## 3 Results
### Compilation and Evaluation of Packages  
This section provides a description for the approach used to compile renovation packages and presents the results. Furthermore, the resulting global cost and primary energy demand for the selected packages alone and in combination with main and secondary systems are presented and analyzed. Having determined the individual effect on energy demand and knowing the cost for applying various energy efficiency actions, different energy supply sources, and renewable energy production systems, we can now use the acquired data to sort the actions and compose renovation packages. The objective of this study is to combine renovation packages based on different approaches for the selection of what a package consists of. Moreover, we identify if using cost-effectiveness as a sorting parameter can yield cost-optimal packages. The compiled renovation packages are differentiated in three target groups, based on the predicted amount of energy savings, which are expressed in percent reduction from the reference. The level of energy savings is set to approximately 20, 40 and 60%. Naturally, packages with lower target have wider selection of possibilities, as less actions are required to reach the target. Therefore, six packages are compiled for target savings of 20%, and two are compiled for 40 and 60%. The approach used to select the contents of packages 1-6 is to include a variety of rather random building elements, adding up to 20% savings. This is done to mimic cases where the elements to be renovated are pre-selected, but the specific solution is not. The selection of the specific element type, insulation thickness, or class is made on the basis of the energy savings and CEP. The sorting is performed on an element level, as grouped in Tables 1-6 in Appendix A. Then, a selection of the specific element type is made from one or more of the tables, depending on the goal of the package. For packages 1-6, CEP and energy savings are considered to make up packages, which are expectedto provide approximately 20% energy savings while still comprised with one of the most cost-effective elements. Alternatively, the elements included in package 7 are selected on the basis of global CEP sorting, across all investigated actions. This is done with aim of identifying if selection solely based on CEP provides cost-optimal packages. Package 8 considers the same level of savings as package 7, although it focuses on reaching the target by implementing fewer building elements with large individual energy savings. For this package, the first priority is to select the building elements with large individual savings and then select the specific type based on element-sorted CEP. Packages 9 and 10 consist of a 60% energy reduction target. Package 9 is compiled by CEP sorting on an element level, and then including all needed elements to reach approximately 60% savings, prioritizing those with large savings first. Lastly, package 10 includes all investigated elements but for the compromise of lower energy class windows and terrace doors. The resulting packages and their content details are presented in Table 2, whereas a list of all elements and their CEP value is available in Appendix A. The last two rows in Table 2 provide the predicted savings by the sum of individual contributions of renovation actions and the achieved global savings by the package. The results for NPV and primary energy demand for each of the specified renovation packages and their combination with main and secondary energy supply are presented in Figure 5. Similarly to the cost-optimality plot shown in Figure 1, all studied combinations and the resulting Pareto curve are presented for the purpose of observing the complete solution space. As the differentiation in Figure 5 is made only by the package and main supply option, there are seven identical symbols appearing for each package.