Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement

被引:359
作者
Longo, Stefano [1 ]
d'Antoni, Benedetto Mirko [2 ]
Bongards, Michael [3 ]
Chaparro, Antonio [4 ]
Cronrath, Andreas [3 ]
Fatone, Francesco [2 ]
Lema, Juan M. [1 ]
Mauricio-Iglesias, Miguel [1 ]
Soares, Ana [5 ]
Hospido, Almudena [1 ]
机构
[1] Univ Santiago de Compostela, Inst Technol, Dept Chem Engn, Santiago De Compostela 15782, Spain
[2] Univ Verona, Dept Biotechnol, Str Grazie 15, I-37134 Verona, Italy
[3] Cologne Univ Appl Sci, Res Grp GECO C, Steinmullerallee 1, D-51643 Gummersbach, Germany
[4] Wellness Smart Cities, Calle Charles Darwin, Seville 41092, Spain
[5] Cranfield Univ, Cranfield Water Sci Inst, Cranfield MK43 0AL, Beds, England
关键词
Wastewater treatment; Energy efficiency; Benchmarking; KPI; OLS; DEA; ENVIRONMENTAL PERFORMANCE; NUTRIENT REMOVAL; BENCHMARKING; EFFICIENCY; OPERATION; SCALE; DEA; INDICATORS; AERATION; REACTORS;
D O I
10.1016/j.apenergy.2016.07.043
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In response to strong growth in energy intensive wastewater treatment, public agencies and industry began to explore and implement measures to ensure achievement of the targets indicated in the 2020 Climate and Energy Package. However, in the absence of fundamental and globally recognized approach evaluating wastewater treatment plant (WWTP) energy performance, these policies could be economically wasteful. This paper gives an overview of the literature of WWTP energy-use performance and of the state of the art methods for energy benchmarking. The literature review revealed three main bench marking approaches: normalization, statistical techniques and programming techniques, and advantages and disadvantages were identified for each one. While these methods can be used for comparison, the diagnosis of the energy performance remains an unsolved issue. Besides, a large dataset of WWTP energy consumption data, together with the methods for synthesizing the information, are presented and discussed. It was found that no single key performance indicators (KPIs) used to characterize the energy performance could be used universally. The assessment of a large data sample provided some evidence about the effect of the plant size, dilution factor and flowrate. The technology choice, plant layout and country of location were seen as important elements that contributed to the large variability observed. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1251 / 1268
页数:18
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