FIELD OF INVENTION

The present invention relates to electricity optimization. More particularly, the invention relates to systems and methods for energy savings and management based on heat analysis.

BACKGROUND OF THE INVENTION

Energy conservation or control of energy costs is one of the high priority issues with businesses and governments of a country. Paying huge electricity bills almost every month in addition to maintenance charges in societies and residential buildings is a big headache for every person. There are certain conventional devices which promise to conserve energy and reduce electricity bills, such as Saimax 3G power saver, SIPL energy saver. However, such devices are still not that efficient in reducing the bills. Other conventional arts involve considering different approaches to remove excessive heat produced within the building by exhaust fans. For example, calculating effective thermal mass of a building for reducing electricity bills. However, such calculations do not involve different types of heat such as sensible and latent . Such methods only involve external and internal heat . however, a lot of heat is produced within the people's group. Such a factor should also be accomplished while considering during calculations.

In addition, environmental conditions may not remain constant every day, hence, systems and methods are required to optimize and manage energy inside the building.

SUMMARY OF THE INVENTION

Accordingly, the present invention provides a method for energy optimization and management in a building. The method includes identifying a plurality of objects in the building as source of heat emission, measuring, scoring and transmitting a plurality of internal heat parameters associated with each of the plurality of objects wherein the parameters are measured over a predefined duration. The method includes the step of receiving the plurality of internal heat parameters at a centralized server for the predefined duration to analyze and determine average heat emission from a building, determining external heat sources and monitoring a plurality of external heat parameters to determine average heat absorption in a building, receiving the plurality of external heat parameters at the centralized server to analyze and determine average heat absorption in a building, and analyzing the internal heat parameters and the external heat parameters to determine a heat gain factor for energy optimization and management.

In another embodiment, the present invention provides an IOT based system for energy optimization and management in a building. The system includes a plurality of objects in the building as source of heat emission, a network of sensors, each sensor configured to measure a plurality of operating parameters of the objects, a plurality of sub memory modules connected to the sensors and configured to store the operating parameters, at least one communication device configured for transmitting the operating parameters to a centralized server wherein the device is in communication with the network of sensors and sub memory modules, wherein the centralized server includes a processor configured for processing the operating parameters to determine a heat gain factor for energy optimization and management. DESCRIPTION OF THE DRAWINGS

Reference will be made to embodiments of the invention, examples of which may be illustrated in the accompanying figures. These figures are intended to be illustrative, not limiting. Although the invention is generally described in the context of these embodiments, it shall be understood that it is not intended to limit the scope of the invention to these embodiments.

Pig. 1 provides an IOT based system 100 for energy optimization and management in accordance with an embodiment of the present invention.

Fig. 2 provides a flowchart of a method for energy optimization and management in accordance with an embodiment of the invention.

Fig. 3 provides tables and graph depicting regression analysis for determining heat gain factor in accordance with an embodiment of the present invention.

Fig.4 provides a graph depicting Chiller Heat Gain {RT} vs QTHGF in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Various embodiments of the present invention provide a system and a method for energy optimization and management in a building.

In an embodiment, the present invention provides a system 100 of energy optimization and management in a building as shown in Fig. 1. The system includes a network of sensors 110 (110a, 110b, 110c) connected to a plurality of sub memory modules 120 (120a, 120b, 120c) . The sensors and sub memory modules connected to a plurality of objects .130 (130a, 130b, 130c) of a building 140. The system 100 includes at least one communication device 150 communicatively connected to the plurality of sub modules and sensors for gathering heat parameters related to the heat emitted by the plurality of objects. The communication device 150 connected to a centralized server 160 with a processor 170 for transmitting the gathered heat parameters to the server 160, where the processor 170 of the server 160 processes the heat parameters to determine a heat gain factor for enabling energy optimization and management in a building 140.

In a related embodiment, the network of sensors determines external heat absorbed by the building 140 based on external temperatures at the walls and roofs of the building 140.

In a related embodiment elements of the system 100 are connected to each other wirelessly through a network 180. In an exemplary embodiment, the present invention discloses a benchmarking based system for energy management in the building. The building may be residential, market places, institutions, firms, and so on.

The system includes a plurality of modules/devices for managing the environmental energy. More the heat produced or resides within the environment of the building, more the energy consumption by electronic devices. For instance, top floor of the building may be hottest of all the floor due to direct solar heat. To maintain comfortable temperature, air conditioners of chiller consume more energy and power to maintain the temperature. However, such maintenance may still not be achieved.

The sensible heat measured by the system 100 defines exchange of heat by a thermodynamic system that changes the temperature of the system without changing some variables such as volume or pressure. As the name implies, sensible heat is the heat that one can feel . In a related aspect, latent heat defines the heat required to convert a solid into a liquid or vapor, or a liquid into a vapor, without change of temperature. in an embodiment, examples of heat from external environment include but not limited to heat gain from exterior walls and roof, solar and conductive heat gain via fenestration, infiltration via partition walls and interior doors, intake of outdoor air into the system, and so on.

In an embodiment, the present invention provides a method of energy optimization and management in a building as depicted by the flowchart 200 in Fig. 2 .

Themethod includes the step S210 to identify a plurality of objects in the building as source of heat emission. In S220 measuring, storing and transmitting a plurality of internal heat parameters associated with each of the plurality of objects wherein the parameters are measured over a predefined duration. In S230 receiving the plurality of internal heat parameters at. a centralized server for the predefined duration to analyze and determine average heat emission from a building. In S240 determining external heat sources and monitoring a plurality of external heat parameters to determine average heat absorption in a building. In S25G receiving the plurality of external heat parameters at the centralized server to analyze and determine average heat absorption in a building. In S260 analyzing the internal heat parameters and the external heat parameters to determine a heat gain factor for energy optimization and management. In an embodiment, the plurality of objects is identified based on their functionality and relevance as a source of heat emission, the objects include electric lights, equipments, appliances and humans.

In an embodiment, the internal and external heat parameters include sensible heat and latent heat .

In an embodiment, the internal and external heat parameters are measured using a plurality of sensors including temperature sensors and heat sensors. In an erabodimerit, each of the plurality of sensors are connected to sub memory modules to store the heat parameters. In an embodiment, the internal and external heat parameters are transmitted to the centralized server using any IOT device connected with the sub memory modules.

In an embodiment, the heat gain factor is determined by evaluating difference between overall average internal and external temperature along with difference between overall average internal and external enthalpy.

In an embodiment, the total heat gain in a building 140 is represented as follows:

However, certain excessive amount of heat needs to be removed from the building, which can be represented as follows: where the Qpeguinxj is the amount of heat gain allowed to maintain the comfortable temperature and QEXC**» the amount of heat to be removed by a third sensor. In some embodiments, the third sensor may be enabled in a chiller.

Further, overall sensible heat gain (SHGi can be calculated as follows:

Where;

Q.¾:G = overall Sensible Heat Gain (Btu) ; he. = overall conductive heat transfer coefficient of surface

l Average Indoor Temperature

overall Total External Surface Area of building (ft ³ ); v ~ volume flow rate of infiltrated air (cfm) ; p ~ air density (lb/ft ^J ); Cpa = specific heat of moist air (Btu/lb.°F); Ss = solar heat coming through windows and convected into a room (Btu) ; Ls - sensible heat from electric lights and convected into a room (Btu) ; Es = sensible heat from equipments and convected into a room (Btu) ; Os ^sensible heat from occupants and convected into a room (Btu)

Overall Latent Heat gain (LHG) can be represented as follows :

where Overall Latent Heat Gain (Btu) ;

latent heat from the interior surface and convicted into a of infiltrated air (Btu); = Enthalpy of room air (lb/lb) ; EL = Latent heat from equipment (Btu) ; OL = Latent heat from occupants (Btu) .

Further, total heat gain can be calculated as follows:

Or

The terms are constants, assumed in the heat load calculations during the design phase. Hence such constants in the Qr equation can be ignored for comparison in the differences in the saving analysis.

Further, So, L _c , E _c , Qa & Ej, can be a fixed heat gain source utilized in heat load calculations during the design phase . Such heat gain sources shall also be ignored in the Q~ equation for comparison in the differences in the saving analysis.

Therefore, the Total Heat Gain Factor (QTHG?) can be written as;

While the preferred embodiment of the present invention and its advantages has been disclosed in the above Detailed Description, the invention is not limited there to but only by the scope of the appended claim. As discussed above, the system in benchmarking based. The benchmarking involves executing the above equations for a duration of 1 complete week, as shown in Tables 01 and 02. During the one complete week of operational benchmarking, the average heat gain due to occupants (people) is automatically included in the Total Chiller Heat Gain (QTCWS ) derivation.

When the data from the above table is plotted for Chiller Heat Gain < RT ) vs QTH«F using excel trendline and equation generation, it provides an equation generating the average chiller heat gain of 360.24 RT for the average occupancy for the week i.e. an average of 1571 persons when Q¾-H«F - 24 BTU. The heat gain value for occupancy by human beings can be captured when regression analysis is carried out for deriving the benchmark equation using QTHQF as shown in table 300 of Pig. 3. In an embodiment, the graph 400 depicting Chiller Keat Gain (RT) vs QTHG.F is shown in Fig. 4.

In an example embodiment, during the benchmarking exercise, each combination of chiller/s operation (referred to as chiller operational configuration) is carried for a duration of 1 complete week of operational

In a related example embodiment, the 1 complete week of operational benchmarking the average heat gain due to occupants {people) is automatically included in the Total Chiller Keat Gain (Qron) derivation.

In another related embodiment, assuming all heat gain sources and types being exactly the same for a said 1 week of benchmarking exercise, the table in the next slide will describe the inclusion for the average heat gain due occupants i.e. average OS + OL.

In a related embodiment, the saving percentage & kWh is derived by the following:

Saving Percentage = [ {Predicted kw - Actual kw) /Predicted kW] *100%

Savings kWh - Predicted kWh - Actual kWh.

While the present invention has been described with reference to one or more exemplary embodiments, it will be understood by those skilled in the art that various changes can be made in respect of the connection of components, without departing from the scope of the present invention, in addition, many modifications can be made to adapt a particular geometry or dimension to the teachings of the disclosure without departing from the scope thereof. Therefore, it is intended that the present invention not be limited to the particular embodiment (s) disclosed as the best mode contemplated, but that the invention will include all embodiments falling within che scope of the appended claims.