Planning and Energy Self-Supply Strategy for Distributed Photovoltaic Microgrids on Highways Considering Regional Layout Constraints

With the widespread adoption of highways in the mountainous regions of southwestern China, the electricity load of numerous tunnels and service areas has increased rapidly. Constructing photovoltaic (PV) microgrids in service areas has become an important means of energy conservation, consumption reduction, and carbon emission mitigation. However, constrained by mountainous terrain, the PV power generation conditions in highway service areas exhibit significant micro-terrain variations, making it difficult to effectively evaluate PV utilization efficiency. This paper proposes a dynamic block optimization model for PV microgrids that considers regional layout constraints. The model utilizes an intelligent adjustment mechanism to plan PV panel layouts in highway service areas, optimizing energy utilization efficiency and economic benefits. Additionally, long short-term memory (LSTM) networks are employed for short-term PV output prediction to address the challenges posed by varying weather and seasonal changes. This approach comprehensively considers the intermittency and instability of PV power generation, enabling dynamic block optimization to autonomously adjust the PV power output in response to load fluctuations. Through simulation case studies, the model is validated to effectively improve the utilization rate and economic performance of PV microgrids under various environmental conditions and demonstrates superior performance compared with traditional static block methods.