A numerical and experimental study on energy saving solutions for mobile hydraulic machinery

Energy saving in mobile hydraulic machinery, aimed to fuel consumption reduction, has been one of the principal interests of many researchers and OEMs in the last years. Many different solutions have been proposed and investigated in the literature in order to improve the fuel efficiency, from novel system architectures and strategies to control the system to hybrid solutions. This thesis deals with the energy analysis of a hydraulic system of a middle size excavator through mathematical tools. In order to conduct the analyses the multibody mathematical model of the hydraulic excavator under investigation will be developed and validated on the basis of experimental activities, both on test bench and on the field. The analyses will be carried out considering the typical working cycles of the excavators defined by the JCMAS standard. The simulations results will be analysed and discussed in detail in order to define different solutions for the energy saving in LS hydraulic systems. Among the proposed energy saving solutions, energy recovery systems seem to be very promising for fuel consumption reduction in mobile machinery. In this thesis a novel energy recovery system architecture will be proposed and described in detail. Its dimensioning procedure takes advantage of the dynamic programming algorithm and a prototype will be realized and tested on the excavator under investigation. Finally the energy saving proposed solutions will be compared referring to the standard machinery architecture and a novel hybrid excavator with an energy saving up to 11% will be presented.

Energy saving and solar electricity in fan-ventilated greenhouses

Greenhouse cultivation is an energy intensive process therefore it is worthwhile to introduce energy saving measures and alternative energy sources. Here we show that there is scope for energy saving in fan ventilated greenhouses. Measurements of electricity usage as a function of fan speed have been performed for two models of 1.25 m diameter greenhouse fans and compared to theoretical values. Reducing the speed can cut the energy usage per volume of air moved by more than 70%. To minimize the capital cost of low-speed operation, a cooled greenhouse has been built in which the fan speed responds to sunlight such that full speed is reached only around noon. The energy saving is about 40% compared to constant speed operation. Direct operation of fans from solar-photovoltaic modules is also viable as shown from experiments with a fan driven by a brushless DC motor. On comparing the Net Present Value costs of the different systems over a 10 year amortization period (with and without a carbon tax to represent environmental costs) we find that sunlight-controlled system saves money under all assumptions about taxation and discount rates. The solar-powered system, however, is only profitable for very low discount rates, due to the high initial capital costs. Nonetheless this system could be of interest for its reliability in developing countries where mains electricity is intermittent. We recommend that greenhouse fan manufacturers improve the availability of energy-saving designs such as those described here.

Achieving Energy Saving through Proxying Applications on behalf of Idle Devices

Several studies in the past have revealed that network end user devices are left powered up 24/7 even when idle just for the sake of maintaining Internet connectivity. Network devices normally support low power states but are kept inactive due to their inability to maintain network connectivity. The Network Connectivity Proxy (NCP) has recently been proposed as an effective mechanism to impersonate network connectivity on behalf of high power devices and enable them to sleep when idle without losing network presence. The NCP can efficiently proxy basic networking protocol, however, proxying of Internet based applications have no absolute solution due to dynamic and non-predictable nature of the packets they are sending and receiving periodically. This paper proposes an approach for proxying Internet based applications and presents the basic software architectures and capabilities. Further, this paper also practically evaluates the proposed framework and analyzes expected energy savings achievable under-different realistic conditions.

Assessing the Potential for Saving Energy by Impersonating Idle Networked Devices

The idea of proxying network connectivity has been proposed as an efficient mechanism to maintain network presence on behalf of idle devices, so that they can “sleep”. The concept has been around for many years; alternative architectural solutions have been proposed to implement it, which lead to different considerations about capability, effectiveness and energy efficiency. However, there is neither a clear understanding of the potential for energy saving nor a detailed performance comparison among the different proxy architectures. In this paper, we estimate the potential energy saving achievable by different architectural solutions for proxying network connectivity. Our work considers the trade-off between the saving achievable by putting idle devices to sleep and the additional power consumption to run the proxy. Our analysis encompasses a broad range of alternatives, taking into consideration both implementations already available in the market and prototypes built for research purposes. We remark that the main value of our work is the estimation under realistic conditions, taking into consideration power measurements, usage profiles and proxying capabilities.

Abatement of energy loss by insulating system and designing automatic water heater

The most suitable temperature range for domestic purposes is about 200C to 260C .Besides, both cold and hot water appear to be essential frequently for industrial purposes. In summer bringing down the water temperature at a comfortable range causes significant energy consumption. This project aims at saving energy to control water temperature by making water tank insulated .Therefore applying better insulation system which would reduce the disparity between the desired temperature and the actual temperature and hence saving energy significantly. Following the investigation, this project used cotton jacket to insulate the tank and the tank was placed under a paddy straw shade with a view to attaining the maximum energy saving. Finally, it has been found that reduction in energy consumption is to be about 50-60% which is quite satisfactory. Since comfortable temperature range varies from person to person this project thus combines insulating effect with automatic water heater.

Energy-pollution nexus for urban buildings

Since the first oil crisis in 1974, economic reasons placed energy saving among the top priorities in most industrialised countries. In the decades that followed, another, equally strong driver for energy saving emerged: climate change caused by anthropogenic emissions, a large fraction of which result from energy generation. Intrinsically linked to energy consumption and its related emissions is another problem: indoor air quality. City dwellers in industrialised nations spend over 90% of their time indoors and exposure to indoor pollutants contributes to ~2.6% of global burden of disease and nearly 2 million premature deaths per year1. Changing climate conditions, together with human expectations of comfortable thermal conditions, elevates building energy requirements for heating, cooling, lighting and the use of other electrical equipment. We believe that these changes elicit a need to understand the nexus between energy consumption and its consequent impact on indoor air quality in urban buildings. In our opinion the key questions are how energy consumption is distributed between different building services, and how the resulting pollution affects indoor air quality. The energy-pollution nexus has clearly been identified in qualitative terms; however the quantification of such a nexus to derive emissions or concentrations per unit energy consumption is still weak, inconclusive and requires forward thinking. Of course, various aspects of energy consumption and indoor air quality have been studied in detail separately, but in-depth, integrated studies of the energy-pollution nexus are hard to come by. We argue that such studies could be instrumental in providing sustainable solutions to maintain the trade-off between the energy efficiency of buildings and acceptable levels of air pollution for healthy living.

Co-optimisation of indoor environmental quality and energy consumption within urban office buildings

This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.

Country review on the main building energy-efficiency policy instrument

Building energy-efficiency (BEE) is the key to drive the promotion of energy saving in building sector. A large variety of building energy-efficiency policy instrument exist. Some are mandatory, some are soft scheme, and some use economic incentives from country to country. This paper presents the current development of implementing BEE policy instruments by examining the practices of BEE in seven selected countries and regions. In the study, BEE policy instruments are classified into three groups, including mandatory administration control instruments, economic incentive instruments and voluntary scheme instruments. The study shows that different countries have adopted different instruments in their practices for achieving the target of energy-saving and gained various kinds of experiences. It is important to share these experiences gained.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

A probabilistic energy model for non-domestic building sectors applied to analysis of school buildings in greater London

The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop models for large scale analysis of the stock. This research proposes a probabilistic, engineering-based, bottom-up model to address these issues. In a recent study we classified London's non-domestic buildings based on the service they provide, such as offices, retail premise, and schools, and proposed the creation of one probabilistic representational model per building type. This paper investigates techniques for the development of such models. The representational model is a statistical surrogate of a dynamic energy simulation (ES) model. We first identify the main parameters affecting energy consumption in a particular building sector/type by using sampling-based global sensitivity analysis methods, and then generate statistical surrogate models of the dynamic ES model within the dominant model parameters. Given a sample of actual energy consumption for that sector, we use the surrogate model to infer the distribution of model parameters by inverse analysis. The inferred distributions of input parameters are able to quantify the relative benefits of alternative energy saving measures on an entire building sector with requisite quantification of uncertainties. Secondary school buildings are used for illustrating the application of this probabilistic method. © 2012 Elsevier B.V. All rights reserved.