IP Library › Granted Patent US 12,242,022
Granted Patent B2
US 12,242,022 · App. 18/346,594 · Granted Mar 4, 2025

System and method for estimating photovoltaic energy through empirical derivation with the aid of a digital computer

Inventor: Thomas E. Hoff (Napa, CA)
Assignee: CLEAN POWER RESEARCH, L.L.C.
G01W1/12G01R21/1331G01W1/02G06F17/11G06F17/16G06F30/20G06Q10/04G06Q50/06H02J3/38H02S50/00H02S50/15G06Q50/04H02J2203/20Y02E10/56Y02E60/00Y02P90/30Y04S40/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,242,022
App. No.
18/346,594
Granted
Mar 4, 2025
Kind
B2
Abstract

The accuracy of photovoltaic simulation modeling is predicated upon the selection of a type of solar resource data appropriate to the form of simulation desired. Photovoltaic power simulation requires irradiance data. Photovoltaic energy simulation requires normalized irradiation data. Normalized irradiation is not always available, such as in photovoltaic plant installations where only point measurements of irradiance are sporadically collected or even entirely absent. Normalized irradiation can be estimated through several methodologies, including assuming that normalized irradiation simply equals irradiance, directly estimating normalized irradiation, applying linear interpolation to irradiance, applying linear interpolation to clearness index values, and empirically deriving irradiance weights. The normalized irradiation can then be used to forecast photovoltaic fleet energy production.

Claims (45)

1. A system for estimating photovoltaic energy through empirical derivation with the aid of a digital computer, comprising:

at least one computer processor configured to:

obtain solar irradiance data comprising a set of irradiance observations that have been recorded for a location at which a photovoltaic plant can be operated with each irradiance observation in the set being separated by regular intervals of time;

obtain measured irradiance associated with at least some of the irradiance observations;

obtain a set of clear sky irradiance with each clear sky irradiance in the set corresponding to one of the irradiance observations;

empirically derive using an optimization approach a weighting factor array using at least some of the measured irradiance and the irradiance observations associated with the at least some measured irradiance;

estimate a set of normalized irradiation, with each normalized irradiation in the set corresponding to one of the irradiance observations, using the weighing factor array and the irradiance observations;

form a time series of clearness indexes with each clearness index in the time series corresponding to one of the irradiance observations, each clearness index comprising a ratio of the irradiance observation's corresponding normalized irradiation estimate and the irradiance observation's corresponding clear sky irradiance; and

forecast photovoltaic energy production for the photovoltaic plant as a function of the time series of the clearness indexes and photovoltaic plant's power rating.

2. A system according to claim 1 , wherein the weighting factor array comprises a plurality of weighing factors and each of the weighing factors is selected to minimize error between one of the irradiance observations and the associated measured irradiance.

3. A system according to claim 2 , wherein the measured irradiance is measured using ground based instrumentation.

4. A system according to claim 1 , wherein the normalized irradiation is obtained using an irradiance array formed by the irradiance observation occurring before the one irradiance observation, the one irradiance observation, and the irradiance observation occurring after the one irradiance observation.

5. A system according to claim 4 , wherein the normalized irradiation comprises a product of the weighing factor array and the irradiance array.

6. A system according to claim 1 , the at least one computer processor further configured to:

determine an average of the irradiance observations; and

determine a set of sky clearness indexes as a ratio of each of the irradiance observations and clear sky global horizontal irradiance, wherein the normalized irradiation is further determined using the average of the irradiance observation and a sky clearness index array formed by the sky clearness index corresponding to the irradiance observation occurring before the one irradiance observation, the sky clearness index corresponding to the one irradiance observation, and the sky clearness index corresponding to the irradiance observation occurring after the one irradiance observation.

7. A system according to claim 1 , wherein a power grid connected to the photovoltaic plant is operated using the forecasted photovoltaic energy production.

8. A system according to claim 1 , the at least one computer processor further configured to:

obtain sets of irradiance observations that have been recorded for a plurality of locations at which a photovoltaic fleet comprising a plurality of photovoltaic plants can be operated;

estimate sets of normalized irradiation for each of the locations and forming time series of clearness indexes in the computer with the sets of normalized irradiation; and

forecast photovoltaic energy production for the photovoltaic fleet as a function of the time series of the clearness indexes and photovoltaic plants' power ratings.

9. A method according to claim 8 , wherein the photovoltaic fleet is integrated into a power grid and wherein the power grid is operated based on the forecast photovoltaic energy production for the photovoltaic fleet.

10. A system according to claim 1 , wherein a sum of weighting factors in the weighting factor array equals 1.

11. A method for estimating photovoltaic energy through empirical derivation with the aid of a digital computer, comprising steps of:

obtaining solar irradiance data comprising a set of irradiance observations that have been recorded for a location at which a photovoltaic plant can be operated with each irradiance observation in the set being separated by regular intervals of time;

obtaining measured irradiance associated with at least some of the irradiance observations;

obtaining a set of clear sky irradiance with each clear sky irradiance in the set corresponding to one of the irradiance observations;

empirically deriving using an optimization approach a weighting factor array using at least some of the measured irradiance and the irradiance observations associated with the at least some measured irradiance;

estimating a set of normalized irradiation, with each normalized irradiation in the set corresponding to one of the irradiance observations, using the weighing factor array and the irradiance observations;

forming a time series of clearness indexes with each clearness index in the time series corresponding to one of the irradiance observations, each clearness index comprising a ratio of the irradiance observation's corresponding normalized irradiation estimate and the irradiance observation's corresponding clear sky irradiance; and

forecasting photovoltaic energy production for the photovoltaic plant as a function of the time series of the clearness indexes and photovoltaic plant's power rating, wherein the steps are performed by at least one suitably-programmed computer.

12. A method according to claim 11 , wherein the weighting factor array comprises a plurality of weighing factors and each of the weighing factors is selected to minimize error between one of the irradiance observations and the associated measured irradiance.

13. A method according to claim 12 , wherein the measured irradiance is measured using ground based instrumentation.

14. A method according to claim 11 , wherein the normalized irradiation is obtained using an irradiance array formed by the irradiance observation occurring before the one irradiance observation, the one irradiance observation, and the irradiance observation occurring after the one irradiance observation.

15. A method according to claim 14 , wherein the normalized irradiation comprises a product of the weighing factor array and the irradiance array.

16. A method according to claim 11 , further comprising:

determining an average of the irradiance observations; and

determining a set of sky clearness indexes as a ratio of each of the irradiance observations and clear sky global horizontal irradiance, wherein the normalized irradiation is further determined using the average of the irradiance observation and a sky clearness index array formed by the sky clearness index corresponding to the irradiance observation occurring before the one irradiance observation, the sky clearness index corresponding to the one irradiance observation, and the sky clearness index corresponding to the irradiance observation occurring after the one irradiance observation.

17. A method according to claim 11 , wherein a power grid connected to the photovoltaic plant is operated using the forecasted photovoltaic energy production.

18. A method according to claim 11 , further comprising:

obtaining sets of irradiance observations that have been recorded for a plurality of locations at which a photovoltaic fleet comprising a plurality of photovoltaic plants can be operated;

estimating sets of normalized irradiation for each of the locations and forming time series of clearness indexes in the computer with the sets of normalized irradiation; and

forecasting photovoltaic energy production for the photovoltaic fleet as a function of the time series of the clearness indexes and photovoltaic plants' power ratings.

19. A method according to claim 18 , wherein the photovoltaic fleet is integrated into a power grid and wherein the power grid is operated based on the forecast photovoltaic energy production for the photovoltaic fleet.

20. A method according to claim 11 , wherein a sum of weighting factors in the weighting factor array equals 1.

Continuity (10)
Continuation 17328688 · May 24, 2021
Continuation 15930259 · May 12, 2020
Continuation 16429534 · Jun 3, 2019
Continuation 15495892 · Apr 24, 2017
Continuation 14056898 · Oct 17, 2013
Continuation In Part 13866901 · Apr 19, 2013
Continuation In Part 13462505 · May 2, 2012
Continuation 13453956 · Apr 23, 2012
Continuation 13190442 · Jul 25, 2011
Related Publication 20230350097A1 · Nov 2, 2023
References Cited (226)
US 3354943A · Mcfarlan · 1967 [cited by applicant]
US 3923038A · Cutchaw · 1975 [cited by applicant]
US 4089143A · La Pietra · 1978 [cited by applicant]
US 4992942A · Bauerle et al. · 1991 [cited by applicant]
US 5001650A · Francis et al. · 1991 [cited by applicant]
US 5177972A · Sillato et al. · 1993 [cited by applicant]
US 5602760A · Chacon et al. · 1997 [cited by applicant]
US 5803804A · Meier et al. · 1998 [cited by applicant]
US 6134511A · Subbarao · 2000 [cited by applicant]
US 6148623A · Park et al. · 2000 [cited by applicant]
US 6366889B1 · Zaloom · 2002 [cited by applicant]
US 6748327B1 · Watson · 2004 [cited by applicant]
US 7451017B2 · McNally · 2008 [cited by applicant]
US 7742892B2 · Fromme et al. · 2010 [cited by applicant]
US 7742897B2 · Herzig · 2010 [cited by applicant]
US 7920997B2 · Domijan et al. · 2011 [cited by applicant]
US 8140193B2 · Lee · 2012 [cited by applicant]
US 8155900B1 · Adams · 2012 [cited by applicant]
US 8326535B1 · Hoff · 2012 [cited by examiner]
US 8369994B1 · Rosen · 2013 [cited by applicant]
US 8370283B2 · Pitcher et al. · 2013 [cited by applicant]
US 9007460B2 · Schmidt et al. · 2015 [cited by applicant]
US 9020650B2 · Lutze · 2015 [cited by applicant]
US 9086585B2 · Hamada et al. · 2015 [cited by applicant]
US 9098876B2 · Steven et al. · 2015 [cited by applicant]
US 9103719B1 · Ho et al. · 2015 [cited by applicant]
US 9171276B2 · Steven et al. · 2015 [cited by applicant]
US 9286464B2 · Choi · 2016 [cited by applicant]
US 9286646B1 · Hoff · 2016 [cited by examiner]
US 9524529B2 · Sons et al. · 2016 [cited by applicant]
US 9599597B1 · Steele et al. · 2017 [cited by applicant]
US 10409241B2 · Wartena et al. · 2019 [cited by applicant]
US 10409925B1 · Hoff · 2019 [cited by examiner]
US 20020055358A1 · Hebert · 2002 [cited by applicant]
US 20030201749A1 · Hossain et al. · 2003 [cited by applicant]
US 20050055137A1 · Andren et al. · 2005 [cited by applicant]
US 20050095978A1 · Blunn et al. · 2005 [cited by applicant]
US 20050222715A1 · Ruhnke et al. · 2005 [cited by applicant]
US 20070084502A1 · Kelly et al. · 2007 [cited by applicant]
US 20070119718A1 · Gibson et al. · 2007 [cited by applicant]
US 20070233534A1 · Martin et al. · 2007 [cited by applicant]
US 20080258051A1 · Heredia et al. · 2008 [cited by applicant]
US 20090037241A1 · Olsen et al. · 2009 [cited by applicant]
US 20090106079A1 · Gutlapalli et al. · 2009 [cited by applicant]
US 20090125275A1 · Woro · 2009 [cited by applicant]
US 20090154384A1 · Todd et al. · 2009 [cited by applicant]
US 20090217965A1 · Dougal et al. · 2009 [cited by applicant]
US 20090271154A1 · Coad et al. · 2009 [cited by applicant]
US 20090302681A1 · Yamada et al. · 2009 [cited by applicant]
US 20100070084A1 · Steinberg et al. · 2010 [cited by applicant]
US 20100161502A1 · Kumazawa et al. · 2010 [cited by applicant]
US 20100188413A1 · Hao et al. · 2010 [cited by applicant]
US 20100198420A1 · Rettger et al. · 2010 [cited by applicant]
US 20100211222A1 · Ghosn · 2010 [cited by applicant]
US 20100219983A1 · Peleg et al. · 2010 [cited by applicant]
US 20100263709A1 · Norman et al. · 2010 [cited by applicant]
US 20100309330A1 · Beck · 2010 [cited by applicant]
US 20100324962A1 · Nesler et al. · 2010 [cited by applicant]
US 20100332373A1 · Crabtree et al. · 2010 [cited by applicant]
US 20110137591A1 · Ishibashi · 2011 [cited by applicant]
US 20110137763A1 · Aguilar · 2011 [cited by applicant]
US 20110145037A1 · Domashchenko et al. · 2011 [cited by applicant]
US 20110272117A1 · Hamstra et al. · 2011 [cited by applicant]
US 20110276269A1 · Hummel · 2011 [cited by applicant]
US 20110282504A1 · Besore et al. · 2011 [cited by applicant]
US 20110307109A1 · Sri-Jayantha · 2011 [cited by applicant]
US 20120065783A1 · Fadell et al. · 2012 [cited by applicant]
US 20120066168A1 · Fadell et al. · 2012 [cited by applicant]
US 20120078685A1 · Krebs et al. · 2012 [cited by applicant]
US 20120084063A1 · Drees et al. · 2012 [cited by applicant]
US 20120095798A1 · Mabari · 2012 [cited by applicant]
US 20120130556A1 · Marhoefer · 2012 [cited by applicant]
US 20120143383A1 · Cooperrider et al. · 2012 [cited by applicant]
US 20120143536A1 · Greaves et al. · 2012 [cited by applicant]
US 20120158350A1 · Steinberg et al. · 2012 [cited by applicant]
US 20120191439A1 · Meagher et al. · 2012 [cited by applicant]
US 20120232701A1 · Carty et al. · 2012 [cited by applicant]
US 20120271576A1 · Kamel et al. · 2012 [cited by applicant]
US 20120278051A1 · Jiang et al. · 2012 [cited by applicant]
US 20120310416A1 · Tepper et al. · 2012 [cited by applicant]
US 20120310427A1 · Williams et al. · 2012 [cited by applicant]
US 20120310729A1 · Dalto et al. · 2012 [cited by applicant]
US 20120330626A1 · An et al. · 2012 [cited by applicant]
US 20130008224A1 · Stormbom · 2013 [cited by applicant]
US 20130030590A1 · Prosser · 2013 [cited by applicant]
US 20130054662A1 · Coimbra · 2013 [cited by applicant]
US 20130060471A1 · Aschheim et al. · 2013 [cited by applicant]
US 20130134962A1 · Kamel et al. · 2013 [cited by applicant]
US 20130152998A1 · Herzig · 2013 [cited by applicant]
US 20130166266A1 · Herzig et al. · 2013 [cited by applicant]
US 20130190940A1 · Sloop et al. · 2013 [cited by applicant]
US 20130204439A1 · Scelzi · 2013 [cited by applicant]
US 20130245847A1 · Steven et al. · 2013 [cited by applicant]
US 20130262049A1 · Zhang et al. · 2013 [cited by applicant]
US 20130268129A1 · Fadell et al. · 2013 [cited by applicant]
US 20130274937A1 · Ahn et al. · 2013 [cited by applicant]
US 20130289774A1 · Day et al. · 2013 [cited by applicant]
US 20130304269A1 · Shiel · 2013 [cited by applicant]
US 20130314699A1 · Jungerman et al. · 2013 [cited by applicant]
US 20130325377A1 · Drees et al. · 2013 [cited by applicant]
US 20140039648A1 · Boult et al. · 2014 [cited by applicant]
US 20140039709A1 · Steven et al. · 2014 [cited by applicant]
US 20140039965A1 · Steven et al. · 2014 [cited by applicant]
US 20140107851A1 · Yoon et al. · 2014 [cited by applicant]
US 20140129197A1 · Sons et al. · 2014 [cited by applicant]
US 20140142862A1 · Umeno et al. · 2014 [cited by applicant]
US 20140214222A1 · Rouse et al. · 2014 [cited by applicant]
US 20140222241A1 · Ols · 2014 [cited by applicant]
US 20140236708A1 · Wolff et al. · 2014 [cited by applicant]
US 20140278108A1 · Kerrigan et al. · 2014 [cited by applicant]
US 20140278145A1 · Angeli et al. · 2014 [cited by applicant]
US 20140278165A1 · Wenzel et al. · 2014 [cited by applicant]
US 20140278203A1 · Lange et al. · 2014 [cited by applicant]
US 20140289000A1 · Hutchings et al. · 2014 [cited by applicant]
US 20140297238A1 · Parthasarathy et al. · 2014 [cited by applicant]
US 20140365017A1 · Hanna et al. · 2014 [cited by applicant]
US 20150019034A1 · Gonatas · 2015 [cited by applicant]
US 20150057820A1 · Kefayati et al. · 2015 [cited by applicant]
US 20150088576A1 · Steven et al. · 2015 [cited by applicant]
US 20150094968A1 · Jia et al. · 2015 [cited by applicant]
US 20150112497A1 · Steven et al. · 2015 [cited by applicant]
US 20150134251A1 · Bixel · 2015 [cited by applicant]
US 20150177415A1 · Bing · 2015 [cited by applicant]
US 20150188415A1 · Abido et al. · 2015 [cited by applicant]
US 20150269664A1 · Davidson · 2015 [cited by applicant]
US 20150278968A1 · Steven et al. · 2015 [cited by applicant]
US 20150323423A1 · Alsaleem · 2015 [cited by applicant]
US 20150326015A1 · Steven et al. · 2015 [cited by applicant]
US 20150330923A1 · Smullin · 2015 [cited by applicant]
US 20150332294A1 · Albert et al. · 2015 [cited by applicant]
US 20150339762A1 · Deal et al. · 2015 [cited by applicant]
US 20150355017A1 · Clarke et al. · 2015 [cited by applicant]
US 20160049606A1 · Bartoli et al. · 2016 [cited by applicant]
US 20160072287A1 · Jia et al. · 2016 [cited by applicant]
US 20160187911A1 · Carty et al. · 2016 [cited by applicant]
US 20160306906A1 · McBrearty et al. · 2016 [cited by applicant]
US 20160348936A1 · Johnson et al. · 2016 [cited by applicant]
US 20170104451A1 · Gostein · 2017 [cited by applicant]
US 20170299446A1 · Lange et al. · 2017 [cited by applicant]
US 20180136366A1 · Vega-Avila · 2018 [cited by examiner]
AU 20112982 · 2012 [cited by applicant]
CN 102155358 · 2011 [cited by applicant]
JP 4799838 · 2011 [cited by applicant]
WO 2007124059 · 2007 [cited by applicant]
WO 2007142693 · 2007 [cited by applicant]
WO 2013181408 · 2013 [cited by applicant]
WO 2014081967 · 2014 [cited by applicant]
Brinkman et al., “Toward a Solar-Powered Grid.” IEEE Power & Energy, vol. 9, No. 3, May/Jun. 2011. [cited by applicant]
California ISO. Summary of Preliminary Results of 33% Renewable Integration Study—2010 CPUC LTPP, May 10, 2011. [cited by applicant]
Ellis et al., “Model Makers.” IEEE Power & Energy, vol. 9, No. 3, May/Jun. 2011. [cited by applicant]
Danny H.W. Li et al., “Analysis of solar heat gain factors using sky clearness index and energy implications.” Energy Conversions and Management, Aug. 2000. [cited by applicant]
Hoff et al., “Quantifying PV Power Output Variability.” Solar Energy 84 (2010) 1782-1793, Oct. 2010. [cited by applicant]
Hoff et al., “PV Power Output Variability: Calculation of Correlation Coefficients Using Satellite Insolation Data.” American Solar Energy Society Annual Conference Proceedings, Raleigh, NC, May 18, 2011. [cited by applicant]
Kuszamaul et al., “Lanai High-Density Irradiance Sensor Network for Characterizing Solar Resource Variability of MW-Scale PV System.” 35th Photovoltaic Specialists Conference, Honolulu, HI. Jun. 20-25, 2010. [cited by applicant]
Serban C. “Estimating Clear Sky Solar Global Radiation Using Clearness Index, for Brasov Urban Area”. Proceedings of the 3rd International Conference on Maritime and Naval Science and Engineering. ISSN: 1792-4707, ISBN:… [cited by applicant]
Mills et al., “Dark Shadows.” IEEE Power & Energy, vol. 9, No. 3, May/Jun. 2011. [cited by applicant]
Mills et al., “Implications of Wide-Area Geographic Diversity for Sort-Term Variability of Solar Power.” Lawrence Berkeley National Laboratory Technical Report LBNL-3884E. Sep. 2010. [cited by applicant]
Perez et al., “Parameterization of site-specific short-term irradiance variability.” Solar Energy, 85 (2011) 1343-1345, Nov. 2010. [cited by applicant]
Perez et al., “Short-term irradiance variability correlation as a function of distance.” Solar Energy, Mar. 2011. [cited by applicant]
Philip, J., “The Probability Distribution of the Distance Between Two Random Points in a Box.” www.math.kth.se/˜johanph/habc.pdf. Dec. 2007. [cited by applicant]
Stein, J., “Simulation of 1-Minute Power Output from Utility-Scale Photovoltaic Generation Systems.” American Solar Energy Society Annual Conference Proceedings, Raleigh, NC, May 18, 2011. [cited by applicant]
Solar Anywhere, 2011. Web-Based Service that Provides Hourly, Satellite-Derived Solar Irradiance Data Forecasted 7 days Ahead and Archival Data back to Jan. 1, 1998. www.SolarAnywhere.com. [cited by applicant]
Stokes et al., “The atmospheric radiance measurement (ARM) program: programmatic background and design of the cloud and radiation test bed.” Bulletin of American Meteorological Society vol. 75, No. 7, pp. 1201-1221, Jul… [cited by applicant]
Hoff et al., “Modeling PV Fleet Output Variability,” Solar Energy, May 2010. [cited by applicant]
Olopade et al., “Solar Radiation Characteristics and the performance of Photovoltaic (PV) Modules in a Tropical Station.” Journal Sci. Res. Dev. vol. 11, 100-109, 2008/2009. [cited by applicant]
Li et al., “Analysis of solar heat gain factors using sky clearness index and energy implications.” 2000. [cited by applicant]
Shahab Poshtkouhi et al., “A General Approach for Quantifying the Benefit of Distributed Power Electronics for Fine Grained MPPT in Photovoltaic Applications Using 3-D Modeling,” Nov. 20, 2012, IEE Transactions on Powee… [cited by applicant]
Pathomthat Chiradeja et al., “An Approaching to Quantify the Technical Benefits of Distributed Generation,” Dec. 2004, IEEE Transactions on Energy Conversation, vol. 19, No. 4, p. 764-773, 2004. [cited by applicant]
Mudathir Funsho Akorede et al., “Distributed Energy Resources and Benefits to the Environment,” 2010, Renewable and Sustainable Energy Reviews 14, p. 724-734. [cited by applicant]
V.H. Mendez, et al., “Impact of Distributed Generation on Distribution Investment Deferral,” Electrical Power and Energy Systems 28, p. 244-252, 2006. [cited by applicant]
Francisco M. Gonzalez-Longatt et al., “Impact of Distributed Generation Over Power Losses on Distribution System,” Oct. 2007, Electrical Power Quality and Utilization, 9th International Conference. [cited by applicant]
M. Begovic et al., “Impact of Renewable Distributed Generation on Power Systems,” 2001, Proceedings of the 34th Hawaii International Conference on System Sciences, p. 1-10. [cited by applicant]
M. Thomson et al., “Impact of Widespread Photovoltaics Generation on Distribution Systems,” Mar. 2007, IET Renew. Power Gener., vol. 1, No. 1 p. 33-40. [cited by applicant]
Varun et al., “LCA of Renewable Energy for Electricity Generation Systems—A Review,” 2009, Renewable and Sustainable Energy Reviews 13, p. 1067-1073. [cited by applicant]
Andreas Schroeder, “Modeling Storage and Demand Management in Power Distribution Grids,” 2011, Applied Energy 88, p. 4700-4712. [cited by applicant]
Daniel S. Shugar, “Photovoltaics in the Utility Distribution System: The Evaluation of System and Distributed Benefits, 1990, Pacific Gas and Electric Company Department of Research and Development,” p. 836-843. [cited by applicant]
Nguyen et al., “Estimating Potential Photovoltaic Yield With r.sun and the Open Source Geographical Resources Analysis Support System,” Mar. 17, 2010, pp. 831-843. [cited by applicant]
Pless et al., “Procedure For Measuring And Reporting The Performance of Photovoltaic Systems In Buildings,” 62 pages, Oct. 2005. [cited by applicant]
Emery et al., “Solar Cell Efficiency Measurements,” Solar Cells, 17 (1986) 253-274. [cited by applicant]
Santamouris, “Energy Performance of Residential Buildings,” James & James/Earchscan, Sterling, VA 2005. [cited by applicant]
Al-Homoud, “Computer-Aided Building Energy Analysis Techniques,” Building & Environment 36 (2001) pp. 421-433. [cited by applicant]
Thomas Huld, “Estimating Solar Radiation and Photovoltaic System Performance,” The PVGIS Approach, 2011 (printed Dec. 13, 2017). [cited by applicant]
Anderson et al., “Modelling The Heat Dynamics Of A Building Using Stochastic Differential Equations,” Energy and Building, vol. 31, 2000, pp. 13-24. [cited by applicant]
J. Kleissl & Y. Agarwal, “Cyber-Physical Energy Systems: Focus on Smart Buildings,” Design Automation Conference, Anaheim, CA, 2010, pp. 749-754, doi: 10.1145/1837274.1837464. (2010). [cited by applicant]
Clito Afonso, “Tracer gas technichue for measurement of air infiltration and natural ventilation: case studies amd new devices for measurement of mechamocal air ventilation in ducts.” 2013, International Journal of Low-… [cited by applicant]
Isaac Turiel et al., “Occupant-generated CO2 as an indicator of ventilation rate,” 1980, Lawrence Berkley Laboratory, 26 pages (Year: 1980). [cited by applicant]
Andrew K. Persily, “Tracer gas techniques for studying building air exchange,” 1988, National Bureau of Standards, 44 pages (Year: 1988). [cited by applicant]
Detlef Laussmann et al., “Air change measurements using tracer gasses,” 2011, In book: Chemistry, Emission Control, Radioactive Pollution and Indoor Air Quality, 42 pages (Year: 2011). [cited by applicant]
Fine_1980 (Analysis of Heat Transfer in Building Thermal Insulation, Oak Ridge National Laboratory ORNL/TM-7481) (Year: 1980). [cited by applicant]
Chapter2_1985 (Rates of Change and the Chain Rule, Springer-Verlag) (Year: 1985). [cited by applicant]
E.S. Mustafina et al. “Problems of Small Heat Power Stations and Ways to Solve Them,” Proceedings. The 8th Russian-Korean International Symposium on Science and Technology, 2004. KORUS 2004. Tomsk, Russia, 2004. pp. 267… [cited by applicant]
Di Yuhui, Di Yulin, Wang Yonghui and Wen Li, “Application and Analusis of Water Source Heat Pump System in Residential Buildings,” 2011 International Symposium on Water Resource and Environmental Protection, 2011, pp. 2… [cited by applicant]
1997 Ashrae Handbook, “Chapter 28 Nonresidential Cooling and Heating Load Calculation Procedures,” 1997, Ashrae, 65 pagges (Year: 1997). [cited by applicant]
2001 Ashrae Handbook, “Chapter 29 Nonresidential Cooling and Heating Load Calculation Procedures,” 2001, Ashrae, 41 pagges (Year: 2001). [cited by applicant]
Jeffrey D. Spitler, “Load Calculation applications Manual (I-P)”, 2014, second edition, chapter “Fundammentals of the Radiant Time Series Method,” Ashrae, 31 pages (Year: 2014). [cited by applicant]
Parsons, Peter. “Determining infiltration rates and predicting building occupancy using CO2 concentration curves.” Journal of Energy 2014 (2014). (Year: 2014). [cited by applicant]
Dong, Bing, and Khee Poh Lam. “A real-time model predictive control for building heating and cooling systems based on the occupancy behavior pattern detection and local weather forecasting.” Building Simulation. vol. 7.… [cited by applicant]
Gruber, Mattias, Anders Truschel, and Jan-Olof Dalenback. “CO2 sensors for occupancy estimations: Potential in building automation applications.” Energy and Buildings 84 (2014): 548-556. (Year: 2014). [cited by applicant]
Hanninen, Otto, et al. “Combining CO2 data from ventilation phases improves estimation of air exchange rates.” Proceedings of Healthy Buildings Conference, Brisbane. 2012. (Year: 2012). [cited by applicant]
Kapalo, Peter, et al. “Determine a methodology for calculating the needed fresh air.” Environmental Engineering. Proceedings of the International Conference on Environmental Engineering. ICEE. vol. 9. Vilnius Gediminas … [cited by applicant]
Wang, Shengwei, and Xinqiao Jin. “CO2-based occupancy detection for on-line outdoor air flow control.” Indoor and Built Environment 7.3 (1998): 165-181. (Year: 1998). [cited by applicant]
Grot, Richard A., et al. Measurement methods for evaluation of thermal integrity of building envelopes. No. PB-83-18017 4; NBSIR-82-2605. National Bureau of Standards, Washington, DC (USA). Center for Building Technolog… [cited by applicant]
Claude-Alain, Roulet, and Flavia Foradini. “Simple and cheap air change rate measurement using CO2 concentration decays.” International Journal of Ventilation 1.1 (2002): 39-44. (Year: 2002). [cited by applicant]
Ng, Lisa Chen, and Jin Wen. “Estimating building airflow using CO2 measurements from a distributed sensor network.” HVAC&R Research 17.3 (2011): 344-365. (Year: 2011). [cited by applicant]
Shuqing Cui et al., “CO2 tracer gas concentration decay method for measuring air change rate,” Nov. 18, 2014, Building and Environment, vol. 84, pp. 162-169; (Year: 2014). [cited by applicant]
Robert C. Sondregger et al., “In-situ measurements of residential energy performance using electric co-heating,” 1980, Lawrence Berkeley Laboratory, 26 pages (Year: 1980). [cited by applicant]
Yu-Pei Ke , “Using carbon dioxide measurements to determine occupancy for ventilation controls,” 1997, https://www.aivc.org/sites/ default/files/airbase_10515.pdf, pp. 1-9 (Year: 1997). [cited by applicant]
T. Leephakpreeda et al., “Occupancy-based control of indoor air ventilation: a theoretical and experimental study,” 2001, ScienceAsia, vol. 27, pp. 279-284 (Year: 2001). [cited by applicant]
Judkoff et al., “Side-by-Side Thermal Tests of Modular Offices: A Validation Study of the STEM Method”, Dec. 2000, NREUTP-550-23940 (Year: 2000). [cited by applicant]
Bauwens et al., “State-of-the-art on the co-heating test methodology”, Jan. 22, 2014, Webinar: “How to determine the real performances of buildings? Building characterisation by co-heating”, URL: dynastee(dot)info/webin… [cited by applicant]
Andrews, John W., Richard F. Krajewski, and John J. Strasser. Electric co-heating in the ASHRAE standard method oftest for thermal distribution efficiency: Test results on two New York State homes. No. BNL-62346; CONF-9… [cited by applicant]
Balcomb, J. D., et al. “Short-term energy monitoring for commercial buildings.” Proceedings of the 1994 ACEEE Summer Study on Energy Efficiency in Buildings. 1994 (Year: 1994). [cited by applicant]
Bauwens, Geert, and Staf Roels. “Co-heating test: A state-of-the-art.” Energy and Buildings 82 (2014): 163-172. (Year: 2014). [cited by applicant]
Carrillo, Antonio, Fernando Dominguez, and Jose M. Cejudo. “Calibration of an EnergyPlus simulation model by the STEM-PSTAR method.” Eleventh International IBPSA Conference, Glasgow, Scotland. 2009. (Year: 2009). [cited by applicant]
Johnston, David, et al. “Whole house heat loss test method (Coheating).” Leeds Metropolitan University: Leeds, UK (2013). (Year: 2013). [cited by applicant]
Judkoff, R., et al. Buildings in a Test Tube: Validation of the Short-Term Energy Monitoring (STEM) Method (Preprint). No. NREL/ CP-550-29805. National Renewable Energy Lab.(NREL), Golden, CO (United States), 2001. (Yea… [cited by applicant]
NHBC Foundation, “Review of co-heating test Methodologies”, Nov. 2013, URL: www(dot)nhbcfoundation(dot)org/wp-content/ uploads/2016/05/NF54-Review-of-co-heating-test-methodologies(dot)pdf (Year: 2013). [cited by applicant]
Siviour, J. “Experimental thermal calibration of houses.” Rapid Thermal Calibration of Houses; Everett, R., Ed.; Technical Report ERG 55 (1981). (Year: 1981). [cited by applicant]
Modera, M. P. “Electric Co-Heating: A Method for Evaluating Seasonal Heating Efficiencies and Heat Loss Rates in Dwellings.” ( 1979). (Year: 1979). [cited by applicant]
Sonderegger, Robert C., Paul E. Condon, and Mark P. Madera. In-situ measurements of residential energy performance using electric co-heating. No. LBL-10117; CONF-800206-4. California Univ., Berkeley (USA). Lawrence Berk… [cited by applicant]
Stoecklein, A., et al. “The household energy end-use project: measurement approach and sample application of the New Zealand household energy model.” Conference Paper. No. 87. 2001. (Year: 2001). [cited by applicant]
Subbarao, K., et al. Short-Term Energy Monitoring (STEM): Application of the PSTAR method to a residence in Fredericksburg, Virginia. No. SERI/TR-254-3356. Solar Energy Research Inst., Golden, CO (USA), 1988. (Year: 198… [cited by applicant]
J. Galvao, S. Leitao, S. Malheiro and T. Gaio, “Model of decentralized energy on improving the efficiency in building services,” Proceedings of the 2011 3rd International Youth Conference on Energetics (IYCE), Leiria, P… [cited by applicant]
Cheng, Pok Lun, and Xiaofeng Li. “Air change rate measurements using tracer gas carbon dioxide from dry ice.” International Journal of Ventilation 13.3 (2014): 235-246. See the abstract, § 1, § 2.1 and §§ 2.3-2.5 ; and … [cited by applicant]
Chamie, G., et al. “Household ventilation and tuberculosis transmission in Kampala, Uganda.” The International journal of tuberculosis and lung disease 17.6 (2013): 764-770. See the abstract and the section “Methods” (Y… [cited by applicant]
ASTM, “Standard Test Method for Determining Air Change in a Single Zone by Means of a Tracer Gas Dilution”, Designation: E 741′-00 (Reapproved 2006)—see§§ 1,4-6, 8, 13-14 (Year: 2006). [cited by applicant]