Increasing population causes Energy consumption and environmental pollution. It is essential to consider renewable forms of energy, especially solar power, to reduce energy consumption. This requires attention to energy issues in the early stages of urban design and practical and creative solutions for more efficient use of this type of energy. This study aims at calculating the annual solar radiation at a city scale through a novel process and methodology. In this regard, artificial intelligence algorithms and satellite data can help maximize the amount of sunlight in neighborhoods and urban blocks in neighborhood units during the development process. In the simulation process, location, and optimization of the urban form, it is necessary to consider the limitations and resources for field study and simulation of urban blocks. Therefore, in this study, Farhangian neighborhood in phase 1 of Kermanshah, Iran, which has a good level of structural diversity and lends itself to field studies, was selected and studied at neighborhood and urban block scales. The case study indicates the significant role of calculating and optimizing the patterns of urban blocks to achieve maximum solar energy. Estimates at different levels show that urban block variables effectively access solar radiation energy and, given various scales of development - from macro-scale spatial planning to micro-scale local design - can improve energy intake by 3 to 5 percent. Accordingly, the results show that to accelerate the calculation of energy at the planning scale, the use of 2.5D locating model and 3D optimization contribute to achieving the maximum or minimum solar radiation, respectively. On the other hand, this method can be used to organize calculations and planning for maximum absorption of solar radiation at different stages of development.
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