Tools and algorithms are proposed that are useful for planning, designing, and operating a distribution network with a significant penetration of distributed generation (DG). In Task 1, a PV system simulation program is developed, which incorporates the most rigorous models for the calculation of insolation, module temperature, and DC and AC power output of a PV system. The effect of random inverter failures is incorporated in the model of a PV system, and a novel performance-derating coefficient is introduced. Furthermore, a novel inverter control algorithm is presented for systems with multiple inverters. The algorithm is designed to increase overall DC/AC conversion efficiency by selectively shutting down some of the inverters during periods of low insolation, thus forcing the remaining inverters to operate at higher efficiency. In Task 2, a procedure is developed to incorporate the uncertainties imposed by stochastic, renewable DG into the conventional tools for analysis of distribution systems. A clustering algorithm is proposed to reduce large input data sets that result from the interaction of stochastic processes that drive DG output with field measurements of feeder load profiles. In addition, a procedure is proposed to determine the boundary points of the original data set, which yield feeder extreme operating conditions. Finally, a Monte Carlo analysis using a reduced data set is presented, to determine the effects of deploying a large number of renewable DG systems on a distribution feeder. In Task 3, the reliability model of an asymmetric, three--phase, non-radial distribution feeder equipped with capacity-constrained DGs is developed and used to quantify the potential reliability improvements due to the intentional islanded operation of parts of the feeder. A procedure for finding optimal positions for DG and protection devices is presented using a custom-tailored adaptive genetic algorithm.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

To combat global climate change, the reduction of carbon emissions in different industries, particularly the power industry, has been gradually moving towards a low-carbon profile to alleviate any irreversible damage to the planet and our future generations. Traditional fossil-fuel-based generation is slowly replaced by more renewable energy generation while it can be harnessed. However, renewables such as solar and wind are stochastic in nature and difficult to predict accurately. With the increasing content of renewables, there is also an increasing challenge to the planning and operation of the grid. With the rapid deployment of smart meters and advanced metering infrastructure (AMI), an emerging approach is to schedule controllable end-use devices to improve energy efficiency. Real-time pricing signals combined with this approach can potentially deliver more economic and environmental advantages compared with the existing common flat tariffs. Motivated by this, the thesis presents an automatic and optimal load scheduling framework to help balance intermittent renewables via the demand side. A bi-level consumer-utility optimization model is proposed to take marginal price signals and wind power into account. The impact of wind uncertainty is formulated in three different ways, namely deterministic value, scenario analysis, and cumulative distributions function, to provide a comprehensive modeling of unpredictable wind energy. To solve the problem in off-the-shelf optimization software, the proposed non-linear bi-level model is converted into an equivalent single-level mixed integer linear programming problem using the Karush-Kuhn-Tucker optimality conditions and linearization techniques. Numerical examples show that the proposed model is able to achieve the dual goals of minimizing the consumer payment as well as improving system conditions. The ultimate goal of this work is to provide a tool for utilities to consider the demand response model into their market-clearing procedure. As high penetration of distributed renewable energy resources are most likely applied to remote or stand-alone systems, planning such systems with uncertainties in both generation and demand sides is needed. As such, a three-level probabilistic sizing methodology is developed to obtain a practical sizing result for a stand-alone photovoltaic (PV) system. The first-level consists of three modules: 1) load demand, 2) renewable resources, and 3) system components, which comprise the fundamental elements of sizing the system. The second-level consists of various models, such as a Markov chain solar radiation model and a stochastic load simulator. The third-level combines reliability indices with an annualized cost of system to form a new objective function, which can simultaneously consider both system cost and reliability based on a chronological Monte Carlo simulation and particle swamp optimization approach. The simulation results are then tested and verified in a smart grid laboratory at the University of Hong Kong to demonstrate the feasibility of the proposed model. In summary, this thesis has developed a comprehensive framework of demand response on variable end-use consumptions with stochastic generation from renewables while optimizing both reliability and cost. Smart grid technologies, such as renewables, microgrid, storage, load signature, and demand response, have been extensively studied and interactively modeled to provide more intelligent planning and management for the smart grid. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

D. Tech. Electrical Engineering. / Discusses the objective of this study is to develop an embedded generator-pump set topology using a wound rotor induction machine using the doubly fed induction generator concept, and a synchronous machine electrically and mechanically coupled to it, powering its magnetisation circuit. An adjustable pitch pump is also coupled to the generating set on the same shaft to provide an embedded generating-pumping solution that can provide co-incident generating ans pumping functions. The research objectives are as follows: to develop an overall plant topology, to identify plant attributes necessary for proper functionality of the proposed plant, to identify a pumping/generation topology that meets the required electro-mechanical and overall topological layout attribute requirements, to develop a primitive mathematical model of the plant that provides insight into fundamental physical behaviour of the plant, to investigate the stability issues arising from the electromechanical coupling of the two machines used, to establish controllability of the proposed configuration, to identify influencing factors on the stable operation of the proposed plant, to develop an overall system model for simulation. This also entails developing a suitable mathematical model for the variable pitch pump and to simulate the system steady state and dynamic behaviour.

No description available.

Thesis (Ph.D.) -- Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

Thesis (M.Sc.)--University of Alberta, 2010. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Power Engineering and Power Electronics, Department of Electrical and Computer Engineering. Title from pdf file main screen (viewed on June 13, 2010). Includes bibliographical references.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology 2014 / In recent times, renewable energy-based distributed generation (DG) has captivated the industrial sector and on a global scale this has become a leading research area. Distributed generation using wind, solar energy or biomass as a source of energy can produce electricity on a small scale. Therefore, there is a strong focus on using renewable energy as a safe alternative source of energy, especially because it can in future play a dominant role in the world’s energy production and help to tackle the increase of global warming caused by fossil energy. However, a major problem facing renewable energies is that they are highly dependent on weather conditions. Since the power generated by DG, as well as consumption, depends on the weather conditions, irregularity of production and consumption leads to frequency and voltage fluctuations, and it can become difficult to determine and monitor consumer usage at any given time. Distributed generation can then be subjected to discrepancies in consumer usage and this can lead to severe overloading. As a result, microgrids powered by DG, operating in a single, stand-alone controllable system mode, face new challenges in terms of balancing a cluster of loads. Balancing a cluster of loads by making sure at all times that the entire system operates without overloading, is an essential requirement for the proper operation of a power system. The microgrid load considered in this project is the sum of sensitive and non-sensitive loads, respectively 5 kW and 100 kW, which constitute load requirement of one village; this total load required by a number of villages is called a cluster load. Depending on the input power generated by a DG-based photovoltaic (PV) system, these loads can be controlled using a logic control switch (LCS). When the power produced is less than the minimum load required by a component of a cluster, overloading occurs. The purpose of using an LCS is to ensure that a stable system is maintained under various loads and resource conditions. An LCS is used to continuously monitor and adjust load through circuit breakers. It is a good alternative to load balancing for a cluster of villages in rural area where a microgrid is operating in stand-alone mode. The focus of this research is to design a photovoltaic system with a maximum capacity of 1 MW providing power to a cluster of rural villages, and operating in stand-alone mode, and then to apply different control techniques (droop control, dq0 reference frame + proportional integral (PI) controller, and PI controller alone) at the inverter terminal of the PV system, in order to evaluate the stability of the output voltage. Another goal of the research is to develop an energy management system (EMS) algorithm to support the PV system in reducing loads. Therefore, a iii stable system under various load and resource conditions, as well as suitable control mechanisms are required to model a PV system. There is a need for the modelling of a PV array using a physical modelling block in MATLAB (SIMULINK) software. The state flow provided by SIMULINK is used in this project to develop an algorithm for load balancing. The state flow gives possibilities of modelling complex algorithms by combining graphical and tabular representations to create sequential decision logic, derived from state transition diagrams and tables, flow charts and truth tables. Furthermore, the design of a microgrid using photovoltaic DG and an energy management system, has been developed. The present work mainly consists of a stand-alone microgrid operation, where the power generated must be equal to the load power. In addition, different control methods, consisting of a dq0 reference frame + PI controller, are analysed at the invertor terminal. Subsequently an LCS algorithm is developed; this is required to maintain the system within certain limits and prevents overloading. LCS algorithms are based on a flowchart and allow switching automatically selected loads, depending on the power (solar radiation) available. In addition, a flow chart provides an easy way of using a graphical transition state and state chart to establish a set of rules for the system. The simulation results show that both droop control and a dq0 reference frame + PI controller are much better than a PI controller alone; these results also compared well with similar studies found in the literature. Also, these results are further improved with an EMS in order to maintain the output voltage of the microgrid, by switching on and off certain loads depending on the input power. The modelling of the microgrid using DG, based on photovoltaic systems with a maximum capacity of 1 MW, supports and improves the PV system by reducing loads. Moreover, droop control, and dq0 transformation + PI control present a better result than PI controller alone.

Thesis submitted in fulfilment of the requirements for the degree Doctor of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology 2014 / Distributed generation (DG) has been reincarnated after its demise by centralised generation. While economy of scale and efficiency are the advantages of the latter, deregulation of the electricity market, environmental concerns and the need to arrest dwindling reserve margins have necessitated the rebirth of the former. Indeed, a full circle has therefore evolved with generation being ‘embedded’ in distribution systems and ‘dispersed’ around the system rather than being located and dispatched centrally or globally. This development is in tandem with the history of industrial revolutions that started from energy and moved through services and communication and back to energy. South Africa is not immune to the global energy, especially tertiary energy, challenge phenomenon. At the peak of the 2007-2008 energy crisis, her generation net reserve margin fell below 10% – well below conventional industry benchmark of at least 15%. Also South Africa is Africa’s largest emitter of CO2 contributing over 40% of Africa’s total CO2 emissions. Therefore, DG’s relevance to South Africa is quite obvious. However, DG integration into distribution networks leads to a number of challenges. For instance, with significant penetration of DG power flow reversal may be experienced and the distribution network will no longer be a passive circuit. This underscores the crucial role of ICT in active distribution network occasioned by DG and especially the emergent of “prosumerism” (a hitherto consumer also becoming a producer). Therefore, a smart grid and similar phrases have all been used to describe a “digitised” and intelligent version of the present-day power grid. There are immense benefits derivable from modelling and simulation. Consequently, a typical radial distribution network model has been developed to evaluate the considerable impacts of DG integration. The modelling and simulation of the network are accomplished using the DIgSILENT PowerFactory simulation package. Impacts of DG on voltage profile, fault level, voltage stability and protection coordination have been investigated and their possible mitigation measures proferred. The results reveal that for a particular DG type its impacts depend mainly on its capacity and point of connection relative to a given load type. Smart grid technology addresses some of these impacts through its inherent capability which includes peer-to-peer relay communication for protective devices on the distribution feeder as well as communication to the DG facility.