# Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy
## 5 Digital Twin Technology for Energy Sector Development
### Software for Energy Prediction-Actual Software Cases
Three optimization objectives were identified: minimizing building energy consumption, maximizing solar potential, and maximizing daylight hours. To perform the performance simulations, the article uses the Ladybug Tools plugin and performs multi-objective optimization in Wallace X. Based on the findings of this study, a design strategy for energy-efficient urban block forms is proposed. It was established that urban form has a significant impact on building energy consumption and solar potential, but few studies have presented a comprehensive framework to discuss both. Another issue that needs to be addressed is how the numerical relationships expressed by the data can be applied to or assist in the design of energy-efficient blocks. Based on this background, this paper proposes an energy efficiency-oriented multi-objective urban form optimization workflow based on the Grasshopper platform, with a case study in Jianhu County, Jiangsu Province. In addition, the quantitative relationship between urban form and building energy consumption as well as solar potential is explored. [PERSON] et al. [PERSON] et al. (2018) investigate the optimization of insulated sunshades for residential building energy performance. The article presents a full building simulation and dynamic envelope system modelling of flat dwelling units in different climate zones in the USA, followed by building modelling and energy analysis using DOE-2 software to determine the optimal placement of dynamic sliding sunshades, and various operational strategies for dynamic sunshades were also considered. The results show that dynamic sunshades have significant energy efficiency potential in all US climatic and design conditions. The influence of various design and operating conditions on the optimal performance of dynamic sunshades is discussed. [PERSON] et al. Jiangsu Province (2018) conducted an energy consumption analysis of energy use behavior within a typical university in northern China. The research methodology consisted mainly of energy use behavior analysis, and simulation calculations of building energy consumption using the DeST energy consumption model, followed by strategies to change energy use behavior to reduce energy consumption. [PERSON] et al. [PERSON] (2012) investigate the use of City Energy Analyst (CEA) for energy modelling and analysis of urban buildings to assess the potential of energy communities. The main tasks include collecting the necessary data on building characteristics, modeling the building using City Energy Analyst (CEA), generating energy demand and PV documentation for the building, defining different energy community configurations and energy sharing algorithms, as well as their main defined parameters, and finally simulating different energy community case scenarios and evaluating them through the introduction of Key Performance Indicators (KPIs). The performance of the KPIs introduced. It is an effective tool for assessing the energy situation and costs. [PERSON] et al. [PERSON] et al. (2018) used a statistical model to investigate the impact of building energy consumption on the built environment around an urban park in Nanjing, China. The study methodology included the creation of grid groups to examine different built environment layouts around urban parks in terms of 3D building characteristics, land cover, and road networks. A spatial regression model was then used to examine the model including the relationship between the built environment and the domain of building energy consumption, with an emphasis on analyzing and comparing the positive and differential effects of the built environment on building energy consumption. Agile heating and cooling energy demand modelling for residential buildings using technologies such as 3D GIS was investigated by [PERSON] et al. [PERSON] (2018) The main research areas and themes of the article include conducting urban energy planning, studying the heating and cooling energy demand of buildings, and considering retrofitting and climate change.