The society is going through transformations in several dimensions at the same time. The energy system is moving towards renewables and reduced resource intensity. Market structures are gradually changing, and new actors emerge to compete with incumbents. Digitization creates fundamentally new conditions for everyone. Cities are being reimagined and are driving much of the transformation. Energy optimization becomes a heated topic for the whole society. This thesis research collaborated with the company SWECO Energy Strategies group investigates one part of energy optimization: proposing different possible scenarios of combining different types of buildings in a city block to urban designers and real estate company. The objective of this research is to find out the suitable combinations leading to an evener and lower demand profile from the perspectives of energy supply and the grid. This thesis project will try different methods to identify the most promising combination of various functioned buildings and develop a new methodology to solve the similar cases. A city block with either several types of building or single type of building can have an even and low energy profile. Moreover, there isn’t a definite relationship between the flatness of energy profile and the correlated amount of total demand. In this project, different scenarios are created and tested by the assistance of Python programing language and Solver installed in Excel. Through a series of tests and analysis, the best case is found with the most area of residential buildings. Qualitatively economic analysis is done, proving that an even energy profile is conducive to the cost-saving. Through the conducted case study, a general methodology is developed, which facilitates urban designers to design similar projects to some extent in the future.