Modeling and forecasting energy demand

Kafazi, Ismail El; Bannari, Rachid; Abouabdellah, Abdellah

doi:10.1109/irsec.2016.7983974

Cited by 15 publications

(8 citation statements)

References 13 publications

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“…In this paper the main contributions are: (i) studying the impact of predicted demand on production; (ii) using the linear regression method to find the best results; (iii) the presentation of preliminary simulation results showing that demand has a positive and significant impact on production. This work is the result of the two previous studies [12], [13].…”

Section: Literature Reviewmentioning

confidence: 61%

“…The SPSS 20 statistical software which offers a choice of linear regression is used for the analysis. According to the previous studies of demand in [12] and energy production in [13], this represents a first attempt to specifically study the impact of predicted demand on energy production in Morocco. The first target of the present paper is the collecting data, analysis and selecting the methodology.…”

Section: Methodsmentioning

confidence: 99%

“…The forecast of energy demand had already studied by the ARIMA model in [12] to determine the needs of consumers in the future years. Therefore, the prediction equation can be formulated as follows: It is concluded that the model can be successfully used as a prediction tool for Moroccan's energy demand [12].…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, the prediction equation can be formulated as follows: It is concluded that the model can be successfully used as a prediction tool for Moroccan's energy demand [12]. The forecast of energy production had already studied in [13].…”

Section: Methodsmentioning

confidence: 99%

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The impact of predicted demand on energy production

Kafazi

Bannari

Aboutafail

2018

IOP Conf. Ser.: Earth Environ. Sci.

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Abstract. Energy is crucial for human life, a secure and accessible supply of power is essential for the sustainability of societies. Economic development and demographic progression increase energy demand, prompting countries to conduct research and studies on energy demand and production. Although, increasing in energy demand in the future requires a correct determination of the amount of energy supplied. Our article studies the impact of demand on energy production to find the relationship between the two latter and managing properly the production between the different energy sources. Historical data of demand and energy production since 2000 are used. The data are processed by the regression model to study the impact of demand on production. The obtained results indicate that demand has a positive and significant impact on production (high impact). Production is also increasing but at a slower pace. In this work, Morocco is considered as a case study. IntroductionThe energy demand should increase considerably in the coming years because of the increase of the population and the economic development (EIA, on 2007). Gradually as economics spend some concept of subsistence to that of industrial production or services, the lifestyles of numerous individuals will know of deep changes. The main increases of energy demand will be the fact of the developing countries where the percentage of the world consumption of energy should cross 46 to 58 percent between 2004 and 2030 (EIA, on 2007. It is planned that the energy consumption in developing countries will increase at an annual average rate of 3 percent between 2004 and 2020. In industrialized countries, where the state economies are mature and the population growth should be relatively weak, the energy demand will progress more slowly at the 0, 9 percent rate a year, although the starting point is much higher. The increase of the world demand for 2030 will be attributable in the electricity production and the fifth at the needs for transport, in particular in the form of petroleumbased fuels (EIA on 2007). The electrical energy can be an important element of any strategy wished to improve the environment provided that the consequences at the level of his production are mastered. Literature reviewThere are various types of conventional and no conventional sources of energy used for electrical power production. The system of solar and wind energy is one of the most important sources of energy. The exploitation of solar and wind energy became more and more necessary because of the nature modular and favorable to the environment [1]. The modeling of energy demand can follow either the approach with a variation of time or the approach with fixed coefficients. Nevertheless, he can be necessary to estimate the underlying statistical behavior of the parameters of energy demand before any significant inference. Z.

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Section: Literature Reviewmentioning

confidence: 61%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

The impact of predicted demand on energy production

Kafazi

Bannari

Aboutafail

2018

IOP Conf. Ser.: Earth Environ. Sci.

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“…Therefore, the forecast is required to consider them in the energy management optimization as mentioned in Fig.1. Forecasting methods for PV and WT can be used [11][12][13]. In our proposal model, we assume that the power of a renewable energy beyond the production scheduling is given and there is no operation cost for renewables.…”

Section: Optimization Modelmentioning

confidence: 99%

Power Scheduling for Renewable Energy Connected to the grid

Bannari

Lassioui

et al. 2018

E3S Web Conf.

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In this work, a scheduling strategy considering an Energy Storage System (ESS) is proposed to manage the distributed energy resources (DERs) optimally in a grid-connected hybrid PV-wind-microgrid. In order to increase the use of the renewable energy sources and ensure a full charge in the battery for the next day. The optimization problem of this study is addressed through a linear mathematical model, to minimize the cost of energy bought from the utility grid and maximize the income for selling electricity generated by hybrid PV-wind. The optimization model is tested by using a simulation of the model. The achieved results confirm the effectiveness of the proposed scheduling strategy.

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