Coordinated Optimization of Distributed New Energy Layout and Spatiotemporal Load Forecasting in Tourism Cities under Urban and Power Integration Planning

With the rapid development of the tourism economy and the deepening of urban energy transformation, power systems in tourist cities face seasonal load fluctuations and challenges in absorbing distributed renewable energy. This study proposes a theoretical framework and method for coordinating distributed renewable energy layout with spatiotemporal load forecasting under urban-power integration planning. Taking a typical tourist city as the research object, a spatiotemporal tourism-load forecasting model based on multi-source data fusion is constructed to reveal the coupling mechanism between tourist flow and power load. A two-level optimization model for renewable energy site selection and capacity determination is then established, incorporating forecast information to achieve coordinated matching between renewable energy layout and load characteristics. The model considers investment cost, operation and maintenance cost, power-generation revenue, energy storage replacement cost, line constraints, voltage constraints, and N-1 safety criteria. The results show that coordinated optimization improves renewable energy absorption and enhances the adaptability of urban power systems to tourism-driven load fluctuations.