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[en] Successful integration of renewable energy sources like wind power into smart grids largely depends on accurate prediction of power from these intermittent sources. Production of wind power cannot be controlled as the wind speed can vary based on weather conditions. Accurate prediction of wind power can assist smart grid that intelligently decides on the usage of alternative power sources based on demand forecast. Time series wind speed data are normally used for wind power prediction. In this paper, we have investigated the usage of a set of secondary features obtained using deep learning for wind power prediction. Deep learning is a special form on neural network that is capable of capturing the structural properties of time series data in terms of a set of numeric features. More precisely, we have designed a two-stage autoencoder (a particular type of deep learning) and incorporated the structural features into a prediction framework. Using the structural features, we have achieved as high as 12.63% better prediction accuracy than traditionally used statistical features.
[en] In this paper, a model of irreversible three-electron-reservoir energy selective electron (ESE) cooling device with heat leakage is established. By utilizing the finite time thermodynamics, the optimal performance of the cooling device is studied and the influences of chemical potential differences of electron reservoirs, center energy level of energy filters and heat leakage on the optimal performances are discussed. On the basis of cooling rate and coefficient of performance (COP) analyses, the exergy-based ecological function and figure of merit are proposed as objective functions. The operation properties of ESE cooling device with different objective functions are investigated and the optimal performance region is obtained. Higher cooling rate and COP can both be attained for the ESE cooling device when it is working in the optimal performance region.
[en] A self-replicating rapid prototyper (RepRap) is a type of 3-D printer capable of printing many of its own components in addition to a wide assortment of products from high-value scientific or medical tools to household products and toys. There is some evidence that these printers could provide low-cost distributed manufacturing in underprivileged rural areas. For the most isolated communities without access to the electric grid, a low-cost alternative energy is needed. Solar energy can be harvested through a stand-alone photovoltaic (PV) power system specifically designed to match the needs of the RepRap. The voltage and current requirement for the printer demands the use of buck along with a bidirectional DC converters to ensure proper operation. This paper provides the design for a stand-alone PV—lithium ion battery power system with an efficient controller. Robust and agile PI controller schemes are utilized to efficiently maintain the distribution of energy through the power system. The system was defined with ordinary differential equations, simulated and tested for two operational conditions in MATLAB/Simulink. The results showed that the controller developed operates the system in a stable condition and the simulation shows steady acceptable behavior that makes this system highly suitable for hardware implementation.
[en] Geothermal energy remains a largely undeveloped natural resource because of the high risk associated with its development. An accurate prediction model for easy identification of potential regions can help to lower the risk and cost associated with development. In this study, geothermal potential regions were identified through the relationship between geothermal emergencies and their controlling factors in Tengchong County, China. Publicly available databases for this analysis including epicenters, active faults, Bouguer gravity, Landsat7 Enhanced Thematic Mapper Plus images, the magnetic data and digital elevation model data were extracted as the b-value map, distance to faults map, distance to main grabens map, land surface temperature map, magnetic anomaly map and distance to rivers map, respectively. Based on the platforms within geographic information system, an entropy theory-integrated information model was established to evaluate the geothermal potential sites within the region. Moreover, factor analysis method was applied to test the conditional independence between the map pairs before modeling application. The results of the weighted information model show that the model shows perfect performance in discovering potential geothermal regions. In the final maps, undeveloped or unexploited geothermal regions can be observed along the Mingguang River and Nu River. Undeniably, these models will help to find undiscovered geothermal regions with limited geological information publically available.
[en] In the heating sector, borehole heat exchangers have become popular for supplying renewable energy. They tap into the subsurface to extract geothermal energy for heating purposes. For advanced applications, borehole heat exchangers require insulation in the upper part of the borehole either to meet legal requirements or to improve their performance. A priori numerical heat transport models of the subsurface are imperative for the systems’ planning and design. Only fully discretized models can account for depth-dependent borehole properties like insulated sections, but the model setup is cumbersome and the simulations come at high computational cost. Hence, these models are often not suitable for the simulation of larger installations. This study presents an analytical solution for the simulation of the thermal interactions of partly insulated borehole heat exchangers. A benchmark with a fully discretized OpenGeoSys model confirms sufficient accuracy of the analytical solution. In an application example, the functionality of the tool is demonstrated by finding the ideal length of a borehole insulation using mathematical optimization and by quantifying the effect of the insulation on the borehole heat exchanger performance. The presented method allows for accommodation of future advancements in borehole heat exchangers in numerical simulations at comparatively low computational cost.
[en] We consider a non-relativistic two-dimensional (2D) hydrogen-like atom in a weak, static, uniform magnetic field perpendicular to the atomic plane. Within the framework of the Rayleigh-Schrödinger perturbation theory, using the Sturmian expansion of the generalized radial Coulomb Green function, we derive explicit analytical expressions for corrections to an arbitrary planar hydrogenic bound-state energy level, up to the fourth order in the strength of the perturbing magnetic field. In the case of the ground state, we correct an expression for the fourth-order correction to energy available in the literature.
[en] Decentralized control of DC microgrid (dcµG) using hybrid renewable energy sources (RES) and battery energy storage system (BESS) which operate with and without grid-connected mode is proposed in this paper. In dcµG integrated with multiple RES and BESS, fluctuating output characteristics of the distributed generations (DGs) due to changing input conditions and the dynamic interactions of the source and load interface converters are main factors which cause stability problem of DC bus voltage. Thus, to solve this problem, the decentralized control scheme which uses bus voltage level as communication link in the control law is proposed in this paper. Accordingly, the control method realizes different operating modes based on the available generations and load demand. Maximum power and constant voltage controls schemes are applied in the DGs interfacing control to regulate the power and voltage variations due to changing input conditions. Furthermore, in the control strategy, the source and battery interfacing converters are controlled autonomously using the bus voltage level without any communication. This maintains the reliability and flexibility of the system. The proposed system model is developed with Matlab/Simulink SimPowerSystem and simulated with real-time simulation using OPAL-RT.
[en] Geothermal resources in China are distributed throughout the country, with hydrothermal systems of high temperature in the Tibet Autonomous Region, Yunnan Province and Taiwan Island and hydrothermal systems of low-medium temperature mainly in various sedimentary basins. Development and exploration of geothermal energy in China are below expectations. The purpose of this study is to comparatively review the characteristics (geology, hydrogeology, hydrochemistry and geophysical data) of typical hydrothermal fields/areas and suggest development and utilization approaches in the future. Hydrothermal systems formed by mountain lifting contain a considerable amount of energy for geothermal power generation, especially in the Tibet Autonomous Region, Yunnan Province and Taiwan Island. However, geothermal water in the Tatun geothermal field has high TDS (total dissolved solids), an issue that requires more research to resolve this problem for power generation. The large storage of geothermal resources has been investigated in Meso–Cenozoic sedimentary basins; it is basically used for heating, bathing or greenhouse plantation. Moreover, hydrothermal resources of low-medium temperature can also be used in binary power plants. Although the enhanced geothermal systems (EGS) in China are promising, the resources have not yet been commercially exploited, because the emerging technologies (hydraulic fracturing) and concerns over environmental impacts (induced micro-seismicity) lead to slow development. On the contrary, shallow geothermal energy has been directly utilized mainly for heating and cooling buildings. Cities like Beijing, Tianjin and Shenyang have established a series of ground-source heat-pump systems, which has led to a massive reduction of CO2 emission of 19.87×106 t.
[en] If used correctly, digitization can accelerate the energy revolution and make it more efficient and cost-effective. In the 2018 issue, the scientists show how information and communication technologies can support the transformation process in order to implement the goals of ecology, economy and social sustainability on an equal footing.
[de]Richtig eingesetzt kann Digitalisierung die Energiewende beschleunigen und sie effizienter und kostengünstiger gestalten. Im Themenheft 2018 zeigen die Wissenschaftlerinnen und Wissenschaftler wie die Informations- und Kommunikationstechnologien den Transformationsprozess unterstützen können, um die Zielrichtungen Ökologie, Ökonomie und soziale Nachhaltigkeit gleichgewichtig umzusetzen.
[en] Large penetration of renewable energies heavily threats the stable and reliable operation of power systems due to their randomness and intermittence characteristics. The first passage time problem is one of the critical issues in reliability assessment of new energy power systems. In this paper, we present and analyze the first passage time problem of power systems with stochastic excitation by collocation method. The power systems with stochastic excitations are modeled by stochastic differential equations. Then, the backward Kolmogorov equations and the generalized Pontryagin equations governing the conditional reliability function and the conditional moments of first passage time, respectively, are established based on the stochastic averaging method. The corresponding initial and boundary conditions are also provided. A numerical collocation method was proposed to solve the equations, and case studies were executed on a single-machine infinite-bus system under Gaussian excitation. Illustrations of the conditional reliability function and probability density functions for some cases are presented.