Polar Phase Screens: A Comparison with Other Methods of Random Phase Screen Generation

This research provides the first organized comparison of random phase screen generation methods, including logarithmic polar Fourier series, using structure functions. Random phase screens are essential elements of simulating light propagation through turbulent media. In order to be effective, they must accurately reflect theory and be practical to implement. This research explains and evaluates three methods of generating random phase screens: using a Fourier series upon a polar frequency grid with logarithmic spacing; using the fast Fourier transform, with its Cartesian frequency grid; and using Zernike polynomials. It provides a comparison of the Polar Fourier Series technique with the two more common techniques (Fast Fourier Transform and Zernike), with the end result of giving the users enough information to choose which method best fits their needs. The evaluation criteria used are generation time (usability) and phase structure function (accuracy)

PSCAD Modeling and Stability Analysis of a Microgrid

As power systems are evolving, engineers are facing, and will continue to face, new challenges with respect to maintaining the system in terms of stable operation. Many different forms of generation are becoming prevalent, including; small synchronous generators, photovoltaic generation, and energy storage techniques in the form of battery and ultracapacitor systems. One of the evolutions occurring in the power system is the emergence of microgrids, small power systems capable of isolating from the major power grid in the form of islands. Microgrids use distributed generation to provide power to small communities, and they come with several advantages and disadvantages. This thesis shows the design process employed to model a microgrid, which contains a variety of distributed resources, in PSCAD, as well as investigate the transient instability of the microgrid when transitioning to islanded operation. Modeling techniques for both grid-connected and islanded operation of the microgrid are considered in this study. In addition to modeling techniques, the effectiveness of proper control of energy storage assets in a microgrid is demonstrated through the implementation and comparison between real & reactive power regulation and voltage & frequency regulation

Optimised Integration of Grid-Connected Renewable Energy Technologies for Domestic Application in Ireland

The utilisation of renewable energy resources for electricity and thermal generation is extremely important in Ireland due to the lack of indigenous fossil fuel resources and the high dependence on imported fossil fuels. The release of environmentally-damaging greenhouse gases in the combustion of fossil fuels in electricity and thermal generation is also a major issue. In Ireland, the domestic dwelling is recognised as one of the biggest energy consumers. The use of renewable energy technologies to provide electricity, heating and hotwater can effectively offset the usage of fossil fuels. The aim of this research study was to develop a novel technique for the optimised integration of grid-connected renewable energy systems to satisfy the entire energy demand in a domestic dwelling. The development of the technique was carried out in a series of logical stages. In the first stage, a sub-technique for the optimised integration of grid-connected micro-renewable electricity generation systems was developed. In this sub-technique a detailed and accurate economic analysis of the investigated systems is performed. Net present value is the metric employed in the economic analysis and the system which achieves the highest net present value is deemed the optimal system. High-resolution measured electrical load data and a user-specified renewable energy requirement are employed in this sub-technique. The renewable energy requirement is the percentage of the household electricity demand that must be satisfied by the on-site grid-connected micro-renewable electricity generation system. In the second stage, a sub-technique for the optimised integration of grid-connected micro-renewable thermal generation systems was developed. In this sub-technique, following the completion of the life cycle cost (economic) analysis of the investigated systems, the system which achieves the lowest life cycle cost is deemed the optimal system. High-resolution measured thermal load data is utilised in this sub-technique. Finally, in the third stage, the overall integration technique was then developed by amalgamating these two sub-techniques. Life cycle cost analysis is again used to determine the optimal system. In order to demonstrate their application, the two sub-techniques and overall technique were deployed with Irish conditions. The investigated systems were formed from commercially-available products; the products selected for this study were six micro wind turbines, three solar PV modules, three air source heat pumps and three solar thermal collectors. When the sub-technique for the optimised integration of grid-connected micro renewable electricity generation systems was deployed under current Irish conditions, the optimal system, which meets the 50% renewable energy requirement, was a single micro wind turbine having a capacity of 2.4 kW. However, this optimal system is not economically viable as its net present value is negative. When the sub-technique for the optimised integration of grid-connected micro renewable thermal generation systems was deployed, the optimal system was a single air source heat pump having a thermal capacity of 14 kW. This optimal system is economically viable in comparison with an oil boiler system or an electrical heating system; however it is not economically viable compared with a gas boiler system. Finally, when the overall integration technique was deployed, the optimal system was a combination of an air source heat pump having a thermal capacity of 14 kW and grid supplied electricity; however this system is not economically viable in comparison with an economically-best-performing conventional combination of grid supplied electricity and a gas boiler system. The influence of several parameters on the economic performance of the investigated systems was also studied with the developed sub-techniques and overall technique. Due to the wide range of micro-renewable energy generation systems available on the market and the broad range of existing capacities, the developed integration technique is extremely useful for performing an accurate economic analysis and determining a system that is most suitable for a domestic dwelling

An assessment of the adaptive unstructured tetrahedral grid, Euler Flow Solver Code FELISA

A three-dimensional solution-adaptive Euler flow solver for unstructured tetrahedral meshes is assessed, and the accuracy and efficiency of the method for predicting sonic boom pressure signatures about simple generic models are demonstrated. Comparison of computational and wind tunnel data and enhancement of numerical solutions by means of grid adaptivity are discussed. The mesh generation is based on the advancing front technique. The FELISA code consists of two solvers, the Taylor-Galerkin and the Runge-Kutta-Galerkin schemes, both of which are spacially discretized by the usual Galerkin weighted residual finite-element methods but with different explicit time-marching schemes to steady state. The solution-adaptive grid procedure is based on either remeshing or mesh refinement techniques. An alternative geometry adaptive procedure is also incorporated

Design, Simulation, and Construction of an IEEE 14-Bus Power System

Today’s bulk power system is massive, complex, and very dynamic. The U.S. power grid spans from coast to coast and even as far reaching as Canada. With the addition of new technologies such as renewable energies and power electronics to aid in power conversion and control, the power system grows more complex by the day. The most common approach of analyzing power system stability is through computer modeling and simulation. Due to the vast size and inaccessibility of transmission systems, real time testing can prove difficult. The motivation of this project was to design, simulate, and construct an IEEE 14 bus power system for future use in a lab setting to test, in real time, novel control techniques for various forms of generation and their impacts on the stability of the grid. This thesis presents the theory used to design and construct an IEEE 14-bus power system. A comparison of results from modeling and simulation with actual lab data obtained from the constructed test set up

Energy management system of a microgrid with distributed generation

An Energy Management System (EMS) is required to control the flow of power and match generation with the load within a microgrid during grid-connected and islanded modes of operation. In grid-connected mode, a microgrid draws/supplies power from/to the main grid, depending on the generation and load requirements, and with suitable market policies to maximize the efficiency/cost etc. Likewise, it can separate itself from the main grid whenever a drastic power quality event (such as a fault occurs in the main grid) and continues to supply power to critical loads. An optimization algorithm is needed to minimise the cost of the energy drawn from the grid, generated within the grid and consumed by the loads. In this thesis, two optimization techniques namely Particle Swarm Optimization (PSO) and Differential Evolution (DE) are used to optimize an EMS for a generic MG comprised of Combined Heat and Power (CHP) plant, Diesel generator, Natural gas-fired generator, Photovoltaic (PV) generator and Wind generator. The EMS is tested for both grid-connected and islanded modes of operation to demonstrate the effectiveness of the optimization algorithms. In grid connected mode, the comparison of the most optimal utilization of grid during on- and off-peak hours and achieve the lowest operational cost. Likewise, for islanded mode of operation the comparison between the utilization of the three generators to match the load demand and achieve the lowest operational cost

Enhancement of On-grid PV System under Irradiance and Temperature Variations Using New Optimized Adaptive Controller

Solar Energy is one of the key solutions to future electrical power generation. Photovoltaic Plants (PV) are fast growing to satisfy electrical power demand. Different maximum power point tracking techniques (MPPT) are used to maximize PV systems generated power. In this paper, on grid PV system model in MATLAB SIMULINK is tested under sudden irradiance and cell temperature variations. Incremental Conductance MPPT is used to maximize generated power from the PV system with the help of new adaptive controller to withstand these heavy disturbances. The new adaptive controller is tuned for optimal operation using two different optimization techniques (Invasive weed and Harmony search).Optimization results for the two techniques are compared. .A robustness test is made to check system stability to withstand different random irradiance and cell temperature patterns without failure to track the maximum power point.Finally, a brief comparison is made with a previous literature and the new adaptive controller gives better results

An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA

The increasing penetration of distributed generation resources demands better economic performance of microgrids under the smart-grid era. In this paper, a comprehensive environmental-economic dispatch method for smart microgrids is proposed, with the objective for minimizing the summation of generation and emission costs in the system. As the proposed model belongs to a large-scale nonlinear and nonconvex programming problem, a hybrid heuristic algorithm, named variable step-size chaotic fuzzy quantum genetic algorithm (VSS_QGA), is developed. The algorithm utilizes complementarity among multiple techniques including the variable step size optimization, the rotation mutational angle fuzzy control, and the quantum genetic algorithm and combines them so as to solve problems with superior accuracy and efficiency. The effectiveness of the proposed model is demonstrated through a case study on an actual microgrid system and the advantages in the performance of VSS_QGA is also verified through the comparison with genetic algorithm (GA), the evolutionary programming approach (EP), the quantum genetic algorithm (QGA), and the chaotic quantum genetic algorithm (CQGA)

A Comparison of Cosmological Hydrodynamic Codes

We present a detailed comparison of the simulation results of various cosmological hydrodynamic codes. Starting with identical initial conditions based on the Cold Dark Matter scenario for the growth of structure, we integrate from redshift $z=20$ to $z=0$ to determine the physical state within a representative volume of size $L^3$ where $L=64 h^{-1} {\rm Mpc}$. Five independent codes are compared: three of them Eulerian mesh based and two variants of the Smooth Particle Hydrodynamics "SPH" Lagrangian approach. The Eulerian codes were run at $N^3=(32^3,~64^3,~128^3,~{\rm and},~256^3)$ cells, the SPH codes at $N^3= 32^3$ and $64^3$ particles. Results were then rebinned to a $16^3$ grid with the expectation that the rebinned data should converge, by all techniques, to a common and correct result as $N \rightarrow \infty$. We find that global averages of various physical quantities do, as expected, tend to converge in the rebinned model, but that uncertainties in even primitive quantities such as $\langle T \rangle$, $\langle \rho^2\rangle^{1/2}$ persists at the 3\%-17\% level after completion of very large simulations. The two SPH codes and the two shock capturing Eulerian codes achieve comparable and satisfactory accuracy for comparable computer time in their treatment of the high density, high temperature regions as measured in the rebinned data; the variance among the five codes (at highest resolution) for the mean temperature (as weighted by $\rho^2$) is only 4.5\%. Overall the comparison allows us to better estimate errors, it points to ways of improving this current generation of hydrodynamic codes and of suiting their use to problems which exploit their individually best features.Comment: 20p plaintex to appear in The Astrophysical Journal on July 20, 199

Development of working fluid control techniques for improved ramping response in geothermal-based organic Rankine cycle generation systems

Thesis (M.S.) University of Alaska Fairbanks, 2021Small-scale low-temperature geothermal-based electricity generation systems are under development for use as grid supporting and grid forming power sources in remote locations. Conversion of low-temperature heat to electrical energy in an organic Rankine cycle using working fluids such as refrigerants is challenging due to the low energy conversion efficiency of the process and the significantly slower thermal response rate in comparison to the time response of the electrical grid for changes in electrical generation and load. There is a need to investigate techniques for controlling the flow of the working fluid in combination with the use of a secondary heat exchanger to improve ramping response of these systems. This research project develops and models a working fluid control technique that incorporates power electronic technologies that could help to improve the ramping response of geothermal-based organic Rankine cycle generation systems. The performance of the model is examined with the aid of simulations in MATLAB® Simulink®. The results from these simulations are used to develop a functional and reliable control technique for ramping response improvement in geothermal-based electricity generation systems using organic Rankine cycles