Performance analyses of statistical approaches for modeling electricity consumption of a commercial building in France

Atalay, Sevcan Demir; Çalış, Gülben; Kuş, Gözde; Kuru, Merve

doi:10.1016/j.enbuild.2019.04.035

Cited by 20 publications

(7 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ARMAX model has been utilized to estimate electricity demand in buildings (June 2015 and April 2016) in Paris, France, with the agenda that building energy consumption is an important component of national energy consumption. Also, authors claim that developing accurate models can lead to an easier solution to energy shortages [35]. ARMAX formulae with AI calculations were used for demand of electricity prediction.…”

Section: Single-variate Time Series (Svts) Methodsmentioning

confidence: 99%

A review on short‐term load forecasting models for micro‐grid application

Kondaiah

Saravanan

Sanjeevikumar

et al. 2022

The Journal of Engineering

View full text Add to dashboard Cite

Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role throughout the operation of the conventional power system. The precise modelling and complex analyses of STLF have become more significant in advanced microgrid (MG) applications. Several models are proposed for STLF and tested successfully in the literature. The selection of a forecasting method is mostly based on data availability and its objectives. This article presents a survey of the latest analytical and approximation techniques reported in the literature to model STLF in an MG environment. This article mainly focusses on the review on important methods applied to forecast renewable energy availability, energy demand, and price and load demand. Different models, their main objectives, methodology, error percentage, and so forth, are critically reviewed and analysed. For quick reference, we have highlighted the important points in the form tables. The researchers can quickly identify and frame their research problem related to the LF area by reading this review paper.

show abstract

Section: Single-variate Time Series (Svts) Methodsmentioning

confidence: 99%

A review on short‐term load forecasting models for micro‐grid application

Kondaiah

Saravanan

Sanjeevikumar

et al. 2022

The Journal of Engineering

View full text Add to dashboard Cite

show abstract

“…Obviously, it can be found that problem (23) is a nonlinear programming problem with an equality constraint. It is difficult to solve such problem (23) exactly because of the complexity of its objective function and constraint. Some scholars have constructed similar optimization problems to search for the optimal parameters.…”

Section: Constructing Optimization Problem For Searching the Optimal mentioning

confidence: 99%

“…From the expression of problem (23), it is a nonlinear programming problem with constraints. Obviously, it can be solved by employing a heuristic search algorithm.…”

Section: Searching Optimal Nonlinear Parameter By the Whale Optimizatmentioning

confidence: 99%

“…In order to utilize the IGGM model to forecast the future, the key issue is to build an IGGM model with optimal parameters. Firstly, the nonlinear parameter µ can be sought out by solving the optimization problem (23). Then, the linear parameters a, b, and c can be estimated by the LS method after determining the coefficient µ.…”

Section: Computational Procedures Of the Grey Modelmentioning

confidence: 99%

“…Li et al [22] proposed an optimized GM(1,1) model based on hybridization of background-value optimization and weighted weakening buffer operator. Atalay et al [23] applied multiple linear regression, time series and grey models to estimate the electricity consumption of the heating, cooling, air conditioning system in a commercial building located in France. Rahman et al [24] employed an improved GM(1,1) model to analyze and forecast the key performance indicators of a medical institution.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Forecasting Japan’s Solar Energy Consumption Using a Novel Incomplete Gamma Grey Model

Zhang

She

2019

Sustainability

View full text Add to dashboard Cite

Energy consumption is an essential basis for formulating energy policy and programming, especially in the transition of energy consumption structure in a country. Correct prediction of energy consumption can provide effective reference data for decision-makers and planners to achieve sustainable energy development. Grey prediction method is one of the most effective approaches to handle the problem with a small amount of historical data. However, there is still room to improve the prediction performance and enlarge the application fields of the traditional grey model. Nonlinear grey action quantity can effectively improve the performance of the grey prediction model. Therefore, this paper proposes a novel incomplete gamma grey model (IGGM) with a nonlinear grey input over time. The grey input of the IGGM model is a revised incomplete gamma function of time in which the nonlinear coefficient determines the performance of the IGGM model. The WOA algorithm is employed to seek for the optimal incomplete coefficient of the IGGM model. Then, the validations of IGGM are performed on four real-world datasets, and the results exhibit that the IGGM model has more advantages than the other state-of-the-art grey models. Finally, the IGGM model is applied to forecast Japan’s solar energy consumption in the next three years.

show abstract

Energy consumption dynamic prediction for HVAC systems based on feature clustering deconstruction and model training adaptation

Liu,

Huang

et al. 2024

Build. Simul.

View full text Add to dashboard Cite

Performance analyses of statistical approaches for modeling electricity consumption of a commercial building in France

Cited by 20 publications

References 41 publications

A review on short‐term load forecasting models for micro‐grid application

A review on short‐term load forecasting models for micro‐grid application

Forecasting Japan’s Solar Energy Consumption Using a Novel Incomplete Gamma Grey Model

Energy consumption dynamic prediction for HVAC systems based on feature clustering deconstruction and model training adaptation

Contact Info

Product

Resources

About