Abstract
This work addresses the economic, social and environmental analysis of an indigenously developed building energy optimization system for residential and office buildings in Germany. The developed system consists of 14 different wireless network embedded sensors, wireless communication protocol, multi-dimensional data warehouse, graphical user interfaces and energy optimization software with artificial intelligence-backed control algorithms. The R&D activity is accomplished in the ‘Intelligent Building Energy Management System’ research project, which is funded by the State of Lower Saxony—Germany in the frame of Innovation Support Program between the years 2014 and 2018. The system is tested in two appropriately selected test buildings in Germany. It has been recorded that the system provides energy efficiency levels between 29.34% and 38.18% under different seasonal and occupancy conditions in office and residential building types. The analysis is accomplished within the framework of four main indicators. These are economic indicators including calculations of lifetime cost and payback rate methods, resource use indicators including the calculation of reduced energy use as a result of the energy efficiency provided by the system, social indicator including additional expendable income calculations and environmental indicators including calculations depicting the benefits of reducing harmful emissions. Analysis results illustrate that building energy optimization systems provide a cost-effective method for promoting energy efficiency goals. Results of the indicators prove monetary benefits for the building occupants in terms of resource use, return on investment and social impact, as well as quantifiable benefits for easing the harmful effects of climate change phenomenon.
Are Genetic Algorithms Really the Best Choice in Building Energy Optimization?
