Daylight Harvesting Optimization for Commercial Buildings using AI Technique

– As Energy consumption in buildings increases considerably from year to year due to the increase in human comfort needs and services . In addition to weather conditions, several factors influence the energy consumption for cooling buildings, such as the structure ofthe walls, the window-to-wall ratio and the orientation of the building. The energy consumption of buildings has been reported to represent a relatively large proportion of global energy consumption. savings The attenuation curves of the DC LEDs were measured with the installed power of the photosensors. The results show that the annual consumption of primary energy available for

Many states in the United States are mandating many rules and regulations to reduce the buildings' energy consumption. For example, New York and California, which house more than 20% of the United States' population, produce less than 10% of its carbon emissions. These two states are leading the way in decreasing energy use through the proliferation of net-zero energy building in addition to other strategies. The definitions apply to network independent facilities. Supplyside option 2 can be used for all definitions if this resource is available during the life of the building [8]. External ZEBs can be achieved by purchasing renewable energy from external sources or, in the case of an external zero-emission building, by purchasing carbon credits. To meet the DOE&#39;s ZEB research needs, the following definitions refer to ZEBs using locally available supply-side options. In the case of ZEBs that obtain part of the renewable generation from external sources, these buildings are referred to as "off-site ZEBs". When the NZEB concept becomes technically and economically feasible, it will be possible to extend its boundaries to groups of buildings, campuses, municipalities, cities, bases or cities. An alternative to individual NZEBs is zero-energy campuses, neighborhoods or communities. The extension of the net zero energy limit beyond a single building takes into account the emergence of communities, neighborhoods and campuses that generate RE for a given group of buildings; However, energy is not necessarily connected directly to the meter of a particular building. This would be considered a Community RE system connected to the grid or to a district heating or cooling system. II. LITERATURE REVIEW Doulos, L.T. et al. [1] used a typical classroom in a Greek public school, examined a range of lighting technologies (AC and DC) and two systems for using sun-shine. The former uses a standalone photo sensor per device, while the latter uses one sensor per control zone to calculate energy savings and adequate lighting. The attenuation curves of the DC LEDs were measured with the installed power of the photosensors. The results show that the annual consumption of primary energy available for lighting can be reduced from 90.5 kWhp/m 2 to 0.55 kWhp/m 2 . The maximum annual reduction in CO 2 emissions was 32.44 kgr/m 2 for the classrooms, which is converted into 201.29t for the entire country. Clearly the path to zero-energy school buildings goes through the mandatory use of sun-shine control. Fathalla Selim et al. [2] presented are the most power system planners are interested in the savings of electrical power consumption. Various references demonstrate that the highest consumed power is by the lighting systems standing around 19% of worldwide energy consumption. This article presents novel design methodology leading to maximizing revenue due to savings in electrical energy consumption through energy efficient installations. This hybrid methodology is built by combining benefits of the two traditional lighting design methods (lumen and specific connected load methods). This results in developing a new mathematical and applicable model with many advantages such as: high accuracy, fast calculations and most economical design. This proposed methodology is supported by MATLAB® package to shorten the long time consumed by conventional procedures and simplify the complex manual calculations. The hybrid method verifies its effectiveness and efficiency for achieving the maximum savings in energies and costs through the detailed discussion of case studies. Mykola Tarasenko et al. [3] analyzed the dependence duration of sun-shine autonomy in office rooms, on the value of sun-shine factor for four European cities. The specific sun-shine autonomy (h/(year•m2)) of office rooms were found. It was proved, that regardless the size of the rooms, the maximum specific sun-shine autonomy in Ternopil city (at illumination of 300 lx, which is prescribed by regulations), with lateral sun-shine, occurs when the sun-shine factor is in the range of 1.7% to 1.9%. Maximaat 1.8%. At illumination of 500 lx, the maximum specific sunshine autonomy will occur at a sun-shine factor range of 2.6% to 3.0%. Maximaat 2.8%. Evangelos Manolis et al. [4] in the lighting market to fill this gap in the relevant literature by focusing on one European country, Greece, to understand the implications of various European and national directives. In order to increase the informative value of the results, a total of 9,609 desk lamps were selected for the European market. After verifying any errors in the data, a careful statistical analysis was carried out to determine the composition of the market, taking into account technical characteristics such as the type and destination of each luminaire, its luminous efficiency, its color temperature and its color rendering index, and some other attributes that affect the compliance of the luminaires with the directives, but also their suitability for an efficient lighting project. The method used in this article is intended to support future policy making as it provides a solid quantitative basis for studying policy implications, but also for lighting designers to understand the current state, but also future trends, of the environment. Adjust accordingly. Choose. The analysis of the light output showed that around 48% of current office luminaires do not exceed the limit value of 85 lm/W set by the EU. Only 5% or 13% of luminaires can be used for general lighting and thus for energy-efficient lighting planning for work lighting without creating more luminaires than necessary. Kateryna Kozak et al. [5] aimed at investigating the parameters of translucent structures of building envelope, and the value of sun-shine factor, for which maximum efficiency of sun-shine usage is achieved in office rooms. The study analyzes the dependence duration of sun-shine autonomy in office rooms, on the value of sun-shine factor for four European cities. Piotr Pracki et al. [6] examines the influence of room and luminaire properties on general lighting conditions and energy efficiency in interiors. Seventeen types of luminaires with different light distributions were arranged in uniform floor plans in rooms of different sizes and reflectivity. Average brightness, uniformity and normalized power density with respect to two horizontal working levels were calculated. The influence of the reduction of the work load, the environmental index and the degree of reflection, the lighting class and the distribution of the luminous intensity of the luminaire on the parameters considered was examined. Using the reduced operating level resulted in an increase in average luminance (average 7.7%), uniformity (average 33%), and normalized power density (average 23%). The influence of the room index and lighting class on average luminance and normalized power density was significant, while the influence of luminaire light intensity distribution and light reflection was weak. The standard power densities for general electric interior lighting with a luminous efficacy of 100 lm/W are in the order of magnitude of: 1.08-3.42 W/m² per 100 lx. Based on these results, a normalized power density of 2 W/m² per 100 lx is recommended for the design and evaluation of new general electrical building lighting. Energy consumer at the end of the 20th century and today consumes about 40% of total energy consumption. Arimaz Hangga et al. [7] aimed at determining the effect of the type of anchor light. The results of this research are expected to increase the efficiency of electricity costs and use the optimal lighting system for classrooms according to the Indonesian National Standard (SNI). Two types of lighting fixtures that were used in this research; H. Fittings for LED tubes and fittings for LED lamps. For this survey, room E11-210 in the E11 building of the Department of Electrical Engineering of the Universitas Negeri Semarang was used with a size of 12 mx 9 mx 3.5 m. The simulation of this study used the DialuxEvo 9 software. The results of the observations and simulations show that the E11-210 class at 350 lux had not yet followed the SNI. Based on the simulation results, it shows that the use of LED tube fittings and LED luminaires can achieve the light intensity of classroom E11-210 in accordance with SNI 6197: 2011. The simulation results show that the The use of LED (Power balance Gen2 RC463B) tubular anchors in classroom E11-210 increases electricity cost efficiency by 27.81%. Meanwhile, the use of LED (Lux space Ace Accent RS750B) lights in classroom E11-210 will increase the cost efficiency of electro centricity by 33.96%. Natalia Sabat et al. [8] uses astronomical relays and motion detectors to determine the cost-effective and energy-efficient use VOL.7, ISSUE 9, SEPTEMBER 2021 www.ijoscience.com 3 of artificial light control using different types of light sources for stairwells (floors and stairwells) in multi-story residential buildings. An analysis of the monthly intensity of movement of residents of 9-story residential buildings through house entrances, house entrances and apartment doors was performed. The cost-effectiveness and energy efficiency of using artificial light control systems with astronomical relays and motion detectors with different light sources were determined. Regardless of the type of light source, using the astronomical relay results in a reduction in the energy consumption of artificial lighting by 43.31% -50.52%. The cost-effectiveness and energy efficiency of using lighting combined with artificial light control for stairwells in multi-storey residential buildings has been demonstrated. Haq Mohammad et al. [9] have shown that lighting control systems provide significant energy savings and can lead to reduced electricity costs. The decline in electricity demand also has a positive impact on the environment as the carbon footprint is reduced. But each of the control technologies has different properties that affect their performance. The behavior patterns of the residents, the geometric properties of the room or building, the ingress of sun-shine, the type of work performed, etc. have profound effects on lighting control systems, as the discussions in this article show. Only with a good study of these factors can a correct technological implementation be obtained, which can lead to significant energy savings and ensure the comfort of residents. During a 12-week real-world experiment in six offices with ten participants, Z. Nagy et al. [10] presented investigations into lighting control systems, the basic control of which depended on how workers worked. Users were satisfied with the results, with the exception of those who did not find automatic lighting control important. The lights were always on on time and the shutdown on time was only logged 75% of the time. Thus, 13.4% of electricity could be saved without significantly harming employee comfort. The result is that the electricity savings obtained are 13.4% with no significant impact on the comfort of residents. III. METHODOLOGY The Building Energy Building Guideline proposed the Smart Buildings theory to encourage renewable energy generation, versatility, and interaction techniques. Numerous interpretations of Smart Buildings (SBs) have been suggested in the study by multiple research communities. The essence and characteristics of smart buildings are also a bit hazy. The idea of building energy retrofit has been proposed to reduce energy usage and attain the Zero Energy Building benchmark. It is critical to transform current retrofitting methodologies to smart retrofitting approaches so that the goal of near-zero energy buildings can be easily accomplished and different sources including seasonal changes and grid can be easily managed. Sun shine Collecting-Light sensors detect the luminous intensity from natural sources and transmit data to the control scheme, which is used in the sun-shine collection system. The electronically controlled lights are then adjusted by the controller based on the measurement scale. In general, there are two different types of sun-shine collecting controller: open-loop and closed-loop systems. The artificial system also isn't needed to provide responses in such a system. A closed-loop system, on the other hand, assessed the quantity of sunlight intensity through both natural and artificial inputs.

Fig.1. Sun-shine collecting control system
An Artificial Intelligence enabled PhotoVoltaic solar collector, fibre optic directing system, leading lights, and control circuits which are enabled by internet of things make up the smart sunshine collecting conceptual model. IoT is used to regulate all of these elements.

Fig.2. The intelligent sun-shine collecting system
This outline demonstration the assembly prototype for commercial building lighting implementations.

RESULT AND DISCUSSION
The proposed methodology is simulated using MATLAB SIMULINK platform to carry out calculations to obtain the Power output from solar panels and from conventional sources. The model is trained using neuro-fuzzy AI technique that automatically control the power requirement according to need. The simulation is performed in following conditions which are discussed as below:

Fig.4. Simulink Model Sun-shine collecting System
This model is designed on Simulink for sun-shine collecting system. To supply in commercial buildings, the model is hybridized with conventional sources and renewable source. The model is designed to maximize the energy supply from sun-shine collecting and minimize the supply from conventional sources.

Fig.5. Simulink Model PV Modelling with variable irradiance
The solar radiation level falling on the PV panels varies depending on the location of the panel and the time intervals in a day. Therefore, solar radiation level has a direct effect on the panel power. As a result, a decrease in solar radiation level reduces the panel power. The figure 5 represents the Simulink model for PV modelling to receive variable irradiance. The model is designed to convert the solar energy to electrical energy.

Intelligent luminaries
Sensor-based Solar Collector

Intelligent guiding system (Fiber optics)
Control Unit Server VOL.7, ISSUE 9, SEPTEMBER 2021 www.ijoscience.com 5 Fig 6 represents the Simulink model for AC supply from the grid and the objective of this simulation is to minimize the usage of this AC supply. Figure 7 represents the AI implementation for automatic control of power supply either in AC form from conventional sources or in DC form from sun-shine collecting. Figure 8 represents the current analysis of PV with conventional source.  Figure 9 represents the voltage analysis of PV with conventional source. Figure 10 represents the power analysis of PV with conventional source. Fig.11. LED Illumination with AC and DC supply Figure 11 demonstrates the illumination of LED lights with AC supply (conventional sources) and DC supply (sun-shine collecting). The green represents the AC supply and blue represents the DC supply. This reduces the overall building energy dependency on AC supply. The LED are integrated with VOL.7, ISSUE 9, SEPTEMBER 2021 www.ijoscience.com 6 AI block that automatically switches between energy supply, i.e., from AC to DC or from DC to AC according to density and load of the room.    Fig.11. Comparative Performance Evaluation Various efforts of investigators for sun-shine collection have been discussed in previous portions. The majority of these studies concentrated their efforts on the collector's architecture, position, variety, and region for collecting sunlight. All these parameters are designed for energy saving. But the change in these parameters will not be cost-effective and while considering energy savings infrastructure will result in increasing cost (design and maintenance). So, there is the requirement of integration of some solutions with existing designs to improve their efficiency. Artificial intelligence is the best solution which pops up. Moreover, there are very few suggestions in this collection that use intelligent automation. Thus, this paper discovers the presentation of AI/ ML to enhance the efficiency of the existing design of a sun-shine collecting system. In this work neuro-fuzzy controller is proposed that can be applied successfully for analysis and control for dynamic changes. Some of the theoretical comparisons of the proposed methodology are discussed in table IV to show the effectiveness of the proposed methodology that makes it energy-effective as well as costeffective when implemented in the real-time scenario.

V. CONCLUSION
The development of smart zero energy buildings results in a building that is ecologically friendly. As the society advances, so does the consumption of energy resources. Building structures today are designed to intake a significant amount of energy globally. Within a few years, all natural resources will be depleted due to this situation. As a result, techniques must be introduced to satisfy current energy requirements while also reducing the waste of conventional energy sources. An efficient as well as less expensive structure is developed in this investigation, which will benefit energy conservation in both new constructions and already available structures. By combining fiber optic cables and solar panels in a hybrid energy sustainability system with Intelligence control systems, power usage within the constructing will be reduced. The effectiveness of a neuro-fuzzy control module that automatically senses the dynamic world and optimises the energy needs was also demonstrated experimentally. The foregoing are some of the work's conclusions:  This control unit also increases the lifetime of the luminaries by reducing unnecessary wastage of power. In this work a review is presented on the existing methods with AI and without AI integration and found.  Most of them are integrated with sensors but there are very few research works that propose AI control units. So, the proposed methodology will results better as compared to existing techniques under a dynamic environment and reduce power consumption. Along with power consumption, the proposed method will also prevent downtime of building equipment, improves sustainability.  The result shows approx. 1.2% of improvement in energy saving policy due to application smart control unit. In future work, the focus of this work would be to implement this methodology over large commercial buildings that can be remotely controlled to improves sustainability as well as reduce costs, and increases profit 40.