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[en] Highlights: • A metering cost minimisation model is built to assist the sampling plan for CDM projects. • The model minimises the total metering cost by the determination of optimal sample size. • The required 90/10 criterion sampling accuracy is maintained. • The proposed metering cost minimisation model is applicable to other CDM projects as well. - Abstract: Clean development mechanism (CDM) project developers are always interested in achieving required measurement accuracies with the least metering cost. In this paper, a metering cost minimisation model is proposed for the sampling plan of a specific CDM energy efficiency lighting project. The problem arises from the particular CDM sampling requirement of 90% confidence and 10% precision for the small-scale CDM energy efficiency projects, which is known as the 90/10 criterion. The 90/10 criterion can be met through solving the metering cost minimisation problem. All the lights in the project are classified into different groups according to uncertainties of the lighting energy consumption, which are characterised by their statistical coefficient of variance (CV). Samples from each group are randomly selected to install power meters. These meters include less expensive ones with less functionality and more expensive ones with greater functionality. The metering cost minimisation model will minimise the total metering cost through the determination of the optimal sample size at each group. The 90/10 criterion is formulated as constraints to the metering cost objective. The optimal solution to the minimisation problem will therefore minimise the metering cost whilst meeting the 90/10 criterion, and this is verified by a case study. Relationships between the optimal metering cost and the population sizes of the groups, CV values and the meter equipment cost are further explored in three simulations. The metering cost minimisation model proposed for lighting systems is applicable to other CDM projects as well
[en] Highlights: • Hybrid MPPT method was developed and utilized in a PV system of closed plant factory. • The tracking of the maximum power output of PV system can be achieved in real time. • Hybrid MPPT method not only decreases energy loss but increases power utilization. • The feasibility of applying PV system to the closed plant factory has been examined. • The PV system significantly reduced CO2 emissions and curtailed the fossil fuels. - Abstract: Photovoltaic (PV) generation systems have been shown to have a promising role for use in high electric-load buildings, such as the closed plant factory which is dependent upon artificial lighting. The power generated by the PV systems can be either directly supplied to the buildings or fed back into the electrical grid to reduce the high economic costs and environmental impact associated with the traditional energy sources such as nuclear power and fossil fuels. However, PV systems usually suffer from low energy-conversion efficiency, and it is therefore necessary to improve their performance by tackling the energy loss issues. The maximum power point tracking (MPPT) control technique is essential to the PV-assisted generation systems in order to achieve the maximum power output in real time. In this study, we integrate the previously proposed direct-prediction MPP method with a perturbation and observation (P and O) method to develop a new hybrid MPPT method. The proposed MPPT method is further utilized in the PV inverters in a PV system installed on the roof of a closed plant factory at National Taiwan University. The tested PV system is constructed as a two-stage grid-connected photovoltaic power conditioning (PVPC) system with a boost-buck full bridge design configuration. A control scheme based on the hybrid MPPT method is also developed and implemented in the PV inverters of the PVPC system to achieve tracking of the maximum power output of the PV system in real time. Based on experimental results obtained in an outdoor environment over a period of one year, the hybrid MPPT method not only decreases energy loss but also increases power utilization. These results demonstrate the applicability of the PV system to a closed plant factory for saving energy consumption and reducing CO2 emissions
[en] Highlights: • An unsupervised framework to detect activities and potential savings in real-time. • Eliminating the need for collecting labeled activity data for training while achieving a high performance. • Three sub-algorithms for action detection, activity recognition and waste estimation. • Experimental validation in a testbed office with five occupants and two single-occupancy apartments. • The framework could potentially be integrated with automation module for appliance control. - Abstract: More than half of the electricity in residential and commercial buildings is consumed by lighting systems and appliances. Consumption by these service systems is directly associated with occupant activities. By recognizing activities and identifying the associated possible energy savings, more effective strategies can be developed to design better buildings and automation systems. In line with this motivation, using inductive and deductive reasoning, we introduce a framework to detect occupant activities and potential wasted energy consumption and peak-hour usage that could be shifted to non-peak hours in real-time. Our framework consists of three sub-algorithms for action detection, activity recognition and waste estimation. As the real-time input, the action detection algorithm receives the data from the sensing system, consisting of plug meters and sensors, to detect the occurred actions (e.g., turning on an appliance) via our unsupervised clustering models. Detected actions are then used by the activity recognition algorithm to recognize the activities (e.g., preparing food) through semantic reasoning on our constructed ontology. Based on the recognized activities, the waste estimation algorithm identifies the potential waste and estimates the potential savings. To evaluate the performance of our framework, an experimental study was carried out in an office with five occupants and in two single-occupancy apartments for two weeks. Following the experiment, the performance of the action detection and activity recognition algorithms was evaluated using the ground truth labels for actions and activities. Average accuracy was 97.6% for action detection using Gaussian Mixture Model with Principal Components Analysis and 96.7% for activity recognition. In addition, 35.5% of the consumption of an appliance or lighting system in average was identified as potential savings.
[en] Highlights: • We evaluate carbon dioxide emissions from residential energy consumption (REC) at county-level. • A stepwise methodological procedure is conducted using satellite imagery of nighttime lights. • We find a high degree of county-level clustering in the distribution of emissions per capita. • High-emission counties tend to be surrounded by counties with relatively low per capita GDP levels. • We stress the need for consideration of other factors in determining emission patterns. - Abstract: As the world’s largest developing country and greenhouse gas emitter, China’s residential energy consumption (REC) is now responsible for over 11% of the country’s total energy consumption. In this paper, we present a novel method that utilizes spatially distributed information from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP–OLS) and human activity index (HAI) to test the hypothesis that counties with similar carbon dioxide emissions from REC are more spatially clustered than would be expected by chance. Our results revealed a high degree of county-level clustering in the distribution of emissions per capita. However, further analysis showed that high-emission counties tended to be surrounded by counties with relatively low per capita GDP levels. Therefore, our results contrasted with other evidence that REC emissions were closely related to GDP levels. Accordingly, we stress the need for the consideration of other factors in determining emission patterns, such as residential consumption patterns (e.g., consumer choices, behavior, knowledge, and information diffusion)
[en] Highlights: •Daylighting and energy performances were studied simultaneously. •Energy demands of lighting and air-conditioning systems were both included. •Luminous comfort was quantified by Ave. DA300 with the range from 29.6% to 57.8%. •Energy Daylight Rate was proposed as a simple multi-objective optimization approach. •Optimal scenarios for all directions were tested and chosen by EDR method. -- Abstract: Being healthy and energy saving have become two important principles of building development. Daylight is an influential factor with the characteristics of both photometry and radiometry. Irradiance brings solar heat gains that transfer to building cooling load, while illuminance provides a luminous environment and affects artificial lighting system at the same time. To balance the energy and daylighting performances, it is reasonable to minimize the environmental load under moderate comfort conditions. This study first quantified luminous comfort with a dynamic daylighting metric, average daylight autonomy (Ave. DA300), from a questionnaire survey and simulation work. The benchmark of this metric should range from 29.6% to 57.8% for high-rise residential buildings. With this guideline, the Hong Kong public housing units is found that part of units lack of daylight due to the high building floor and density, while some units have potential to save energy by compromising daylighting performance. Therefore, a new index, energy daylight rate (EDR), is proposed to help decide the best scenario of envelope design for both daylighting and shading purposes. The results show that opening a secondary window is an efficient way to bring more light in and lengthening overhang is an efficient way to block excessive sunlight. This method and the new index are proved to have the ability to help defining proper building envelope design at the early stage.
[en] In this study, various energy conservation measures (ECMs) on heating, ventilating and air conditioning (HVAC) and lighting systems for a four-storied institutional building in sub-tropical (hot and humid climate) Queensland, Australia are evaluated using the simulation software called DesignBuilder (DB). Base case scenario of energy consumption profiles of existing systems are analysed and simulated first then, the simulated results are verified by on-site measured data. Three categories of ECMs, namely major investment ECMs (variable air volume (VAV) systems against constant air volume (CAV); and low coefficient of performance (COP) chillers against high COP chillers); minor investment ECMs (photo electric dimming control system against general lighting, and double glazed low emittance windows against single-glazed windows) and zero investment ECMs (reset heating and cooling set point temperatures) are evaluated. It is found that the building considered in this study can save up to 41.87% energy without compromising occupancies thermal comfort by implementing the above mentioned ECMs into the existing system.
[en] This paper presents a solar-powered lighting system, using cold-cathode fluorescent-lamps (CCFLs), with its battery-charging circuit and lamp-ignition circuit being separated so that its solar panels can be installed at any distance deemed necessary away from the lighting site in order to receive the maximum solar energy available. This system adopts the maximum-power point tracking (MPPT) method to control the power output of the solar panels and uses the zero-voltage switching (ZVS) DC-DC converter, as the charging circuit, to increase the panels' power generation efficiency and the charging circuit's conversion efficiency. The electronic ballast circuit for the CCFL is constructed with a half-bridge inverter, a resonant inductor, and a Rosen-type piezoelectric transformer, which forms a piezoelectric resonant-type inverter: to simplify the circuitry and to improve the power conversion efficiency, the ballast circuit is designed to directly step up the battery voltage in igniting the lamp. We also establish the transmission-parameter model for the piezoelectric resonant-type inverter to provide the base for the electric-power circuit design. Our experimental results indicate that the proposed system possesses some advantages, such as greater energy efficiency, circuitry simplicity, and so on, and is suitable for night lighting in house yards, parks and advertising panels
[en] Highlights: • The IDHVAC system is optimized using the integrated meta-model and GA. • The design of experiments method is applied to train the integrated meta-model. • The GA-optimized models are compared with the reference model. • The GA-optimized IDHVAC model shows the best performance among them. - Abstract: The use of daylight in buildings to save energy while providing satisfactory environmental comfort has increased. Integration of the daylighting and thermal energy systems is necessary for environmental comfort and energy efficiency. In this study, an integrated meta-model for a daylighting, heating, ventilating, and air conditioning (IDHVAC) system was developed to predict building energy performance by artificial lighting regression models and artificial neural network (ANN) models, with a database that was generated using the EnergyPlus model. The design of experiments (DOE) method was applied to generate the database that was used to train robust ANN models without overfitting problems. The IDHVAC system was optimized using the integrated meta-model and genetic algorithm (GA), to minimize total energy consumption while satisfying both thermal and visual comfort for occupants. During three months in the winter, the GA-optimized IDHVAC model showed, on average, 13.7% energy savings against the conventional model.
[en] This paper presents the development and analysis of a new airlift-driven raceway reactor configuration for energy-efficient algal cultivation. A theoretical analysis of the energy requirements for traditional paddlewheel-driven raceway reactors and the proposed airlift-driven raceway reactors is presented. A hydrodynamic model was developed to predict the liquid circulation velocity in the reactor system based on theoretical energy balance. The predicted liquid velocity agreed well with experimentally measured liquid velocity with r2 = 0.89. Based on the results of this analysis, the energy required for maintaining typical raceway velocity of 14 cm/s for mixing and keeping the cultures in suspension in a paddlewheel-driven raceway could be reduced by as much as 80% with the proposed configuration. Growth of Scenedesmus sp. was evaluated in a laboratory scale, 20 L version of the proposed reactor configuration using artificial lighting under ambient temperatures without any supplementary carbon dioxide sparging. The volumetric algal biomass productivity achieved in the proposed configuration (0.16 ± 0.03 dry g/L day) is comparable or better than that reported in the literature for paddlewheel-driven raceways.
[en] Highlights: • Integration of natural and artificial lighting is examined in a classroom. • Simulation of a LED lighting plant characterized by a control logic system. • Visual comfort is guaranteed while meeting the regulations EN 12464-1. • The aim is the energy efficiency and economic advantage with respect to the reliability. • A significant increase of energy efficiency and MTBF (Mean Time Between Failure) is reported. - Abstract: The necessity to reduce energy requirements of lighting systems should bring among engineers a more mature and conscious vision while planning and this means that their main goals should be the visual comfort and a decrease in energy and maintenance costs. Therefore this paper examines the case study of a classroom located in the Faculty of Engineering of Sapienza University in Rome and, to evaluate the possibility to combine natural and artificial light, it focuses on the realization of a new lighting system. This new solution is formed by LED sources and control systems able to modulate the power absorbed by every single lamp (to adapt, according to the hour and day, to the conditions of the natural light). In order to meet the EN 12464-1, the process of incorporating natural and artificial light must occur while guaranteeing both the minimum levels expected for the average illuminance E_m [lx] and the uniformity coefficient (E_m_i_n/E_m) and this is the reason why a simultaneous exertion of artificial lights and a variable shielding system of glass surfaces activated through a motorized electronic control unit is required. Thanks to the software DIALux Evo 5.1 a 3D model of the classroom was reproduced and validated in order to simulate the combination of natural and artificial lighting and to verify if the results complied with the regulations. This was followed by an analysis concerning: the reliability of the system (through the examination of the MTBF – Mean Time Between Failure) and energetic and economic aspects (through the software ecoCALC 4.5.4). The novelty of this study is represented by the fact that in order to obtain the highest results in each of the three fields examined, it is possible to avoid the exertion of those negative feedback control-type systems (requiring high installation and maintenance costs due to sensor devices), thanks to pre-programmed logic control systems based on the data obtained with the simulations by prediction softwares. In this case study the solution suggested, while using a pre-programmed control logic, presents a MTBF of 1205 h (about twice of a negative feedback system solution) with payback periods that justify the higher costs presented by the electronic characterizing the control logic system with respect to traditional plant solutions.