Optimization and Evaluation of the PEDF System Configuration Based on Planning and Operating Dual-Layer Model  
[PERSON]  
1 School of Energy and Electrical Engineering, Chang'an University, Xi'an 710018, China;  
1 [EMAIL_ADDRESS] (T.L. ); [EMAIL_ADDRESS] (T.L. ); [EMAIL_ADDRESS] (T.L. ); m187362235926163.com (H.W.) [PERSON]  
1 School of Energy and Electrical Engineering, Chang'an University, Xi'an 710018, China;  
1 [EMAIL_ADDRESS] (T.L. ); [EMAIL_ADDRESS] (T.L. ); [EMAIL_ADDRESS] (T.L. ); m187362235926163.com (T.L. ); [EMAIL_ADDRESS] (T.L. ); m187362235926163.com (T.L. ); m187362235926163.com (T.L. and \"flexibility\" relates to the adaptable load characteristics of a building, which can be scheduled flexibly to help alleviate supply-demand conflicts and enhance the utilization rate of renewable energy [4; 5]. The PEDF system aims to establish a new type of power distribution system for buildings that align with carbon neutrality goals by focusing on photovoltaics, energy storage, direct current, and flexibility [6; 7; 8]. According to China's Action Plan for Carbon Peak, it is essential to \"improve the electrification level of building terminals and build PEDF buildings that integrate photovoltaic power generation, DC distribution, energy storage, and flexible electricity consumption\" before 2030. In recent years, there has been a significant increase in research and its applications. However, the existing research, standards, and systems for PEDF in buildings are still incomplete, with many studies remaining in the preliminary exploration stage. Many researchers highlight the importance of developing renewable energy systems for PEDF buildings to achieve carbon neutrality goals and innovate energy systems [9; 10]. Several studies have examined the planning, operating, and control aspects of DC microgrids, identifying relevant challenges and opportunities, while summarizing control strategies [11; 12]. Some studies focused on the feasibility of distributed photovoltaic and energy storage systems, exploring configurations for various building types and climates [13]. Others have proposed methods to improve the self-sufficiency rate (SSR) and self-consumption rate (SCR) of these systems by addressing issues like transformer losses and load curves [14]. Research has also explored balancing strategies between electricity costs and carbon dioxide emissions [15]. Some studies have proposed dual-layer configuration models for photovoltaic energy storage in DC solar storage microgrids based on interval linear programming to enhance both economic and operational efficiency [16; 17]. Optimal operation planning models for scalable DC microgrids have been developed in [18], considering factors like demand response, islanding operation, and battery degradation costs. Moreover, some studies aimed to adopt intelligent optimization algorithms based on a dual-layer configuration model of DC microgrids, with grid compatibility and annual net profit of microgrids as internal and external optimization goals, effectively improving both economic efficiency and operational stability [19; 20; 21]. At the same time, some studies have noted the critical role of intelligent optimization algorithms in optimizing system capacity configuration, utilizing intelligent optimization algorithms (such as Particle swarm, Whale, and Grey wolf) to determine the optimal configuration of system capacity that meets user needs [13; 14; 18; 19; 20; 21]. Overall, current research on the PEDF system is transitioning to applied stages, but there is still a need for in-depth studies on optimizing and evaluating system capacity configuration across different scenarios. Capacity configuration and energy scheduling, as core issues in system planning and operating, are often treated separately, leading to a failure to consider the coordinated configuration of key interactive devices within the system. This oversight can result in inefficient capacity optimization or insufficient operational capacity in existing systems.