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Herman Carstens
Centre for New Energy Systems, University of Pretoria, Pretoria 0002, South Africa

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Journal article
Published: 06 February 2018 in Energies
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Energy Measurement and Verification (M&V) aims to make inferences about the savings achieved in energy projects, given the data and other information at hand. Traditionally, a frequentist approach has been used to quantify these savings and their associated uncertainties. We demonstrate that the Bayesian paradigm is an intuitive, coherent, and powerful alternative framework within which M&V can be done. Its advantages and limitations are discussed, and two examples from the industry-standard International Performance Measurement and Verification Protocol (IPMVP) are solved using the framework. Bayesian analysis is shown to describe the problem more thoroughly and yield richer information and uncertainty quantification results than the standard methods while not sacrificing model simplicity. We also show that Bayesian methods can be more robust to outliers. Bayesian alternatives to standard M&V methods are listed, and examples from literature are cited.

ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Bayesian Energy Measurement and Verification Analysis. Energies 2018, 11, 380 .

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Bayesian Energy Measurement and Verification Analysis. Energies. 2018; 11 (2):380.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2018. "Bayesian Energy Measurement and Verification Analysis." Energies 11, no. 2: 380.

Journal article
Published: 01 February 2018 in Renewable and Sustainable Energy Reviews
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ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Measurement uncertainty in energy monitoring: Present state of the art. Renewable and Sustainable Energy Reviews 2018, 82, 2791 -2805.

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Measurement uncertainty in energy monitoring: Present state of the art. Renewable and Sustainable Energy Reviews. 2018; 82 ():2791-2805.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2018. "Measurement uncertainty in energy monitoring: Present state of the art." Renewable and Sustainable Energy Reviews 82, no. : 2791-2805.

Journal article
Published: 05 January 2018 in IEEE Access
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The probability distribution is often sought in engineering for the purpose of expanded uncertainty evaluation and reliability analysis. Although there are various methods available to approximate the distribution, one of the commonly used ones is the method based on statistical moments (or cumulants). Given these parameters, the corresponding solution can be reliably approximated using various algorithms. However, the commonly used algorithms are limited by only four moments and assumes that the corresponding distribution is unimodal. Therefore, this paper analyzes the performance of a relatively new and improved parametric distribution fitting technique known as the moment-constrained maximum entropy method, which overcomes these shortcomings. It is shown that the uncertainty (or reliability) estimation quality of the proposed method improves with the number of moments regardless of the distribution modality. Lastly, the paper uses case studies from a lighting retrofit project and an electromagnetic sensor design problem to substantiate the computational efficiency and numerical stability of the moment method in design optimization problems. The results and discussions presented in the paper could guide engineers in employing the maximum entropy method in a manner that best suits their respective systems.

ACS Style

Arvind Rajan; Ye Chow Kuang; Melanie Po-Leen Ooi; Serge N. Demidenko; Herman Carstens. Moment-Constrained Maximum Entropy Method for Expanded Uncertainty Evaluation. IEEE Access 2018, 6, 4072 -4082.

AMA Style

Arvind Rajan, Ye Chow Kuang, Melanie Po-Leen Ooi, Serge N. Demidenko, Herman Carstens. Moment-Constrained Maximum Entropy Method for Expanded Uncertainty Evaluation. IEEE Access. 2018; 6 (99):4072-4082.

Chicago/Turabian Style

Arvind Rajan; Ye Chow Kuang; Melanie Po-Leen Ooi; Serge N. Demidenko; Herman Carstens. 2018. "Moment-Constrained Maximum Entropy Method for Expanded Uncertainty Evaluation." IEEE Access 6, no. 99: 4072-4082.

Preprint
Published: 06 December 2017
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Energy Measurement and Verification (M&V) aims to make inferences about the savings achieved in energy projects, given the data and other information at hand. Traditionally, a frequentist approach has been used to quantify these savings and their associated uncertainties. We demonstrate that the Bayesian paradigm is an intuitive, coherent, and powerful alternative framework within which M&V can be done. Its advantages and limitations are discussed, and two examples from the industry-standard International Performance Measurement and Verification Protocol (IPMVP) are solved using the framework. Bayesian analysis is shown to describe the problem more thoroughly and yield richer information and uncertainty quantification than the standard methods while not sacrificing model simplicity. We also show that Bayesian methods can be more robust to outliers. Bayesian alternatives to standard M&V methods are listed, and examples from literature are cited.

ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Bayesian Energy Measurement and Verification Analysis. 2017, 1 .

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Bayesian Energy Measurement and Verification Analysis. . 2017; ():1.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2017. "Bayesian Energy Measurement and Verification Analysis." , no. : 1.

Journal article
Published: 01 November 2017 in Energy and Buildings
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ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit. Energy and Buildings 2017, 154, 430 -447.

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit. Energy and Buildings. 2017; 154 ():430-447.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2017. "Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit." Energy and Buildings 154, no. : 430-447.

Journal article
Published: 01 September 2017 in Energy and Buildings
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ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli; Arvind Rajan. Efficient longitudinal population survival survey sampling for the measurement and verification of lighting retrofit projects. Energy and Buildings 2017, 150, 163 -176.

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli, Arvind Rajan. Efficient longitudinal population survival survey sampling for the measurement and verification of lighting retrofit projects. Energy and Buildings. 2017; 150 ():163-176.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli; Arvind Rajan. 2017. "Efficient longitudinal population survival survey sampling for the measurement and verification of lighting retrofit projects." Energy and Buildings 150, no. : 163-176.

Journal article
Published: 01 February 2017 in Applied Energy
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ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Low-cost energy meter calibration method for measurement and verification. Applied Energy 2017, 188, 563 -575.

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Low-cost energy meter calibration method for measurement and verification. Applied Energy. 2017; 188 ():563-575.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2017. "Low-cost energy meter calibration method for measurement and verification." Applied Energy 188, no. : 563-575.

Preprint
Published: 13 October 2016
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Energy meters need to be calibrated for use in Measurement and Verification (M&V) projects. However, calibration can be prohibitively expensive and affect project feasibility negatively. This study presents a novel low-cost in-situ meter data calibration technique using a relatively low accuracy commercial energy meter as a calibrator. Calibration is achieved by combining two machine learning tools: the SIMulation EXtrapolation (SIMEX) Measurement Error Model, and Bayesian regression. The model is trained or calibrated on half-hourly building energy data for 24 hours. Measurements are then compared to the true values over the following months to verify the method. Results show that the hybrid method significantly improves parameter estimates and goodness of fit when compared to Ordinary Least Squares regression or standard SIMEX. This study also addresses the effect of mismeasurement in energy monitoring, and implements a powerful technique for mitigating the bias that arises because of it. Meters calibrated by the technique presented have satisfactory accuracy for most M&V applications, at a significantly lower cost.

ACS Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. Low-Cost Energy Meter Calibration Method for Measurement and Verification. 2016, 1 .

AMA Style

Herman Carstens, Xiaohua Xia, Sarma Yadavalli. Low-Cost Energy Meter Calibration Method for Measurement and Verification. . 2016; ():1.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Sarma Yadavalli. 2016. "Low-Cost Energy Meter Calibration Method for Measurement and Verification." , no. : 1.

Journal article
Published: 01 August 2014 in Applied Energy
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An improved model for reducing the cost of long-term monitoring in Clean Development Mechanism (CDM) lighting retrofit projects is proposed. Cost-effective longitudinal sampling designs use the minimum numbers of meters required to report yearly savings at the 90% confidence and 10% relative precision level for duration of the project (up to 10 years) as stipulated by the CDM. Improvements to the existing model include a new non-linear Compact Fluorescent Lamp population decay model based on the Polish Efficient Lighting Project, and a cumulative sampling function modified to weight samples exponentially by recency. An economic model altering the cost function to a net present value calculation is also incorporated. The search space for such sampling models is investigated and found to be discontinuous and stepped, requiring a heuristic for optimisation; in this case the Genetic Algorithm was used. Assuming an exponential smoothing rate of 0.25, an inflation rate of 6.44%, and an interest rate of 10%, results show that sampling should be more evenly distributed over the study duration than is currently considered optimal, and that the proposed improvements in model accuracy increase monitoring costs by 21.4% in present value terms.Centre for New Energy Systems and the National Hub for the Postgraduate Programme in Energy Efficiency and Demand Side Management at the University of Pretoria.http://www.elsevier.com/locate/apenergyhb201

ACS Style

Herman Carstens; Xiaohua Xia; Xianming Ye. Improvements to longitudinal Clean Development Mechanism sampling designs for lighting retrofit projects. Applied Energy 2014, 126, 256 -265.

AMA Style

Herman Carstens, Xiaohua Xia, Xianming Ye. Improvements to longitudinal Clean Development Mechanism sampling designs for lighting retrofit projects. Applied Energy. 2014; 126 ():256-265.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Xianming Ye. 2014. "Improvements to longitudinal Clean Development Mechanism sampling designs for lighting retrofit projects." Applied Energy 126, no. : 256-265.

Conference paper
Published: 01 September 2013 in 2013 Africon
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A model derived from existing biological logistic population growth equations is proposed for modelling the decay of Compact Fluorescent Lamp populations over time. Its adequacy is analysed by implementing a least-squares system identification approach using accepted benchmark data. The model is found to be as accurate as the existing CFL decay model, but wider in its potential applications. Such a model contributes to the theoretical foundation necessary for further research into tracking the efficacy of Energy Efficiency programmes.

ACS Style

Herman Carstens; Xiaohua Xia; Jiangfeng Zhang; Xianming Ye. Characterising Compact Fluorescent Lamp population decay. 2013 Africon 2013, 1 -5.

AMA Style

Herman Carstens, Xiaohua Xia, Jiangfeng Zhang, Xianming Ye. Characterising Compact Fluorescent Lamp population decay. 2013 Africon. 2013; ():1-5.

Chicago/Turabian Style

Herman Carstens; Xiaohua Xia; Jiangfeng Zhang; Xianming Ye. 2013. "Characterising Compact Fluorescent Lamp population decay." 2013 Africon , no. : 1-5.