Abstract
Light regulation systems in industrial or office buildings play an important role in minimizing the use of fossil energy resources, while providing both economic and ergonomic optimal functionality. Although industrial buildings resolve the problem of interaction or disturbance mitigation by providing constant light levels exclusively from artificial sources, office landscapes may benefit from up to a 20% decrease in costs if mixed light sources are optimized properly. In this paper, we propose a theoretical framework based on model predictive control (MPC) to resolve a multi-system with strong dynamic interactions and multi-objective cost optimization. Centralized and distributed predictive control strategies are compared on various office landscaping structures and functionality conditions. Economic and ergonomic indexes are evaluated in a scaled laboratory setting.
Highlights
In recent years, the climate has become one of the most discussed topics in world politics
Light regulation systems in industrial or office buildings play an important role in minimizing the use of fossil energy resources, while providing both economic and ergonomic optimal functionality
Industrial buildings resolve the problem of interaction or disturbance mitigation by providing constant light levels exclusively from artificial sources, office landscapes may benefit from up to a 20% decrease in costs if mixed light sources are optimized properly
Summary
The climate has become one of the most discussed topics in world politics. It is clear that CO2 emissions should be reduced drastically. 40% of total CO2 emissions worldwide are caused by the production of electricity and heat, as summarized in Figure 1 (left stacked bar chart) [1]. The electricity consumption for lighting in office buildings accounts for about 25% of the total energy consumption within these premises [2,3]. Two main solutions to reduce both the electricity costs and its ecological footprint are:
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