In Europe, green hydrogen and biogas/green gas are considered important renewable energy carriers, besides renewable electricity and heat. Still, incentives proceed slowly, and the feasibility of local green gas is questioned. A supply chain of decentralised green hydrogen production from locally generated electricity (PV or wind) and decentralised green gas production from locally collected biomass and biological power-to-methane technology was analysed and compared to a green hydrogen scenario. We developed a novel method for assessing local options. Meeting the heating demand of households was constrained by the current EU law (RED II) to reduce greenhouse gas (GHG) emissions by 80% relative to fossil (natural) gas. Levelised cost of energy (LCOE) analyses at 80% GHG emission savings indicate that locally produced green gas (LCOE = 24.0 €ct kWh−1) is more attractive for individual citizens than locally produced green hydrogen (LCOE = 43.5 €ct kWh−1). In case higher GHG emission savings are desired, both LCOEs go up. Data indicate an apparent mismatch between heat demand in winter and PV electricity generation in summer. Besides, at the current state of technology, local onshore wind turbines have less GHG emissions than PV panels. Wind turbines may therefore have advantages over PV fields despite the various concerns in society. Our study confirms that biomass availability in a dedicated region is a challenge.
Lectorale redeboekje naar aanleiding van de intrede in het lectoraat Systeemintegratie in de energietransitie
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Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Membrane downstream processing (DSP) offers many opportunities to make process water purification, food supplement concentration and fatty acid hydrogenations more sustainable. Zuyd University of Applied Sciences (ZUYD)/Center of Expertise (CoE) CHemelot Innovation and Learning Labs (CHILL) and Utrecht University of Applied Sciences (HU)/ Utrecht Science Park Innovation Lab (I-Lab) will extend their current field labs with (reactor-)membrane set-ups to assist small- and medium-sized enterprises (SMEs) with implementation and dissemination of membrane DSP. Experimental and theoretical scale-up will quantify the membrane DSP contribution to the transition of the chemical industry to become climate neutral. The MEM4CHEM consortium spans the chemical and high tech equipment (HTE) sectors and covers all aspects related to hardware, i.e. reactors, membranes and gas/liquid streams, to implement sustainable innovations for chemical end users. The membrane DSP field labs will be disseminated to extend the research network. In MEM4CHEM the overarching question: How can we implement (reactor-)membrane DSP set-ups in chemical process innovation and disseminate their advantages? and research question: How far can energy/material savings be increased in chemical processes by the use of membrane DSP? will be answered by: i) extending field labs with modular plug-and-play (reactor-)membrane set-ups tailored for the chemical process industry. ii) establishing guidelines for further optimization/upscaling. iii) quantifying energy and material savings using membrane DSP. iv) speeding up industrial implementation of membrane DSP by dissemination, research network expansion, integration of membrane knowledge in education and establishing young professionals as knowledgeable ambassadors. SMEs will be supported by: a) dissemination of the advantages of membrane DSP high tech equipment to facilitate implementation. b) the possibility for SME end users to quantify energy- and material savings in accessible field labs.
Aerogel fibers consist of up to 99.9% of air which leads to outstanding insulation proper-ties for e.g. house construction. The simple use of aerogel fibers as wallpaper could lead to 25% energy savings. According to calculations of Advanced Manufacturing Office, energy savings of 1% saves 7500 million gallons of gasoline every year in the USA which equals, depending on the oil price, more than 18 billon USD. In this KIEM project, the cellulose purity needed to be able to spin cellulose into a fila-ment for aerogel production will be determined. Cellulose is the most abundant polymer on the planet. In principle, cellulose-based aerogels could replace petroleum-based and partly toxic polystyrene which is currently used for insulation purposes and which leads to toxic waste. The cellulosic starting material is generated via the “Beta process” as developed by a company called DSD. The “Beta process” offers an efficient way of generating ethanol from sugar beets. The by-product of that process contains cellulose, pectines and hemi-cellulose. To be able to use this mixture for wet spinning, this mixture needs to be puri-fied. Researchers and students from Zuyd University of Applied Sciences will, in collabora-tion with DSD, pursue the purification of the waste stream material in the labs of the Centre of Expertise CHILL. Next, the obtained cellulose grades will be processed as spinning dope in a wet spinning process on lab scale with up to 60 ml per batch at AMI-BM. The results will be used as feedback for the purification process. Several possible partners such as DSD, ACRRES (Application Center for Renewable Resources), Technoforce (extraction), Greenfields (fermentation) and VAM (washing in-stallations) show high interest for the up-scaling of the process and for the validation and implementation in the built environment, showing the feasibility a follow-up project.
