Simulation of Electrical Characteristics of a Solar Panel

The fast-growing photovoltaic system market leads to the necessity of the informed choice of major energy components and optimization of operating conditions in order to improve energy efficiency. Development of mathematical models of the main components of photovoltaic systems to ensure their comprehensive study is an urgent problem of improving and practical using of the technology of electrical energy production. The paper presents a mathematical model of the solar module implemented in the popular software MATLAB/Simulink. Equivalent circuit of the solar cell with a diode parallel without derived resistance is used for modelling. The serie8s resistance of the solar module is calculated by Newton's iterative method using the data of its technical specifications. It ensures high precision of simulation. Model validity was evaluated by the well-known technical characteristics of the module Solarex MSX 60. The calculation results of the experiment showed that the obtained current-voltage and current-watt characteristics of the model are compatible with those of the manufacturer

Method for selecting parameters and assessing efficiency of wind-diesel power plants for autonomous electrical supply systems

The article presents an original technique for selecting parameters and evaluating the efficiency of wind-diesel power plants for isolated power supply systems. The initial data to perform energy calculations are simulation models of electric load and wind speed. The load is simulated using typical schedules of electric loads of a decentralized consumer, taking into account a random component for each hour of the day. To create a simulation model of the wind, a typical climatic series of wind speeds at a prospective site of the power plant has been constructed according to the data of long-term meteorological observations. The proposed technique was verified through the example of choosing a wind-diesel power plant for the village of Ust-Olenyok of the Republic of Sakha (Yakutia)

Method for Prediction of the Power Output from Photovoltaic Power Plant under Actual Operating Conditions

Solar photovoltaic technology is one of the most rapidly growing renewable sources of electricity that has practical application in various fields of human activity due to its high availability, huge potential and environmental compatibility. The original simulation model of the photovoltaic power plant has been developed to simulate and investigate the plant operating modes under actual operating conditions. The proposed model considers the impact of the external climatic factors on the solar panel energy characteristics that improves accuracy in the power output prediction. The data obtained through the photovoltaic power plant operation simulation enable a well-reasoned choice of the required capacity for storage devices and determination of the rational algorithms to control the energy complex

The experimental studies of operating modes of a diesel-generator set at variable speed

A diesel generator set working at variable speed to save fuel is studied. The results of experimental studies of the operating modes of an autonomous diesel generator set are presented. Areas for regulating operating modes are determined. It is demonstrated that the transfer of the diesel generator set to variable speed of the diesel engine makes it possible to improve the energy efficiency of the autonomous generator source, as well as the environmental and ergonomic performance of the equipment as compared with general industrial analogues

Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV

This paper presents optimal parameters selection of particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking of photovoltaic array under partially shaded conditions. Under partial shading, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. The two proposed controllers include dynamic Particle Swarm Optimization, and constant particle swarm optimization. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. The results indicate that the dynamic particle swarm optimization algorithm can very fast track the GMPP within 128 ms for different shading conditions. In addition, the average tracking efficiency of the proposed algorithm is higher than 99.89%, which provides good prospects to apply this algorithm in the control search unit for the global maximum power point in stations

Mathematical model of solar radiation based on climatological data from NASA SSE

An original model of solar radiation arriving at the arbitrarily oriented surface has been developed. The peculiarity of the model is that it uses numerical values of the atmospheric transparency index and the surface albedo from the NASA SSE database as initial data. The model is developed in the MatLab/Simulink environment to predict the main characteristics of solar radiation for any geographical point in Russia, including those for territories with no regular actinometric observations

Development of The Structural and Functional Design of the Laboratory Bench for Experimental Research Diesel Generator Sets on Variable Speed

A diesel generator set working at variable speed to save fuel is studied. A description is provided of a laboratory bench for conducting experimental studies of a variable speed diesel generator set. Its component parts are described, and its technical characteristics are given

Power Balance Management of an Autonomous Hybrid Energy System Based on the Dual-Energy Storage

The urgent task of modern energy is to ensure reliable and efficient power supply to consumers, even those located in remote, far end places. A hybrid energy system with renewable energy sources is a promising way to ensure such a process. A characteristic feature of the modes of such systems, especially with high penetration levels of renewable energy sources, is the presence of ripples in the charge–discharge currents of the batteries used as energy storage devices. Batteries operation with such current fluctuations leads to rapid degradation of its characteristics as well as a reduction in its lifetime. Furthermore, it leads to a decrease in the reliability of the power supply system and an increase in the cost of generated electricity. A significant drawback of hybrid systems built according to well-known standard schemes is the inefficient use of the primary renewable energy, which is especially critical for energy systems located geographically in areas with severe climatic conditions. This article proposes a new construction method and an algorithm for controlling the modes of hybrid energy systems based on a dual-circuit energy storage device, which increases their reliability and energy efficiency. The prominent outcomes of operating modes of a hybrid power plant with a high penetration of renewable sources are presented, which proves that the proposed method of construction and the proposed control algorithm provide reliable and efficient control of the power balance of the hybrid power system in all possible operating conditions. In addition, the overall efficiency of the proposed renewable energy system is increased from 28% to 60% compared to standard hybrid power plants

Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process

The primary task of the design and feasibility study for the use of wind power plants is to predict changes in wind speeds at the site of power system installation. The stochastic nature of the wind and spatio-temporal variability explains the high complexity of this problem, associated with finding the best mathematical modeling which satisfies the best solution for this problem. In the known discrete models based on Markov chains, the autoregressive-moving average does not allow variance in the time step, which does not allow their use for simulation of operating modes of wind turbines and wind energy systems. The article proposes and tests a SDE-based model for generating synthetic wind speed data using the stochastic differential equation of the fractional Ornstein-Uhlenbeck process with periodic function of long-run mean. The model allows generating wind speed trajectories with a given autocorrelation, required statistical distribution and provides the incorporation of daily and seasonal variations. Compared to the standard Ornstein-Uhlenbeck process driven by ordinary Brownian motion, the fractional model used in this study allows one to generate synthetic wind speed trajectories which autocorrelation function decays according to a power law that more closely matches the hourly autocorrelation of actual data. In order to demonstrate the capabilities of this model, a number of simulations were carried out using model parameters estimated from actual observation data of wind speed collected at 518 weather stations located throughout Russia