A novel probabilistic method has been developed for modelling the operation of energy storage in electricity systems with significant amounts of wind and solar powered generation. This method is based on a spectral analysis of the variations of wind speed and solar irradiance together with profiles of electrical demand. The method has been embodied in two Matlab computer programs: Wind power only: This program models wind power on any time scale from seconds to years, with limited modelling of demand profiles. This program is only capable of modelling stand-alone systems, or systems in which the electrical demand is replaced by a weak grid connection with limited export capacity. 24-hours: This program models wind power, solar PV power and electrical demand, including seasonal and diurnal effects of each. However, this program only models store cycle times (variations within a time scale) of 24 hours. This program is capable of modelling local electrical demand at the same time as a grid connection with import or export capacity and a backup generator. Each of these programs has been validated by comparing its results with those from a time step program, making four Matlab programs in total. All four programs calculate the power flows to and from the store, satisfied demand, unsatisfied demand and curtailed power. The programs also predict the fractions of time that the store spends full, empty, filling or emptying. The results obtained are promising. Probabilistic program results agree well with time step results over a wide range of input data and time scales. The probabilistic method needs further refinement, but can be used to perform initial modelling and feasibility studies for renewable energy systems. The probabilistic method has the advantage that the required input data is less, and the computer run time is reduced, compared to the time step method.

In this thesis, solar-hydrogen Stand-Alone Power System (SAPS) which is planned to be built for the emergency room of a hospital is designed. The system provides continuous, off-grid electricity during the whole period of a year without any external electrical power supply. The system consists of Photovoltaic (PV) panels, Proton Exchange Membrane (PEM) based electrolyzers, PEM based fuel cells, hydrogen tanks, batteries, a control mechanism and auxiliary equipments such as DC/AC converters, water pump, pipes and hydrogen dryers. The aim of this work is to investigate the optimal system configuration and component sizing which yield to high performance and low cost for different user needs and control strategies. TRNSYS commercial software is used for the overall system design and simulations. Numerical models of the PV panels, the control mechanism and the PEM electrolyzers are developed by using theoretical and experimental data and the models are integrated into TRNSYS. Overall system models include user-defined components as well as the default software components. The electricity need of the emergency room without any shortage is supplied directly from the PV panels or by the help of the batteries and the fuel cells when the solar energy is not enough. The pressure level in the hydrogen tanks and the overall system efficiency are selected as the key design parameters. The major component parameters and various control strategies affecting the hydrogen tank pressure and the system efficiency are analyzed and the results are presented.

This work focuses on the safe and stable operation of an autonomous power system interconnecting an AC source with various types of power electronic loads. The stability of these systems is a challenge due to the inherent nonlinearity of the circuits involved. Traditionally, the stability analysis in this type of power systems has been approached by means of small-signal methodology derived from the Nyquist stability criterion. The small-signal analysis combined with physical insight and the adoption of safety margins is sufficient, in many cases, to achieve a stable operation with an acceptable system performance. Nonetheless, in many cases, the margins adopted result in conservative measures and consequent system over designs. This work studies the system stability under large-perturbations by means of three different tools, namely parameter space mapping, energy functions, and time domain simulations. The developed parameters space mapping determines the region of the state and parameter space where the system operation is locally stable. In this way stability margins in terms of physical parameters can be established. Moreover, the boundaries of the identified stability region represent bifurcations of the system where typical nonlinear behavior appears. The second approach, based on the Lyapunov direct method, attempts to determine the region of attraction of an equilibrium point, defined by an operation condition. For this a Lyapunov function based on linear matrix inequalities was constructed and tested on a simplified autonomous system model. In Addition, the third approach simulates the system behavior on a computer using a detailed system model. The higher level of model detail allows identifying unstable behavior difficult to observe when simpler models are used. Because the stability of the autonomous power system is strongly associated with the characteristics of the energy source, an improved voltage controller for the generator is also presented. The generator of an autonomous power system must provide a good performance under a wide variety of regimes. Under these conditions a model based controller is a good solution because it naturally adapts to the changing requirements. To this extent a controller based on the model of a variable frequency synchronous generator has been developed and tested. The results obtained show a considerable improvement performance when compared to previous practices. / Ph. D.