Online short-term forecast of greenhouse heat load using a weather forecast service

Abstract

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Regulation Flexibility Assessment and Optimal Aggregation Strategy of Greenhouse Loads in Modern Agricultural Parks

“…Indoor and outdoor temperatures, outdoor water vapor density, soil temperature, and outdoor wind speed are assumed to be constant during the regulation time period. Based on ( 17)-( 20), the switching time of the HL from xin1 to xin2 can be calculated using (35)…”

Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods

“…[29] gives a method to circumvent the problem faced by the ordinary least squares estimator in the presence of co-linear features. The model used here is the same as that given in (5), but in addition to the regular assumption on ε, the model also considers a prior Gaussian distribution p(q) on the parameters q and maximizes the logarithm of the likelihood L ðqÞ ¼ pðqjyÞ using Bayes rules, i.e.,:…”

“…Here, with the same case study as that of [2], the best error was shown to be 11.5%, albeit for an extended test period including the autumn months. In more recent work [5], a customized recursive least square forecaster was used for forecasting the short term greenhouse heat load in a district heating system; the model was shown to be a simple, yet reliable forecaster. Polynomial regression models were shown to supplement artificial neural networks in Ref.…”

Flexible energy management in an uncertain greenhouse

“…There is also research relating to the role of errors within the weather forecast on the uncertainty in the prediction of greenhouse heating demand (Sigrimis et al, 2001;Vogler-Finck et al, 2017). While other studies have assessed the impact of forecast error on the performance of greenhouses that are controlled using an optimal controller (Doeswijk et al, 2006;Tap et al, 1996).…”

“…The potential impact of weather forecast errors on greenhouse prediction uncertainty has been partially addressed. Vogler-Finck et al, (2017) use a simple linear model and a recursive least squares approach to predict the heat demand of a Danish greenhouses using short term weather forecasts. Vogler-Finck concluded that the inclusion of real weather forecasts significantly improved the online prediction of heat load over using simplified weather forecasts.…”