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Abstract The objective of this work is to evaluate the surge characteristics of an axial compressor operating under surge conditions, by using a hybrid BDF/harmonic balance method. During a surge event, a large amount of backflow occurs in the compressor. Consequently, the airflow oscillates along the axial direction at a low frequency, which can considerably damage the compressor. In this paper, a numerical investigation is performed to examine the effects of the system volume and average mass flow on the surge characteristics of a transonic high speed single stage axial compressor (stage 35) designed and evaluated at the NASA Glenn Center. The results show that the oscillation frequency of the airflow in the compressor generally ranges from 14.32–26.04 Hz during surge conditions, and both the system volume and average mass flow considerably influence the surge characteristics. For a constant average mass flow, as the system volume decreases, the oscillation frequency of the airflow in the compressor increases slightly, while the oscillation amplitude of the exit static pressure decreases significantly, and the maximum static pressure at the outlet remains nearly constant. In the case of a constant system volume, with the decrease in the average mass flow, the oscillation frequency of the airflow in the compressor gradually decreases, and the oscillation amplitude of the exit pressure increases significantly. With a further decrease in the average mass flow, the oscillation frequency stabilizes at a certain point and does not change thenceforth. Furthermore, the surge frequency obtained using the numerical method shows a same tendency with the Helmholtz frequency, but there is a considerable difference between them.

Abstract Flow behavior of particles in a two-dimensional spouted bed with a draft tube is studied using a continuous kinetic-friction stresses model. The kinetic stress of particles is predicted from kinetic theory of granular flow, while the friction stress is computed from a model proposed by Johnson et al. (1990) . A stitching function is used to smooth from the rapid shearing viscous regime to the slow shearing plastic regime. The distributions of concentration and velocities of particles are predicted in the spouted bed with a draft tube. Simulated results compare with the vertical velocity of particles ( Zhao et al., 2008 ) measured and in the spout bed with draft plates and solid circulation rate ( Ishikura et al., 2003 ) measured in the spouted bed with a draft tube. The impact of the friction stress of particles on the spout, annulus, fountain and entrancement regions is analyzed in gas–solid spouted bed with a draft tube. Numerical results show that the gas flow rate through the annulus increases with the increase of the entrainment zone. The solids circulation rate decreases with the decrease of inlet gas velocity and the height of the entrainment zone. The effect of spouting gas velocity on distributions of concentration, velocity and particle circulation is discussed.

Abstract In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the e -insensitive loss function, admits of the residual within the boundary values of e -tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.

Abstract With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.

Short term load forecasting plays an increasingly important role in Smart Grid. Short term load forecasting is also an important part of enterprise power system management. Providing accurate load time series data for a certain period of time in the future can enable enterprises to ensure the smooth operation of production while making a reasonable power plan, reducing power consumption and basic electricity charges, thus reducing the production cost of enterprises. In addition, lower electricity consumption means lower carbon dioxide emissions, which has far-reaching implications for sustainable development strategies. This paper presents a short-term load forecasting method based on time series. The model divides the time series data into four parts: trend item, period item, holiday item and error item. In the experiment part, this paper provides a set of preprocessing method flow. Aiming at the problem that the sampling rate of the current smart grid data is not constant, a data smoothing algorithm is proposed.

Abstract The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.

Main characteristics and advantages of static VAR compensators (SVC) based on thyristor-switched schemes are presented. The operating features of compensator circuits when forming inductive and capacitive reactive power are considered. The reactive power regulation principles that provide the sinusoidal form of reactive current are explained on examples of operation of inductive and capacitive SVCs. The specificity of the operation of SVC control systems ensuring reliable operation in transient and steady-state working modes is discussed. The tasks of experimental research of SVC physical models are formulated. Experimental results obtained on the SVC physical models illustrating main characteristics of such devices are presented.

Abstract In the current study, a new solar-driven triple cycle is proposed to allow power generation during low insolation periods. This triple cycle integrates the solar gas-turbine top cycle, the steam Rankine cycle, and the Kalina bottom cycle. During the top cycle of the proposed system, compressed air was heated to 1000 °C or higher in the solar tower receiver. The heated compressed air was then used to drive the gas turbine to generate electricity. A Rankine cycle with a back-pressure steam turbine was utilized to recover waste heat from the gas turbine, thereby generating electricity through the steam turbine. The bottom cycle is the Kalina cycle, which comprises another back-pressure turbine and utilizes ammonia–water mixture as working fluid. After driving the steam Rankine cycle, the flue gas from the gas turbine sequentially heats the ammonia–water mixture to produce power. A new operational strategy was presented to generate electricity during low insolation period without the backup of fossil fuel. In middle insolation periods, the air is heated by the solar field and then directly drives the steam Rankine cycle, bypassing the gas turbine. In low insolation periods, the heated air directly drive the Kalina cycle, bypassing the Brayton cycle and the steam Rankine cycle. The off-design performance was investigated and the irreversibility was disclosed with the aid of the energy-utilization diagram method. Thus, the proposed system can utilize low insolation to generate electricity. This study provides a possibility to improve the solar–electric efficiency.

Technical solutions for optimizing the flame aerodynamics and the design of tangentially arranged burners in a TGMP-314 boiler are proposed. The implementation of these solutions will make it possible to achieve more reliable operation of the boiler during fuel oil combustion, smaller amount of NOx emissions during the combustion of gas and fuel oil, and a somewhat lower air excess factor in the furnace.