Journal of Energy Engineering

Rural households are mainly heated using kangs in northern China. In this study, elevated kangs (EK) were constructed in six rural houses in Zhuanglang County. Indoor and outdoor temperatures were monitored hourly in houses using the traditional type of kang (TK) and the elevated kang. A polynomial regression model was designed to analyze the time series data on fuel consumption and temperature change. The thermal effectiveness of the two types of kang was modeled according to the daily life scenario of rural households. The results show that the EK can improve fuel efficiency and the indoor thermal comfort of rural residents in winter. At a given fuel consumption, the EK $T_{ha}$ (hourly average temperature difference during the heating period) was 5.1°C higher than the TK $T_{ha}$ in Gaoyahan village and 6.6°C higher than the TK $T_{ha}$ in Xiawan village. At a given indoor temperature, EK fuel consumption was less than that of TK. Use of the EK improved fuel utilization efficiency, which indicated that the method can help solve heating problems in rural houses. The thermal efficiency of the EK was between 35 and 36%, which was more than double that of the TK. This suggests that the EK should be actively promoted in western rural China.

In natural-gas transmission, a compressor station often consists of multiple types of compressors. For any given suction pressure, discharge pressure, and total mass flow, an operation manager needs to decide the set of compressors to work, the rotation speed of each working compressor, and the natural-gas flow allocation among all the working compressors. In this paper, two solution approaches are investigated and compared: mixed-integer linear programming and dynamic programming. Both approaches require the discretization of actual volumetric flow. Numerical results reveal that when the discrete interval is $0.1{\mathrm{m}}^3/\mathrm{s}$, dynamic programming takes less computation time than mixed-integer linear programming does. However, this order is reversed when the discrete interval is 0.01 or $0.001{\mathrm{m}}^3/\mathrm{s}$.

An exergy and energy analysis on a solar parabolic dish collector (PDC) is carried out. In the experimental conditions the destructed exergy due to solar energy absorption by receiver and heat losses from the receiver end up being approximately 60% waste of total exergy in some cases. The maximum exergy efficiency in the experiments is less than 10%. An objective function for maximizing the exergy efficiency is developed mainly based on heat transfer fluid (HTF) inlet temperature and mass flow rate. Optimization results indicate that the HTF outlet temperature as design parameter can be specified based on the given system application. At optimum values of operating parameters, the maximum destructed exergy due to solar absorption and heat losses from the receiver are less than 45 and 15%, respectively. A parametric study based on the developed objective function shows that exergy efficiency greater than 20% is attainable. In this condition an optimum HTF inlet temperature to the receiver is found to be approximately 310 K. The intensity of solar irradiation has significant effect on the optimum HTF mass flow rate. To achieve the maximum exergy efficiency, depending on solar intensity, the optimum HTF mass flow rate must be selected from optimization results.

An experimental investigation is conducted to evaluate the performance, combustion, and emission characteristics of a diesel engine using cerium oxide (${\mathrm{CeO}}_2$) nanoparticles as diesel fuel additives. Using cetyl trimethyl ammonium bromide (CTAB) as the cationic surfactant and with ultrasonic vibration, ${\mathrm{CeO}}_2$ nanoparticles at dosing levels of 50 and $100\mathrm{mg}/\mathrm{L}$ can be stably and uniformly dispersed in diesel. Physically, the mixing of fuel blends with air is enhanced by microexplosion events because of the large surface-volume ratio and intensified thermal transmissibility of nanoparticles. Moreover, chemically, ${\mathrm{CeO}}_2$ in diesel fuel plays a positive role in the dehydrogenation reaction at a high temperature because of its excellent redox ability. As a result, the addition of $\mathrm{nano}\text{-}{\mathrm{CeO}}_2$ to neat diesel (50 and $100\mathrm{mg}/\mathrm{L}$) leads to a gradual increase in the cylinder pressure compared with the reference neat diesel. Meanwhile, the ignition of fuel blends with a high dosing level of $\mathrm{nano}\text{-}{\mathrm{CeO}}_2$ occurs earlier by approximately 1.2° crank angle (CA) and 1.8°CA, respectively. At full load, the effective thermal efficiencies for $\mathrm{nano}\text{-}{\mathrm{CeO}}_2$ fuels are augmented by approximately 1.7 and 2.3%. Because of the distinctive merits of $\mathrm{nano}\text{-}{\mathrm{CeO}}_2$ in promoting fuel atomization and its favorable intrinsic catalytic effect, the level of harmful pollutants (such as HC, CO, ${\mathrm{NO}}_{\mathrm{x}}$, and soot) in exhaust gases is appreciably reduced to varying degrees.

The integration of renewable energy sources (RE) and electric vehicles (EV) into the low voltage (LV) networks can create a number of power quality issues. RE or EV can cause voltage unbalance and low power factor when it injects or absorbs real power from the network. The energy storage system can be connected to the network to manipulate the power flow from or to those devices with the use of reactive power as a complementary support, hence correcting the voltage unbalance and power factor effectively without wasting any generated energy. To be able to correct the voltage unbalance and power factor effectively under the intermittent power of RE and EV, a novel fuzzy controller is developed and implemented in the energy storage to manipulate the flow of real and reactive power between the energy storage and the network based on the network conditions. The fuzzy controller is able to reduce any voltage excursions with the use of real and reactive power from the energy storage, hence reducing the voltage unbalance and improving the power factor. Numerous experiments have been carried out to verify the effectiveness of the fuzzy controller. The experimental results show that the voltage unbalance and power factors are constantly maintained below the thresholds under the high intermittent power output of the photovoltaic systems.

Gasification of high-ash coal in dry and slurry entrained flow gasifiers is investigated through equilibrium modeling. Effects of oxygen- and steam-to-coal mass flow rate ratios in a dry-fed gasifier and also the effect of water concentration in slurry on composition, temperature, heating value, and cold gas efficiency are studied. It is observed that adding steam to the gasifier reduces oxygen consumption, and the optimum ratio of oxygen-to-coal mass flow (O/F) decreases. At high enough O/F ratios, the steam-to-coal mass flow (S/F) and water-to-coal mass flow (W/F) ratios have no significant influences on gasifier efficiency. It is also observed that for coal, which has a high ash content, dry-fed gasification is preferable. In this type of gasifier, optimum O/F and S/F ratios with respect to cold gas efficiency are determined to be 0.5 and 0.8, respectively. Simulation of the integrated gasification combined cycle (IGCC) in Thermoflow indicates that, for a typical 450-MW combined cycle, $56.6\mathrm{kg}/\mathrm{s}$ of coal is required to produce a net power of 385 MW.

Biomass gasification shows a great potential to displace fossil fuels. In this study, the gasification of pelletized hard wood using a 10 kW downdraft gasifier is investigated. The variations of pressure and temperature parameters during the gasification process with air as a reagent medium were controlled. The gasifier started in continuous mode to burn the wood pellet feedstock. The results from the continuous mode indicate average temperatures of 838 and 754°C for combustion and reduction zones inside the gasifier, respectively, which shows a low temperature gasification process. Moreover, the pressure in the combustion zone varied on average from $-1.30$ to $-1.64\mathrm{kPa}$, while the pressure on top of the main reactor showed average variation of less than 0.07 kPa. The pressure drop is assumed to be caused by bridging of the feedstock, which results in a large part of the feedstock to not flow and be burnt inside the reactor. The shape of feedstock is theorized to be the major reason for the feedstock to bridge, with air leaks in the reactor resulting from sealing challenges intensifying the problem.

Because today’s power systems encounter so many uncertainties, probabilistic methods, such as probabilistic power flow (PPF), are useful to analyze the systems. One of these methods is Monte-Carlo Simulation (MCS), which has the ability to consider all uncertainties, including renewable energy power production, load, and random outages of components. In this paper, the proposed method is based on MCS and data clustering to improve drawback of MCS, which include high burden of computations. The proposed method cannot only reduce the runtime, but also considers correlation between load and wind power generation (WPG). This correlation would be important to power systems having large-scale wind farms (WFs). The proposed method first was validated by applying it on an IEEE 24-bus reliability test system (RTS). Then the modified version of the method, which can model outages of components, was implemented by using analysis software on a power system that is an actual bulk power system. To demonstrate importance of applying the proposed method, the method was implemented on the system two times. For the first time, the power system was analyzed in the presence of a WF; in the second one, the power system was analyzed such that conventional power plants were replaced with the WF. The results show how much is necessary to apply the probabilistic power flow method on power systems, including WFs.

Utilization of blended coal has been a great issue due to the increasing off-specification coals received in power plants, while the reduction of nitrogen oxide is also attracting extensive attention in China. This study deals with the effect of volatile-char interaction on nitrogen oxide emission during combustion of blended coal using a specially designed tubular multilayer reactor to achieve the separate combustion of volatile and char in a rapid succession. The volatile-char interaction can promote NO reduction at low temperature, while it could give rise to more ${\mathrm{N}}_2\mathrm{O}$. The temperature shows a nonmonotonic influence on the conversion of fuel nitrogen. The conversion of volatile nitrogen to NO of blended coal has slight relevance to blending ratio and oxygen content, while the case for char $\mathrm{N}$ is significantly different. High oxygen content can promote the transformation from NO to ${\mathrm{N}}_2\mathrm{O}$ on char surfaces. The interaction between component coals mainly occurs on char during combustion of blended coals. The present study provides insight into the possible interactions on nitrogen oxide release and further ${\mathrm{NO}}_{\mathrm{x}}$ reduction in blended coal-fired power plants.

This paper proposes a novel method for transmission loss allocation in restructured power systems. It is based on circuit laws and the orthogonal projection theory. In this method, the current flow in each branch is divided into two components. The first one is due to the power transfer from generators to loads. The second component is due to the voltage differences between generators’ buses. The later currents are called no-load or circulating currents. These two current components are computed by using the superposition principle. The contribution of each load and generator to power losses in each branch of the network is derived analytically. Hence, the share of each load or generator in the overall transmission network losses is estimated. Furthermore, the impact of bilateral and multilateral contracts is incorporated in the power loss allocation algorithm. The contribution of each contract to the total transmission system power loss is estimated accurately. The method also takes into account the time variation of loads and wind generation. The proposed method is applied to two test systems and compared to the prorate, game theory, and $Z$-bus approaches.

Climate change has raised consciousness of the need to use cleaner energy instead of fossil fuels. Meanwhile, a change of consciousness regarding resource use has to be achieved, which can be triggered by energy consumption monitoring studies that also provide useful recommendations for energy saving. Over time, researchers have identified behaviors by monitoring energy consumption in households, but these studies are usually limited to the number of monitored households and/or to the geographical region in which the monitoring takes place. In this research work, a study with a global reach is proposed to mitigate these limitations. Using a hierarchical clustering algorithm, three distinct groups were identified using the collected data, representative of distinct behaviors. The results illustrate several behaviors regarding energy consumption, like cold temperatures, seasonal behaviors, wake up hour, stay-at-home periods, and standby device consumption.

Using artificial intelligence (AI) models, cost effective electricity meter, and easily accessible weather data, this paper discusses a methodology for improved prediction of hourly residential space heating electricity use. Four AI models [back propagation neural network (BPNN), radial basis function neural network (RBFNN), general regression neural network (GRNN), and support vector regression (SVR)] were used for predicting hourly residential heating electricity use. For this study, a typical single-family house was used to obtain the data used for AI prediction models. Results showed SVR’s ability to predict hourly residential heating electricity use was better when compared with other AI models. Furthermore, through comparison of prediction performance in different time periods, additional investigation was conducted to evaluate the effect of dynamic human behaviors on the prediction accuracy of the AI models. Results revealed that dynamic human behaviors have a negative effect on the prediction performance.

In this paper, the mathematical model of the intermediate band quantum dot solar cell (IBQDSC) is investigated by using one and two intermediate bands (IBs). The IBs arise from the quantum dot (QD) semiconductor material within the barrier bandgap energy. Some factors, such as the thickness of the quantum dot ($T_{\mathrm{QD}}$) and the thickness of the barrier or inter-dot distances between quantum dots ($T_B$), are studied to show their influence on the performance of the IBQDSC. In the proposed model, the cubic shape of QDs from ${\mathrm{InAs}}_{0.9}{\mathrm{N}}_{0.1}$ and the barrier or bulk semiconductor material from ${\mathrm{GaAs}}_{0.98}{\mathrm{Sb}}_{0.02}$ are utilized. The time-independent Schrödinger equation is solved by employing the Kronig-Penney model. From the obtained results, after a homogenous range of the $T_{\mathrm{QD}}$ and $T_B$ is assigned for each one IB (1IB) and two IBs (2IBs) quantum dot solar cells (QDSCs), various comparative studies between the induced efficiency and the parameters of 1IB and 2IB QDSCs are investigated for one and maximum sun concentrations (MSCs). Consequently, reassigned ranges of the $T_{\mathrm{QD}}$ and the $T_B$, according to the type of IBs and sun concentration, are determined. The $T_{\mathrm{QD}}$ is an essential parameter for determining the number, location, and thickness of IBs into the QDSC. The small variation of $T_B$ is noticeable for each type of IBQDSC at different sun concentrations. Consequently, the induced values of the 1IB energy width ($\mathrm{\Delta }$) and the 2IBs energy widths (${\mathrm{\Delta }}_1$ and ${\mathrm{\Delta }}_2$) are determined. The value of $\mathrm{\Delta }$ is held constant, whereas the values of ${\mathrm{\Delta }}_1$ and ${\mathrm{\Delta }}_2$ are changed according to the solar cell (SC). However, the difference in the value of ${\mathrm{\Delta }}_2$ is large and noticeable. The $T_{\mathrm{QD}}$ and $T_B$ values, which achieve the optimum efficiency, are varied from 2.1 and 2.5 nm to 2.4 and 2.3 nm for the 1IB QDSC at one sun to MSC, respectively. The $T_{\mathrm{QD}}$ and $T_B$ values are also varied from 5.3 and 3 nm to 5.25 and 2.09 nm for the 2IBs QDSC at one sun to MSC, respectively. One can notice that, in the case of 2IBs, an improvement into the efficiency is achieved. The optimum efficiencies of the 1IB QDSC and 2IBs QDSC for the model under study are 42.39 and 58.01% at one sun and 66.21 and 73.55% at MSC, respectively.

Impeller trimming can improve the hydrodynamic performances of the centrifugal pump and expand the application range of the pumps. However, most researches focus on single-impeller cutting method; the literature slightly lacks a comparison of the different impeller trimming methods, which is very important in deciding on an impeller trimming method. In this paper, by taking the centrifugal pump as the research object, the accuracy of computational fluid dynamics (CFD) was verified by comparing experimental results and those of the numerical simulation. On the basis of impeller straight trimming, miscut, and triangle trimming methods, a new unconventional parabolic impeller trimming method was put forward. In different trimming sizes and operating conditions, performance curves of four impeller trimming methods were compared to get several different trimming models. By researching the flow field of centrifugal pump, the change reasons of centrifugal pump’s performance curves were further revealed. The turbulent kinetic energy distribution and pressure distribution of the four trimming methods at best efficiency points (BEPs) were compared. The results showed that impeller trimming can improve pressure distribution of the impeller outlet, decrease shaft power, and increase energy saving.

This paper presents a two-dimensional analytical method for investigating the triple-flame temperature profile in a microcombustor. For this purpose, the microcombustor chamber is divided into a preheat and a reaction zone and the role of heat recirculation from the flame zone into the preheat zone is taken into account in this research. It is indicated that the maximum temperature is strongly dependent on this phenomenon. This analysis is done by applying the energy conversion equation in each zone and then solving these equations along with required boundary and matching conditions by the use of partial differential equation method. The outcome of this research leads to the temperature profile in preheat and flame zone, and also the effects of combustor characteristics on the temperature distribution.

The layout of an air-cooled steam condenser (ACSC) has a great impact on a power plant’s operation. This is owed to the fact that the performance of the condenser and subsequently of the whole power plant is strongly affected by meteorological conditions. Hence, it is of great significance to determine the optimal design of wind angle that gives a higher performance for an air-cooled power plant. This study applies an existing numerical model in order to investigate the wind angle’s impact on the performance of an air-cooled steam condenser, as well as on the whole power plant. Moreover, the optimal design of wind angle is obtained based on the corresponding sensitivity analysis. Finally, the benefit to the power plant’s performance at the optimal-design wind angle is calculated through the comparison with the actual design values at a wind angle of $\beta =22.5°$. The obtained results show that the net power and thermal efficiency can be improved by amplitudes of 1.2 and 0.37%, respectively, at the wind angle of $\beta =90°$, which should be proposed as the design wind angle for air-cooled power plants.

Low-infrared-emissivity coatings were prepared using metallic particles (including Cu, Al, Ni, Ag, etc.) and an ethylene-propylene-diene monomer (EPDM) binder. The effects of size, shape, morphology, and content of metallic particles on infrared emissivity of the coatings were systematically investigated. The principles of the low-infrared-emissivity and low-solar-reflectance coatings are discussed in terms of reflection, emissions, and chemical structure. The thermal insulation performance of composite coatings is studied via a simulation model. Mechanical properties of composite coatings are studied by using circle-cut test and impact strength test. The composite coatings are also tested for corrosion behavior with potentiodynamic polarization. The results indicate that when the Cu particles and Al particles are flaky and high-leafing, they have the minimum coating emissivity, exhibiting infrared emissivity values of 0.33–0.40 and solar reflectance values of 0.38–0.53. The formation of low-infrared-emissivity coatings depends highly on the size and shape of the metallic particles. A simulation model is proposed to account for thermal insulation properties of the coatings, which indicates that an EPDM/Cu-powder coating achieves good thermal insulation performance, with a 4°C relative temperature drop. The low-infrared-emissivity composite coatings also show excellent corrosion resistance and mechanical performance.

The centrifugal impeller is one of the most critical aerodynamic parts of centrifugal compressors. The previous experimental investigation demonstrated that the fully shrouded impeller is better in terms of efficiency whereas the unshrouded configuration is typical for wide flow range. To compromise between the high efficiency and wide flow range requirements, partially shrouded impellers have been developed, attaining reductions in the efficiency loss due to tip clearance while keeping a sufficient surge margin. However, the selection of the optimum shrouded percentage is influenced by several variables including stage efficiency, pressure losses coefficient, manufacturing cost, required power cost, resonance frequency, and stable operating range influenced. Hence, an optimization is required to compromise between these parameters to ensure better performance. This paper will introduce a new empirical approach to model the effect of shrouded percentage on these parameters which will help to specify the optimum configuration at an early preliminary design stage based on the sort of the application and according to the expected variation in the operating conditions. This model has been examined at high and very low flow coefficients and Mach numbers operating conditions, and the obtained parameters are compared with the computational fluid dynamics (CFD) simulation results and the recorded measured data in order to emphasize the validity of the new method. The conducted comparison revealed a good agreement between the obtained parameters by the new model and those derived numerically and experimentally with a maximum deviation of around $\pm 3.0\%$. One of the main features of the developed method over the CFD approach is the fact that it does not require deep knowledge about the stage geometrical features; thus, it can be used in the early preliminary design process. Moreover, the included optimization emphasizes the need for a compromise decision in order to select the impeller configuration.

To increase power output and outlet fluid temperature from a solar trough concentrating photovoltaic/thermal (CPV/T) system, a system with a solar parabolic trough concentrating PV/T unit as the first stage and a solar trough concentrating collector as the second heating stage was suggested and tested. In the second stage, a metal cavity receiver was employed to collect solar radiation concentrated by the parabolic trough to heat the fluid from the CPV/T unit of the system. The output characteristics of the CPV/T unit with $1.8{\mathrm{m}}^2$ mirrors, and systems with a CPV/T unit of $1.8{\mathrm{m}}^2$ aperture area and a concentrating collector with respective aperture area of 15 and $30{\mathrm{m}}^2$ were tested, respectively. Also, the performance of the system with a CPV/T unit of $1.8{\mathrm{m}}^2$ aperture area and a concentrating collector of $30{\mathrm{m}}^2$ aperture in the cases of the working fluid being one-pass and continuous circulation through solar cells and cavity receivers were analyzed. The results showed the overall output performance in the one-one flow mode was higher than that in the continuous circulation mode, but the outlet fluid temperature in the latter case was higher, and fluid temperature of 62.8°C in the storage tank of the system was measured after 30 min of operation.

This paper seeks to examine the characteristics and importance of the heat transfer phenomena in combustion chamber walls. In-cylinder pressure and combustion chamber wall temperature ($T_w$) were measured under motored and fired conditions in a spark-ignition (SI) engine. Parameters were measured at a constant engine speed (1,500 rpm), at different ignition timings, and same $\varphi =1.0$, separately for LPG, gasoline, or hydrogen. Cooling loss and heat release were investigated with different heat transfer equations for all three fuels. Also, the cooling loss of hydrogen was compared with fossil fuels to investigate the differences in heat transfer. The values for a correction constant required for each fuel were determined using different heat transfer equations. The findings of this study suggest that the proposed model has better prediction results than Eichelberg’s heat transfer coefficient equation and Burnt’s specific heat ratio equation for all ignition timings and fuels.

Particulate matter (PM) emission has been a concern in recent years because of its impact on the atmospheric environment and human health. Recently the dual-fuel premixed charge compression ignition (PCCI) combustion strategy has become a popular option of reducing PM emissions from compression-ignition engines. In the current paper, the variations of PM emissions from the diesel–dimethyl ether (DME) dual-fuel premixed charge compression ignition combustion engine are investigated under the various input DME energy ratios, diesel injection timings, speeds, and loads. An electrical low pressure impactor (ELPI) is used for characterizing the particle number/mass and size distribution. The particulate number and mass concentrations for DME-diesel dual-fuel premixed charge compression ignition operation are lower than those of conventional direct-injection compression ignition (DICI) operation and reduce with a rise of port DME ratio under all operating conditions because of oxygen content and no C-C bond in DME molecular. The injection timing and speed also influence the particulate number and mass concentrations from the DME-diesel PCCI engine. Moreover, the particulate number and mass concentrations increase significantly with an increase in load for both conventional diesel operation and DME-diesel dual-fuel PCCI operation.

Management measures for peak-load shifting are employed to alleviate power shortages during the peak hours in some countries with power-supply shortages, such as China. One of the most popular measures is to rank the electricity users with respect to their relative importance in the society. In ranking the sequence, the decision maker may encounter difficulties because the types of data employed for this purpose are not consistent. Thus, a ranking method capable of handling different types of data is necessary and presented in this paper. To prioritize electricity users in a reasonable manner, an evaluation system for the purpose of peak-load shifting is established from three aspects: economic, social, and environmental impacts. Then a mixed-data dominance method is employed in this work to determine the comprehensive closeness degree of each user under each index, and an optimal comprehensive weight model is then presented with both the subjective weights and objective weights. Based on the attained optimal comprehensive weight and the comprehensive closeness degree, the weighted closeness degree of each electricity user can be calculated and the final ranking result for all electricity users obtained. The proposed approach is demonstrated by actual data of Guangzhou city in China.

The paper reports on the utilization of liquefied petroleum gas (LPG) as a primary fuel with diesel as an ignition pilot fuel in a direct injection diesel engine. A detailed account on brake-specific fuel consumption (BSFC), exhaust emissions, and combustion characteristic parameters in a wide range of engine load conditions with different LPG substitution ratios (SR) has been presented. From the results it was observed that, at low engine loads, the peak cylinder pressure, pressure rise rate, and heat release rate decreased with the increase of LPG SR, and at high engine loads, these parameters of dual fuel with a LPG SR of 25% were highest. The ignition delay period increased with the increase of LPG SR, and the combustion duration also increased with the increase of LPG SR at low engine loads, but firstly increased and then decreased at high engine loads. At each engine load, there existed a LPG SR at which the BSFC was lowest. The BSFC of dual fuel was higher than that of diesel fuel at low engine loads and lower at high engine loads. With the increase of LPG SR, hydrocarbon and carbon monoxide emissions evidently increased, but smoke emission decreased. Nitrogen oxide emissions of dual fuel were lower than those of diesel fuel and hardly varied with the increase of LPG SR.

The prediction of pollutant emissions and fuel consumption under real operating conditions of any motor vehicle requires the use of complex mathematical models and experimental tools. In the present research, biharmonic maps (BM) were used to predict NOx (nitrogen oxides) emissions and relative fuel–air ratio (Fr) of a passenger city bus. For the collection of experimental data, an instrumented city bus was tested during real passenger transportation. The data were classified into four dynamic sequences: acceleration, idling, deceleration with fuel consumption, and deceleration without fuel consumption. Among them, the acceleration sequence was selected due to high NOx emissions and high fuel consumption. Experimental results were in good agreement with BM predictions. Significant parameters for predicting NOx concentration were vehicle velocity and relative fuel–air ratio (Fr). While for predicting Fr, significant parameters were the exhaust gas flow (EGF) rate, vehicle velocity, and NOx concentration, BM is a good technique for predicting NOx emissions and Fr of a city bus under transient operation.

This work presents a thermodynamic analysis of a triple-level pressure combined power plant with supplementary firing. The supplementary firing is a technological development for improving and increasing the output power of a combined-cycle (CC) power plant. In Mexico, there is a plant operating with this configuration, which generates a net power of 1,170 MW, with a power ratio of the gas turbine (GT) to the steam turbine (ST) of $1.35:1$. This plant is composed of four combined-cycle units with supplementary firing, each providing an output power of 292.5 MW. The energetic and exergetic analyses of the combined cycle with and without supplementary firing are pursued, taking into account the combustion process of natural gas and humid air. These analyses are also carried out for the heat recovery steam generator, considering the waste gases of the gas turbine and of the supplementary firing as the energy sources. The obtained results are fuel, steam, and humid air flows; excess of air; gas and steam turbines output works and powers; thermal efficiencies; irreversibilities; and exergetic efficiencies of the main components of the plant. This analysis is carried out, considering the following ambient conditions: 23°C, 101.3 kPa (1.013 bar), and 90% relative humidity. The computed results show that the CC with supplementary firing increased the output power by 12.2% and the efficiency of the heat recovery steam generator by 2.07% although the thermal efficiency of the combined cycle decreased by 1.4% compared with the scenario without supplementary firing.

In islanding microgrids (MGs), distributed generation units are in charge of controlling voltage, frequency, and current of the grid on their own without any assistance from the main grid. Therefore, it is of utmost importance to select and design a controller that is robust against disturbances and load variations. In this study, a new sliding mode controller with a rotating reference voltage algorithm is proposed that improves the load sharing between distributed generators (DGs) in an islanded mode MG. In the proposed algorithm, in order to improve the performance and convergence rate of the controller, the amplitude of the reference voltage signal of the controller is adaptively modified. As a case study, the proposed strategy is studied based on the assumption that there are three DGs in the grid. One of the DGs is in charge of regulating voltage and frequency based on a reference signal, and the two other DGs are responsible for load sharing and loads the current control mode. The MG under study consists of three low-voltage distributed generation units operating in parallel mode. In order to have a realistic case study, it is assumed that the MG consists of different types of loads such as balanced/unbalanced resistive, inductive, and nonlinear loads. The extensive simulations are applied to indicate that the proposed framework is able to provide more desirable total harmonic distortion (THD), lower steady-state error, and faster response compared with classic sliding mode controllers.

Residential building energy consumption in rural areas of China is changing from noncommercial energy to commercial energy, which is detrimental to sustainable development. In order to utilize renewable energy to satisfy the energy demands of farmers in cold regions of China, a hybrid energy supply system of heat, electricity, and biogas and external wall insulation were developed and constructed for a typical rural residential building, and an experimental study and analysis has been conducted to evaluate their performance. The results showed that (1) the accumulated heat energy supplied from solar energy was 11,619 MJ, and the corresponding proportion was 64.6%; (2) the total biogas yield satisfied the cooking fuel demands of the residents; (3) the electricity generated was sufficient for the hybrid system, but the excess was wasted due to a mismatch between the time of electricity generation and utilization; and (4) the annual energy saving rate was 85% and the static payback period was 7 years. Also, some crucial issues are discussed for the improvement of room temperature and utilization efficiency of solar energy.