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

Optimal chiller loading in dual-temperature chilled water plants for energy saving

Buildings account for almost 40% of global energy consumption. Due to the high energy consumption of chilled water plants, various studies have optimized chiller loading in plants with multiple chillers for energy conservation. However, few studies have optimized dual-temperature chiller plants, even though better energy efficiency could be achieved than that of typical single-temperature chiller plants. This paper proposes two optimal control strategies for dual-temperature chilled water plants, strategy B and strategy C. Strategy B optimizes the cooling load distribution of the chillers in each group by adjusting the cooling load ratio of each chiller. Under this strategy, the energy consumption of the chiller plant for the entire cooling season was reduced by 10.1%. Meanwhile, strategy C optimizes the cooling load distribution among chillers in the same chiller group and between two chiller groups, by simultaneously adjusting the temperature setpoint of the air leaving the primary cooling coils and the partial load ratio of each chiller. By considering both the impact of the chilled water loop and the air handling process, strategy C achieved greater energy saving (16.4%) for the entire cooling season. In hot summer months, the energy savings arise mainly from optimization of the cooling load distribution among chillers in each chiller group, as this optimization accounts for 63–68% of the total savings. In moderate months, optimizing the cooling load distribution among chillers in the same group and optimizing the distribution between two chiller groups account for nearly the same proportion of the total energy savings

A review of optimization approaches for controlling water-cooled central cooling systems

Buildings consume a large amount of energy across all sectors of society, and a large proportion of building energy is used by HVAC systems to provide a comfortable and healthy indoor environment. In medium and large-size buildings, the central cooling system accounts for a major share of the energy consumption of the HVAC system. Improving the cooling system efficiency has gained much attention as the reduction of cooling system energy use can effectively contribute to environmental sustainability. The control and operation play an important role in central cooling system energy efficiency under dynamic working conditions. It has been proven that optimization of the control of the central cooling system can notably reduce the energy consumption of the system and mitigate greenhouse gas emissions. In recent years, numerous studies focus on this topic to improve the performance of optimal control in different aspects (e.g., energy efficiency, stability, robustness, and computation efficiency). This paper provides an up-to-date overview of the research and development of optimization approaches for controlling water-cooled central cooling systems, helping readers to understand the new significant trends and achievements in this area. The optimization approaches have been classified as system-model-based and data-based. In this paper, the optimization methodology is introduced first by summarizing the key decision variables, objective function, constraints, and optimization algorithms. The principle and performance of various optimization approaches are then summarized and compared according to their classification. Finally, the challenges and development trends for optimal control of water-cooled central cooling systems are discussed

Energy-efficient HVAC systems: Simulation-empirical modelling and gradient optimization

This paper addresses the energy saving problem of air-cooled central cooling plant systems using the model-based gradient projection optimization method. Theoretical-empirical system models including mechanistic relations between components are developed for operating variables of the system. Experimental data are collected to model an actual air-cooled mini chiller equipped with a ducted fan-coil unit of an office building located in hot and dry climate conditions. Both inputs and outputs are known and measured from field monitoring in one summer month. The development and algorithm resulting from the gradient projection, implemented on a transient simulation software package, are incorporated to solve the minimization problem of energy consumption and predict the system's optimal set-points under transient conditions. The chilled water temperature, supply air temperature and refrigerant mass flow rate are calculated based on the cooling load and ambient dry-bulb temperature profiles by using the proposed approach. The integrated simulation tool is validated by using a wide range of experimentally collected data from the chiller in operation. Simulation results are provided to show possibility of significant energy savings and comfort enhancement using the proposed strategy. © 2012 Elsevier B.V

Application of Near-Optimal Tower Control and Free Cooling on the Condenser Water Side for Optimization of Central Cooling Systems

This paper presents an application of tower fan control for optimization of the performance of chiller plants combined with free cooling on the condenser water side. Mathematical models including all the main components of an existing cooling plant were developed and implemented in MATLAB. Simulation results include a mapping of the performance of the plant working in free cooling mode which was used to select control parameters for free cooling operation. Then a mapping of the plant operating with chillers was developed to find the correlation between load and near-optimal air flow, which is the basis of the near-optimal tower control (NOTC) strategy. Finally, simulations were carried out using three consecutive years of historical data to predict the performance of the plant under three different control strategies: 1) tower fan control aiming to keep the temperature of the water supplied to chiller condensers at a constant set point (current control strategy), 2) NOTC and 3) NOTC and free cooling combined. Comparison of the performance of the plant with the baseline (constant condenser water temperature) shows that significant savings can be achieved through the implementation of NOTC along with free cooling. It is expected that the methodology and results of this study provide a useful framework for optimization of cooling plants

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’eficàcia 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’àrea 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 pràctica. 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 càrregues 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’anàlisi i actuació complet mitjançant una base de dades experimental adquirida en una planta pilot durant el període d’investigació de la tesi. Els resultats obtinguts demostren l’eficàcia 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’eficàcia 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’àrea 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 pràctica. 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 càrregues 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’anàlisi i actuació complet mitjançant una base de dades experimental adquirida en una planta pilot durant el període d’investigació de la tesi. Els resultats obtinguts demostren l’eficàcia 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

Chilled Water Storage Feasibility with District Cooling Chiller in Tropical Environment

The difficulties of efficiently operating a chiller cooling system are manifest in the high-energy consumption under partial-cooling loads. The performance of a chiller cooling system declines when operating away from the optimal design conditions, which is typically 75% of chiller capacity. One pathway has been found to overcome this problem using multiple smaller chillers within the same chiller plant, accompanied by a smart control system that is designed and constructed based on the cooling demand profile. Thermal energy storage integration with chiller cooling system is proposed to shave the cooling peak demand. This can be achieved by storing chilled water during the lower electricity-tariff period by the thermal energy storage system, which will then be discharged during the higher tariff-rate, thus, aiming for sustainable operating cost. The present paper studies the feasibility of sensible thermal energy storage to be integrated with two chillers, of 30-ton capacity each, under hot-and-humid climates. A computational model validated with experimental results is developed for three chiller cooling system case scenarios. The smart control scenario, as well as the thermal energy storage scenario results, showed great potential for energy and electricity cost saving. In addition, the carbon dioxide emissions reduction is calculated based on the amount of energy saving

A Control Scheme of Enhanced Reliability for Multiple Chiller Plants Using Mergerd Building Cooling Load Measurements

This paper presents a control scheme which utilizes the enhanced instantaneous cooling load measurements to improve the reliability of chiller sequencing control. The enhanced measurement is obtained by merging two different measurements of building cooling load using data fusion technique. One is the direct cooling load measurement, which is obtained directly using the differential water temperature and water flow rate measurements. The other is the indirect cooling load measurement, which estimates the cooling load using chiller models based on the instantaneous chiller electrical power input and condition measured variables. The control performance of the proposed scheme is validated in this paper