Karabetskyi D. Computer-aided design of hybrid solar power systems

Українська версія

Thesis for the degree of Candidate of Sciences (CSc)

State registration number

0421U103915

Applicant for

Specialization

  • 05.13.12 - Системи автоматизації проектувальних робіт

23-09-2021

Specialized Academic Board

Д 26.062.08

National Aviation University

Essay

One of the main trends of recent decades is the search for and implementation of renewable energy sources, including solar energy. Given that this type of energy is becoming more attractive and more accessible every year, the problems of dependence on environmental conditions are also becoming increasingly important. Since individual energy sources are unable to meet the load requirements due to uncertainties in the environment, hybridization of the system should be considered in the direction of using additional energy sources in combination with energy storage systems. The purpose of the dissertation research is to increase the efficiency of HSPS, as well as its elements, by building a system of computer-aided design based on the use of intelligent approaches, in particular, multi-criteria optimization methods. The dissertation develops the structure of the computer-aided design system of the hybrid solar power system (HSPS), which allows to optimize the structure and parameters of the solar power system, minimize the cost of the system, increase reliability, minimize energy shortages for consumers, minimize environmental pollution, based on multi-objective optimization (MOO) methods. The approach to the optimization of the structure of the HSPS, which is used in the problem of automated design, in two modes: independent and connected to the network. The proposed HSPS consists of a solar energy system (SPS), a energy storage system based on batteries, a set of diesel generators and a network interaction system. The dissertation defines the power models of the HSPS elements, the proposed control algorithm based on the rules for assessing the state of the system during operation. Energy models in connection with the control algorithm allow the stage of modeling the system for a given time interval. The proposed approach is based on the use of solving the problem of MOO. MOO takes into account the minimization of system costs and total system cost, minimization of fuel use, maximization of reliability and minimization of the use of non-renewable energy sources. The solution of the MOO problem is based on the use of the Pareto-optimal solution search algorithm based on the NSGA-II genetic algorithm using the proposed set of crossing, mutation and selection operators. The developed procedure allows to determine the structure of the HSPS, which includes a set of the number of solar panels, batteries and DGs. As a result, three versions of the HSPS for a household for two people (Kyiv, Ukraine) are presented in an autonomous mode and in the mode with connection to the electric network. Due to the possibility of selling electricity at a green tariff during the year, the solution found allows to reduce the estimated cost of the system to 45%. A detailed analysis of the system behavior during the year due to the use of simulation is provided. The structure of SPS for UAVs on solar energy has been developed, which includes a hybrid energy storage system (batteries and supercapacitors), the parameters of which are determined as a result of solving the optimization problem, which allows to increase reliability, increase flight time, increase peak UAV power system. A new maximum power point search algorithm (MPPT) has been developed, which allows to increase the efficiency and speed of finding the maximum power point in partial shading conditions based on the use of the evolutionary method of Mine Blast Algorithm. A system of simulation models of HSPS elements has been developed, it includes SPS elements (solar panels, a set of DC and AC converters), a diesel generator, and a hybrid energy storage system. The developed system of computer-aided design of HSPS has been implemented at DP "VO Kyivprylad".

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