Academic literature on the topic 'Residential demand modelling'

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Journal articles on the topic "Residential demand modelling"

1

Dilaver, Zafer, and Lester C. Hunt. "Modelling and forecasting Turkish residential electricity demand." Energy Policy 39, no. 6 (2011): 3117–27. http://dx.doi.org/10.1016/j.enpol.2011.02.059.

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2

Assimakopoulos, V. "Residential energy demand modelling in developing regions." Energy Economics 14, no. 1 (1992): 57–63. http://dx.doi.org/10.1016/0140-9883(92)90025-9.

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3

Worthington, Andrew C., and Mark Hoffman. "AN EMPIRICAL SURVEY OF RESIDENTIAL WATER DEMAND MODELLING." Journal of Economic Surveys 22, no. 5 (2008): 842–71. http://dx.doi.org/10.1111/j.1467-6419.2008.00551.x.

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4

Atalla, Tarek N., and Lester C. Hunt. "Modelling residential electricity demand in the GCC countries." Energy Economics 59 (September 2016): 149–58. http://dx.doi.org/10.1016/j.eneco.2016.07.027.

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5

Alcocer Yamanaka, Víctor Hugo, and Velitchko G. Tzatchkov. "Neyman-Scott-based water distribution network modelling." Ingeniería e Investigación 32, no. 3 (2012): 32–36. http://dx.doi.org/10.15446/ing.investig.v32n3.35937.

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Residential water demand is one of the most difficult parameters to determine when modelling drinking water distribution networks. It has been proven to be a stochastic process which can be characterised as a series of rectangular pulses having set intensity, duration and frequency. Such parameters can be determined using stochastic models such as the Neyman-Scott rectangular pulse model (NSRPM). NSRPM is based on resolving a non-linear optimisation problem involving theoretical moments of the synthetic demand series (equiprobable) and of the observed moments (field measurements) statistically
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6

Megri, Ahmed Cherif, and Yao Yu. "Study of residential underfloor air distribution (UFAD) systems using a new modelling approach." Indoor and Built Environment 26, no. 1 (2016): 5–20. http://dx.doi.org/10.1177/1420326x15597544.

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Although single/multi-zone thermal models have their own advantages, like simple and fast computations of building energy demand, the accuracy of these models is problematic. The assumption of a uniform room temperature reduces the accuracy of the final energy demand results. In fact, the single/multi-zone thermal models are not able to predict indoor thermal behaviours or building energy demands accurately, if a non-uniform environment in a room or building is created by a single or multiple heating, ventilation, and air conditioning (HVAC) systems, i.e. an underfloor air distribution (UFAD)
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7

Starr, Claudia, Thomas G. Cowing, and David L. McFadden. "Microeconomic Modelling and Policy Analysis: Studies in Residential Energy Demand." Journal of the Operational Research Society 37, no. 8 (1986): 823. http://dx.doi.org/10.2307/2581969.

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8

Chatterjee, Samprit, Thomas G. Cowing, Daniel L. McFadden, and Paul C. Stern. "Macroeconomic Modelling and Policy Analysis: Studies in Residential Energy Demand." Journal of Business & Economic Statistics 3, no. 4 (1985): 413. http://dx.doi.org/10.2307/1391737.

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9

Starr, Claudia. "Microeconomic Modelling and Policy Analysis: Studies in Residential Energy Demand." Journal of the Operational Research Society 37, no. 8 (1986): 823–24. http://dx.doi.org/10.1057/jors.1986.145.

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10

Ben Zaied, Younes, and Marie Estelle Binet. "Modelling seasonality in residential water demand: the case of Tunisia." Applied Economics 47, no. 19 (2015): 1983–96. http://dx.doi.org/10.1080/00036846.2014.1002896.

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