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Techno-economic comparison of membrane distillation and MVC in a zero liquid discharge application
(2018)
Membrane distillation (MD) is a thermally driven membrane process for the separation of vapour from a liquid stream through a hydrophobic, microporous membrane. However, a commercial breakthrough on a large scale has not been achieved so far. Specific developments on MD technology are required to adapt the technology for applications in which its properties can potentially outshine state of the art technologies such as standard evaporation. In order to drive these developments in a focused manner, firstly it must be shown that MD can be economically attractive in comparison to state of the art systems. Thus, this work presents a technological design and economic analysis for AGMD and v-AGMD for application in a zero liquid discharge (ZLD) process chain and compares it to the costs of mechanical vapour compression (MVC) for the same application. The results show that MD can potentially be ~40% more cost effective than MVC for a system capacity of 100 m3/day feed water, and up to ~75% more cost effective if the MD is driven with free waste heat.
Membrane distillation (MD) is a thermal separation process which possesses a hydrophobic, microporous
membrane as vapor space. A high potential application for MD is the concentration of hypersaline brines, such as
e.g. reverse osmosis retentate or other saline effluents to be concentrated to a near saturation level with a Zero
Liquid Discharge process chain. In order to further commercialize MD for these target applications, adapted MD
module designs are required along with strategies for the mitigation of membrane wetting phenomena. This
work presents the experimental results of pilot operation with an adapted Air Gap Membrane Distillation
(AGMD) module for hypersaline brine concentration within a range of 0–240 g NaCl /kg solution. Key performance
indicators such as flux, GOR and thermal efficiency are analyzed. A new strategy for wetting mitigation
by active draining of the air gap channel by low pressure air blowing is tested and analyzed. Only small reductions
in flux and GOR of 1.2% and 4.1% respectively, are caused by air sparging into the air gap channel.
Wetting phenomena are significantly reduced by avoiding stagnant distillate in the air gap making the air blower
a seemingly worth- while additional system component.
It is considered necessary to implement advanced controllers such as model predictive control (MPC) to utilize the technical flexibility of a building polygeneration system to support the rapidly expanding renewable electricity grid. These can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints, amongst other features. One of the main issues identified in the literature regarding deploying these controllers is the lack of experimental demonstrations using standard components and communication protocols. In this original work, the economic-MPC-based optimal scheduling of a real-world heat pump-based building energy plant is demonstrated, and its performance is evaluated against two conventional controllers. The demonstration includes the steps to integrate an optimization-based supervisory controller into a typical building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms to solve a mixed integer quadratic problem. Technological benefits in terms of fewer constraint violations and a hardware-friendly operation with MPC were identified. Additionally, a strong dependency of the economic benefits on the type of load profile, system design and controller parameters was also identified. Future work for the quantification of these benefits, the application of machine learning algorithms, and the study of forecast deviations is also proposed.
With the need for automatic control based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear behaviour of the components but also certain unknown process dynamics like their internal control logic. At the Institute of Energy Systems Technology in Offenburg we have built a real-life microscale trigeneration plant and present in this paper a rational modelling procedure that satisfies the necessary characteristics for models to be applied in model predictive control for grid-reactive optimal scheduling of this complex energy system. These models are validated against experimental data and the efficacy of the methodology is discussed. Their application in the future for the optimal scheduling problem is also briefly motivated.
Am 1. Juli 2022 trafen sich im Rahmen des Abschlusskolloquiums des Projekts ACA-Modes rund 60 Teilnehmende aus Forschung, Lehre und Industrie zu einer internationalen Konferenz an der Hochschule Offenburg. Hier wurden die Projektergebnisse rund um die erfolgreiche Implementierung modellprädiktiver Regelstrategien vorgestellt, aktuelle Fragestellungen diskutiert und Entwicklungspfade hin zu einem netzdienlichen Betrieb von Energieverbundsystemen skizziert.
Microscale trigeneration systems are highly flexible in their operation and thus offer the technical possibility for peak load shifting in building demand side management. However to harness their potential modern control methods such as model predictive control must be implemented for their optimal scheduling. In literature the need for experimental investigation of microscale trigeneration systems to identify typical characteristics of the components and their interactions has been identified. On a real-life setup control specific information of the components is collected and lessons learnt during commissioning of the equipment is shared. The data is analysed to draw the vital characteristics of the system and it will be used for creating models of the components that can be utilised for optimal control.
The transformation of the building energy sector to a highly efficient, clean, decentralised and intelligent system requires innovative technologies like microscale trigeneration and thermally activated building structures (TABS) to pave the way ahead. The combination of such technologies however presents a scientific and engineering challenge. Scientific challenge in terms of developing optimal thermo-electric load management strategies based on overall energy system analysis and an engineering challenge in terms of implementing these strategies through process planning and control. Initial literature research has pointed out the need for a multiperspective analysis in a real life laboratory environment. To this effect an investigation is proposed wherein an analytical model of a microscale trigeneration system integrated with TABS will be developed and compared with a real life test-rig corresponding to building management systems. Data from the experimental analysis will be used to develop control algorithms using model predictive control for achieving the thermal comfort of occupants in the most energy efficient and grid reactive manner. The scope of this work encompasses adsorption cooling based microscale trigeneration systems and their deployment in residential and light commercial buildings.
The energy system of the future will transform from the current centralised fossil based to a decentralised, clean, highly efficient, and intelligent network. This transformation will require innovative technologies and ideas like trigeneration and the crowd energy concept to pave the way ahead. Even though trigeneration systems are extremely energy efficient and can play a vital role in the energy system, turning around their deployment is hindered by various barriers. These barriers are theoretically analysed in a multiperspective approach and the role decentralised trigeneration systems can play in the crowd energy concept is highlighted. It is derived from an initial literature research that a multiperspective (technological, energy-economic, and user) analysis is necessary for realising the potential of trigeneration systems in a decentralised grid. And to experimentally quantify these issues we are setting up a microscale trigeneration lab at our institute and the motivation for this lab is also briefly introduced.
Cooling towers or recoolers are one of the major consumers of electricity in a HVAC plant. The implementation and analysis of advanced control methods in a practical application and its comparison with conventional controllers is necessary to establish a framework for their feasibility especially in the field of decentralised energy systems. A standard industrial controller, a PID and a model based controller were developed and tested in an experimental set-up using market-ready components. The characteristics of these controllers such as settling time, control difference, and frequency of control actions are compared based on the monitoring data. Modern controllers demonstrated clear advantages in terms of energy savings and higher accuracy and a model based controller was easier to set-up than a PID.
Drawing off the technical flexibility of building polygeneration systems to support a rapidly expanding renewable electricity grid requires the application of advanced controllers like model predictive control (MPC) that can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints amongst other features. In this original work, an economic-MPC-based optimal scheduling of a real-world building energy system is demonstrated and its performance is evaluated against a conventional controller. The demonstration includes the steps to integrate an optimisation-based supervisory controller into a standard building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms for solving complex nonlinear mixed integer optimal control problems. With the MPC, quantitative benefits in terms of 6–12% demand-cost savings and qualitative benefits in terms of better controller adaptability and hardware-friendly operation are identified. Further research potential for improving the MPC framework in terms of field-level stability, minimising constraint violations, and inter-system communication for its deployment in a prosumer-network is also identified.
Optimisation based economic despatch of real-world complex energy systems demands reduced order and continuously differentiable component models that can represent their part-load behaviour and dynamic responses. A literature study of existing modelling methods and the necessary characteristics the models should meet for their successful application in model predictive control of a polygeneration system are presented. Deriving from that, a rational modelling procedure using engineering principles and assumptions to develop simplified component models is applied. The models are quantitatively and qualitatively evaluated against experimental data and their efficacy for application in a building automation and control architecture is established.
Energy consumption for cooling is growing dramatically. In the last years, electricity peak consumption grew significantly, switching from winter to summer in many EU countries. This is endangering the stability of electricity grids. This article outlines a comprehensive analysis of an office building performances in terms of energy consumption and thermal comfort (in accordance with static – ISO 7730:2005 – and adaptive thermal comfort criteria – EN 15251:2007 –) related to different cooling concepts in six different European climate zones. The work is based on a series of dynamic simulations carried out in the Trnsys 17 environment for a typical office building. The simulation study was accomplished for five cooling technologies: natural ventilation (NV), mechanical night ventilation (MV), fan-coils (FC), suspended ceiling panels (SCP), and concrete core conditioning (CCC) applied in Stockholm, Hamburg, Stuttgart, Milan, Rome, and Palermo. Under this premise, the authors propose a methodology for the evaluation of the cooling concepts taking into account both, thermal comfort and energy consumption.
Since 2003, most European countries established heat health warning systems to alert the population to heat load. Heat health warning systems are based on predicted meteorological conditions outdoors. But the majority of the European population spends a substantial amount of time indoors, and indoor thermal conditions can differ substantially from outdoor conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) extended the existing heat health warning system (HHWS) with a thermal building simulation model to consider heat load indoors. In this study, the thermal building simulation model is used to simulate a standardized building representing a modern nursing home, because elderly and sick people are most sensitive to heat stress. Different types of natural ventilation were simulated. Based on current and future test reference years, changes in the future heat load indoors were analyzed. Results show differences between the various ventilation options and the possibility to minimize the thermal heat stress during summer by using an appropriate ventilation method. Nighttime ventilation for indoor thermal comfort is most important. A fully opened window at nighttime and the 2-h ventilation in the morning and evening are more sufficient to avoid heat stress than a tilted window at nighttime and the 1-h ventilation in the morning and the evening. Especially the ventilation in the morning seems to be effective to keep the heat load indoors low. Comparing the results for the current and the future test reference years, an increase of heat stress on all ventilation types can be recognized.
Dieser technische Bericht stellt die Verwendung der Zuwendung und der erzielten Ergebnisse im Einzelnen dar. Die Gegenüberstellung mit den vorgegebenen Zielen erfolgt anhand der Beschreibung des Arbeitspakete. Die Verwendung der Zuwendung und Gegenüberstellung mit den vorgegebenen Zielen wird anhand der Arbeitspakete beschrieben, um den Abgleich zwischen Planung und durchgeführten Arbeiten unmittelbar darstellen zu können.
There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.
A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings. The thermophysiological load in the interior and exterior environments can be reduced in the medium and long term, through urban planning and building physics measures. In the short term, an increasingly vulnerable population must be effectively informed of an impending heat wave. Building simulation models can be favorably used to evaluate indoor heat stress. This study presents a generic simulation model, developed from monitoring data in urban multi-unit residential buildings during a summer period and using statistical methods. The model determines both the average room temperature and its deviations and, thus, consists of three sub-models: cool, average, and warm building types. The simulation model is based on the same mathematical algorithm, whereas each building type is described by a specific data set, concerning its building physical parameters and user behavior, respectively. The generic building model may be used in urban climate analyses with many individual buildings distributed across the city or in heat–health warning systems, with different building and user types distributed across a region. An urban climate analysis (with weather data from a database) may evaluate local differences in urban and indoor climate, whereas heat–health warning systems (driven by a weather forecast) obtain additional information on indoor heat stress and its expected deviations.
Thermisch angetriebene (Adsorptions-)Kältemaschinen können mit einem verhältnismäßig geringen elektrischen Energieaufwand bzw. mit einer hohen elektrischen Leistungszahl Kälte bereitstel-len. Wird die zum Antrieb erforderliche Wärme aus industrieller Abwärme bereitgestellt, ist diese Kältebereitstellung energetisch effizienter als die Kältebereitstellung über eine Kompressionskäl-temaschine. Wird die Wärme jedoch in Kraft-Wärme-Kopplung bereitgestellt, ist die primärenergetische Bewertung sowohl von mehreren Teilwirkungsgraden als auch den Primärenergiefaktoren für den eingesetzten Brennstoff und die erzeugte bzw. bezogene elektrische Energie abhängig. Eine umfangreiche Messkampagne im Sommer 2018 liefert unter realitätsnahen Randbedingungen in einer Labor umgebung detaillierte Energiekennzahlen für einen typischen Tagesgang des Kältebedarfs. Damit gelingt es, Teilenergiekennwerte für die Planungspraxis abzuleiten und das Gesamtsystem energetisch mit einer konventionellen Kompressionskältemaschine zu vergleichen.
The German Weather Service (DWD) releases a heat warning, when the weather forecast provides a warm, humid, sunny, and windless weather condition during the next days. The heat stress is calculated by the so called Klima-Michel model. If the apparent air temperature exceeds ca. 32°C / 38°C, there is a strong / extreme heat stress. The smallest forecast area is each administrative district. As people (and especially the vulnerable population) stay most of the time indoors, the heat health warning system was extended by the prediction of heat stress in typical rooms. Therewith it is feasible to forecast the heat stress using a combination of the outdoor and indoor heat stress. The prediction for the indoor heat stress is based on the same weather forecast like the Heat Health Warning Systems (HHWS).and calculates the heat stress by the PMV-model (predicted mean vote). Based on a sophisticated data analysis and simulation study, realistic but summer-critical living situations were defined and implemented in the building simulation program ESP-r. As the simulation runs especially for extreme weather conditions, a simplified building model cannot be used. Standardized input/output routines and an adaptive handover of start values provide for short run times for each forecast area. Good building designs and urban planning provide effective measures to reduce heat stress in cities. However, we have to also pay attention to the present building stock under climate change and a higher heat-wave risk. The extended German HHWS provide information for the emergency services to support the social assistants during heat waves.