This study focuses on the design, construction and operation of a distributed generation system based on micro-hydro technology. The project is sited in the Totara Valley, a small rural community approximately 70km from the Massey University, Turitea campus, Palmerston North. The Massey University Centre for Energy Research (MUCER) has a long history of renewable energy research within the Totara Valley community. This project complements these existing schemes and provides a foundation for future research into distributed generation technologies. The project encompasses the following objectives: - to gain practical experience in the design, engineering and implementation of a distributed generation system in rural New Zealand; - to evaluate contemporary micro-hydro technology and compare the performance of this equipment in a theoretical and practical context; - to identify barriers that hinder the widespread adoption of micro-hydro systems in rural New Zealand; - to develop a spreadsheet based life cycle costing tool. The results from this study demonstrate that economic considerations are the fundamental aspect to be considered when assessing the long-term viability of these projects. The viability of micro-hydro projects are primarily determined by four factors: - the volume and head (height) of water available above the turbine site; - the length and therefore the cost of the pipeline required for transporting water to the turbine; - the legal and administrative costs involved in obtaining a resource consent to maintain access to the water resources; - the prices received and paid for electricity. Considerable charges were payable to the local authority to secure and maintain the right to harness the water resources at this site. This cost contributed considerable risk to the project and creates a significant barrier to establishing similar systems at other sites. The reduction of resource consent charges to levels that fairly reflect the negligible environmental impacts of these projects would encourage the adoption of this technology and deliver benefits to rural New Zealand communities.

In the context of the envisioned electric power delivery system of the future, the smart grid, this dissertation focuses on control and management strategies for integration of distributed energy resources in the power system. This work conceptualizes a hierarchical framework for the control of microgrids---the building blocks of the smart grid---and develops the notion of potential functions for the secondary control for devising intermediate set points to ensure feasibility of operation of the system. A scalar potential function is defined for each controllable unit of the microgrid such that its minimization corresponds to achieving the control goal. The set points are dynamically updated using communication within the microgrid. This strategy is generalized to (i) include both local and system-wide constraints and (ii) allow a distributed implementation. This dissertation also proposes and evaluates a simple yet elaborate distributed strategy to mitigate the transients of controllable devices of the microgrid using local measurements. This strategy is based on response monitoring and is augmented to the existing controller of a power system device. This strategy can be implemented based on either set point automatic adjustment (SPAA) or set point automatic adjustment with correction enabled (SPAACE) methods. SPAA takes advantage of an approximate model of the system to calculate intermediate set points such that the response to each one is acceptable. SPAACE treats the device as a generic system and monitors its response and modulates its set point to achieve the desired trajectory. SPAACE bases its decisions on the trend of variations of the response and accounts for inaccuracies and unmodeled dynamics. Case studies using the PSCAD/EMTDC software environment and MATLAB programming environment are presented to demonstrate the application and effectiveness of the proposed strategies in different scenarios.

In the context of the envisioned electric power delivery system of the future, the smart grid, this dissertation focuses on control and management strategies for integration of distributed energy resources in the power system. This work conceptualizes a hierarchical framework for the control of microgrids---the building blocks of the smart grid---and develops the notion of potential functions for the secondary control for devising intermediate set points to ensure feasibility of operation of the system. A scalar potential function is defined for each controllable unit of the microgrid such that its minimization corresponds to achieving the control goal. The set points are dynamically updated using communication within the microgrid. This strategy is generalized to (i) include both local and system-wide constraints and (ii) allow a distributed implementation. This dissertation also proposes and evaluates a simple yet elaborate distributed strategy to mitigate the transients of controllable devices of the microgrid using local measurements. This strategy is based on response monitoring and is augmented to the existing controller of a power system device. This strategy can be implemented based on either set point automatic adjustment (SPAA) or set point automatic adjustment with correction enabled (SPAACE) methods. SPAA takes advantage of an approximate model of the system to calculate intermediate set points such that the response to each one is acceptable. SPAACE treats the device as a generic system and monitors its response and modulates its set point to achieve the desired trajectory. SPAACE bases its decisions on the trend of variations of the response and accounts for inaccuracies and unmodeled dynamics. Case studies using the PSCAD/EMTDC software environment and MATLAB programming environment are presented to demonstrate the application and effectiveness of the proposed strategies in different scenarios.

The growing interest in small-scale electricity generation located near customers, known as Distributed Generation (DG), is driven primarily by emerging technologies, environmental regulations and concerns, electricity market restructuring, and growing customer demand for increased quality and reliability of the electricity supply. Wind turbines are one of the renewable DG technologies that have become an important source of electricity in many parts of the world. Wind power can be used in many places to provide a viable solution to rising demand, energy security and independence, and climate change mitigation. This research aims broadly at facilitating the integration of wind-based DG without jeopardizing the system’s economics and reliability. To achieve this goal, the thesis tackles wind power from three perspectives: those of the policy maker, the investor, and the system operator. Generally, the economic viability of a project is determined within the framework of relevant policies. Therefore, these policies influence the decisions of potential investors in wind power. From this perspective, chapters 3 and 4 investigate the influence of policies on the economic viability of wind-based DG projects. In chapter 3, the role of Ontario’s taxation and incentive policies in the economic viability of wind-based DG projects is investigated. In this study, the effects of provincial income taxes, capital cost allowances, property taxes, and relevant federal incentives are considered. Net Present Value (NPV) and Internal Rate of Return (IRR) for different scenarios are used to assess the project’s viability under the Ontario Standard Offer Program (SOP) for wind power. In chapter 4, the thesis proposes the use of wind power as a source of electricity in a new city being developed in the Duqm area of Oman, where no policies supporting renewable energy exist. The study shows that the cost of electricity produced by wind turbines is higher than that of the existing generation system, due to the subsidized prices of domestically available natural gas. However, given high international natural gas prices, the country’s long-term Liquefied Natural Gas (LNG) export obligations, and the expansion of natural gas-based industries, investments in wind power in Duqm can be justified. A feed-in tariff and capital cost allowance policies are recommended to facilitate investments in this sector. From a wind-based DG investor’s perspective, the optimal selection of wind turbines can make wind power more economical, as illustrated in chapters 5 and 6. In chapter 5, the thesis presents a new generic model for Capacity Factor (CF) estimation using wind speed characteristics at any site and the power performance curve parameters of any pitch-regulated wind turbine. Compared to the existing model, the proposed formulation is simpler and results in more accurate CF estimation. CF models can be used by wind-based DG investors for optimal turbine-site matching applications. However, in chapter 6, the thesis demonstrates that using CF models as the sole basis for turbine-site matching applications tends to produce results that are biased towards higher towers but do not include the associated costs. Therefore, a novel formulation for the turbine-site matching problem, based on a modified CF formulation that does include turbine tower height, is introduced in chapter 6. The proposed universal Turbine-Site Matching Index (TSMI) also includes the effects of turbine rated power and tower height on the initial capital cost of wind turbines. Chapter 7 tackles wind power from a power system operator’s perspective. Despite wind power benefits, the effects of its intermittent nature on power systems need to be carefully examined as penetration levels increase. In this chapter, the thesis investigates the effects of different temporal wind profiles on the scheduling costs of thermal generation units. Two profiles are considered: synoptic-dominated and diurnal-dominated variations of aggregated wind power. To simulate wind profile impacts, a linear mixed-integer unit commitment problem is formulated in a GAMS environment. The uncertainty associated with wind power is represented using a chance constrained formulation. The simulation results illustrate the significant impacts of different wind profiles on fuel saving benefits, startup costs, and wind power curtailments. In addition, the results demonstrate the importance of the wide geographical dispersion of wind power production facilities to minimize the impacts of network constraints on the value of the harvested wind energy and the amount of curtailed energy.

The growing interest in small-scale electricity generation located near customers, known as Distributed Generation (DG), is driven primarily by emerging technologies, environmental regulations and concerns, electricity market restructuring, and growing customer demand for increased quality and reliability of the electricity supply. Wind turbines are one of the renewable DG technologies that have become an important source of electricity in many parts of the world. Wind power can be used in many places to provide a viable solution to rising demand, energy security and independence, and climate change mitigation. This research aims broadly at facilitating the integration of wind-based DG without jeopardizing the system’s economics and reliability. To achieve this goal, the thesis tackles wind power from three perspectives: those of the policy maker, the investor, and the system operator. Generally, the economic viability of a project is determined within the framework of relevant policies. Therefore, these policies influence the decisions of potential investors in wind power. From this perspective, chapters 3 and 4 investigate the influence of policies on the economic viability of wind-based DG projects. In chapter 3, the role of Ontario’s taxation and incentive policies in the economic viability of wind-based DG projects is investigated. In this study, the effects of provincial income taxes, capital cost allowances, property taxes, and relevant federal incentives are considered. Net Present Value (NPV) and Internal Rate of Return (IRR) for different scenarios are used to assess the project’s viability under the Ontario Standard Offer Program (SOP) for wind power. In chapter 4, the thesis proposes the use of wind power as a source of electricity in a new city being developed in the Duqm area of Oman, where no policies supporting renewable energy exist. The study shows that the cost of electricity produced by wind turbines is higher than that of the existing generation system, due to the subsidized prices of domestically available natural gas. However, given high international natural gas prices, the country’s long-term Liquefied Natural Gas (LNG) export obligations, and the expansion of natural gas-based industries, investments in wind power in Duqm can be justified. A feed-in tariff and capital cost allowance policies are recommended to facilitate investments in this sector. From a wind-based DG investor’s perspective, the optimal selection of wind turbines can make wind power more economical, as illustrated in chapters 5 and 6. In chapter 5, the thesis presents a new generic model for Capacity Factor (CF) estimation using wind speed characteristics at any site and the power performance curve parameters of any pitch-regulated wind turbine. Compared to the existing model, the proposed formulation is simpler and results in more accurate CF estimation. CF models can be used by wind-based DG investors for optimal turbine-site matching applications. However, in chapter 6, the thesis demonstrates that using CF models as the sole basis for turbine-site matching applications tends to produce results that are biased towards higher towers but do not include the associated costs. Therefore, a novel formulation for the turbine-site matching problem, based on a modified CF formulation that does include turbine tower height, is introduced in chapter 6. The proposed universal Turbine-Site Matching Index (TSMI) also includes the effects of turbine rated power and tower height on the initial capital cost of wind turbines. Chapter 7 tackles wind power from a power system operator’s perspective. Despite wind power benefits, the effects of its intermittent nature on power systems need to be carefully examined as penetration levels increase. In this chapter, the thesis investigates the effects of different temporal wind profiles on the scheduling costs of thermal generation units. Two profiles are considered: synoptic-dominated and diurnal-dominated variations of aggregated wind power. To simulate wind profile impacts, a linear mixed-integer unit commitment problem is formulated in a GAMS environment. The uncertainty associated with wind power is represented using a chance constrained formulation. The simulation results illustrate the significant impacts of different wind profiles on fuel saving benefits, startup costs, and wind power curtailments. In addition, the results demonstrate the importance of the wide geographical dispersion of wind power production facilities to minimize the impacts of network constraints on the value of the harvested wind energy and the amount of curtailed energy.

In recent years, with the energy shortage, the use of renewable energy is inevitable. With CO2 the most important greenhouse gas causing global warming as well as the increase of population, renewable energy is one way to save energy and reduce carbon emissions. The traditional capacity investment for serving the load in distribution systems usually considered the addition of new substations or expansion of the existing substation and associated new feeder requirement. Nowadays, there are a lots of distributed generations (DG¡¦s) to be chosen. Factors of the choice taken into account will include lower pollution, higher efficiency, higher return rate for construction of distributed power generation systems. This thesis assumes that the distributed generation can be invested for long-term power plant planning. The planning of DG would be investigated from the perspectives of the independent investors. The modified Particle Swarm Optimization is proposed to determine the optimal sizing and sit of DG¡¦s addition in distribution systems with the constrains of CO2 limitation and addition of distributed generation to maximize profits. This thesis deals with discrete programming problem of optimal power flow, which includes continuous and discrete types of variables. The continuous variables are the generating unit real power output and the bus voltage magnitudes, the discrete variables are the shunt capacitor banks and sit problems. The Miaoli-Houlong system of Taiwan power will be used in this thesis for the verification of the feasibility of the proposed method.

Distributed generation (DG) is electricity generation by small generating units, which are interconnected at distribution level with capacity less than 50 MW. Environmental concerns and the idea of using cheap and domestic renewable resources increased the popularity of DG following the developments in equipment technology. In Turkey, interconnection of DG is realized through the distribution busbars of 154/36 kV substation. The interconnection of DG at 36 kV feeders is not allowed by distribution system authority. This thesis proposes an interconnection rule which includes technical analyses to be conducted before the permission of interconnection of DG at 36 kV feeders. Moreover, the protection functions and operational requirements needed for the proper and safe operation of distribution system in presence of DG are introduced. A sample distribution system with relevant parameters is used for the simulation studies in Digsilent software. In order to determine the operational reserve requirement against the variations in wind generation, a statistical method including Weibull distribution, standard deviation and monthly average wind speeds is used. Convenience of hydropower plants&rsquo / response for being backup generation against the fluctuations in wind generation is analyzed by a mid-term dynamic model of the power system. A secondary control mechanism for the integration of wind power is suggested. Finally, an economic comparison between the interconnection alternatives of hydropower and photovoltaic power plants at the distribution busbar of the 154/36 kV substation and the 36 kV feeder is done by present worth analysis using the up to date power plant costs and incentives.

The Master's Thesis research focuses on analyzing the possibilities of using Direct Current distribution systems to distribute power to end users. Considering the shift in load types in the past few decades and also a growing demand of distributed generation, DC distribution can potentially offer higher efficiencies and cost savings to utilities. The incorporation of DC distribution offers the opportunity to eliminate multiple conversion stages for devices which are powered using DC electricity. The integration of power sources such as photovoltaics and fuel cells, which produce DC power, offer further incentives to consider the use of DC systems. Using DC systems can help eliminate the conversion losses associated with rectifiers and inverters which would be part of the infrastructure if AC distribution was used. In the literature, the study of DC distribution has been limited to customized systems. The objective of this research is to analyze DC distribution when applied to systems based on standard IEEE test feeder systems. The IEEE 13 node test feeder and the IEEE 37 node test feeder will be used as the basis for the analysis. Issues such as associated costs, protection and integration of appliances will also be addressed.

Grid-connected photovoltaic (PV) capacity is increasing worldwide, mainly due to extensive subsidy schemes for renewable electricity generation. A majority of newly installed systems are distributed small-scale systems located in distribution grids, often at residential customers. Recent developments suggest that such distributed PV generation (PV-DG) could gain more interest in Sweden in the near future. With prospects of decreasing system prices, an extensive integration does not seem impossible. In this PhD thesis the opportunities for utilisation of on-site PV generation and the consequences of a widespread introduction are studied. The specific aims are to improve modelling of residential electricity demand to provide a basis for simulations, to study load matching and grid interaction of on-site PV and to add to the understanding of power system impacts. Time-use data (TUD) provided a realistic basis for residential load modelling. Both a deterministic and a stochastic approach for generating different types of end-use profiles were developed. The models are capable of realistically reproducing important electric load properties such as diurnal and seasonal variations, short time-scale fluctuations and random load coincidence. The load matching capability of residential on-site PV was found to be low by default but possible to improve to some extent by different measures. Net metering reduces the economic effects of the mismatch and has a decisive impact on the production value and on the system sizes that are reasonable to install for a small-scale producer. Impacts of large-scale PV-DG on low-voltage (LV) grids and on the national power system were studied. Power flow studies showed that voltage rise in LV grids is not a limiting factor for integration of PV-DG. Variability and correlations with large-scale wind power were determined using a scenario for large-scale building-mounted PV. Profound impacts on the power system were found only for the most extreme scenarios. / Felaktigt tryckt som Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 711

Solar photovoltaic (PV) systems are distributed energy sources that are an environmentally friendly and renewable source of energy. However, solar PV power fluctuates due to variations in radiation and temperature levels. Furthermore, when the solar panel is directly connected to the load, the power that is delivered is not optimal. A maximum peak power point tracker is therefore necessary for maximum efficiency. A complete PV system equipped maximum power point tracking (MPPT) system includes a solar panel, MPPT algorithm, and a DC-DC converter topology. Each subsystem is modeled and simulated in a Matlab/Simulink environment; then the whole PV system is combined with the battery load to assess the overall performance when subjected to varying weather conditions. A PV panel model of moderate complexity based on the Shockley diode equation is used to predict the electrical characteristics of the cell with regard to changes in the atmospheric parameter of irradiance and temperature. In this dissertation, five MPPT algorithms are written in Matlab m-files and investigated via simulations. The standard Perturb and Observe (PO) algorithm along with its two improved versions and the conventional Incremental Conductance (IC) algorithm, also with its two-stage improved version, are assessed under different atmospheric operating conditions. An efficient two-mode MPPT algorithm combining the incremental conductance and the modified constant voltage methods is selected from the five ones as the best model, because it provides the highest tracking efficiencies in both sunny and cloudy weather conditions when compared to other MPPT algorithms. A DC-DC converter topology and interface study between the panel and the battery load is performed. This includes the steady state and dynamic analysis of buck and boost converters and allows the researcher to choose the appropriate chopper for the current PV system. Frequency responses using the state space averaged model are obtained for both converters. They are displayed with the help of Bode and root locus methods based on their respective transfer functions. Following the simulated results displayed in Matlab environment for both choppers, an appropriate converter is selected and implemented in the present PV system. The chosen chopper is then modeled using the Simulink Power Systems toolbox and validates the design specifications. The simulated results of the complete PV system show that the performances of the PV panel using the improved two-stage MPPT algorithm provides better steady state and fast transient characteristics when compared with the conventional incremental conductance method. It yields not only a reduction in convergence time to track the maximum power point MPP, but also a significant reduction in power fluctuations around the MPP when subjected to slow and rapid solar irradiance changes. / Thesis (M.Sc.Eng)-University of KwaZulu-Natal, Durban, 2011.