# Optimization of Heat Pump Systems in Buildings by Minimizing Costs and CO\({}_{2}\) Emissions
These methods allowed the authors to optimize key performance parameters, such as module sizes, and to minimize both cost and environmental impact. The results of the study showed that the system could self-generate nearly 29.4% of the total HVAC electricity needs. The use of nonlinear programming and multi-objective optimization techniques was crucial in achieving these results. In a study by [PERSON] et al. [32], a methodology called SPRINT was presented, which optimizes the design and operation of air-source HP systems for residential buildings. This approach involves a two-stage optimization process using MINLP and multiple objectives such as costs and emission minimization over a one-year period. In the first stage, an annual dynamic building performance simulation is used to optimize system design using surrogate-based optimization. The second stage uses GA with the same dynamic simulation models to optimize system controller settings. By considering both stages together through the intensification of the process, costs can be reduced by up to 36%, and emissions can be reduced by up 51% compared with standard procedures. Despite the advancements in the relevant research, there is still a gap in the available literature that requires attention regarding the selection of optimal heat pump heating systems for various buildings, including apartment buildings, commercial buildings, and public buildings. Currently, there is limited research in this area that specifically analyzes the best heating system from the available options taking into account cost and emission minimization over a long-term period. This makes it imperative to conduct a study on the optimal selection of HPs for different types of buildings to address this gap in the literature. The main objective of the study presented in this paper is to propose a novel methodology aimed at the selection of optimal heat production and supply systems for different types of buildings by minimizing total costs and reducing CO2 emissions. The optimization problem takes into account various technical, economic, environmental, and social factors and analyzes various types of HPs, EHs, and their combination in a heat production and supply system. The methodology is applied to a range of building types, including renovated and unrenovated apartment buildings, schools, kindergartens, and a supermarket. The scientific novelty of this paper lies in providing an innovative and practical approach to selecting optimal heat production and supply systems for different types of buildings, which could lead to significant energy savings and environmental benefits. This paper is structured as follows: Section 2 describes in detail the proposed methodology for the analysis including the developed mathematical model. Section 3 introduces the main assumptions and data used in the case study. Application of the proposed model as well as the main results are presented in Section 4. Implications of the main findings are discussed, and future research directions are highlighted in Section 5. Finally, in Section 6, the study's concluding remarks are presented.