• Energy Research

With increasing concern over global climate change and rapid rise in energy consumption on the data-driven market, data centres are an important renewable energy target. As cooling contributes a substantial portion of the energy use of data centres, minimising the cooling energy demand in data centres is one of the main objectives for improving renewable energy. This paper investigates overall energy consumption and the energy efficiency of the cooling system for a data centre in Finland as a case study. The temporal energy consumption characteristics, cooling infrastructure and operation of the data centre are analysed. The main problems associated with cooling energy efficiency and the factors that may contribute toward higher efficiency are identified and further suggestions are put forward. Results are presented of an extensive evaluation of the energy performance of the study data centre with a view to energy recovery. The conclusion we can draw is that even though the analysed data centre demonstrat...

Suvilahti, a suburb of the city of Vaasa in western Finland, was the first area to use seabed sediment heat as the main source of heating for a high number of houses. Moreover, in the same area, a unique land uplift effect is ongoing. The aim of this paper is to solve the challenges and find opportunities caused by global warming by utilizing seabed sediment energy as a renewable heat source. Measurement data of water and air temperature were analyzed, and correlations were established for the sediment temperature data using Statistical Analysis System (SAS) Enterprise Guide 7.1. software. The analysis and provisional forecast based on the autoregression integrated moving average (ARIMA) model revealed that air and water temperatures show incremental increases through time, and that sediment temperature has positive correlations with water temperature with a 2-month lag. Therefore, sediment heat energy is also expected to increase in the future. Factor analysis validations show that the data have a normal cluster and no particular outliers. This study concludes that sediment heat energy can be considered in prominent renewable production, transforming climate change into a useful solution, at least in summertime.

Abstract This paper proposes a novel and efficient CO2-based demand-controlled ventilation (DCV) strategy for use as an alternative to the proportional-plus-integral (PI) and the proportional-integral-derivative (PID) controls most often used for CO2 control in buildings. The new strategy “Pseudo Session DCV” divides opening hours into pseudo training sessions and breaks. For each pseudo training session, the outdoor airflow rate is calculated through the CO2 mass balance equation to keep indoor CO2 near the set point. For each pseudo break, the outdoor airflow rate is set at either the prescribed ventilation rate or the minimum outdoor air required by industry standards. Simulations were performed for a sports training center using both simulated and experimental CO2 generation rates. The results show that Pseudo Session DCV performs similar to PID for all possible cases, but achieves better energy savings performance than proportional control. For example, the Pseudo Session DCV strategy saves 34–38% of the energy required to condition outdoor air and 62–79% of fan energy compared to a proportional control strategy. Pseudo Session DCV is simple, efficient, capable of utilizing schedules for optimal ventilation control and no tuning is needed. Therefore Pseudo Session DCV control is easier to implement than PI or PID control.

Abstract Providing a comfortable and pleasant indoor environment for the occupants is the primary objective of an efficient ventilation process. Therefore, it is important to gain a proper understanding between the interaction of airflow and the occupants which determines the ultimate ventilation strategy and as one of the final outcomes, the architecture layout itself. The CFD (Computational Fluid Dynamics) methods provide an accurate and robust tool to simulate the complex airflow structure in enclosed spaces. Among the CFD simulation approaches, the large eddy simulation (LES) and its hybrid variants such as detached eddy simulation (DES) provides the information on the flow behavior by modeling the small turbulent structures of the airflow encountered in an indoor environment. These methods are highly sensitive to the boundary conditions which are the pivotal factors in an indoor airflow modeling and its accuracy. The main objectives of this paper are: (a) to assess the performance of different LES and DES models in capturing velocity and thermal fields (b) to investigate the effect of manikin’s shape on the accuracy of predictions. Three LES SGS (sub-grid scale) and one DES models are applied in this study considering the cases with and without the radiation from the manikin. Moreover, the effect of simplifying the manikins’ geometry on velocity and thermal distribution is investigated. Results showed that a detailed manikin shape can provide more accurate predictions (4–10%) at some locations, especially those close to the manikin’s body. As for performance of the applied models, Comparisons showed that ZEM and WALE models provide a better predictions of velocity and temperature fields by 3–10% at different locations.

Simulation models have been used widely to help design, operate, control and optimize the processes of exploration and exploitation of natural gas hydrates and been responsible for many of the most important technology breakthroughs. Currently, a rich body of literature exists and is still evolving. This paper presents a critical review of the most influential works that are recognised as representative and important simulation models and links to the techniques commonly used in natural gas hydrate exploration and exploitation. Model background, ideal assumptions and main results are presented. Models are broadly classified into two categories: physically and empirically based models. Models are reviewed with comprehensive, although not exhaustive, publications. The strengths and limitations of the models are discussed. The paper is concluded by outlining open questions and new directions for future work. The review is useful for understanding the innovation process and the current and future status of simulation models on exploration and exploitation of natural gas hydrate and highlights the key aspects of model improvement.

Abstract Improving the performance of air-to-air heat recovery systems, as measured by supply air temperature efficiency, is an important energy saving strategy that is often regulated by building codes. The high nonlinearity of supply air temperature efficiency with airflow rate in a run-around heat recovery system makes the trend prediction of supply air temperature efficiency especially challenging for field measurement. This paper proposes a simple and novel field measurement based methodology, supported by the power law relationship of air-side heat transfer, to evaluate the performance of run-around heat recovery systems. A system dependent power, signature power, is proposed that establishes a linear relationship between the supply air temperature increment across the supply air heat exchanger and a parameter—the maximum temperature difference between exhaust and supply airstreams divided by the signature power of the supply airflow rate. This methodology can predict the supply air temperature efficiency and is verified using four run-around heat recovery systems with field measurements. This new methodology can possibly be applied to other types of air-to-air heat recovery systems. This paper also describes a tuning method for determining the signature power based on field measurements and addresses the heat recovery efficiency of run-around heat recovery systems.

The 5th generation (5G) cellular networks offer high speeds, low latency, and greater capacity, but they face greater penetration loss through buildings than 4G due to their higher frequency bands. To reduce this loss in energy-efficient buildings, a passive antenna system was developed and integrated into sandwich walls. However, the thermal effects of this system, which includes highly thermally conductive metals, require further study. In this research, three-dimensional heat transfer simulations were performed using COMSOL Multiphysics to determine the thermal transmittances (U-values) of 5G antenna walls. The results revealed that, using stainless steel as the connector material (current design), the U-value rose from 0.1496 (for the wall without antenna) to 0.156 W/m2K, leading to an additional heating loss per year of only 0.545 KWh/m2 in Helsinki. In contrast, with the previous design that used copper as the connector material, the U-value increased dramatically to 0.3 W/m2K, exceeding the National Building Code of Finland’s limit of 0.17 W/m2K and causing 12.8 KWh/m2 additional heat loss (23.5 times more than the current design). The current design significantly reduces thermal bridging effects. Additionally, three analytical methods were used to calculate antenna wall U-values: parallel paths, isothermal planes, and ISO 6946 combined. The isothermal planes method was found to be more accurate and reliable. The study also found that a wall unit cell with a single developed 5G antenna and a wall consisting of nine such cells arranged in a 3 × 3 grid pattern had the same U-values. Furthermore, areas affected by thermal bridging were typically smaller than the dimensions of a wall unit cell (150 mm × 150 mm).

AbstractThis paper proposes a method using neural networks to calibrate numerical models. The approach passes the output of numerical model to a neural network for calibration. An experimental study was conducted using a simulation of unheated and uncooled indoor temperature of a sports hall. The proposed neural network-based model improves the results and produces more accurate calibrated indoor temperature. Furthermore, the developed calibration method requires only measurements of indoor temperatures as the necessary inputs, thus significantly simplifying the calibration procedure needed to model the building performances.