Energy generation from metal-water reaction for power systems, underwater and aerospace propulsion applications

Author(s):  
Ghedjatti Ilyes ◽  
Yuan Shiwei ◽  
Wang Haixing
2018 ◽  
Vol 33 (4) ◽  
pp. 4308-4322 ◽  
Author(s):  
Roohallah Khatami ◽  
Masood Parvania ◽  
Pramod P. Khargonekar

2019 ◽  
Vol 9 (7) ◽  
pp. 1484 ◽  
Author(s):  
Xiangwu Yan ◽  
Weichao Zhang

Due to the irreversible energy substitution from fossil fuels to clean energy, the development trend of future power systems is based on renewable energy generation. However, due to the incompatibility of converter-based non-dispatchable renewable energy generation, the stability and reliability of traditional power systems deteriorate as more renewables are introduced. Since conventional power systems are dominated by synchronous machines (SM), it is natural to utilize a virtual synchronous generator (VSG) control strategy that intimates SM characteristics on integrated converters. The VSG algorithm developed in this paper originates from mimicking mathematic models of synchronous machines. Among the different models of implementation, the second-order model is simple, stable, and compatible with the control schemes of current converters in traditional power systems. The VSG control strategy is thoroughly researched and case studied for various converter-interfaced systems that include renewable generation, energy storage, electric vehicles (EV), and other energy demands. VSG-based integration converters can provide grid services such as spinning reserves and inertia emulation to the upper grids of centralized plants, distributed generation networks, and microgrids. Thus, the VSG control strategy has paved a feasible way for an evolutionary transition to a power electronics-based future power grid. By referring to the knowledge of traditional grids, a hierarchical system of operations can be established. Finally, generation and loads can be united in universal compatibility architecture under consolidated synchronous mechanisms.


Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1333 ◽  
Author(s):  
Diego Francisco Larios ◽  
Enrique Personal ◽  
Antonio Parejo ◽  
Sebastián García ◽  
Antonio García ◽  
...  

The complexity of power systems is rising mainly due to the expansion of renewable energy generation. Due to the enormous variability and uncertainty associated with these types of resources, they require sophisticated planning tools so that they can be used appropriately. In this sense, several tools for the simulation of renewable energy assets have been proposed. However, they are traditionally focused on the simulation of the generation process, leaving the operation of these systems in the background. Conversely, more expert SCADA operators for the management of renewable power plants are required, but their training is not an easy task. SCADA operation is usually complex, due to the wide set of information available. In this sense, simulation or co-simulation tools can clearly help to reduce the learning curve and improve their skills. Therefore, this paper proposes a useful simulator based on a JavaScript engine that can be easily connected to any renewable SCADAs, making it possible to perform different simulated scenarios for novel operator training, as if it were a real facility. Using this tool, the administrators can easily program those scenarios allowing them to sort out the lack of support found in setting up facilities and training of novel operator tasks. Additionally, different renewable energy generation models that can be implemented in the proposed simulator are described. Later, as a use example of this tool, a study case is also performed. It proposes three different wind farm generation facility models, based on different turbine models: one with the essential generation turbine function obtained from the manufacturer curve, another with an empirical model using monotonic splines, and the last one adding the most important operational states, making it possible to demonstrate the usefulness of the proposed simulation tool.


Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 171 ◽  
Author(s):  
Hua Zhou ◽  
Huahua Wu ◽  
Chengjin Ye ◽  
Shijie Xiao ◽  
Jun Zhang ◽  
...  

With the rapid growth of renewable energy generation, it has become essential to give a comprehensive evaluation of renewable energy integration capability in power systems to reduce renewable generation curtailment. Existing research has not considered the correlations between wind power and photovoltaic (PV) power. In this paper, temporal and spatial correlations among different renewable generations are utilized to evaluate the integration capability of power systems based on the copula model. Firstly, the temporal and spatial correlation between wind and PV power generation is analyzed. Secondly, the temporal and spatial distribution model of both wind and PV power generation output is formulated based on the copula model. Thirdly, aggregated generation output scenarios of wind and PV power are generated. Fourthly, wind and PV power scenarios are utilized in an optimal power flow calculation model of power systems. Lastly, the integration capacity of wind power and PV power is shown to be able to be evaluated by satisfying the reliability of power system operation. Simulation results of a modified IEEE RTS-24 bus system indicate that the integration capability of renewable energy generation in power systems can be comprehensively evaluated based on the temporal and spatial correlations of renewable energy generation.


Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6375
Author(s):  
Elkin D. Reyes ◽  
Arturo S. Bretas ◽  
Sergio Rivera

The high penetration of renewable sources of energy in electrical power systems implies an increase in the uncertainty variables of the economic dispatch (ED). Uncertainty costs are a metric to quantify the variability introduced from renewable energy generation, that is to say: wind energy generation (WEG), run-of-the-river hydro generators (RHG), and solar photovoltaic generation (PVG). On other side, there are associated uncertainties to the charge/uncharge of plug-in electric vehicles (PEV). Thus, in this paper, the uncertainty cost functions (UCF) and their marginal expressions as a way of modeling and assessment of stochasticity in power systems with high penetration of smart grids elements is presented. In this work, a mathematical analysis is presented using the first and second derivatives of the UCF, where the marginal uncertainty cost functions (MUCF) and the UCF’s minimums for PVG, WEG, PEV, and RHG are derived. Further, a model validation is presented, considering comparative test results from the state of the art of the UCF minimum, developed in a previous study, to the minimum reached with the presented (MUCF) solution.


2017 ◽  
Vol 70 ◽  
pp. 1090-1098 ◽  
Author(s):  
Giancarlo Aquila ◽  
Edson de Oliveira Pamplona ◽  
Anderson Rodrigo de Queiroz ◽  
Paulo Rotela Junior ◽  
Marcelo Nunes Fonseca

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