Optimal metering plan for measurement and verification on a lighting case study

Ye, Xianming; Xia, Xiaohua

doi:10.1016/j.energy.2015.11.077

Cited by 18 publications

(21 citation statements)

References 25 publications

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“…Some simulations showing the effectiveness of the proposed controller to stabilize a FO system are also presented in the paper. The optimal maintenance planning (OMP) for sustainable energy efficiency lighting is proposed by Ye et al [54][55][56][57]. In addition, this optimal control model is ultimately solved by a model predictive control (MPC) approach under the control system framework.…”

Section: Cooperative Controlmentioning

confidence: 99%

Energy Informatics and Fractional Calculus

Liu

Zhang

Chen

2017

Volume 9: 13th ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications

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Energy informatics (EI) is relatively a blossoming and dynamic research area especially in today’s green manufacturing world. Using renewable energy and clean technology are the keys to a revitalization of the world manufacturing and job creation. Green manufacturing, which reduces resource use, waste and emissions and saving the energy, has become the priority for the manufacturers. Therefore, EI has come into a desirable solution. The fractional calculus (FC) is a mighty tool which can characterize the complex properties of the natural and social phenomena. In this paper, we have provided an overview on the current EI by describing current research topics and methods and then pointed out an outlook of how this new field might be evolved with FC in the coming future.

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Section: Cooperative Controlmentioning

confidence: 99%

Energy Informatics and Fractional Calculus

Liu

Zhang

Chen

2017

Volume 9: 13th ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications

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“…In addition, longitudinal CDM sampling designs for lighting retrofit projects are proposed in [48] when considering a linear lamp population decay pattern, and improved longitudinal CDM sampling designs are developed in [9] by incorporating nonlinear lamp population decay characteristics. In order to obtain the best metering and sampling plan for M&V of largescale lighting projects, three M&V metering cost minimisation approaches are provided in [46] by using spatial optimisation, longitudinal optimisation, and combined spatial and longitudinal optimisation strategies. These studies achieve cost savings for M&V projects by applying optimal sample sizes to handle the sampling uncertainty.…”

Section: Introductionmentioning

confidence: 99%

A cost-effective approach to handle measurement and verification uncertainties of energy savings

Olinga

Xia

2017

Energy

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Measurement and verification (M&V) function has been adopted in many energy efficiency (EE) programmes to quantify energy savings, identify new energy efficiency opportunities, improve EE programme design, and reduce EE programme performance risks. Budgetary constraints in EE programmes necessitate careful planning to minimise M&V cost whilst maintaining M&V accuracy. For this purpose, this study presents an M&V cost minimisation model to handle M&V sampling and modelling uncertainties costeffectively. In the proposed model, the objective function is the total M&V project cost, which consists of M&V sampling cost, modelling cost, and overhead cost. The required M&V accuracy in terms of the 90/10 criterion is formulated as the constraints of this optimisation problem. Optimal solutions to the proposed model specify the required baseline model accuracy and sample sizes to achieve the desired M&V accuracy. The proposed model is applied to design an optimal M&V sampling and modelling plan for a traffic light retrofit project. Results show that the optimal M&V plan reduces the sampling cost by 42% and the total M&V cost by 11% against the solutions obtained by partial optimisation.

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“…The first is population survival: establishing how many of the originally installed (retrofitted) units are still effective at a given point in time. This entails survey sampling and has been the focus of previous works [14][15][16][17][18][19][20]. The second factor is the average annual energy use per unit.…”

Section: Introductionmentioning

confidence: 99%

Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit

Carstens

Xia

Yadavalli

2017

Energy and Buildings

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Measurement and Verification (M&V) is often required for energy efficiency or demand side management projects in buildings, to demonstrate that savings were in fact achieved. For projects where sampling has to be done, these costs can be the most significant driver of the overall M&V project cost, especially in multi-year (longitudinal) projects. This study presents a method for calculating efficient combined metering and survey sample designs for longitudinal M&V of retrofit projects. In this paper, a building lighting retrofit case study is considered. A Dynamic Linear Model (DLM) with Bayesian forecasting is used. The Bayesian component of the model determines the sample size-weighted uncertainty bounds on multi-year metering studies, with results from previous years incorporated into the overall calculation to reduce forecast uncertainty. The DLM is compared to previous meter sampling methods, and an investigation into the robustness of efficient sampling plans is also conducted. The Mellin Transform Moment Calculation method is then used to combine the DLM with a Dynamic Generalised Linear Model describing the uncertainty in survey results for the longitudinal monitoring of lamp population decay. A genetic algorithm is employed to optimise the combined sampling design. Besides the reliable uncertainty quantification features of the method, results show a reduction in sampling costs of 40% for simple random sampling, and approximately 26.6% for stratified sampling, as compared to realistic benchmark methods.

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Optimal metering plan for measurement and verification on a lighting case study

Cited by 18 publications

References 25 publications

Energy Informatics and Fractional Calculus

Energy Informatics and Fractional Calculus

A cost-effective approach to handle measurement and verification uncertainties of energy savings

Efficient metering and surveying sampling designs in longitudinal Measurement and Verification for lighting retrofit

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