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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.

The impact of global warming and climate change is one of the most critical challenges of the 21st century. The greenhouse effect caused by technological development and industrial pollution has accelerated the speed of global warming. The continuous improvement in automobile energy consumption is one of the most effective ways to reduce global warming. A comparative analysis is proposed to examine the various automobiles that utilize technological innovation to improve their energy consumption. Their contribution to CO 2 emissions is then investigated. This study focuses on technical innovation and output power of a conventional engine. The results indicate that innovative engines (such as the Ford turbo petrol/diesel engine, the EcoBoost/TDCi) have improved energy consumption and reduce CO 2 emissions. In addition, the Toyota hybrid vehicles have also improved energy consumption and reduced greenhouse gases emissions.

This paper investigates a passive control method of a point absorbing wave energy converter by considering the displacement and velocity constraints under irregular waves in the time domain. A linear generator is used as a power take-off unit, and the equivalent damping force is optimized to improve the power production of the wave energy converter. The results from nonlinear and linear passive control methods are compared, and indicate that the nonlinear passive control method leads to the excitation force in phase with the velocity of the converter that can significantly improve the energy production of the converter.

A true physical understanding of the mysteries involved in the recovery process of the wake momentum deficit, downstream of utility-scale wind turbines in the atmosphere, has not been obtained to date. Field data are not acquired at sufficient spatial and temporal resolutions to dissect some of the mysteries of wake turbulence. It is here that the actuator line method has evolved to become the technology standard in the wind energy community. This work presents the actuator line method embedded into an Open source Field Operation and Manipulation (OpenFOAM) large-eddy simulation solver and applies it to two small wind farms, the first one consisting of an array of two National Renewable Energy Laboratory 5 Megawatt (NREL 5-MW) turbines separated by seven rotor diameters in neutral and unstable atmospheric boundary-layer flow and the second one consisting of five NREL 5-MW wind turbines in unstable atmospheric conditions arranged in two staggered arrays of two and three turbines, respectively. Detailed statistics involving power spectral density (PSD) of turbine power along with standard deviations reveal the effects of atmospheric turbulence and its space and time scales. High-resolution surface data extracts provide new insight into the complex recovery process of the wake momentum deficit governed by turbulence transport phenomena.

The battery critical functions such as State-of-Charge (SoC) and State-of-Health (SoH) estimations, over-current, and over-/under-voltage protections mainly depend on current and voltage sensor measurements. Therefore, it is imperative to develop a reliable sensor fault diagnosis scheme to guarantee the battery performance, safety and life. This paper presents a systematic model-based fault diagnosis scheme for a battery cell to detect current or voltage sensor faults. The battery model is developed based on the equivalent circuit technique. For the diagnostic scheme implementation, the extended Kalman filter (EKF) is used to estimate the terminal voltage of battery cell, and the residual carrying fault information is then generated by comparing the measured and estimated voltage. Further, the residual is evaluated by a statistical inference method that determines the presence of a fault. To highlight the importance of battery sensor fault diagnosis, the effects of sensors faults on battery SoC estimation and possible influences are analyzed. Finally, the effectiveness of the proposed diagnostic scheme is experimentally validated, and the results show that the current or voltage sensor fault can be accurately detected.

In solid biofuel manufacture technological and material variables influence the densification process and thus also the final briquette quality. The impact of these technological variables, especially compression pressure and compression temperature, and also of the material parameters (particle size and moisture content) can generally be observed during biomass densification in the quality indicators, where the abovementioned variables have a significant influence, especially on the mechanical indicators of quality (briquette density, mechanical durability, etc .). This paper presents the results of experimental research dealing with determining the relationship between the technological and the material variables during densification of beech sawdust. The main goal of the paper is to determine the mutual interaction between compression pressure, compression temperature and material particle size. Research findings were obtained using single-axis densification. The influence of the particle size interacting with compression pressure and compression temperature on the final briquette density was determined. The research findings obtained should prove valuable in briquette production and also in the engineering of densification machines.

High-availability seamless redundancy (HSR) is a protocol for Ethernet networks that provides duplicated frames with zero recovery time in the event of any network component’s failure. It is suited for applications that demand high availability and a very short time-outs such as substation automation systems (SAS). However, HSR generates excessive unnecessary unicast frames and spreads them throughout connected-ring networks, whether or not the destination node exists in network’s rings. This unnecessary redundant traffic causes high bandwidth consumption, resulting in degradation of network performance. In this paper, we introduce a novel approach for filtering and reducing HSR unicast traffic in connected-ring networks, called “filtering HSR traffic” (FHT). The purpose of FHT is to filter HSR unicast traffic and remove circulated traffic for all rings in connected-ring networks. Therefore, FHT significantly reduces network unicast traffic in connected-ring networks. The traffic performance of FHT has been analyzed, evaluated, and compared to that of standard HSR protocol and the port locking (PL) approach. Various simulations were conducted to validate the traffic performance analysis. Analytical and simulation results showed that, for our sample network, FHT reduced network unicast traffic by about 82% compared with standard HSR and by about 56% compared with the PL approach, thus freeing up network bandwidth and improving network traffic performance.

An increasing number of studies in the environmental and resource economic literature suggest that preferences for changes or improvements in environmental amenities, from water quality to recreation, are spatially heterogeneous. One of these effects in particular, distance decay, suggests that respondents exhibit a higher willingness to pay (WTP) the closer they live to a proposed environmental improvement and vice versa. The importance of spatial effects cannot be underestimated. Several of these studies find significant biases in aggregate WTP values, and therefore social welfare, from models that disregard spatial factors. This relationship between spatial aspects and preferences, however, remains largely ignored in the non-market valuation literature applied to valuing preferences for renewable energy, generally, and wind power, specifically. To our knowledge, fourteen peer-reviewed studies have been conducted to estimate stated preferences (SP) for onshore and/or offshore wind development, yet less than half of those utilize any measure to account for the relationship between spatial effects and preferences. Fewer still undertake more robust measures that account for these spatially dependent relationships, such as via GIS, outside incorporating a single ‘distance’ attribute within the choice experiment (CE) referenda. This paper first reviews the methodologies of the SP wind valuation studies that have integrated measure(s) to account for spatial effects. We then categorize these effects into three dimensions—distance to a proposed wind project, distance to existing wind project(s), and cumulative effects—supporting each with a discussion of significant findings, including those found in the wind hedonic and acceptance literature. Policy implications that can be leveraged to maximize social welfare when siting future wind projects as well as recommendations for additional research to control for preference spatial heterogeneity in wind CEs are also posited.

The increasing share of distributed energy resources poses a challenge to the distribution network operator (DNO) to maintain the current availability of the system while limiting the investment costs. Related to this, there is a clear trend in DNOs trying to better monitor their grid by installing a distribution management system (DMS). This DMS enables the DNOs to remotely switch their network or better localize and solve faults. Moreover, the DMS can be used to centrally control the grid assets. Therefore, in this paper, a control strategy is discussed that can be implemented in the DMS for solving current congestion problems posed by the increasing share of renewables in the grid. This control strategy controls wind turbines in order to avoid congestion while mitigating the required investment costs in order to achieve a global cost-efficient solution. Next to the application and objective of the control, the parameter tuning of the control algorithm is discussed.

The production of biogas from six agricultural crops was analysed regarding energy efficiency and greenhouse gas (GHG) performance for vehicle fuel from a field-to-tank perspective, with focus on critical parameters and on calculation methods. The energy efficiency varied from 35% to 44%, expressed as primary energy input per energy unit vehicle gas produced. The GHG reduction varied from 70% to 120%, compared with fossil liquid fuels, when the GHG credit of the digestate produced was included through system expansion according to the calculation methodology in the ISO 14044 standard of life cycle assessment. Ley crop-based biogas systems led to the highest GHG reduction, due to the significant soil carbon accumulation, followed by maize, wheat, hemp, triticale and sugar beet. Critical parameters are biogenic nitrous oxide emissions from crop cultivation, for which specific emission factors for digestate are missing today, and methane leakage from biogas production. The GHG benefits were reduced and the interrelation between the crops changed, when the GHG calculations were instead based on the methodology stated in the EU Renewable Energy Directive, where crop contribution to soil carbon accumulation is disregarded. All systems could still reach a 60% GHG reduction, due to the improved agricultural management when digestate replaces mineral fertilisers.

Medium-scale solar hot water systems with a total solar panel area varying from 60 to 166 m2 have been installed in Lithuania since 2002. However, the performance of these systems varies depending on the type of energy users, equipment and design of the systems, as well as their maintenance. The aim of this paper was to analyse operational SHW systems from the perspective of energy production and economic benefit as well as to outline the differences of their actual performance compared to the numerical simulation results. Three different medium-scale solar thermal systems in Lithuania were selected for the analysis varying in both equipment used (flat type solar collectors, evacuated tube collectors) and type of energy user (swimming pool building, domestic hot water heating, district heating). The results of the analysis showed that in the analysed cases the gap between measured and modelled data of heat energy produced by SHW systems was approx. 11%. From the economical perspective, the system with flat type solar collectors used for domestic hot water production was proved to be most efficient. However, calculation of Internal Rate of Return showed that a grant of 35% is required for this project to be fully profitable. Keywords: solar heat energy; solar water heating; simulation and monitoring; energy analysis; financial analysis.

Improved industrial energy efficiency is a cornerstone in climate change mitigation. Research results suggest that there is still major untapped potential for improved industrial energy efficiency. The major model used to explain the discrepancy between optimal level of energy efficiency and the current level is the barrier model, e.g., different barriers to energy efficiency inhibit adoption of cost-effective measures. The measures outlined in research and policy action plans are almost exclusively technology-oriented, but great potential for energy efficiency improvements is also found in operational measures. Both technology and operational measures are combined in successful energy management practices. Most research in the field of energy management is grounded in engineering science, and theoretical models on how energy management in industry is carried out are scarce. One way to further develop and improve energy management, both theoretically as well as practically, is to explore how a socio-technical perspective can contribute to this understanding. In this article we will further elaborate this potential of cross-pollinating these fields. The aim of this paper is to relate energy management to two theoretical models, situated action and transaction analysis. We conclude that the current model for energy management systems, the input-output model, is insufficient for understanding in-house industrial energy management practices. By the incorporation of situated action and transaction analysis to the currently used input-output model, an enhanced understanding of the complexity of energy management is gained. It is not possible to find a single energy management solution suitable for any industrial company, but rather the idea is to find a reflexive model that can be adjusted from time to time. An idea for such a reflexive model would contain the structural elements from energy management models with consideration for decisions being situated and impossible to predict.

It is well known that the methane hydrate dissociation process may lead to unstable behavior such as large ground deformations, uncontrollable gas production, etc. A linear instability analysis was performed in order to investigate which variables have a significant effect on the onset of the instability behavior of methane hydrate-bearing soils subjected to dissociation. In the analysis a simplified viscoplastic constitutive equation is used for the soil sediment. The stability analysis shows that the onset of instability of the material system mainly depends on the strain hardening-softening parameter, the degree of strain, and the permeability for water and gas. Then, we conducted a numerical analysis of gas hydrate-bearing soil considering hydrate dissociation in order to investigate the effect of the parameters on the system. The simulation method used in the present study can describe the chemo-thermo-mechanically coupled behaviors such as phase changes from hydrates to water and gas, temperature changes and ground deformation. From the numerical results, we found that basically the larger the permeability for water and gas is, the more stable the simulation results are. These results are consistent with those obtained from the linear stability analysis.

In this paper, a self-adaptive flange is proposed for the wind turbine shrouded by a flanged diffuser to reduce the wind loads acting on the flanged diffuser at high wind velocities. The self-adaptive flange can maintain the advantages of the flanged diffuser at wind velocities lower than the rated velocity and reduce the wind loads acting on the diffuser and blades at higher wind velocities. Numerical analyses of fluid-structure interactions are carried out to investigate the flow field around the diffuser with a self-adaptive flange and the variation of wind load acting on the diffuser due to the reconfiguration of the self-adaptive flange at various wind velocities. Numerical results show that the wind load acting on the total flanged diffuser can be reduced by about 35% at 60 m/s due to the reconfiguration of the self-adaptive flange.