WO2013140279A1

WO2013140279A1 - A system and method for creating intelligent energy billing

Info

Publication number: WO2013140279A1
Application number: PCT/IB2013/051526
Authority: WO
Inventors: Saeed Reza BAGHERI; Dagnachew Birru
Original assignee: Koninklijke Philips N.V.
Priority date: 2012-03-20
Filing date: 2013-02-26
Publication date: 2013-09-26

Abstract

The present invention provides a method and system for determining true energy usage among regions within a property. The method provides of determination of a true energy usage based on heat transfer models among adjacent areas or regions. The heat transfer models account for the effect of energy usage of one area on an adjacent area. The measured usage is adjusted by the determined effect of energy usage among adjacent areas, cost based on the adjusted energy usage is then provided for each of the areas.

Description

A SYSTEM AND METHOD FOR

CREATING INTELLIGENT ENERGY BILLING

The present invention relates to the field of property management and more particularly to a system and method for creating an intelligent method for determining true energy usage.

The importance of efficient energy usage in properties is well documented. See for example, "An Analysis of the energy and Cost Savings Potential of Occupancy Sensors for Commercial Lighting Systems," B. VonNeida, etc., J. of Illuminating

Engineering Society, 30, pp. 111-125 (2001) and "Energy Management and Control Laboratory" D.D. Hately, et al., Report PNNL-15074, Pacific Northwest National

Laboratory, Richland, WA. (2005). Several demonstrations have established that one can optimize the energy use of a property through installation of sophisticated control and sensor networks. See, for example, "High Performance Commercial Buildings; A Technology Roadmap," US Department of Energy, Washington, DC (2000) and "Growth Drivers in the North American Energy Services Market," S. Ramakrishnan, Frost & Sullivan Market Insight Reports (2008).

However, the extent of this optimization depends, in part, on the investment made during the installation of the control system. Consequently, not every tenant or owner in a property may be willing or able to participate in such an upgrade. Current billing systems focus on reporting and charging tenants or owners based on their provided energy consumption (e.g., kilowatts of electrical power or cubic feet of gas). However, this method of measuring of provided usage based on consumption fails to provide a true energy usage.

Thus, an intelligent bill system that can distinguish between multiple tenants and allow for a true energy use billing system is needed. The present invention provides method and system for determining true energy usage among regions within a property is disclosed. The method provides of determination of a true energy usage based on heat transfer models among adjacent areas or regions. The heat transfer models account for the effect of energy usage of one area on an adjacent area. The measured usage is adjusted by the determined effect of energy usage among adjacent areas. A cost based on the adjusted energy usage is then provided for each of the areas.

In one aspect of the invention, a method operable in a computer system receives information from at least one sensor within each of a plurality of regions within a property. The sensor information includes temperature, lighting, etc. In addition control information is provided to the computer system. The control information includes information regarding settings for air conditioning, lighting, window treatment, etc. In addition, physical characteristics of each region are provided to the computer system. The physical characteristics may include position of the region with respect to other regions, the geographical position of the region, the number of windows, the orientation of the windows, etc. The computer system further receives an energy transfer model associated with two regions and determines a true energy usage based on the energy transfer occurring between two regions. A cost for the true energy usage may then be determined. In another aspect of the invention, a billing apparatus includes a processor that executes code for receiving sensor, control and physical characteristic information and determines a true energy usage of each region based on an energy transfer model and the sensor, control and physical characteristic information of corresponding regions. A cost for the true energy usage may then be determined. The above and other exemplary features, aspects, and advantages of the present invention will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

Figure 1 illustrates an exemplary system for determining true energy usage in accordance with the principles of the invention.

Figure 2 illustrates an exemplary process for modeling true energy usage in accordance with the principles of the invention.

Figure 3 illustrates an example of the processing for determining true energy usage in accordance with the principles of the invention.

Figure 4 illustrates an example of the processing for determining true energy usage in accordance with the principles of the invention.

Figure 5 illustrates an exemplary process for determining true energy usage in accordance with the principles of the invention.

It is to be understood that these drawings are solely for purposes of illustrating the concepts of the invention and are not intended as a definition of the limits of the invention. It will be appreciated that the same reference numerals, possibly

supplemented with reference characters, where appropriate, have been used throughout to identify corresponding parts. Integrated control and optimization of energy systems in buildings is a key enabler of green building initiative and intelligent building realization. As discussed above, not all involved parties are equally interested, motivated and/or able to participate in this new energy control and optimization trend. Hence, it is crucial to the success of implementation and its sustainability that the participants are fairly compensated based on their true energy usage and corresponding savings.

With the advancement of information technology and computing power, a variety of sophisticated billing and reporting systems have been developed. However, all of these energy billing and reporting systems are focused on energy usage and not the energy itself. This approach is fundamentally flawed in scenarios where multiple tenants/owners share a property by occupying different regions of the building. In such scenarios billing based on energy usage would be unfair and inaccurate.

Fig. 1 illustrates a system 100 for the incorporation of a true energy usage billing system in accordance the principles of the invention. In an exemplary illustration of the principles of the invention, a first inner area 110 and second inner area 120 are adjacent to each other and adjacent to an outside area 190. Each of the inner areas 110 and 120 include at least one of a climate control system 150, (e.g., an air conditioner), a window treatment or cover 155, a lighting system 160 and climate control means (e.g., a thermostat) 165. A user may provide inputs to control the use of the climate control devices and/or systems within a corresponding area. For example, the user may change the thermostat 165 setting and/or change the position or height and/or slat angle of the window treatment system 155 and/or turn on or turn off the lighting system 160.

In addition, each inner area 110 and 120 may include at least one of a sensor for measuring luminance 170 within the respective inner area, a sensor for measuring a temperature 180 within the respective inner area, a gas meter sensor 180 for measuring gas consumption in a respective inner area and an electric meter sensor 185 for measuring electrical consumption in a respective inner area.

Fig. 1 further illustrates a sub-billing machine 130 receiving setting information from various controllers (e.g. temperature controller) and readings from various sensors (e.g. inside thermostat) continuously or at pre-set time intervals. The controller settings may be set automatically or by a user. The system shown in Fig. 1 provides for direct or indirect interaction with a user. In addition, the sub-billing machine 130 receives detail information regarding the property 100 (e.g. location, climate, structure, HVAC/lighting system, use, region definitions, utility pricing policy, and user objectives) directly from a property database 140.

In addition, conditions associated with an outside area 190 may be provided to the sub-billing machine 130 by sensors 192, 194.

The sub-billing machine 130 may also receive information regarding the property 100. For example, the location, the orientation of the inner areas 110, 120 with regard to the rising and setting of the sun, etc.

Specifically, a state within each inner area 110, 120 may be defined as: s = (t, d, w, i, b, q, o_t, o o_gm, o_em, u) (1) where

t £ T = [0...24] represents time of the day,

d £ D = [0....6] represents day of the week,

w £ W = [0...51] represents week of the year,

i I = [0,1] represents the normalized intensity of a ceiling or desk lamp (i represents a vector of lamp intensities),

b ε B = [0,1] represents the normalized height of a blind, q ε Q = [0...π] represents the angle of a blind,

o_t ε 0 = [0... oo) represents the temperature sensor measurements in a given location,

O; ε O = [0... oo) represents the illuminance sensors measurement in a given location,

o_gm ε O = [0... oo) represents the gas meter sensors measurement for a given period of time,

o_em ε O = [0... oo) represents the electricity meter sensors measurement for a given period of time; and

u ε U = {0,1,2... } represents the user ID with zero for an absent user and a non-zero value of k for a present user performing a task with task ID k.

In addition, in the general case, multiple lamps, blinds, users and sensors may be included in one or more areas and hence, the state variable may be defined as:

(2)

£ = ■ b (3)

u = [u_t, .. ^{■ u}nu] (7) where

n_x represents a number of each respective element \, b, q,

Ot, Oj and u within a respective area. The state variable is constructed through sensor readings and maintained over given periods of time for each region or area 100, 120 within a property 100. Each region is referred to by a number that will also be used as the state variable index. It should be noted that the "outside" area 190 is considered an additional region with index of zero. For instance, for the property shown in Fig. 2(a), five regions 210, 220, ... 250 are identified inside the property plus an additional region 260 is identified for outside the property. Thus, a system using a vector of state variables may be formed as:

^{5 =} (⁵0> ⁵1> ⁵2> ⁵3> ⁵4> ⁵5) (8) An inter-region energy transfer model represents an abstract model that governs energy (e.g. heat) transfer between the different regions in a property. These transfers may include heat transfer through conduction, convection or radiation. They may also include mass transfer through air conditioning. One of the key aspects of these transfer models is that they abstract the key elements involved in the transfer based on the specific situation of the current property. For instance, the conduction coefficient is calculated based on building material, wall width, etc., and kept as a part of this model. These transfer models are referred to herein as T_t where the index /^' represents a particular region whose energy transfer characteristics have been modeled.

Fig. 2(b) illustrates a graphic representation of energy interaction between the regions 210... 250 for the exemplary property with five internal regions shown in Fig. 2(a). Fig. 2(b) resembles a graph with regions representing nodes and transfer models representing edges.

An energy pattern recognition solution (EPR) may be determined for each region, wherein each edge in the graph shown in Fig. 2(b) represents an actual transfer of energy between nodes at the two ends of the corresponding edge. The actual transfer of energy between the nodes is of course a function of the states at the end nodes as well as the transfer model as represented by the edge. EPRs are a collection of pre-calculated transfer patterns associated with different combinations of states and models. That is, for each model, once we have the EPR, it is straight forward to calculate the actual transfer of energy between the two ends (nodes) of the model edge.

For instance, for the system shown in Fig. 2(b), the actual energy transfers regions may be represented as:

E = EPR(s,r) (9) where T = (J^, ... T₇) represents the model; and

E = (E_t, ... E₇) represents the energy transfers associated with the edges of the graph shown in Fig. 2(b).

In one embodiment, EPRs represent simplified solutions to the transfer problem that is linear to all involved parameters (i.e. state values), but only works for a particular type of energy transfer model and an energy transfer model variable range (e.g.

particular range of the conductivity constant).

→

In the embodiment illustrated, calculation of f is fairly efficient. However, in one aspect of the invention, the EPRs (independent of how they are used) may be stored in a database 585 and, thus, as more areas or regions within properties are analyzed there is less need for calculation of a new EPR.

As an example of an application of the invention claimed and without loss of generality and for simplicity, a two region property 310, 320 shown in Fig. 3, is described. However, it would be understood that the example provided herein may be applied to properties having a plurality of regions, without altering the scope of the invention.

With regard to the two region (area) property shown in Fig. 3(a), a simplified state description for energy transfer may be expressed as: s = (b, o_tl, o_t2)

1 where b refers to the height of a blind (zero for closed and 1 for

completely open),

o_tl refers to the temperature sensor in the middle of the region and

o_t2 refers to the temperature sensor near an air conditioning opening.

In addition, the energy transfer models may be expressed as: = _llT_2l T₃), (11) where

Ji= cond(/e_ow, i4_ow) + matr(/, c_air) + rad(a, _4_w) (12)

T₂= cond(/e_ow, i4_ow) + matr(/, c_air) + rad(a, _4_w) (13) r₃= cond(fc_iw,_4_iw) (14) wherein,

cond(/e, A) refers to a conduction model with known conductivity coefficient k and known mean area A, matr( , c) refers to a mass transfer model with a known rate of / and a known heat capacity constant of c; rad(a, A) refers to a radiation model with mean sigma value of σ and effective area of A; and

^ow kiw air> A_w, Ai_w, A_ow and represent the outside wall conductivity, inside wall conductivity, heat capacity of air, window area, inside wall area, outside wall area and a/c air flow rate, respectively.

These transfer processes are shown in more details in Fig. 3(b).

Once these transfer models are fixed, the EPRs may be determining by writing the energy balance e uations as:

El ⁼

Ez ⁼ k_owA_ow (s₀₁ — s₂i) + fc_ai_r(s₂2 — 5₂i) + rA_ws_i0(s_0i ⁴— s_2i ⁴) + k_iwA_iw(_Sll - s₂₁) (16) Simplifying the above equation yields:

0, k_0WA_0W + aA_ws₁₀(s₀₁ ³ + SQ^S^ + Soi⁵n² + Sii ³), 0

0> ~kowA₀w ^~ f^cair ~ ^σ·*4νι/⁵ιο (⁵oi³ + ⁵oi²⁵n + ⁵oi⁵n² + ⁵ii ³ ) ^— A_iwk_iw, fc_air n A . k . n

(17)

In the particular case shown in Fig. 4, the state vector for area 110 of Fig. 4 may be formulated as:

s = (18)

wherein

the outside temperature is 80 degrees F;

the temperature of region 110 is 72 degrees F; and the temperature of region 120 is 73 degrees F.

In addition, the temperature in corresponding regions 110, 120 near an air conditioning unit 150 is 70 degrees. Further illustrated, the blind system 155 in region 110 is closed, while the blind system 155 in region 120 is open.

Heat flow, as represented by the direction of the arrows 410, shows that heat flows into regions 110 and 120 from the outside region. Thus, the arrows 410 represent factors that contribute to heating a corresponding region. Similarly, a loss of heat flow is represented by the direction of the arrows 420. In this case, surrounding heat is drawn into the air conditioning units in corresponding regions and is, thus, cooled. Similarly, heat is drawn from region 120 into region 110 as region 110 is at a lower temperature. That is, heat flows from region 120 at 73 degrees F to region 110 which is at 72 degrees F.

A similar calculation may be performed for the second region 120 shown in Figure 4. Thus, because region 120 loses heat to region 110 the energy costs of region 120 to maintain a relatively constant temperature of 73 degrees F are higher than if heat had not been lost. Similarly, the energy costs of region 110 to maintain a relatively constant temperature of 72 degrees F are higher to compensate for the increased heat provided from region 120.

Figure 5 illustrates a process 500 for determining true energy usage in accordance with the principles of the invention. In the first step, all property details (such as location, climate, structure, HVAC/lighting system details, region definitions, utility pricing policy and user objectives) 505 are collected from a property data base 140 and all associated inter-region energy transfer models are built 510. Once a particular transfer model is built it may be reused in other scenarios where similar assumptions/situations hold true. If a corresponding ERP does not already exist in the ERP repository 515, then ERP database 585 is populated using calculations and/or simulations 520.

At step 525, sensor readings are collected 530 during an EPR time period 535 and then are converted to true energy usage for that period 540 and stored in a report and billing database 545.

At step 550, based on user objectives (e.g., temperature setting, window blind positions, lighting, etc.), actual calculated energy uses and current sensor readings, the revised recommended controller settings are calculated and recorded in the report and billing data base 555, 560. Once the end of billing cycle is reached 565 all energy usage and recommendations are combined into a billing and recommendation report 570. This process can continue as long as intelligent billing is desired or as long as specific objectives are not met. The actual bill itself, among other things, can involve the total cost of energy used by different regions based on the local value of energy as well as the breakdown of this cost in terms of different contributing factors through the energy transfer models and stored in a report data base 580.

The sub-billing machine 130 may include a processor which receives the sensor inputs on a regular or on a predetermined periodic basis. In addition, sensor inputs may be provided to the sub-billing machine 130 when conditions within a corresponding area change. For example, the sub-billing machine may receive an indication of a change in blind (window treatment) position caused by a user adjusting (open or closing) the window treatment system or when lights are turned on or off or the temperature setting of the air conditioning unit is changed.

The different sensor setting may further adjust the usage calculation as changes to the element within the region changes.

In addition, the above-described methods according to the present invention can be implemented in hardware, firmware or as software or computer code that can be stored in a recording medium such as a CD ROM, an RAM, a floppy disk, a hard disk, or a magneto-optical disk or computer code downloaded over a network originally stored on a remote recording medium or a non-transitory machine readable medium and to be stored on a local recording medium, so that the methods described herein can be rendered in such software that is stored on the recording medium using a general purpose computer, or a special processor or in programmable or dedicated hardware, such as an ASIC or FPGA. As would be understood in the art, the computer, the processor, microprocessor, controller or the programmable hardware includes memory components, e.g., RAM, ROM, Flash, etc. that may store or receive software or computer code that when accessed and executed by the computer, processor or hardware implement the processing methods described herein. In addition, it would be recognized that when a general purpose computer accesses code for implementing the processing shown herein, the execution of the code transforms the general purpose computer into a special purpose computer for executing the processing shown herein. In addition, the processing illustrated may be performed sequentially or in parallel using different processors to determine specific values.

While there has been shown, described, and pointed out fundamental novel features of the present invention as applied to preferred embodiments thereof, it will be understood that various omissions and substitutions and changes in the apparatus described, in the form and details of the devices disclosed, and in their operation, may be made by those skilled in the art without departing from the spirit of the present invention. It is expressly intended that all combinations of those elements that perform substantially the same function in substantially the same way to achieve the same results are within the scope of the invention. Substitutions of elements from one described embodiment to another are also fully intended and contemplated. For example, any numerical values presented herein are considered only exemplary and are presented to provide examples of the subject matter claimed as the invention. Hence, the invention, as recited in the appended claims, is not limited by the numerical examples provided herein.

Claims

What is claimed is:

1. A method, operable in a computing system, for determining energy usage within a region (110, 120) contained within a property (100), said property containing a plurality of adjacent regions, the method comprising the steps of: collecting sensor information from each of at least one sensor (170, 175, 180, 185) within each of the plurality of adjacent regions, said sensor information including energy usage; collecting control data for each of at least one control system (150, 155, 160, 165) within each of the plurality of regions (110, 120), said control system data including setting information regarding energy consu mption devices; collecting physical characteristic information regarding each of the plurality of regions; obtaining energy transfer models (T ) between each of the plurality of regions; adjusting the energy usage (EPR) for each of the plurality of regions within the property based on a corresponding energy transfer models (T ) , wherein the energy usage considers the collected sensor data, control data and physical characteristic information of the corresponding regions.

2. The method of claim 1, further comprising; determining a cost for each region (110, 120) based on the adjusted energy usage.

3. The method of claim 1, wherein the plurality of regions further comprises a region external to the property (190).

4. The method of claim 1, wherein the energy transfer models model energy transfer between the different regions of the property, said energy transfer model being determined based on energy transfer through at least one of: conduction, convection and radiation.

5. The method of claim 4, wherein the energy transfer models are pre-stored in a database (585).

6. The method of claim 4, wherein the energy transfer models are determined based on the simulations of corresponding ones of the regions.

7. The method of claim 1, wherein collection of each of the sensor and control data is performed for a predetermined time period.

8. The method of claim 1, wherein the collection of each of the sensor and control data is performed when a change in sensor and control data is determined.

9. The method of claim 7, further comprising: providing a report regarding the adjusted energy usage at the conclusion of the predetermined time period.

10. A billing apparatus (130) for determining energy usage within a region contained within a property containing a plu rality of adjacent regions, the billing apparatus comprising: a processor in communication with a memory, the memory including code which when accessed by the processor causes the processor to: collect sensor information from each of at least one sensor (170, 175, 180, 185) within each of the plurality of regions (110, 120), said sensor information including energy usage; collect control data for each of at least one control system (150, 155, 160, 165) within each of the plurality of regions (110, 120), said control system data including setting information regarding energy consu mption devices; collect physical characteristic information regarding each of the plu rality of regions; obtain energy transfer models (T ) between each of the plurality of regions; adjust the energy usage for each of the plurality of regions (110,120) within the

→

property (100) based on corresponding ones of the energy transfer models (T ), wherein the adjusted energy usage is based on the collected sensor data, control data and physical characteristic information of the corresponding regions; and determine a cost of energy usage for each region based on the adjusted energy usage.

11. The apparatus of claim 10, wherein the plurality of regions further comprises a region external to the property (190).

12. The apparatus of claim 10, wherein the energy transfer models govern energy transfer between the different regions of the property, said energy transfer model being determined based on energy transfer through at least one of: conduction, convection and radiation.

13. The apparatus of claim 12, wherein the energy transfer models are pre-stored in a database (585).

14. The apparatus of claim 12, wherein the energy transfer models are determined based on the simulations of corresponding ones of the regions.

15. The apparatus of claim 10, wherein collection of each of the sensor and control data is performed for a predetermined time period.

16. The apparatus of claim 10, wherein the collection of each of the sensor and control data is performed when a change in sensor and control data is determined.

17. The apparatus of claim 15, further comprising: providing a report regarding the adjusted energy usage at the conclusion of the predetermined time period.

18. A billing apparatus receiving sensor information (170) for each of a plurality of regions within (110, 120) and outside (190) a property; receiving control information of each of at least one control system (150) in the plurality of regions; receiving physical characteristics of each of the regions, said physical characteristics including a physical placement of the regions;

→

obtaining an energy transfer model (T ) for each of two adjacent regions; adjusting an amount of energy usage of a region, indicated by sensor information, based on said energy transfer model; and determining a cost for energy usage based on the adjusted amount of energy usage.

19. The billing apparatus of claim 18, wherein the cost is determined after a

predetermined time has expired.

20. The billing apparatus of claim 18, wherein the physical characteristics of each of the regions is stored in a data base (140).