function of the model is to minimize the expected total operating cost [5]. Considering the integration of electric vehicles in the traditional microgrid model, the microgrid system has been studied by various researchers [6]. A multi-objective function, including the operating cost of the microgrid and the charging and discharging cost for electric vehicle users, was established. A wind-solar-hydrogen multi-energy complementary microgrid optimization method has been proposed to address the economic cost optimization problem in the context of multi-energy complementary microgrids, taking into account the demand-side response [7]. Many experts and scholars have utilized different models and algorithms to improve the optimization scheduling and energy control of microgrids. A coordinated and balanced control strategy for the emergency fuel-storage auxiliary power unit in the emergency microgrid is proposed in the literature [8]. During power outages, energy storage and diesel generators are used as the main power sources to provide emergency power supply. The literature [9] presents quasi-oppositional differential evolution to solve the reactive power dispatch problem of a power system. However, research on the flexibility and sustainable power supply of mobile microgrids is still in its infancy; therefore, the study of mobile hybrid energy microgrid systems is of significant theoretical and practical importance. Recently, research on hybrid energy systems (HESs) has become a hot topic. Researchers [10] have studied the use of an Integrated Energy System (IES) and the application of Hydrogen Compressed Natural Gas (HCNG) and Power to Gas (P2G) equipment in IESs. An optimal scheduling mode was proposed in the literature [11] for minimizing the operating costs of an isolated microgrid (MG) by using chance-constrained programming by modeling the uncertainty of spinning reserves provided by energy storage with probabilistic constraints. Researchers have [12] proposed methods for multi-objective optimal design of hybrid renewable energy systems (HRES) in both isolated-island and grid-connected modes.