Journal of Energy Engineering

A data-driven approach for development of a virtual wind-speed sensor for wind turbines is presented. The virtual wind-speed sensor is built from historical wind-farm data by data-mining algorithms. Four different data-mining algorithms are used to develop models using wind-speed data collected by anemometers of various wind turbines on a wind farm. The computational results produced by different algorithms are discussed. The neural network (NN) with the multilayer perceptron (MLP) algorithm produced the most accurate wind-speed prediction among all the algorithms tested. Wavelets are employed to denoise the high-frequency wind-speed data measured by anemometers. The models built with data-mining algorithms on the basis of the wavelet-transformed data are to serve as virtual wind-speed sensors for wind turbines. The wind speed generated by a virtual sensor can be used for different purposes, including online monitoring and calibration of the wind-speed sensors, as well as providing reliable wind-speed input to a turbine controller. The approach presented in this paper is applicable to utility-scale wind turbines of any type.

This experimental study focused on improving performance characteristics of a low-heat rejection (LHR) diesel engine operating with biodiesel fuel. To ensure LHR conditions, the cylinder head and valves of the test engine were coated with a ${\mathrm{Y}}_2{\mathrm{O}}_3-{\mathrm{ZrO}}_2$ (yttria-stabilized zirconia) layer of 0.35 mm thickness over a NiCrAl bond coat of 0.15 mm thickness. The fuel used in the engine tests was produced from sunflower oil with transesterification methods. The engine test results showed that brake-specific fuel consumption (BSFC) and brake thermal efficiency were improved with biodiesel usage and thermal barrier coating (TBC) application. Further, exhaust gas temperature was decreased with use of biodiesel, while it was increased with TBC application.

The duct leakage in forced-air distribution systems has been recognized for years as a major source of energy losses in residential buildings. Recently, a measurement technique for estimating the total air leakage from residential duct systems, called Delta-Q, has been proposed. It focuses on measuring the total supply and return air leakage flows outside at operating conditions that are required for energy loss calculations. This paper discusses the Delta-Q measurement technique and proposes improvements on its model to increase the accuracy of the total leakage estimations and to provide appropriate estimation of local leakages. Accurate estimations of the total and local leakages can help to focus the choice for both the right house and location in the duct system for performing the potential repair job. Proper information as to where the leakages are located inside the duct system can reduce the time required for the duct sealing task. This study uses detailed laboratory measurements to validate the original and improved Delta-Q technique procedure and calculations. The air duct leakage laboratory (ADLL) has two different air duct configurations and a wide range of leakage levels controlled by holes created at several locations in the ductwork. This work also includes a set of simulation results to provide an insight into the performance of Delta-Q under different conditions. The simulation and experimental studies showed that the proposed Delta-Q models can improve the accuracy of total leakage estimation and provide useful information when these leakages are located inside the duct.

The building sector is one of the fastest growing in terms of energy consumption. To guarantee energy savings and to reduce carbon dioxide (${\mathrm{CO}}_2$) emissions, building energy conservation assessment is an important option. A building energy conservation assessment will strongly promote development of the building’s thermal characteristics and application of new energy conservation technologies and products. Because of the unquantifiable and incomplete information of evaluation criteria, a multihierarchical gray evaluation methodology is proposed for building energy conservation assessment. To determine the weights of the factors, a linear combination weighting method combining an analytic hierarchical process (AHP) method and the technique for order preference by similarity to ideal solution (TOPSIS) method is proposed. The integrated assessment results and the integrated assessment values are calculated, and a building energy conservation star is proposed and determined. Then, an example is used to illustrate the proposed approach and the proposed method is validated. The results demonstrate the engineering practicability and effectiveness of this proposed method.

The experimental study of a single-effect modular adsorption cooling system with an activated carbon-methanol working pair is presented in this paper. The test unit is comprised of an adsorber, a condenser, and an evaporator in vertical alignment. Heating and cooling at the adsorber is by hot water at 70–90°C, whereas heating at the evaporator is performed by water at the ambient temperature. At the evaporator, a sonic wave generator enhances heat transfer for the boiling of methanol during the adsorption process. The system performance by considering the coefficient of performance (COP), specific cooling power (SCP), and volumetric cold production (VCP) is evaluated, and the sonic wave is demonstrated to reduce the evaporation time of methanol, which results in better system performances compared with the results in literature. The highest COP and SCP obtained from this system are 0.718 and $248.90\mathrm{W}/\mathrm{kg}$, respectively.

All kinds of biomasses pull carbon out of the air as they grow. Waste biomass can be made into usable fuel by densification. These biomasses can then replace some coal in power plants, which will reduce carbon emissions and greenhouse gas effects. Densification of low-density biomass (agricultural and agro-industrial waste) is called biomass briquetting. The briquette form facilitates easy transportation, enables better handling and storage, and is efficient to use as an alternative fuel to coal and firewood. The high temperature developed during the high-pressure densification process assists the inherent lignin, which is the binder in the biomass, to bind the biomass and form a densified fuel called briquettes. In this paper, four kinds of biomasses (mango leaves, eucalyptus leaves, wheat straw, and sawdust) were briquetted. Physicochemical and thermochemical characterization of the biomass residues was carried out by using standard methods. A hydraulic press and an automatic compression testing machine were used for the briquetting and testing. The effect of various parameters, such as compression pressure, pressure application rate, holding time, particle size, and moisture content, on the density of the briquettes was studied. The impact resistance test was carried out by using the standard ASTM method. All the briquettes prepared from the biomass studied in this paper have more heating value than half of Indian coal; thus, they can be used as an alternative to coal and firewood.