scholarly journals Self-Powered Dynamic Systems in the Framework of Optimal Uncertainty Quantification

2017 ◽  
Vol 139 (9) ◽  
Author(s):  
Farbod Khoshnoud ◽  
Ibrahim I. Esat ◽  
Clarence W. de Silva ◽  
Michael M. McKerns ◽  
Houman Owhadi
Keyword(s):  
Renewable Energy ◽  
Dynamic System ◽  
Uncertainty Quantification ◽  
Supply And Demand ◽  
System A ◽  
Rigorous Framework ◽  
Energy Excess ◽  
Optimal Bounds ◽  
Self Powered ◽  
Solar Powered

The energy that is needed for operating a self-powered device is provided by the energy excess in the system in the form of kinetic energy, or a combination of regenerative and renewable energy. This paper addresses the energy exchange issues pertaining to regenerative and renewable energy in the development of a self-powered dynamic system. A rigorous framework that explores the supply and demand of energy for self-powered systems is developed, which considers uncertainties and optimal bounds, in the context of optimal uncertainty quantification. Examples of regenerative and solar-powered systems are given, and the analysis of self-powered feedback control for developing a fully self-powered dynamic system is discussed.

scholarly journals Balancing of supply and demand of renewable energy power system: A review and bibliometric analysis

2020 ◽  
Vol 2 ◽  
pp. 100013 ◽  
Author(s):  
Lu Gan ◽  
Pengyan Jiang ◽  
Benjamin Lev ◽  
Xiaoyang Zhou
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Bibliometric Analysis ◽  
Supply And Demand ◽  
System A

Flywheel energy storage systems and their applications in power engineering

2021 ◽  
Vol 6 ◽  
pp. 26-34
Author(s):  
Vladimir Poltavets ◽  
Irina Kolchanova
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage Systems ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Electric Energy ◽  
Energy Generation ◽  
Flywheel Energy Storage ◽  
Energy Storage Systems ◽  
Continuous Growth

The continuous growth of renewable energy sources has drastically changed the paradigm of electric energy generation and distribution. Flywheel energy storage systems are a clean and efficient method to level supply and demand in energy grids, including those incorporating renewable energy generation. Environmental safety, resilience, high power capacity and quality make flywheel energy storage very promising. This paper contains a review of flywheel energy storage systems, already being in operation, and applications of flywheel energy storage in general.

scholarly journals Development of Solar Powered Sprinkler Robot Based on Watering Plant Using IOT Approach

2021 ◽  
Vol 2107 (1) ◽  
pp. 012024
Author(s):  
Lim Xin You ◽  
Nordiana Shariffudin ◽  
Mohd Zamri Hasan
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
System Analysis ◽  
Tracking System ◽  
Sprinkler System ◽  
Solar Panel ◽  
Maximum Efficiency ◽  
Solar Tracking ◽  
Solar Tracker ◽  
Solar Powered

Abstract Nowadays, solar energy’s popularity is growing consistently every year, along with the growth of amazing solar technologies, which is considered to be one of the most popular. Non-renewable energy like petrol and gasoline is being replaced with solar energy, which is renewable energy. The main objective of this project is to design and simulate a robot solar system. The robot is developed using Arduino Mega 2560 as the main brain of the system. This system is equipped with a solar tracking system to track the movement of the sun and LDR is used to detect the presence of sunlight. The solar tracker is used to get the maximum efficiency of solar energy and reduce power losses. In addition, the solar tracker can rotate from 0° - 180°, which is the best angle for the solar panel to reach the sunlight. This robot will be attached to the sprinkler system to perform the watering process. This robot is developed for use in the agriculture field to reduce the manpower and cost of the watering process. Three analyses will be conducted in this project such as solar panel analysis, Wi-Fi connectivity analysis and sprinkler system analysis. The result shows the solar panel will gain the highest intensity of the sunlight at 12.00 pm and a sunny day compared to the other time and a cloudy day. The maximum range of Wi-Fi connectivity and the water pump, time used to finish the watering process and watering area will be discussed.

Leontev Input-Output Balance Model as a Dynamic System Control Problem

2021 ◽  
pp. 66-82
Author(s):  
S.N. Masaev
Keyword(s):  
Dynamic System ◽  
Matrix Representation ◽  
External Environment ◽  
Balance Model ◽  
System Control ◽  
Operational Mode ◽  
Input Output ◽  
System A ◽  
The Matrix ◽  
Research Show

The purpose of the study was to determine the problem of control of a dynamic system of higher dimension. Relying on Leontev input-output balance, we formalized the dynamic system and synthesized its control. Within the research, we developed a mathematical model that combines different working objects that consume and release various resources. The value of the penalty for all nodes and objects is introduced into the matrix representation of the problem, taking into account various options for their interaction, i.e., the observation problem. A matrix representation of the planning task at each working object is formed. For the formed system, a control loop is created; the influencing parameters of the external environment are indicated. We calculated the system operational mode, taking into account the interaction of the nodes of objects with each other when the parameters of the external environment influence them. Findings of research show that in achieving a complex result, the system is inefficient without optimal planning and accounting for the matrix of penalties for the interaction of nodes and objects of the dynamic system with each other. In a specific example, for a dynamic system with a dimension of 4.8 million parameters, we estimated the control taking into account the penalty matrix, which made it possible to increase the inflow of additional resources from the outside by 2.4 times from 130 billion conv. units up to 310 conv. units in 5 years. Taking into account the maximum optimization of control in the nodes, an increase of 3.66 times in the inflow of additional resources was ensured --- from 200.46 to 726.62 billion rubles

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