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Cooling load forecasting-based predictive optimisation for chiller plants
Extensive electric power is required to maintain indoor thermal comfort using heating, ventilation and air conditioning (HVAC) systems, of which, water-cooled chiller plants consume more than 50% of the total electric power. To improve energy efficiency, supervisory optimisation control can be adopted. The controlled variables are usually optimised according to instant building cooling load and ambient wet bulb air temperature at regular time intervals. In this way, the energy efficiency of chiller plants has been improved. However, with an inherent assumption that the instant building cooling load and ambient wet bulb temperature remain constant in the coming time interval, the energy efficiency potential has not been fully realised, especially when cooling loads vary suddenly and extremely. To solve this problem, a cooling load forecasting-based predictive optimisation method is proposed. Instead of minimising the instant system power according to the instant building cooling load and ambient wet bulb temperature, the controlled variables are derived to minimise the sum of the instant system power and one-time-step-ahead future system power according to both instant and forecasted future building cooling loads. With this method, the energy efficiency potential of a chiller plant can be further improved without shortening the operation time interval. 80% redundant energy consumption has been reduced for the sample chiller plant; energy can be saved for chiller plants that work for years. The evaluation on the effect of cooling load forecasting accuracy turns out that the more accurate the forecasts are, the more redundant energy consumption can be reduced
Solar cooling: a case study
Throughout the years various methods for heat prevention and indoor temperatures control in
the summer have been used. The alternative cooling strategies are based on various passive and low
energy cooling technologies for protection of the buildings via design measures or special components
to moderate the thermal gains, or to reject the excess heat to the ambient environment. All these
techniques aim to reduce summer cooling loads and electricity demand for air conditioning. During
the summer the demand for electricity increases because of the extensive use of heating ventilation air
conditioning (HVAC) systems, which increase the peak electric load, causing major problems in the
electric supply. The energy shortage is worse during ‘dry’ years because of the inability of the
hydroelectric power stations to function and cover part of the peak load.
The use of solar energy to drive cooling cycles for space conditioning of most buildings is an
attractive concept, since the cooling load coincides generally with solar energy availability and
therefore cooling requirements of a building are roughly in phase with the solar incidence. Solar
cooling systems have the advantage of using absolutely harmless working fluids such as water, or
solutions of certain salts. They are energy efficient and environmentally safe.
The purpose of this paper is to describe a Solar Cooling System to be installed on the roof of a
building in Rome, the headquarters of the State Monopoly. The medium size power plant is composed
of the following components:
− Solar Collectors;
− Thermal Storage Tank;
− Absorption Chiller;
The plant design is based on a dynamic simulation in TRNSYS, a dynamic simulation tool used
by engineers all over the world to make energy calculations in a transient state
High resolution performance analysis of micro-trigeneration in an energy-efficient residential building
Trigeneration has long been proposed as a means to improve energy-efficiency for large and medium sized buildings. To curb increasing energy demand in the residential sector, researchers are now focusing their attention on adapting trigeneration to residential buildings. Literature is full of examples pertaining to the performance of trigeneration in large and medium sized commercial buildings, however little is known on the performance of micro-trigeneration inside residential buildings, particularly under a range of operating conditions. To understand the influence that parameters such as changes in thermal and electrical loading or different plant configurations have on the performance of micro-trigeneration, this research makes use of a detailed model of a Maltese apartment building, and associated micro-trigeneration system. The performance of the model is simulated using a whole building simulation tool run at high-resolution minute time frequency over a number of different operating conditions and scenarios. Each scenario was then assessed on the basis of the system's energetic, environmental and economic performance. The results show that, compared to separate generation the use of a residential micro-trigeneration system reduces primary energy consumption by about 40%, but also that the system's financial performance is highly susceptible to the operating conditions
The Importance of Monitoring Renewable Energy Plants: Three Case Histories
Many renewable energy plants are put into operation without providing a monitoring
system to evaluate their performance over time. Then if is often difficult to realise the bad working of
the system and the loss of efficiency results in an economic loss. In the Author\u2019s experience as
designer or supervisor of such plants, he came across various examples that pointed out the
advantages of having installed a monitoring system, of course with a careful data analysis. Problems
sometimes arose from poorer performance than anticipated in the design, but more often from
inefficient plant operations after some months or years from the starting.
Three quite different examples, derived from the Author\u2019s direct experience, are reported to
illustrate how real performance can be lower than designed due respectively:
1. To bad settings of the parameters;
2. To a hurried commissioning that did not reveal the mistakes in the design of the plant;
3. To a failure of a single component over time
Technical Proposal for FASER: ForwArd Search ExpeRiment at the LHC
FASER is a proposed small and inexpensive experiment designed to search for
light, weakly-interacting particles during Run 3 of the LHC from 2021-23. Such
particles may be produced in large numbers along the beam collision axis,
travel for hundreds of meters without interacting, and then decay to standard
model particles. To search for such events, FASER will be located 480 m
downstream of the ATLAS IP in the unused service tunnel TI12 and be sensitive
to particles that decay in a cylindrical volume with radius R=10 cm and length
L=1.5 m. FASER will complement the LHC's existing physics program, extending
its discovery potential to a host of new, light particles, with potentially
far-reaching implications for particle physics and cosmology.
This document describes the technical details of the FASER detector
components: the magnets, the tracker, the scintillator system, and the
calorimeter, as well as the trigger and readout system. The preparatory work
that is needed to install and operate the detector, including civil
engineering, transport, and integration with various services is also
presented. The information presented includes preliminary cost estimates for
the detector components and the infrastructure work, as well as a timeline for
the design, construction, and installation of the experiment.Comment: 82 pages, 62 figures; submitted to the CERN LHCC on 7 November 201
Advanced energy management strategies for HVAC systems in smart buildings
The efficacy of the energy management systems at dealing with energy consumption in buildings has been a topic with a growing interest in recent years due to the ever-increasing global energy demand and the large percentage of energy being currently used by buildings. The scale of this sector has attracted research effort with the objective of uncovering potential improvement avenues and materializing them with the help of recent technological advances that could be exploited to lower the energetic footprint of buildings. Specifically, in the area of heating, ventilating and air conditioning installations, the availability of large amounts of historical data in building management software suites makes possible the study of how resource-efficient these systems really are when entrusted with ensuring occupant comfort. Actually, recent reports have shown that there is a gap between the ideal operating performance and the performance achieved in practice.
Accordingly, this thesis considers the research of novel energy management strategies for heating, ventilating and air conditioning installations in buildings, aimed at narrowing the performance gap by employing data-driven methods to increase their context awareness, allowing management systems to steer the operation towards higher efficiency. This includes the advancement of modeling methodologies capable of extracting actionable knowledge from historical building behavior databases, through load forecasting and equipment operational performance estimation supporting the identification of a building’s context and energetic needs, and the development of a generalizable multi-objective optimization strategy aimed at meeting these needs while minimizing the consumption of energy.
The experimental results obtained from the implementation of the developed methodologies show a significant potential for increasing energy efficiency of heating, ventilating and air conditioning systems while being sufficiently generic to support their usage in different installations having diverse equipment. In conclusion, a complete analysis and actuation framework was developed, implemented and validated by means of an experimental database acquired from a pilot plant during the research period of this thesis. The obtained results demonstrate the efficacy of the proposed standalone contributions, and as a whole represent a suitable solution for helping to increase the performance of heating, ventilating and air conditioning installations without affecting the comfort of their occupants.L’eficà cia dels sistemes de gestió d’energia per afrontar el consum d’energia en edificis és un tema que ha rebut un interès en augment durant els darrers anys a causa de la creixent demanda global d’energia i del gran percentatge d’energia que n’utilitzen actualment els edificis. L’escala d’aquest sector ha atret l'atenció de nombrosa investigació amb l’objectiu de descobrir possibles vies de millora i materialitzar-les amb l’ajuda de recents avenços tecnològics que es podrien aprofitar per disminuir les necessitats energètiques dels edificis. Concretament, en l’à rea d’instal·lacions de calefacció, ventilació i climatització, la disponibilitat de grans bases de dades històriques als sistemes de gestió d’edificis fa possible l’estudi de com d'eficients són realment aquests sistemes quan s’encarreguen d'assegurar el confort dels seus ocupants. En realitat, informes recents indiquen que hi ha una diferència entre el rendiment operatiu ideal i el rendiment generalment assolit a la prà ctica. En conseqüència, aquesta tesi considera la investigació de noves estratègies de gestió de l’energia per a instal·lacions de calefacció, ventilació i climatització en edificis, destinades a reduir la diferència de rendiment mitjançant l’ús de mètodes basats en dades per tal d'augmentar el seu coneixement contextual, permetent als sistemes de gestió dirigir l’operació cap a zones de treball amb un rendiment superior. Això inclou tant l’avanç de metodologies de modelat capaces d’extreure coneixement de bases de dades de comportaments històrics d’edificis a través de la previsió de cà rregues de consum i l’estimació del rendiment operatiu dels equips que recolzin la identificació del context operatiu i de les necessitats energètiques d’un edifici, tant com del desenvolupament d’una estratègia d’optimització multi-objectiu generalitzable per tal de minimitzar el consum d’energia mentre es satisfan aquestes necessitats energètiques. Els resultats experimentals obtinguts a partir de la implementació de les metodologies desenvolupades mostren un potencial important per augmentar l'eficiència energètica dels sistemes de climatització, mentre que són prou genèrics com per permetre el seu ús en diferents instal·lacions i suportant equips diversos. En conclusió, durant aquesta tesi es va desenvolupar, implementar i validar un marc d’anà lisi i actuació complet mitjançant una base de dades experimental adquirida en una planta pilot durant el perÃode d’investigació de la tesi. Els resultats obtinguts demostren l’eficà cia de les contribucions de manera individual i, en conjunt, representen una solució idònia per ajudar a augmentar el rendiment de les instal·lacions de climatització sense afectar el confort dels seus ocupant
Advanced energy management strategies for HVAC systems in smart buildings
The efficacy of the energy management systems at dealing with energy consumption in buildings has been a topic with a growing interest in recent years due to the ever-increasing global energy demand and the large percentage of energy being currently used by buildings. The scale of this sector has attracted research effort with the objective of uncovering potential improvement avenues and materializing them with the help of recent technological advances that could be exploited to lower the energetic footprint of buildings. Specifically, in the area of heating, ventilating and air conditioning installations, the availability of large amounts of historical data in building management software suites makes possible the study of how resource-efficient these systems really are when entrusted with ensuring occupant comfort. Actually, recent reports have shown that there is a gap between the ideal operating performance and the performance achieved in practice.
Accordingly, this thesis considers the research of novel energy management strategies for heating, ventilating and air conditioning installations in buildings, aimed at narrowing the performance gap by employing data-driven methods to increase their context awareness, allowing management systems to steer the operation towards higher efficiency. This includes the advancement of modeling methodologies capable of extracting actionable knowledge from historical building behavior databases, through load forecasting and equipment operational performance estimation supporting the identification of a building’s context and energetic needs, and the development of a generalizable multi-objective optimization strategy aimed at meeting these needs while minimizing the consumption of energy.
The experimental results obtained from the implementation of the developed methodologies show a significant potential for increasing energy efficiency of heating, ventilating and air conditioning systems while being sufficiently generic to support their usage in different installations having diverse equipment. In conclusion, a complete analysis and actuation framework was developed, implemented and validated by means of an experimental database acquired from a pilot plant during the research period of this thesis. The obtained results demonstrate the efficacy of the proposed standalone contributions, and as a whole represent a suitable solution for helping to increase the performance of heating, ventilating and air conditioning installations without affecting the comfort of their occupants.L’eficà cia dels sistemes de gestió d’energia per afrontar el consum d’energia en edificis és un tema que ha rebut un interès en augment durant els darrers anys a causa de la creixent demanda global d’energia i del gran percentatge d’energia que n’utilitzen actualment els edificis. L’escala d’aquest sector ha atret l'atenció de nombrosa investigació amb l’objectiu de descobrir possibles vies de millora i materialitzar-les amb l’ajuda de recents avenços tecnològics que es podrien aprofitar per disminuir les necessitats energètiques dels edificis. Concretament, en l’à rea d’instal·lacions de calefacció, ventilació i climatització, la disponibilitat de grans bases de dades històriques als sistemes de gestió d’edificis fa possible l’estudi de com d'eficients són realment aquests sistemes quan s’encarreguen d'assegurar el confort dels seus ocupants. En realitat, informes recents indiquen que hi ha una diferència entre el rendiment operatiu ideal i el rendiment generalment assolit a la prà ctica. En conseqüència, aquesta tesi considera la investigació de noves estratègies de gestió de l’energia per a instal·lacions de calefacció, ventilació i climatització en edificis, destinades a reduir la diferència de rendiment mitjançant l’ús de mètodes basats en dades per tal d'augmentar el seu coneixement contextual, permetent als sistemes de gestió dirigir l’operació cap a zones de treball amb un rendiment superior. Això inclou tant l’avanç de metodologies de modelat capaces d’extreure coneixement de bases de dades de comportaments històrics d’edificis a través de la previsió de cà rregues de consum i l’estimació del rendiment operatiu dels equips que recolzin la identificació del context operatiu i de les necessitats energètiques d’un edifici, tant com del desenvolupament d’una estratègia d’optimització multi-objectiu generalitzable per tal de minimitzar el consum d’energia mentre es satisfan aquestes necessitats energètiques. Els resultats experimentals obtinguts a partir de la implementació de les metodologies desenvolupades mostren un potencial important per augmentar l'eficiència energètica dels sistemes de climatització, mentre que són prou genèrics com per permetre el seu ús en diferents instal·lacions i suportant equips diversos. En conclusió, durant aquesta tesi es va desenvolupar, implementar i validar un marc d’anà lisi i actuació complet mitjançant una base de dades experimental adquirida en una planta pilot durant el perÃode d’investigació de la tesi. Els resultats obtinguts demostren l’eficà cia de les contribucions de manera individual i, en conjunt, representen una solució idònia per ajudar a augmentar el rendiment de les instal·lacions de climatització sense afectar el confort dels seus ocupantsPostprint (published version
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