scholarly journals Assessment of Reliability and Quality Performance using the Impact of Shortfall Generation Capacity Index on Power Systems

2019 ◽  
Vol 9 (6) ◽  
pp. 4937-4941
Author(s):  
B. M. Alshammari

This paper presents a novel practical technique developed and applied for assessment of reliability and quality in real-life power systems. System-wide integrated performance indices are capable of addressing and revealing areas of deficiencies and bottlenecks as well as shortfalls in the composite generation-transmission-demand structure of large-scale power grids. The new evaluation methodology offers a general and comprehensive framework to assess the harmony and compatibility of generation capacities, transmission and required demand in a power system. The technique used in this paper is evaluated by the shortfall generation capacity index which is based on three dimensions introduced to represent the relationship between certain system generation capacity and demand. Also, practical applications to the Saudi power grid are presented for demonstration purposes.

2021 ◽  
Vol 11 (2) ◽  
pp. 6930-6934
Author(s):  
A. S. Alshammari ◽  
B. M. Alshammari ◽  
T. Guesmi ◽  
R. Abbassi

Power system planning faces various issues related to reliability and quality evaluation. The power system network planning is by nature a complex, huge-scale, and mixed-objective optimization problem, especially when concerning its non-linear behavior and the requirements of future unknown loads. In this regard, the electric power utilities attempt to maintain a balance between the generation energy, the transmission capacity, and the needed demand. The main purpose of the current paper is to utilize modern modeling techniques and computational procedures, including the advanced deficit transmission system evaluation method and sparse-matrix network analysis algorithms, in order to evaluate, with sufficient accuracy, the deficit and reliability levels in practical real-life large-scale power systems. The new evaluation methodology is based on three quantities representing the relationship between the generation push in the grid, the maximum limitation of the transmission capacity, and the needed load. The main contribution of the paper is assessing the deficit transmission system index with novel formulas.


Author(s):  
Krzysztof Jurczuk ◽  
Marcin Czajkowski ◽  
Marek Kretowski

AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.


Author(s):  
Gianluca Bardaro ◽  
Alessio Antonini ◽  
Enrico Motta

AbstractOver the last two decades, several deployments of robots for in-house assistance of older adults have been trialled. However, these solutions are mostly prototypes and remain unused in real-life scenarios. In this work, we review the historical and current landscape of the field, to try and understand why robots have yet to succeed as personal assistants in daily life. Our analysis focuses on two complementary aspects: the capabilities of the physical platform and the logic of the deployment. The former analysis shows regularities in hardware configurations and functionalities, leading to the definition of a set of six application-level capabilities (exploration, identification, remote control, communication, manipulation, and digital situatedness). The latter focuses on the impact of robots on the daily life of users and categorises the deployment of robots for healthcare interventions using three types of services: support, mitigation, and response. Our investigation reveals that the value of healthcare interventions is limited by a stagnation of functionalities and a disconnection between the robotic platform and the design of the intervention. To address this issue, we propose a novel co-design toolkit, which uses an ecological framework for robot interventions in the healthcare domain. Our approach connects robot capabilities with known geriatric factors, to create a holistic view encompassing both the physical platform and the logic of the deployment. As a case study-based validation, we discuss the use of the toolkit in the pre-design of the robotic platform for an pilot intervention, part of the EU large-scale pilot of the EU H2020 GATEKEEPER project.


2020 ◽  
Vol 34 (01) ◽  
pp. 630-637 ◽  
Author(s):  
Ferdinando Fioretto ◽  
Terrence W.K. Mak ◽  
Pascal Van Hentenryck

The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setpoints for power and voltage, given a set of load demands. It is often solved repeatedly under various conditions, either in real-time or in large-scale studies. This need is further exacerbated by the increasing stochasticity of power systems due to renewable energy sources in front and behind the meter. To address these challenges, this paper presents a deep learning approach to the OPF. The learning model exploits the information available in the similar states of the system (which is commonly available in practical applications), as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF. The proposed model is evaluated on a large collection of realistic medium-sized power systems. The experimental results show that its predictions are highly accurate with average errors as low as 0.2%. Additionally, the proposed approach is shown to improve the accuracy of the widely adopted linear DC approximation by at least two orders of magnitude.


2015 ◽  
Vol 25 (12) ◽  
pp. 1550167
Author(s):  
Lei Wang ◽  
Hsiao-Dong Chiang

This paper presents online methods for controlling local bifurcations of power grids with the goal of increasing bifurcation values (i.e. increasing load margins) via network topology optimization, a low-cost control. In other words, this paper presents online methods for increasing power transfer capability subject to static stability limit via switching transmission line out/in (i.e. disconnecting a transmission line or connecting a transmission line). To illustrate the impact of network topology on local bifurcations, two common local bifurcations, i.e. saddle-node bifurcation and structure-induced bifurcation on small power grids with different network topologies are shown. A three-stage online control methodology of local bifurcations via network topology optimization is presented to delay local bifurcations of power grids. Online methods must meet the challenging requirements of online applications such as the speed requirement (in the order of minutes), accuracy requirement and robustness requirement. The effectiveness of the three-stage methodology for online applications is demonstrated on the IEEE 118-bus and a 1648-bus practical power systems.


2020 ◽  
pp. 1-7
Author(s):  
Sumit Kumar Gupta ◽  

Nanotechnology is new frontiers of this century. The world is facing great challenges in meeting rising demands for basic commodities(e.g., food, water and energy), finished goods (e.g., cellphones, cars and airplanes) and services (e.g., shelter, healthcare and employment) while reducing and minimizing the impact of human activities on Earth’s global environment and climate. Nanotechnology has emerged as a versatile platform that could provide efficient, cost-effective and environmentally acceptable solutions to the global sustainability challenges facing society. In recent years there has been a rapid increase in nanotechnology in the fields of medicine and more specifically in targeted drug delivery. Opportunities of utilizing nanotechnology to address global challenges in (1) water purification, (2) clean energy technologies, (3) greenhouse gases management, (4) materials supply and utilization, and (5) green manufacturing and hemistry. Smart delivery of nutrients, bio-separation of proteins, rapid sampling of biological and chemical contaminants, and nano encapsulation of nutraceuticals are some of the emerging topics of nanotechnology for food and agriculture. Nanotechnology is helping to considerably improve, even revolutionize, many technology and Industry sectors: information technology, energy, environmental science, medicine, homeland security, food safety, and transportation, among many others. Today’s nanotechnology harnesses current progress in chemistry, physics, materials science, and biotechnology to create novel materials that have unique properties because their structures are determined on the nanometer scale. This paper summarizes the various applications of nanotechnology in recent decades Nanotechnology is one of the leading scientific fields today since it combines knowledge from the fields of Physics, Chemistry, Biology, Medicine, Informatics, and Engineering. It is an emerging technological field with great potential to lead in great breakthroughs that can be applied in real life. Novel Nano and biomaterials, and Nano devices are fabricated and controlled by nanotechnology tools and techniques, which investigate and tune the properties, responses, and functions of living and non-living matter, at sizes below100 nm. The application and use of Nano materials in electronic and mechanical devices, in optical and magnetic components, quantum computing, tissue engineering, and other biotechnologies, with smallest features, widths well below 100 nm, are the economically most important parts of the nanotechnology nowadays and presumably in the near future. The number of Nano products is rapidly growing since more and more Nano engineered materials are reaching the global market the continuous revolution in nanotechnology will result in the fabrication of nanomaterial with properties and functionalities which are going to have positive changes in the lives of our citizens, be it in health, environment, electronics or any other field. In the energy generation challenge where the conventional fuel resources cannot remain the dominant energy source, taking into account the increasing consumption demand and the CO2 .Emissions alternative renewable energy sources based on new technologies have to be promoted. Innovative solar cell technologies that utilize nanostructured materials and composite systems such as organic photovoltaic offer great technological potential due to their attractive properties such as the potential of large-scale and low-cost roll-to-roll manufacturing processes


2020 ◽  
Vol 492 (3) ◽  
pp. 4268-4282 ◽  
Author(s):  
Adam Soussana ◽  
Nora Elisa Chisari ◽  
Sandrine Codis ◽  
Ricarda S Beckmann ◽  
Yohan Dubois ◽  
...  

ABSTRACT The intrinsic correlations of galaxy shapes and orientations across the large-scale structure of the Universe are a known contaminant to weak gravitational lensing. They are known to be dependent on galaxy properties, such as their mass and morphologies. The complex interplay between alignments and the physical processes that drive galaxy evolution remains vastly unexplored. We assess the sensitivity of intrinsic alignments (shapes and angular momenta) to active galactic nuclei (AGN) feedback by comparing galaxy alignment in twin runs of the cosmological hydrodynamical Horizon simulation, which do and do not include AGN feedback, respectively. We measure intrinsic alignments in three dimensions and in projection at $z$ = 0 and $z$ = 1. We find that the projected alignment signal of all galaxies with resolved shapes with respect to the density field in the simulation is robust to AGN feedback, thus giving similar predictions for contamination to weak lensing. The relative alignment of galaxy shapes around galaxy positions is however significantly impacted, especially when considering high-mass ellipsoids. Using a sample of galaxy ‘twins’ across simulations, we determine that AGN changes both the galaxy selection and their actual alignments. Finally, we measure the alignments of angular momenta of galaxies with their nearest filament. Overall, these are more significant in the presence of AGN as a result of the higher abundance of massive pressure-supported galaxies.


Author(s):  
Farhad Namdari ◽  
Fatemeh Soleimani ◽  
Esmaeel Rokrok

<p><em>Environmental concerns along with the increasing demand on electrical power, have led to power generation of renewable sources like wind. Connecting wind turbines in large scale powers with transmission network makes new challenges like the impact of these renewable sources on power system protection. This paper studies the impact of fault resistance and its location on voltage and current fundamental frequencies of faulted lines connected to DFIG based wind farms and it will be demonstrated that because of the large differences between these frequencies, impedance measuring of distance relays is inefficient. Hence in these power systems using conventional impedance measurements is not suitable anymore and new impedance measuring approaches are required in distance relays.</em></p>


2019 ◽  
Vol 112 ◽  
pp. 02011
Author(s):  
Cristian-Gabriel Alionte ◽  
Daniel-Constantin Comeaga

The importance of renewable energy and especially of eolian systems is growing. For this reason, we propose the investigation of an important pollutant - the noise, which has become so important that European Commission and European Parliament introduced Directive 2002/49/CE relating to the assessment and management of environmental noise. So far, priority has been given to very large-scale systems connected to national energy systems, wind farms whose highly variable output power could be regulated by large power systems. Nowadays, with the development of small storage capacities, it is feasible to install small power wind turbines in cities of up to 10,000 inhabitants too. As a case study, we propose a simulation for a rural locality where individual wind units could be used. This specific case study is interesting because it provides a new perspective of the impact of noise on the quality of life when the use of this type of system is implemented on a large scale. This option, of distributed and small power wind turbine, can be implemented in the future as an alternative or an adding to the common systems.


Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6532
Author(s):  
Vahab Rostampour ◽  
Thom S. Badings ◽  
Jacquelien M. A. Scherpen

We present a Buildings-to-Grid (BtG) integration framework with intermittent wind-power generation and demand flexibility management provided by buildings. First, we extend the existing BtG models by introducing uncertain wind-power generation and reformulating the interactions between the Transmission System Operator (TSO), Distribution System Operators (DSO), and buildings. We then develop a unified BtG control framework to deal with forecast errors in the wind power, by considering ancillary services from both reserves and demand-side flexibility. The resulting framework is formulated as a finite-horizon stochastic model predictive control (MPC) problem, which is generally hard to solve due to the unknown distribution of the wind-power generation. To overcome this limitation, we present a tractable robust reformulation, together with probabilistic feasibility guarantees. We demonstrate that the proposed demand flexibility management can substitute the traditional reserve scheduling services in power systems with high levels of uncertain generation. Moreover, we show that this change does not jeopardize the stability of the grid or violate thermal comfort constraints of buildings. We finally provide a large-scale Monte Carlo simulation study to confirm the impact of achievements.


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