## 1 Introduction  
Nowadays, massive photovoltaic power stations are integrated into smart power grids. As the coverage area of the grid continues expanding, a large number of facilities are arranged in special areas, such as mountains or hilly terrains, which means management and global monitoring become an urgent problem [1]. Unmanned Aerial Vehicles (UAVs) have become a key enabling technology of interest in recent decades due to their high mobility, low cost, and ease of deployment and have been used in a wide range of scenarios such as natural disaster rescue, cargo delivery, etc. UAVs can be broadly categorized into four types: multi-rotor UAVs, fixed-wing UAVs, single-rotor UAVs, and fixed-wing hybrid vertical takeoff and landing UAVs, which have unique advantages that can be applied to different application scenarios, such as data acquisition [1; 2; 3], Mobile Edge Computing (MEC) [4; 5; 6; 7], and flight relay [8; 9]. In particular, the high maneuverability of UAVs in the air gives them the ability to provide better line-of-sight transmissions, which makes it possible to rapidly deploy communication systems with complex network structures and greatly improves the quality of service to users when UAVs are used as base stations. Nowadays, research on the application of UAVs in the field of communication has led to a large number of achievements. In particular, UAVs can play an important role in providing timely airborne data services, such as search and rescue and surveillance in emergencies or disasters [10; 11], and they can help wireless communication systems recover quickly from paralysis. UAVs can also act as mobile base stations or flying relay stations to provide reliable communications to small and power-limited terrestrial IoT devices or end-users [10; 11; 12], and their fully controllable maneuverability allows them to get close enough to ground-based devices to establish low-altitude air-to-ground communication links [13]. In situations where the ground-based IoT infrastructure is limited, UAVs can be used to flexibly collect sensing information, thereby saving transmission energy for sensor devices and extending the network lifetime [14]. Due to its unique advantages (mobility, independence, special extreme situation employment, etc. ), the UAV is a very potential technique for data collecting in photovoltaic system. Thus, UAV-assisted data collecting and state monitoring will be a prospective solution for photovoltaic system. While UAVs bring us convenient communication services by virtue of their unique advantages, they still face many challenges. UAVs have difficulty carrying large-capacity batteries due to their small size, resulting in short endurance, and thus insufficient energy has become a major obstacle to the development of UAV communication [15; 16; 17]. The energy consumption of UAVs mainly consists of the motion energy consumption to overcome gravity and air resistance, and the energy consumed by communication only accounts for a small portion of the total energy consumption of UAVs, so if UAVs perform their tasks under energy constraints, it is very important to make reasonable decisions on their trajectory, design, and optimization. Currently, a large number of researchers have used traditional optimization algorithms to solve the trajectory optimization problem, which requires the acquisition of environmental information such as channel conditions and the positions of other devices before the UAV takes off [16]. However, in practice, the environment of the UAV is complex and dynamic; it is not easy and is even challenging for UAVs to acquire the precise location information of sensor nodes (SNs) in some practical scenarios, such as disaster relief, dangerous areas, and unpredictable scenes.