A bottom-up methodology for long term electricity consumption forecasting of an industrial sector - Application to pulp and paper sector in Brazil

被引:28
|
作者
Silva, Felipe L. C. [1 ,2 ]
Souza, Reinaldo C. [3 ]
Cyrino Oliveira, Fernando L. [3 ]
Lourenco, Plutarcho M. [4 ]
Calili, Rodrigo F. [5 ]
机构
[1] Pontifical Catholic Univ Rio de Janeiro PUC Rio, Elect Engn Dept, BR-22453900 Rio De Janeiro, RJ, Brazil
[2] Univ Fed Rural Rio de Janeiro, Math Dept, BR 465,KM 7, BR-23897000 Seropedica, RJ, Brazil
[3] Pontifical Catholic Univ Rio de Janeiro PUC Rio, Ind Engn Dept, BR-22453900 Rio De Janeiro, RJ, Brazil
[4] Pontifical Catholic Univ Rio de Janeiro PUC Rio, Inst Energy, BR-22453900 Rio De Janeiro, RJ, Brazil
[5] Pontifical Catholic Univ Rio de Janeiro PUC Rio, Posgrad Programme Metrol, BR-22453900 Rio De Janeiro, RJ, Brazil
关键词
Bottom-up approach; Hierarchical structure; Energy efficiency measures; Long term forecasting; ENERGY EFFICIENCY IMPROVEMENT; CHINA CEMENT INDUSTRY; CO2; EMISSIONS; RENEWABLE ENERGY; TOP-DOWN; GENERATE ALTERNATIVES; MODEL; DEMAND; TECHNOLOGY; POTENTIALS;
D O I
10.1016/j.energy.2017.12.078
中图分类号
O414.1 [热力学];
学科分类号
摘要
Long term annual electricity consumption forecasting is very important for country's energy planning. These forecasts are influenced by several factors (political, technological, social, environmental and economic), and brings with itself a high uncertainty degree in its results and difficulties in the evaluation of such factors over them. A methodology that eases to take into account these factors aiming improve the results and help understanding the electricity consumption annual trajectory till the forecast horizon is, therefore, very much useful and desired. So, we propose a modelling structure Using the bottom-up approach to cope with these matters and to evaluate the trajectory of long term annual electricity consumption of a sector of the Brazilian industry up to 2050 considering energy efficiency (EE) scenarios. It is important to emphasize that Brazil is a developing country, and to build a bottom-up approach was a challenge, mainly due to the fact that this model is data intensive. In particular, this modelling was applied in the pulp and paper sector. The main goal was to consider technological diffusion scenarios in EE measures, and show the energy savings achieved. The results point an energy savings in the order of 25% when an actual scenario is considered. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1107 / 1118
页数:12
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