ISSN 1991-2927
 

ACP № 2 (56) 2019

Author: "Vladimir Fedorovich Belov"

Svetlana Aleksandrovna Rozhkova, Ogarev Mordovia State University, graduated from the Faculty of Mathematics and Information Technologies at Ogarev Mordovia State University; Post-graduate Student, Lecturer of the Department of Computer-Aided Design at Ogarev Mordovia State University; an author of articles in the field of mathematical modeling of home energy management systems. [e-mail: rozhkova_sa@mail.ru]S. Rozhkova,

Vladimir Fedorovich Belov, Ogarev Mordovia State University, Doctor of Engineering, Professor; graduated from the Faculty of Electronics at Ogarev Mordovia State University; Head of the Department of Computer-Aided Design at Ogarev Mordovia State University; an author of articles, monographs, and inventions in the field of the design of autonomous electric power systems, in which power quality parameters are controllable. [e-mail: belovvf@mail.ru]V. Belov

Optimal Scheduling of Local Battery Storage 000_4.pdf

Nowadays energetics is characterized by consistent trend of the development of distributed power generation systems (microgrids) and alternative energy sources implementation as its components. In these systems using local electric batteries became actual and possible for automatic energy consumption management. These devices significantly increase the reliability and electronic characteristics of electricity supply through optimal choice of energy sources using rapid connection of the power sources to the power consumers. The authors analyze the algorithm for optimal control of the power system consisting of two energy sources - one of them is battery storage and another one is external centralized grid where time-varying electricity pricing is released. The problem of finding the algorithm for optimal control generation as a task of the creating working timetable of electric storage, which has to minimize expenses for power supply is considered. Within a given time interval, a microprocessor controls a power storage battery releasing process. Particle Swarm Optimization (PSO) is selected as a numerical method for solving this problem. Based on experiment numerical results that were performed, conclusions about effectiveness of developed battery schedule optimization algorithm are given; also recommendations were given for further improvements of microprocessor programming.

Control, microgrid, electric energy consumption, battery energy storage, optimization, non-linear programming, particle swarm optimization.

2016_ 1

Sections: Automated control systems

Subjects: Automated control systems, Electrical engineering and electronics.


Vladimir Fedorovich Belov, N.P. Ogarev Mordovian State University, Doctor of Engineering, Professor; graduated from the Faculty of Electronics at N.P. Ogarev Mordovian State University; Head of the Department of Computer-Aided Design at N.P. Ogarev Mordovian State University; an author of articles, monographs, and inventions in the field of the design of autonomous electric power systems, in which power quality parameters are controllable. [e-mail: belovvf@mail.ru]V. Belov,

Anna Aleksandrovna Butkina, N.P. Ogarev Mordovian State University, graduated from the Faculty of Mathematics at N.P. Ogarev Mordovian State University; Lecturer of the Department of Computer-Aided Design at N.P. Ogarev Mordovian State University; an author of articles in the field of numerical method application for mathematical simulation of electric power systems. [e-mail: butkinaaa@gmail.com]A. Butkina,

Alexey Valentinovich Shamaev, N.P. Ogarev Mordovian State University, Candidate of Engineering; graduated from the Faculty of Electronics at Ogarev Mordovian State University; Associate Professor at the Department of Computer-Aided Design at N.P. Ogarev Mordovian State University; an author of articles in the field of mathematical simulation and optimization of electric power filters. [e-mail: shamaevav@list.ru]A. Shamaev

Mathematical Simulation of Power Conversation Systems for Micro Grid 36_7.pdf

Mathematical model of AC/DC/AC converter with energy storage device is developed on the base of the bridge element concept. This model is intended for the analysis of conducted interference at the designing stage of micro Smart Grid, which contain AC/DC/AC converters, as well as for the emulation of the control object at the software development stage of microcontrollers.Bridge element (B-element) is a generalized model of the m-phase bridge converter of electric power, in which transistors are modeled by ideal switches. Rules to represent a graph of the equivalent circuit of AC/DC/AC converter with energy storage as a set of subgraphs corresponding standardized bridge elements are developed. Application of these rules provides correctness of algorithm functioning of forming and solution of differential equations of the equivalent circuit at any state of the switches automatically.Computational aspects of the algorithm have been investigated on the example of mathematical simulation of AC/DC/AC converter with MPI distributed computing technology. Preliminary results showed that increasing of the simulation speed may be achieved by application of parallel computing technology for solution of the complete differential equations system formed on the B-element base. Element-wise forming and solution of differential equations systems does not increase the computational efficiency. Additional studies are required for final confirmation of these results.

Smart grid, smart grid, power converter, mathematical model, power quality, parallel computation.

2014_ 2

Sections: Mathematical modeling

Subjects: Mathematical modeling.


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