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A Novel Stochastic-Programming-Based Energy Management System to Promote Self-Consumption in Industrial Processes

一个新奇 Stochastic-Programming-Based 精力管理系统将在工业过程支持自我消费

作     者:Barrientos, Jorge David Lopez, Jose Valencia, Felipe 

作者机构:Univ Antioquia UDEA Fac Engn SISTEMIC Calle 70 52-21 Medellin 1226 Colombia Univ Chile Fac Math & Phys Sci Energy Ctr Santiago 8370451 Chile 

出 版 物:《ENERGIES》 (能源)

年 卷 期:2018年第11卷第2期

页      面:441页

核心收录:

学科分类:0820[工学-石油与天然气工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基  金:FONDAP/CONiCYT project Solar Energy Research Center  SERC-Chile 

主  题:non-conventional energy sources energy management system stochastic programming industrial processes 

摘      要:The introduction of non-conventional energy sources (NCES) to industrial processes is a viable alternative to reducing the energy consumed from the grid. However, a robust coordination of the local energy resources with the power imported from the distribution grid is still an open issue, especially in countries that do not allow selling energy surpluses to the main grid. In this paper, we propose a stochastic-programming-based energy management system (EMS) focused on self-consumption that provides robustness to both sudden NCES or load variations, while preventing power injection to the main grid. The approach is based on a finite number of scenarios that combines a deterministic structure based on spectral analysis and a stochastic model that represents variability. The parameters to generate these scenarios are updated when new information arrives. We tested the proposed approach with data from a copper extraction mining process. It was compared to a traditional EMS with perfect prediction, i.e., a best case scenario. Test results show that the proposed EMS is comparable to the EMS with perfect prediction in terms of energy imported from the grid (slightly higher), but with less power changes in the distribution side and enhanced dynamic response to transients of wind power and load. This improvement is achieved with a non-significant computational time overload.

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