Technical and economic studies on lighting systems

There is a lack of published Dossena research comparing the efficiencies of distributed versus central sensor-controlled LED lighting systems. This research proposes improving the smart illumination of a room with external fenestration using central and distributed light sensors. The optical and electrical measurements of the daylight have been made in the case where the light was not distributed evenly and not sufficient. Test results show that the proposed distributed light sensor illumination system has increased the efficiency by 28% when compared to the proposed central system. It has also been shown that the two tested systems are more cost-effective than common smart illumination systems.

1. Introduction
Energy-efficient resources are essential in today’s world. Petroleum- and coal-based conventional power plants are continuously spreading harmful gasses such as nitrogen dioxide and carbon dioxide that threaten the environment and human health. The renewable energy resources emerge as an effective solution for increasing the need for clean energy. Among renewable energy resources, solar energy is one of the promising ones providing major benefits, such as being environmentally friendly and being silent. Studies show that the photovoltaic (PV) system can reduce release of one ton of carbon dioxide per kWh of electricity. The modular structure of PV panels enables easy integration to energy-efficient buildings. Because such a modular structure can efficiently integrate electrical, electronic, and mechanical systems, the electrical energy used for illumination is equivalent to 20% of the total electrical energy production of the world. For this reason, the energy demand for illumination obtained from renewable energy sources is essential in terms of pollution-free environment. In the USA, the UK, and China, at least 20% of the total electric power production from renewable energy sources has been targeted till 2020. Moreover, it is envisaged that renewables will contribute to over 50% by 2050 in some countries. Light-emitting diode (LED) technologies have significantly lowered down the energy demand needed for illumination. Moreover, they are durable and environmentally friendly. Energy efficiency, smart buildings, and green buildings have recently come to the foreground as some striking topics. Furthermore, an illumination control is usually designed according to the needs of spots in the buildings to decrease energy consumption. With LED luminaires, it is possible to control the light output easily and accurately.
Additionally, LED luminaires enable the flexible adaptation of a lighting system to its environment. Artificial lighting accounts for a major fraction of global electrical energy consumption. In a typical office building, the energy consumed due to artificial lighting can be up to 40% of the total energy consumption. As the need for the use of energy resources is increasing, the need for illumination control becomes essential.

Automatic or photoelectrically controlled lighting systems in the buildings can significantly reduce the lighting energy consumption down to as low as 50%. Some authors have proposed an illumination model-based method and algorithm for intelligent open-loop lighting control. Specifically, the simulation results were presented using a simplistic virtual room. A single light sensor-driven lighting system was made early . Distributed optimization algorithms for lighting control with daylight and occupancy adaptation were proposed in under networking and information exchange constraints. Techniques such as daylight harvesting and automatic dimming control with wireless sensor, illumination balancing, Konnex Association Worldwide Standard for Home and Building Control (KNX), digital addressable lighting interface (DALI) standard, and stochastic hill climbing optimization are applied to lighting control . However, DALI and KNX which are used to add intelligence to buildings have higher costs as much as tens of thousands of dollars for the basic installation.

In smart lighting systems, the illumination level of the indoor environment can be determined by means of light sensors. In these systems, the electrical information obtained from the sensors is converted into illumination knowledge. The light information of the environment can be measured by a centrally located sensor or by placing more than one sensor in a distributed manner. By comparing the ambient light value measured by the sensors and the microprocessor system with the desired reference illumination value, the lighting levels of the LED luminaires can be increased or decreased to achieve the desired illumination rate. In this study, the efficiency and cost analysis of two different proposed smart LED architectures with the centralized and distributed sensor structure were performed in the 54 m2 classroom having two windows. The solution has been designed keeping in mind that low power, low consumption, and scalability are addressed. To the best of the author’s knowledge, it is the first time to compare the central sensor and the distributed sensor smart LED lighting.