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We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs.

A large body of the forecasting literature so far has been focused on forecasting the conditional mean of future observations. However, there is an increasing need for generating the entire conditional distribution of future observations in order to effectively quantify the uncertainty in time series data. We present two different methods for probabilistic time series forecasting that allow the inclusion of a possibly large set of exogenous variables. One method is based on forecasting both the conditional mean and variance of the future distribution using a traditional regression approach. The other directly computes multiple quantiles of the future distribution using quantile regression. We propose an implementation for the two methods based on boosted additive models, which enjoy many useful properties including accuracy, flexibility, interpretability and automatic variable selection. We conduct extensive experiments using electricity smart meter data, on both aggregated and disaggregated scales, to compare the two forecasting methods for the challenging problem of forecasting the distribution of future electricity consumption. The empirical results demonstrate that the mean and variance forecasting provides better forecasts for aggregated demand, while the flexibility of the quantile regression approach is more suitable for disaggregated demand. These results are particularly useful since more energy data will become available at the disaggregated level in the future.

Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality- the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.

Lowering the exergy content of heat required for heating purposes decreases the primary energy consumption. District heating systems are often an important link between facilities that generate heat with low exergy content and consumers. Exergetic efficiency of heat distribution is an important performance criterion in heat supply to consumers. It can serve as a criterion for optimization, towards a more sustainable distribution-network design and operation. This paper presents a methodology for an exergy-based distribution-network analysis in a district heating system. Criteria for performance evaluations are defined. They can be used to evaluate heat supply to different points in the network, or individual system components. A case study is performed on an existing district heating system. Energetic and exergetic efficiencies of supply lines are analyzed. Exergy destructions and exergy losses are studied. Large differences in efficiency of heat supply to different points in the network are discovered. Over-dimensioned parameters of the distribution network are investigated.

Integrated energy-economic modelling is needed to support the development of energy and climate policies. This study asserts that it is important to consider a system dynamics modelling approach that includes dynamics, endogenous treatment of uncertainty and risks, and both aggregate economic and disaggregate technical or engineering levels of analysis. The study examined the economic growth and the factors of production, elasticities, macro- and technical substitutability; energy cost shares, heat engine efficiencies and energy services efficiencies. Emphasis was laid on the support of the future development of integrated energy-economic models covering (a) the key factors or components; (b) the relationships among these components; (c) a quantification of parameters; and (d) the implications for the development of an integrated energy-economic system dynamics model. The study suggested the following: a non-linear relationship in production and consumption; large variations among price and income elasticity values across time frames, across countries and regions, and across energy goods; a far from perfect substitution among factors of production and among energy goods on a macro-level; technical/engineering limits to substitution on a micro-level; and engineering and behavioural limits on what can be achieved with increased efficiencies. The study argues that integrated energy-economic modelling intensifies the accounting for the factors, relationships, quantifications, and implications, and that this practice allows for such models to describe a complex, emergent energy-economic reality that informs better energy policy.

The ability to predict the expected internal behaviour of a given solid-propellant rocket motor under transient conditions is important. Research towards predicting and quantifying undesirable transient axial combustion instability symptoms typically necessitates a comprehensive numerical model for internal ballistic simulation under dynamic flow and combustion conditions. On the mitigation side, one in practice sees the use of inert or reactive particles for the suppression of pressure wave development in the motor chamber flow. With the focus of the present study placed on reactive particles, a numerical internal ballistic model incorporating relevant elements, such as a transient, frequency-dependent combustion response to axial pressure wave activity above the burning propellant surface, is applied to the investigation of using aluminum particles within the central internal flow (particles whose surfaces nominally regress with time, as a function of current particle size, as they move downstream) as a means of suppressing instability-related symptoms in a cylindrical-grain motor. The results of this investigation reveal that the loading percentage and starting size of the aluminum particles have a significant influence on reducing the resulting transient pressure wave magnitude.

Temperature plays a key role in driving the electricity demand. We adopt the “recency effect”, a term drawn from psychology, to represent the fact that the electricity demand is affected by the temperatures of the preceding hours. In the load forecasting literature, the temperature variables are often constructed in the form of lagged hourly temperatures and moving average temperatures. In the past, computing power has limited the amount of temperature variables that can be used in a load forecasting model. In this paper, we present a comprehensive study to model the recency effect using a big data approach. We take advantage of modern computing power to answer a fundamental question: how many lagged hourly temperatures and/or moving average temperatures are needed in a regression model in order to capture the recency effect fully without compromising the forecasting accuracy? Using a case study based on data from the load forecasting track of the Global Energy Forecasting Competition 2012, we first demonstrate that a model with the recency effect outperforms its counterpart (a.k.a. Tao’s Vanilla Benchmark Model) by 18% to 21% for forecasting the load series at the top (aggregated) level. We then model the recency effect in order to customize load forecasting models at the bottom level of a geographic hierarchy, again showing a superiority over the benchmark model of 12% to 15% on average. Finally, we discuss four different implementations of the recency effect modeling by hour of a day. In addition, this paper also presents two interesting findings: 1) the naive models are not useful for benchmark purposes in load forecasting at aggregated level due to their lack of accuracy; and 2) slicing the data into 24 pieces to develop one model for each hour is not necessarily better than building one interaction regression model using all 24 hours together.

Since recently Mozambique is actively developing its large reserves of coal, natural gas and hydropower. Against this background, we present in this paper the first integrated long-run scenario model of the Mozambican energy sector. Our model makes use of the LEAP framework and is calibrated on the basis of recently developed local energy statistics, demographic and urbanization trends as well as cross-country based GDP elasticities for biomass consumption, sector structure and vehicle ownership. We develop four scenarios to evaluate the impact of the anticipated surge in natural resources exploration on aggregate trends in energy supply and demand, the energy infrastructure and economic growth in Mozambique. Our analysis shows that until 2030, primary energy production is likely to increase at least six-fold, and probably much more. This is roughly 10 times the expected increase in energy demand; most of the increase in energy production is destined for export. As a result, Mozambique is rapidly developing into an important player at international energy markets. Therefore, a major challenge for energy policy in Mozambique is to strike a balance in meeting domestic and international demand for energy, such that energy production benefits the entire Mozambican population.

International audience; Over the past decade, the rapid increase in shale gas and shale oil production in the United States has profoundly changed energy markets in North America, and has led to a significant decrease in American natural gas prices. The possible existence of large shale deposits in continental Europe, mainly in France, Denmark, the Netherlands and Germany, has fostered speculation on whether the U.S. shale revolution could be duplicated in Europe. However, a number of uncertainties, notably geological, technological, regulatory, and relating to public acceptance make this possibility unclear. We present a techno-economic model of shale gas production amenable to direct estimation on historical production data to analyze the main determinants of the profitability of shale wells and plays. We contribute an in-depth analysis of an extensive production dataset covering 40,000 wells and accounting for nearly 90% of shale gas production in the six main plays of the continental United States from 2004 to 2014. We combine this analysis with a discussion of the main differences between the American and European contexts to calibrate our model and conduct Monte-Carlo simulations. This enables us to estimate the distribution of breakeven prices for shale gas extraction in continental Europe. We find a median gross breakeven price before taxes and royalties of $10.1 per MMBtu. This would make extraction unprofitable in Europe in the current natural gas price environment, with < 47% of the well distribution reaching breakeven at the mean 2011–2016 price. Sensitivity analysis reveals that the breakeven price is most sensitive to initial production rate, drilling and completion costs, and decline rates. We also find that the economic outlook would be slightly better if the productivity of European shale gas plays was comparable to that of U.S. plays of similar depth, but not significantly so. We conclude that under assumptions calibrated on existing shale gas production data, it is unlikely that the U.S. shale revolution can be duplicated in continental Europe.

The aim of this paper is to analyze the impact of the so-called “shale oil revolution” on oil prices and economic growth. We employ a general equilibrium model of the world oil market in which Saudi Arabia is the dominant firm, with the rest of the producers as a competitive fringe. Our results suggest that most of the expected increase in US oil supply due to the shale oil revolution has already been incorporated into prices and that it will produce an additional increase of 0.2% in the GDP of oil importers in the period 2010–2018. We also employ the model to analyze the collapse in oil prices in the second half of 2014 and conclude that it was mainly due to positive unanticipated supply shocks.

To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a new approach to assess the local wind energy potential. First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.

This paper forecasts the spatial distribution of Danish husbandry production from 2009 until 2025, allowing an assessment of the potential future biogas production at a local level. The study builds on a unique time series data set (1999–2009) for the number of livestock units (including piglets, finishers, sows, dairy cattle and young stock) measured by 1 km 2 grid cells for the whole of Denmark. A Markov Chain Model (MCM) was applied to estimate transition probabilities for the future livestock intensity composition, based on state classes reflecting Danish agricultural legislation. The modelled transition probabilities were assumed to be stationary. This assumption was tested and good fit between the model and the data was found for all state classes, except for those farms which are in the largest state class. Regional differences in development trends were documented, supporting the argument of disaggregating data by georegion and livestock type. Throughout the period 2009–2020 slurry based biomass is expected to decrease by approx. 10% in Denmark. The largest changes are found in the Northern and Western parts of the country whereas the most frequent changes are expected to occur in the central parts of the country. The strategic objective of the model and its application within spatial assessment of the potential of biogas production is to form the basis for a location analysis for future biogas plants.

A nonrenewable resource extraction model is embedded within a lake model of industry-specific employment, where flows to (from) employment from (to) unemployment depend on the attachment (separation) rate. The attachment and separation rates vary with resource extraction, and the results, driven by the rate of extraction and the remaining resource stock, indicate that changes in the stationary employment level can be positive, negative, or zero. There is a range where the separation rate is decreasing (increasing) and the attachment rate is increasing (decreasing), and the change in employment is determined by the combined effect of these changes. Using data on coal production and employment in the U.S. as a guide, simple calculations provide a range of years beyond 2013 when it is expected that peak employment will be reached in the Marcellus Shale, and the results suggest that employment gains will likely continue for at least a decade.

The countries of the Gulf Cooperation Council (GCC) have both large fossil fuel resources and vast renewable energy potentials. Here, we investigate in a literature meta-analysis and a survey, whether there is a need for renewables in the GCC, what barriers and risks presently deter investments, and what possible policy-solutions could be. We find that there is a long-term need for renewables, to diversify the economy and prepare for a post-fossil fuel era. In the short term, two main obstacles deter investments: inefficient bureaucracy, and the combination of fossil fuel/electricity subsidies and the absence of renewable energy support. Removing fossil fuel and consumption subsidies or introducing a support scheme could make investments in renewables profitable. Eliminating energy subsidies appears particularly beneficial to the economic outlook but this seems particularly difficult to implement, due to the political economy of rentier states. Increased bureaucratic transparency and efficiency is needed, so that potentially attractive investments can rapidly and predictably obtain the necessary permissions. Hence, the administrative and economic environment for renewable energy investments in the GCC is not right today, and no breakthrough is on the horizon, but there is a range of policy solutions to enable investments in the future., Energies, 8 (8), ISSN:1996-1073

This research is aligned with the engineering challenge of scaling-up individual battery cells into a complete energy storage system (ESS). Manufacturing tolerances, coupled with thermal gradients and the differential electrical loading of adjacent cells, can result in significant variations in the rate of cell degradation, energy distribution and ESS performance. The uncertain transition from cell to system often manifests itself in over-engineered, non-optimal ESS designs within both the transport and energy sectors. To alleviate these issues, the authors propose a novel model-based framework for cell-in-the-loop simulation (CILS) in which a physical cell may be integrated within a complete model of an ESS and exercised against realistic electrical and thermal loads in real-time. This paper focuses on the electrical integration of both real and simulated cells within the CILS test environment. Validation of the CILS approach using real-world electric vehicle data is presented for an 18650 cell. The cell is integrated within a real-time simulation model of a series string of similar cells in a 4sp1 configuration. Results are presented that highlight the impact of cell variability ( i.e. , capacity and impedance) on the energy available from the multi-cell system and the useable capacity of the physical cell.

The enzyme-assisted aqueous extraction of oil from wet microalgae was employed to avoid the energy consumption of a dewatering process. In this paper, oil-rich microalgae Scenedesmus sp. G4 was hydrolyzed by enzyme mixtures for oil extraction. The results showed that the algae concentration had the greatest influence on yield of extracted oil, and the temperature and the ratio of enzyme mixtures affected the results as follows: the maximum yield of oil extracted from Scenedesmus sp. G4 reached 86.1% under optimal conditions with an algae concentration at 2.5 g/L, temperature 30/50 °C, pH 3.5/4.5 and a cellulase:pectinase:hemicellulase ratio of 1:1:1 or 1:2:1 (w/w/w). The results also indicated that the enzyme mixtures had a significant impact on the integrity of microalgae cells and the crystallization index increased from 30.7% to around 36.0% after enzymatic hydrolysis treatment. The cell wall of Scenedesmus sp. G4 has a high content of cellulose Iα and low crystallization, which is beneficial to the oil extraction by the enzyme-assisted hydrolysis method.

This study was conducted to develop an artificial neural network (ANN)-based prediction model that can calculate the amount of cooling energy during the setback period of accommodation buildings. By comparing the amount of energy needed for diverse setback temperatures, the most energy-efficient optimal setback temperature could be found and applied in the thermal control logic. Three major processes that used the numerical simulation method were conducted for the development and optimization of an ANN model and for the testing of its prediction performance, respectively. First, the structure and learning method of the initial ANN model was determined to predict the amount of cooling energy consumption during the setback period. Then, the initial structure and learning methods of the ANN model were optimized using parametrical analysis to compare its prediction accuracy levels. Finally, the performance tests of the optimized model proved its prediction accuracy with the lower coefficient of variation of the root mean square errors (CVRMSEs) of the simulated results and the predicted results under generally accepted levels. In conclusion, the proposed ANN model proved its potential to be applied to the thermal control logic for setting up the most energy-efficient setback temperature.

Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC) method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.

In the context of sustainable buildings, this paper investigates power flow management for an isolated DC microgrid and focuses on efficiency and energy cost reduction by optimal scheduling. Aiming at high efficiency, the local produced power has to be used where, when, and how it is generated. Thus, based on photovoltaic sources, storage, and a biofuel generator, the proposed DC microgrid is coupled with the DC distribution network of the building. The DC bus distribution maximizes the efficiency of the overall production-consumption system by avoiding some energy conversion losses and absence of reactive power. The isolated DC microgrid aims to minimize the total energy cost and thus, based on forecasting data, a cost function is formulated. Using a mixed integer linear programming optimization, the optimal power flow scheduling is obtained which leads to an optimization-based strategy for real-time power balancing. Three experimental tests, operated under different meteorological conditions, validate the feasibility of the proposed control and demonstrate the problem formulation of minimizing total energy cost.

This paper considers the problem of distributed frequency regulation based on the consensus control protocol in smart grids. In this problem, each system component is coordinated to collectively provide active power for the provision of ancillary frequency regulation service. Firstly, an approximate model is proposed for the frequency dynamic process. A distributed control algorithm is investigated, while each agent exchanges information with neighboring agents and performs behaviors based on communication interactions. The objective of each agent is to converge to a common state considering different dynamic load characteristics, and distributed frequency control strategy is developed to enable the agents to provide active power support. Then, the distributed proportional integral controllers with the state feedback are designed considering the consensus protocol with topology . The theory of distributed consensus protocol isfurther developed to prove the stability of the proposed control algorithm. Whenproperly controlled, the controllers can provide grid support services in a distributed manner that turn out the grid balanced globally. Finally, simulations of the proposed distributed control algorithm are tested to validate the availability of the proposed approach and the performance in the electrical networks.

With the increasing popularity enjoyed by ultra-micro scale turbomachinery, designers are often faced with severe challenges due to the substantial phenomenological difference between the low-Reynolds fluid-dynamics in rotating or strongly curved flows and the established knowledge acquired through decades of theoretical and experimental studies on medium and large-scale machines. The problem is complicated by the absence of an extended and reliable database that might be used for preliminary design and provide indications for scale-up or scale-down. As a result, custom-designed experimental campaigns are necessary that make the development of any new machine exceedingly costly. The situation has seen some improvement in recent years, after the publication of a sufficient number of experimental results and numerical simulations that pave the way towards a development of semi-empirical correlations. The purpose of this work is to present and discuss a preliminary and simple method to extend the currently available design maps into the small scale range (Re &lt, 105) by introducing in the Balje charts an efficiency correction that depends on the specific speed ns. The method results in a Stodola-like formula which originates a lower-than-standard Cordier curve on the classical Balje charts. A validation with some experimental results is also presented and discussed. Though the agreement is more than satisfactory, it must be stressed that the method provides only approximate results, and thus it must be considered as an evolving temporary solution, that needs to be updated as long as larger series of (numerical or physical) experimental results become available.

In this paper, we present the design and evaluation of a software-based wireless power transfer platform that enables the development of a prototype involving various open- and closed-loop power control functions. Our platform is based on a loosely coupled planar wireless power transfer circuit that uses a class-E power amplifier. In conjunction with this circuit, we implement flexible control functions using a National Instruments Data Acquisition (NI DAQ) board and algorithms in the MATLAB/Simulink. To verify the effectiveness of our platform, we conduct two types of power-control experiments: a no-load or metal detection using open-loop power control, and an output voltage regulation for different receiver positions using closed-loop power control. The use of the MATLAB/Simulink software as a part of the planar wireless power transfer platform for power control experiments is shown to serve as a useful and inexpensive alternative to conventional hardware-based platforms.

Inverter voltage control is an important task in the operation of a DC/AC microgrid system. To improve the inverter voltage control dynamics, traditional approaches attempt to measure and feedforward the load current, which, however, needs remote measurement with communications in a microgrid system with distributed loads. In this paper, a load current observer (LCO) based control strategy, which does not need remote measurement, is proposed for sinusoidal signals tracking control of a three-phase inverter of the microgrid. With LCO, the load current is estimated precisely, acting as the feedforward of the dual-loop control, which can effectively enlarge the stability margin of the control system and improve the dynamic response to load disturbance. Furthermore, multiple PR regulators are applied in this strategy conducted in a stationary frame to suppress the transient fluctuations and the total harmonic distortion (THD) of the output voltage and achieve faster transient performance compared with traditional dual-loop control in a rotating dq0 frame under instantaneous change of various types of load (i.e., balanced load, unbalanced load, and nonlinear load). The parameters of multiple PR regulators are analyzed and selected through the root locus method and the stability of the whole control system is evaluated and analyzed. Finally, the validity of the proposed approach is verified through simulations and a three-phase prototype test system with a TMS320F28335 DSP.

A linear function submission-based double auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP). This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor.

In this study we design and test a novel solar tracking generation system. Moreover, we show that this system could be successfully used as an advanced solar power source to generate power in greenhouses. The system was developed after taking into consideration the geography, climate, and other environmental factors of northeast China. The experimental design of this study included the following steps: (i) the novel solar tracking generation system was measured, and its performance was analyzed, (ii) the system configuration and operation principles were evaluated, (iii) the performance of this power generation system and the solar irradiance were measured according to local time and conditions, (iv) the main factors affecting system performance were analyzed, and (v) the amount of power generated by the solar tracking system was compared with the power generated by fixed solar panels. The experimental results indicated that compared to the power generated by fixed solar panels, the solar tracking system generated about 20% to 25% more power. In addition, the performance of this novel power generating system was found to be closely associated with solar irradiance. Therefore, the solar tracking system provides a new approach to power generation in greenhouses.

Biodiesel as a clean energy source could reduce environmental pollution compared to fossil fuel, so it is becoming increasingly important. In this study, we investigated the effects of different pilot injection timings from before top dead center (BTDC) and exhaust gas recirculation (EGR) on combustion, engine performance, and exhaust emission characteristics in a common rail diesel engine fueled with canola oil biodiesel-diesel (BD) blend. The pilot injection timing and EGR rate were changed at an engine speed of 2000 rpm fueled with BD20 (20 vol % canola oil and 80 vol % diesel fuel blend). As the injection timing advanced, the combustion pressure, brake specific fuel consumption (BSFC), and peak combustion pressure (P max ) changed slightly. Carbon monoxide (CO) and particulate matter (PM) emissions clearly decreased at BTDC 20° compared with BTDC 5°, but nitrogen oxide (NO x ) emissions increased slightly. With an increasing EGR rate, the combustion pressure and indicated mean effective pressure (IMEP) decreased slightly at BTDC 20° compared to other injection timings. However, the P max showed a remarkable decrease. The BSFC and PM emissions increased slightly, but the NO x emission decreased considerably.

Household energy consumption has been increasing in the last decades, the residential sector is responsible for about 40% of the total final energy use in Europe. Energy efficiency measures can both reduce energy needs of buildings and energy-related CO2 emissions. For this reason, in recent years, the European Union has been making efforts to enhance energy saving in buildings by introducing various policies and strategies, in this context, a common methodology was developed to assess and to certify energy performance of buildings. The positive effects obtained by energy efficiency measures need to be verified, but measuring and monitoring building energy performance is time consuming and financially demanding. Alternatively, energy efficiency can also be evaluated by specific indicators based on energy consumption. In this work, a methodology to investigate the level of energy efficiency reached in the Umbria Region (Central Italy) is described, based on data collected by energy certificates. In fact, energy certificates, which are the outcomes of simulation models, represent a useful and available tool to collect data related to the energy use of dwellings. A database of building energy performance was developed, in which about 6500 energy certificates of residential buildings supplied by Umbria region were inserted. On the basis of this data collection, average energy and CO2 indicators related to the building heritage in Umbria were estimated and compared to national and international indicators derived from official sources. Results showed that the adopted methodology in this work can be an alternative method for the evaluation of energy indicators, in fact, the ones calculated considering simulation data were similar to the ones reported in national and international sources. This allowed to validate the adopted methodology and the efficiency of European policies.

This paper presents a reinforcement learning (RL)–based energy management strategy for a hybrid electric tracked vehicle. A control-oriented model of the powertrain and vehicle dynamics is first established. According to the sample information of the experimental driving schedule, statistical characteristics at various velocities are determined by extracting the transition probability matrix of the power request. Two RL-based algorithms, namely Q-learning and Dyna algorithms, are applied to generate optimal control solutions. The two algorithms are simulated on the same driving schedule, and the simulation results are compared to clarify the merits and demerits of these algorithms. Although the Q-learning algorithm is faster (3 h) than the Dyna algorithm (7 h), its fuel consumption is 1.7% higher than that of the Dyna algorithm. Furthermore, the Dyna algorithm registers approximately the same fuel consumption as the dynamic programming–based global optimal solution. The computational cost of the Dyna algorithm is substantially lower than that of the stochastic dynamic programming.

Fiber-optic daylighting systems have been shown to be a promising and effective way to transmit sunlight in the interior space whilst reducing electric lighting energy consumption. To increase efficiency in terms of providing uniform illumination in the interior, the current need is to illuminate optical fiber-bundle with uniform light flux. To this end, we propose a method for achieving collimated light, which illuminates the fiber-bundle uniformly. Light is collected through a parabolic concentrator and focused toward a collimating lens, which distributes the light over each optical fiber. An optics diffusing structure is utilized at the end side of the fiber bundle to spread light in the interior. The results clearly reveal that the efficiency in terms of uniform illumination, which also reduces the heat problem for optical fibers, is improved. Furthermore, a comparison study is conducted between current and previous approaches. As a result, the proposed daylighting system turns out convenient in terms of energy saving and reduction in greenhouse gas emissions.

Greenhouse gas emissions in China have been increasing in line with its energy consumption and economic growth. Major means for energy-related greenhouse gases mitigation in the foreseeable future are transition to less carbon intensive energy supplies and structural changes in energy consumption. In this paper, a bottom-up model is built to examine typical projected scenarios for energy supply and demand, with which trends of energy-related carbon dioxide emissions by 2050 can be analyzed. Results show that low-carbon technologies remain essential contributors to reducing emissions and altering emissions trends up to 2050. By pushing the limit of current practicality, emissions reduction can reach 20 to 28 percent and the advent of carbon peaking could shift from 2040 to 2030. In addition, the effect of electrification at end-use sectors is studied. Results show that electrifying transport could reduce emissions and bring the advent of carbon peaking forward, but the effect is less significant compared with low-carbon technologies. Moreover, it implies the importance of decarbonizing power supply before electrifying end-use sectors.

Densified Biomass Solid Fuel (DBSF) is a typical solid form of biomass, using agricultural and forestry residues as raw materials. DBSF utilization is considered to be an alternative to fossil energy, like coal in China, associated with a reduction of environmental pollution. China has abundant biomass resources and is suitable to develop DBSF. Until now, a number of policies aimed at fostering DBSF industry have been proliferated by policy makers in China. However, considering the seasonality and instability of biomass resources, these inefficiencies could trigger future scarcities of biomass feedstocks, baffling the resilience of biomass supply chains. Therefore, this review paper focuses on DBSF policies and strategies in China, based on the supply chain framework. We analyzed the current developing situation of DBSF industry in China and developed a framework for policy instruments based on the supply chain steps, which can be used to identify and assess the deficiencies of current DBSF industry policies, and we proposed some suggestions. These findings may inform policy development and identify synergies at different steps in the supply chain to enhance the development of DBSF industry.

The location of ground faults in railway electric lines in 2 × 5 kV railway power supply systems is a difficult task. In both 1 × 25 kV and transmission power systems it is common practice to use distance protection relays to clear ground faults and localize their positions. However, in the particular case of this 2 × 25 kV system, due to the widespread use of autotransformers, the relation between the distance and the impedance seen by the distance protection relays is not linear and therefore the location is not accurate enough. This paper presents a simple and economical method to identify the subsection between autotransformers and the conductor (catenary or feeder) where the ground fault is happening. This method is based on the comparison of the angle between the current and the voltage of the positive terminal in each autotransformer. Consequently, after the identification of the subsection and the conductor with the ground defect, only the subsection where the ground fault is present will be quickly removed from service, with the minimum effect on rail traffic. This method has been validated through computer simulations and laboratory tests with positive results.

The main objective of this study is to discuss the economical and the environmental analysis of a net zero energy (NZE) tourist village in Alexandria, Egypt, by maximizing the renewable energy fraction and minimizing the greenhouse gases (GHG) emissions. The hybrid photovoltaics (PV)/wind/diesel/battery system is found to be the optimum hybrid renewable energy system (HRES) for the proposed tourist village under the study. The optimum HRES consists of 1600 kW of PV panels (58.09% solar energy penetration), 1000 kW of wind turbines (41.34% wind energy penetration), 1000 kW of power converters, 200 kW diesel generator (only 0.57% diesel generator penetration) in addition to 2000 batteries with the capacity of 589 Ah each. The levelized cost of energy (COE) from the optimum HRES is $0.17/kWh and the total net present cost (NPC) of this system is $15,383,360. Additionally, the maximum renewable energy fraction is 99.1% and the amount of GHG emitted from the optimum HRES is only 31,289 kg/year, which is negligible in comparison with the other system configurations, therefore the optimum HRES can be considered as a green system. In addition to this, the achieved percentage of the capacity shortage and the unmet load in the optimal HRES is only 0% for both.

This paper presents a novel staggered-teeth cylindrical transverse-flux permanent-magnet linear machine (TFPMLM), which aims to improve the power factor and force density. Due to the compact structure and high performance requirement, thermal problems should be seriously considered. The three-dimensional (3-D) temperature field model is established. The determination of convection heat transfer coefficients is discussed. Equivalent thermal conductivities of stator core and winding are given to simplify the analysis. With the thermal effect of the adhesive coatings among permanent magnets (PMs) and mover yoke taken into account, the temperature field distribution and variation rules of the TFPMLM are obtained using the finite volume method (FVM). The influences of slot filling factor and air flow velocity on the temperature field distribution are analyzed. It is found that the hottest spot of the TFPMLM appears in the middle of the end winding, and there is no risk of demagnetization for PMs.

The paper discusses Home Area Networks (HAN) communication technologies for smart home and domestic application integration. The work is initiated by identifying the application areas that can benefit from this integration. A broad and inclusive home communication interface is analysed utilizing as a key piece a Gateway based on machine-to-machine (M2M) communications that interacts with the surrounding environment. Then, the main wireless networks are thoroughly assessed, and later, their suitability to the requirements of HAN considering the application area is analysed. Finally, a qualitative analysis is portrayed.

In recent years, the accumulated environmental problems resulting from excessive usage of fossil fuels have gradually loomed. Thus, an environmental tax, as an important policy tool, has been put on the agenda in China. In this paper, a dynamic recursive multi-sector Computable General Equilibrium (CGE) model is applied to explore the impacts of the environmental tax on China’s economy. To comprehensively analyze the impacts, we introduce four kinds of typical contaminants and set two kinds of scenarios: different tax rates and different tax refunds. The results show that the environmental tax is conducive to environmental improvement, but the economic variables are adversely affected, for example, the loss of GDP at the low level tax rate is 0.46%. In order to offset the negative impacts, we presume the government refunds the tax. The results show that this can indeed relieve the negative effects. When the government refunds the production tax and corporate income tax, 0.49% and 0.34% of GDP is relieved by respectively. This paper provides a comprehensive analysis of the implementation of the environmental tax in China and lays a solid foundation for the introduction of the environmental tax.

In order to solve environmental problems such as global warming and resource depletion in the construction industry, interest in new renewable energy (NRE) systems has increased. The ground source heat pump (GSHP) system is the most efficient system among NRE systems. However, since the initial investment cost of the GSHP is quite expensive, a feasibility study needs to be conducted from the life-cycle perspective. Meanwhile, the efficiency of GSHP depends most significantly on the entering water temperature (EWT) of the ground heat exchanger (GHE). Therefore, this study aims to assess the environmental and economic effects of the use of GHE for selecting the optimal GHE. This study was conducted in three steps: (i) establishing the basic information and selecting key factors affecting GHE performances, (ii) making possible alternatives of the GHE installation by considering EWT, and (iii) using life-cycle assessment and life-cycle cost, as well as comprehensive evaluation of the environmental and economic effects on the GHE. These techniques allow for easy and accurate determination of the optimal design of the GHE from the environmental and economic effects in the early design phase. In future research, a multi-objective decision support model for the GSHP will be developed.

Hydrothermal liquefaction (HTL) presents a viable route for converting a vast range of materials into liquid fuel, without the need for pre-drying. Currently, HTL studies produce bio-crude with properties that fall short of diesel or biodiesel standards. Upgrading bio-crude improves the physical and chemical properties to produce a fuel corresponding to diesel or biodiesel. Properties such as viscosity, density, heating value, oxygen, nitrogen and sulphur content, and chemical composition can be modified towards meeting fuel standards using strategies such as solvent extraction, distillation, hydrodeoxygenation and catalytic cracking. This article presents a review of the upgrading technologies available, and how they might be used to make HTL bio-crude into a transportation fuel that meets current fuel property standards.

Wave energy is one of the most promising alternatives to fossil fuels due to the enormous available resource; however, its development may be slowed as it is often regarded as uneconomical. The largest cost reductions are expected to be obtained through economies of scale and technological progress. In this sense, the incorporation of wave energy systems into offshore wind energy farms is an opportunity to foster the development of wave energy. The synergies between both renewables can be realised through these co-located energy farms and, thus, some challenges of offshore wind energy can be met. Among them, this paper focuses on the longer non-operational periods of offshore wind turbines—relative to their onshore counterparts—typically caused by delays in maintenance due to the harsh marine conditions. Co-located wave energy converters would act as a barrier extracting energy from the waves and resulting in a shielding effect over the wind farm. On this basis, the aim of this paper is to analyse wave energy economics in a holistic way, as well as the synergies between wave and offshore wind energy, focusing on the shadow effect and the associated increase in the accessibility to the wind turbines.

Effects of the recycle solvent hydrotreatment on oil yield of direct coal liquefaction were carried out in the 0.18 t/day direct coal liquefaction bench support unit of National Engineering Laboratory for Direct Coal Liquefaction (China). Results showed that the hydrogen-donating ability of the hydrogenated recycle solvent improved and the hydrogen consumption of solvent hydrotreatment was increased by decreasing liquid hourly space velocity (LHSV) from 1.5 to 1.0 h −1 and increasing reaction pressure from 13.7 to 19.0 MPa. The hydrogen-donating ability of the hydrogenated recycle solvent was enhanced, thus promoting the oil yield and coal conversion of the liquefaction reaction. The coal conversion and distillates yield of coal liquefaction were increased from 88.74% to 88.82% and from 47.41% to 49.10%, respectively, with the increase in the solvent hydrotreatment pressure from 13.7 to 19.0 MPa. The coal conversion and distillates of coal liquefaction were increased from 88.82% to 89.27% and from 49.10% to 54.49%, respectively, when the LHSV decreased from 1.5 to 1.0 h −1 under the solvent hydrotreatment pressure of 19.0 MPa.

Initial cracking pressure and locations are important parameters in conducting cross-measure hydraulic fracturing to enhance coal seam permeability in underground coalmines, which are significantly influenced by in-situ stress and occurrence of coal seam. In this study, stress state around cross-measure fracturing boreholes was analyzed using in-situ stress coordinate transformation, then a mathematical model was developed to evaluate initial cracking parameters of borehole assuming the maximum tensile stress criterion. Subsequently, the influences of in-situ stress and occurrence of coal seams on initial cracking pressure and locations in underground coalmines were analyzed using the proposed model. Finally, the proposed model was verified with field test data. The results suggest that the initial cracking pressure increases with the depth cover and coal seam dip angle. However, it decreases with the increase in azimuth of major principle stress. The results also indicate that the initial cracking locations concentrated in the second and fourth quadrant in polar coordinate, and shifted direction to the strike of coal seam as coal seam dip angle and azimuth of maximum principle stress increase. Field investigation revealed consistent rule with the developed model that the initial cracking pressure increases with the coal seam dip angle. Therefore, the proposed mathematical model provides theoretical insight to analyze the initial cracking parameters during cross-measure hydraulic fracturing for underground coalmines.

Climate changes, incidents like nuclear disasters, and associated political objectives call for significant changes to the current energy system. Despite these far-reaching transformation processes, within the intended changes security of supply and precautions against the possible consequences of climate change must be ensured. Consequently, the question arises how to direct energy systems. In this context the processes of guiding orientations with the help of the guiding concept of “resilient systems” and feasible and addressee-oriented guiding design principles can be an option to provide guidance in transformation processes. However, it is questionable whether and how such processes are effective in the long term and if they are able to give direction by doing so. Within the framework of empirical studies of a regional guiding orientation process for the energy system of Northwestern Germany, the long-term effectiveness of the process and its spread resilient guiding design principles of “low-exergy solutions” and “climate-adapted and energy-efficient refrigeration” has been confirmed. Such effectiveness requires the implementation of a four-phase guiding orientation process which takes content-related and process-related effectiveness factors into account. Therefore, the study shows how regional energy systems can be designed toward the major challenges of ensuring security and precaution.

Single-shaft gas turbine and its cycles are sensitive to frequency drops and, therefore, sudden change loads or large frequency dips might affect their stability. This phenomenon is related to the reduction of the air mass flow passing through the machine during the frequency dips, which might lead to an interaction between governor and temperature control loop. In this paper, the performance of the combined cycle and steam-injected gas turbine are studied during frequency dips and transient maneuvers. For this purpose, two similar units are developed based on these cycles and their performances are studied in different scenarios. The simulation results show that the steam injected gas turbine has a better performance during frequency drops and it can handle relatively larger change loads.

The effect of reduced form of sulfur compounds on granular sludge was investigated. Significant release of extracellular polymeric substance (EPS) from the granular sludge occurred in the presence of sulfide and methanethiol according to various concentrations. Granular sludge also showed a rapid increase in turbidity and decrease in diameter in accordance with sulfide concentration during the long-term shaking, suggesting that the strength of the granules was reduced with high-concentration sulfide. A continuous experiment of up-flow anaerobic sludge blanket reactors with different concentrations of sulfide (10, 200, 500 mg-S/L) influence demonstrated that the reactor fed with higher concentration of sulfide allowed more washout of small particle-suspended solid (SS) content and soluble carbohydrate and protein, which were considered as EPS released from biofilm. Finally, the presence of sulfide negatively affected methane production, chemical oxygen demand removal and sludge retention in operational performance.

This paper presents an exergy analysis of an actual two-pass (RO) desalination system with the seawater solution treated as a real mixture and not an ideal mixture. The actual 127 ton/h two pass RO desalination plant was modeled using IPSEpro software and validated against operating data. The results show that using the (ERT) and (PX) reduced the total power consumption of the SWRO desalination by about 30% and 50% respectively, whereas, the specific power consumption for the SWRO per m 3 water decreased from 7.2 kW/m 3 to 5.0 kW/m 3 with (ERT) and 3.6 kW/m 3 with (PX). In addition, the exergy efficiency of the RO desalination improved by 49% with ERT and 77% with PX and exergy destruction was reduced by 40% for (ERT) and 53% for (PX). The results also showed that, when the (ERT) and (PX) were not in use, accounted for 42% of the total exergy destruction. Whereas, when (ERT) and (PX) are in use, the rejected seawater account maximum is 0.64%. Moreover, the (PX) involved the smallest area and highest minimum separation work.

This paper aims to present an improved version of a typical particle swarm optimization (PSO) algorithm, such that the global maximum power point (MPP) on a P-V characteristic curve with multiple peaks can be located in an efficient and precise manner for a photovoltaic module array. A series of instrumental measurements are conducted on variously configured arrays built with SANYO HIP2717 PV modules, either unshaded, partially shaded, or malfunctioning, as the building blocks. There appear two, triple and quadruple peaks on the corresponding P-V characteristic curves. Subsequently, the tracking performance comparisons, made by some practical experiments, indicate the superiority of this improved MPP tracking algorithm over the typical one.

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a single diode model and double diode model using this improved artificial bee colony. Experimental results clearly demonstrate the effectiveness of the proposed method and its superior performance compared to other competing methods.

This paper presents a novel grouping method for lithium iron phosphate batteries. In this method, a simplified electrochemical impedance spectroscopy (EIS) model is utilized to describe the battery characteristics. Dynamic stress test (DST) and fractional joint Kalman filter (FJKF) are used to extract battery model parameters. In order to realize equal-number grouping of batteries, a new modified K-means clustering algorithm is proposed. Two rules are designed to equalize the numbers of elements in each group and exchange samples among groups. In this paper, the principles of battery model selection, physical meaning and identification method of model parameters, data preprocessing and equal-number clustering method for battery grouping are comprehensively described. Additionally, experiments for battery grouping and method validation are designed. This method is meaningful to application involving the grouping of fresh batteries for electric vehicles (EVs) and screening of aged batteries for recycling.

In this paper, a novel hybrid excitation linear eddy current brake is presented as a braking system for high-speed road and rail vehicles. The presence of the permanent magnets (PMs), whose flux lines in the primary core are oppositely directed with respect to the flux lines by the excitation windings, has the effect of mitigating the saturation of the iron in the teeth of the primary core. This allows the brake to be fed with more intense currents, improving the braking force. First, using the magnetic equivalent circuit method and the layer theory approach, the analytical model of the hybrid excitation linear eddy current brake was developed, which can account for the saturation effects occurring in the iron parts. The saturation effects make the design and control of eddy current brakes more difficult. Second, the relationship between the braking force characteristics and the design parameters were analyzed to provide useful information to the designers of eddy current brakes. Then, the controller of the hybrid excitation linear eddy current brake was designed to control the amplitude of the braking force. Finally, experimental measurements were conducted to verify the validity of the theoretical analysis.

Balancing battery cells is a key task for battery management systems (BMS). Imbalances of cells decrease the capacity and lifetime of the battery pack. Many balancing topologies and strategies have been proposed to balance the electric charges among cells and most of the intelligent control strategies select cells (to shuttle charges) by comparing their terminal voltages. However, the nature of battery equalization is to balance the energy stored in individual cells. The measured terminal voltage is just an external characteristic and cannot accurately reflect the state of charge (SOC) of the cell, especially in a noisy environment. Additionally, when the consistencies of cells are very poor, balancing the cells with terminal voltages will lead to serious errors. In this paper, we introduced a novel battery balancing method, in which the charge-balancing criterion was not the cell voltage, but the shuttling capacities among cells. Data stream mining (DSM) technique was used to calculate the shuttling capacities. A single switched capacitor (SSC) based cell balancing topology was used to test the performance of the proposed method. With the obtained summary information, the cells, the sequence, and the quantity of the equalized charge can be decided automatically by the proposed algorithm. The simulation and experiment results have shown that the proposed method was effective and convenient.