Analysis of model predictive control through a power converter in a renewable energy system

Predictive control developments for applications in the field of renewable energy systems are still under investigation. In this article, the fundamentals of predictive control are studied with a focus on model predictive control (MPC). Based on this techniques, a control strategy for flexible power supply can be developed which could be implemented in renewable energy systems, such as solar photovoltaic (PV) systems

Адаптивная система обеспечения максимальной выходной мощности фотоэлектрической станции на основе робастного прогнозного управления

Photovoltaic power plants have non-linear voltage-current characteristic, with specific maximum power point, which depends on operating conditions, viz. irradiation and temperature. In targeting the maximum power, it is by far known that the photovoltaic arrays have to operate at the maximum power point despite unpredicted weather changes. For this reason the controllers of all photovoltaic power electronic converters employ some method for maximum power point tracking. This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. Further, during the advanced stages of this research study, the model will compare the results obtained for tracking the maximum power point from model predictive controller and a PID-controller as they are integrated Perturb and Observe algorithm. The obtained results will verify that the adaptive PID-controller Perturb and Observe algorithm has limitation for tracking the precise MPP during the transient insulation conditions. As compared to the proposed adaptive/modified model predictive controller for Perturb and Observe algorithm we illustrate that by adopting this method we will get to establish more accurate and efficient results of the obtained power in any dynamic environmental conditions: advantages as on regulation time (six times under the accepted experimental conditions) and by the number of fluctuations.Фотоэлектрические станции (ФЭС) характеризуются нелинейной зависимостью выходного тока и напряжения с уникальной точкой  максимальной  выходной мощности (МВМ), зависящей от условий эксплуатации – температуры и уровня солнечной радиации. Поэтому для повышения эффективности фотоэлектрического преобразования необходимо обеспечить работу ФЭС в точке МВМ. Это достигается применением соответствующих алгоритмов управления, наиболее известными из которых являются P&O («возмущение и наблюдение»). Эти алгоритмы основаны на изменении напряжения постоянного тока ФЭС с помощью преобразователя постоянного тока (регулятора), выходное напряжение которого должно изменяться по определенному закону с изменением условий эксплуатации. При этом используются регуляторы: пропорциональные (П), интегральные (И), дифференциальные (Д) или чаще всего их комбинации ПИД. В статье исследуется эффективность применения регулятора с прогнозным адаптивным управлением (MPC). Посредством численных экспериментов на разработанной имитационной модели показано, что ПИД-регуляторы в интеграции с P&O и INC алгоритмами не обеспечивают достаточно быстрой реакции при изменении условий внешней среды. В то же время МРС в сочетании с P&O имеет преимущества как по времени регулирования (в шесть раз при принятых условиях эксперимента), так и по количеству колебаний

Адаптивная система обеспечения максимальной выходной мощности фотоэлектрической станции на основе робастного прогнозного управления

Photovoltaic power plants have non-linear voltage-current characteristic, with specific maximum power point, which depends on operating conditions, viz. irradiation and temperature. In targeting the maximum power, it is by far known that the photovoltaic arrays have to operate at the maximum power point despite unpredicted weather changes. For this reason the controllers of all photovoltaic power electronic converters employ some method for maximum power point tracking. This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. Further, during the advanced stages of this research study, the model will compare the results obtained for tracking the maximum power point from model predictive controller and a PID-controller as they are integrated Perturb and Observe algorithm. The obtained results will verify that the adaptive PID-controller Perturb and Observe algorithm has limitation for tracking the precise MPP during the transient insulation conditions. As compared to the proposed adaptive/modified model predictive controller for Perturb and Observe algorithm we illustrate that by adopting this method we will get to establish more accurate and efficient results of the obtained power in any dynamic environmental conditions: advantages as on regulation time (six times under the accepted experimental conditions) and by the number of fluctuations

Mathematical Modeling of Hybrid Electrical Engineering Systems

A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the processes has been obtained in the paper. The equation contains both continuous and discrete components, which characterize an amplitude signal modulation. An equation for probability density of phase coordinate distribution in the system has been developed on the basis of a mathematical model for a hybrid system

Cooperative Unmanned Air and Ground Vehicles for Landmine Detection

The unmanned aerial vehicle used in this research is multi-functional quadcopter with infrared camera and Ground Penetrating Radar (GPR). The unmanned aerial vehicle detects the landmines using infrared camera and GPR; maps a pin in digital map for future use by ground vehicle. The ground vehicle used in this research is Belarus132N mobile robot. It has the following onboard sensors: stereo pair camera, GPS, and image processing system. The ground vehicle will use onboard sensors: stereo pair camera, GPS and the map provided by the quadcopter to traverse the region, and locate the mapped landmines. The base station consists of a laptop that provides a communication link between the aerial and ground vehicle systems and for saving information from any destruction. This proposed system will demonstrate how an air-ground vehicle system use to cooperatively detect, locate and traverse of landmines

Progress in the discovery of selective, high affinity A2B adenosine receptor antagonists as clinical candidates

The selective, high affinity A2B adenosine receptor (AdoR) antagonists that were synthesized by several research groups should aid in determining the role of the A2B AdoR in inflammatory diseases like asthma or rheumatoid arthritis (RA) and angiogenic diseases like diabetic retinopathy or cancer. CV Therapeutics scientists discovered the selective, high affinity A2B AdoR antagonist 10, a 8-(4-pyrazolyl)-xanthine derivative [CVT-6883, Ki(hA2B) = 22 nM; Ki(hA1) = 1,940 nM; Ki(hA2A) = 3,280; and Ki(hA3) = 1,070 nM] that has favorable pharmacokinetic (PK) properties (t1/2 = 4 h and F > 35% rat). Compound 10 demonstrated functional antagonism at the A2B AdoR (KB = 6 nM) and efficacy in a mouse model of asthma. In two phase 1 clinical trials, CVT-6883 was found to be safe, well tolerated, and suitable for once daily dosing. A second compound 20, 8-(5-pyrazolyl)-xanthine, has been nominated for development from Baraldi’s group in conjunction with King Pharmaceuticals that has favorable A2B AdoR affinity and selectivity [Ki(hA2B) = 5.5 nM; Ki(hA1) > 1,000 nM; Ki(hA2A) > 1,000; and Ki(hA3) > 1,000 nM], and it has been demonstrated to be a functional antagonist. A third compound 32, a 2-aminopyrimidine, from the Almirall group has high A2B AdoR affinity and selectivity [Ki(hA2B) = 17 nM; Ki(hA1) > 1,000 nM; Ki(hA2A) > 2,500; and Ki(hA3) > 1,000 nM], and 32 has been moved into preclinical safety testing. Since three highly selective, high affinity A2B AdoR antagonists have been nominated for development with 10 (CVT-6883) being the furthest along in the development process, the role of the A2B AdoR in various disease states will soon be established

МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ ГИБРИДНЫХ ЭЛЕКТРОТЕХНИЧЕСКИХ СИСТЕМ

A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the processes has been obtained in the paper. The equation contains both continuous and discrete components, which characterize an amplitude signal modulation. An equation for probability density of phase coordinate distribution in the system has been developed on the basis of a mathematical model for a hybrid system.К электротехническим системам относится большой класс систем, нашедших применение в различных отраслях промышленности и быту, в электрифицированных транспортных объектах и энергетике. Их характерная черта – комбинация непрерывного и дискретного режимов работы, что нашло отражение в появлении относительно нового термина «гибридные системы». Широкий класс гибридных систем – это импульсные преобразователи постоянного тока, работающие в режиме широтно-импульсной модуляции и являющиеся нелинейными системами с переменной структурой. Используя различные приемы линеаризации, можно получить линейные математические модели, которые достаточно точно имитируют поведение таких систем. Однако наличие в математических моделях экспоненциальных нелинейностей создает значительные трудности при реализации системы на цифровых аппаратных средствах. Решение может быть найдено применением аппроксимации показательных функций полиномами первого порядка, что нарушает строгость соответствия аналитической модели характеристикам реального объекта. Существуют два подхода в практике синтеза алгоритмов управления гибридных систем. Первый основан на представлении всей системы дискретной моделью, описываемой разностными уравнениями, и на основе этого – синтез дискретных алгоритмов. Второй подход основан на описании системы дифференциальными уравнениями – синтез непрерывных алгоритмов и дальнейшая реализация их в цифровой вычислительной машине, включенной в контур управления системой. Рассмотрено моделирование гибридной электротехнической системы с помощью дифференциальных уравнений. Пренебрегая длительностью импульсов, поведение компонент вектора фазовых координат гибридной системы предлагается описать стохастическими дифференциальными уравнениями, содержащими в общем случае нелинейные не дифференцируемые случайные функции. Получено векторно-матричное стохастическое уравнение, описывающее динамику процессов, в котором представлены как непрерывная, так и дискретная составляющие, характеризующие амплитудную модуляцию сигналов. На основе математической модели гибридной системы получено уравнение для плотности вероятности распределения фазовых координат системы.

ИМПУЛЬСНОЕ УПРАВЛЕНИЕ ГИБРИДНОЙ ЭЛЕКТРОТЕХНИЧЕСКОЙ СИСТЕМОЙ

This paper extends the recently introduced approach for modeling and solving the optimal control problem of fixedswitched mode DC-DC power converter. DCDC converters are a class of electric power circuits that used extensively in regulated DC power supplies, DC motor drives of different types, in Photovoltaic Station energy conversion and other applications due to its advantageous features in terms of size, weight and reliable performance. The main problem in controlling this type converters is in their hybrid nature as the switched circuit topology entails different modes of operation, each of it with its own associated linear continuous-time dynamics.This paper analyses the modeling and controller synthesis of the fixed-frequency buck DC-DC converter, in which the transistor switch is operated by a pulse sequence with constant frequency. In this case the regulation of the DC component of the output voltage is via the duty cycle. The optimization of the control system is based on the formation of the control signal at the output.It is proposed to solve the problem of optimal control of a hybrid system based on the formation of the control signal at the output of the controller, which minimizes a given functional integral quality, which is regarded as a linear quadratic Letov-Kalman functional. Search method of optimal control depends on the type of mathematical model of control object. In this case, we consider a linear deterministic model of the control system, which is common for the majority of hybrid electrical systems. For this formulation of the optimal control problem of search is a problem of analytical design of optimal controller, which has the analytical solution.As an example of the hybrid system is considered a step-down switching DC-DC converter, which is widely used in various electrical systems: as an uninterruptible power supply, battery charger for electric vehicles, the inverter in solar photovoltaic power plants.. A qualitative change in the projected illustration of the control signal, a sequence of control pulses and output management object (inverter).Рассматриваются особенности математического моделирования гибридной электротехнической системы, к классу которых относятся системы, содержащие в своем составе как непрерывные, так и дискретные элементы. Управление гибридными системами является актуальной задачей, обусловленной широким использованием дискретной обработки сигналов в силовой электронике, в промышленных системах, в электрифицированном транспорте (электромобили, троллейбусы, трамваи).Предлагается решать задачу оптимального управления гибридной системой на основе формирования такого сигнала управления на выходе контроллера (регулятора), который минимизирует заданный интегральный функционал качества, в качестве которого рассматривается линейный квадратичный функционал Летова-Калмана. Метод поиска оптимального управления зависит от вида математической модели системы управления. В данном случае рассматривается линейная детерминированная модель системы управления, характерная для большинства гибридных электротехнических систем.В качестве примера гибридной системы рассмотрен понижающий импульсный преобразователь постоянного тока, который находит широкое применение в различных электротехнических системах: в качестве источника бесперебойного питания, зарядного устройства для электромобилей, преобразователя в составе солнечных фотоэлектрических станций.. Представлена качественная иллюстрация изменения прогнозируемого сигнала управления в виде последовательности управляющих импульсов и выходного сигнала объекта управления