The main objective of this study is to analyze the impact of the stochastic renewable distributed generation (DG) system on the urban distribution network. Renewable DG systems, particularly photovoltaic (PV) systems, dispersed on the distribution network may, in spite of their relatively small individual capacities, change the behavior of such a network. Therefore, this study (1) developed tools and algorithms useful for planning, designing, and operating such a network, (2) addressed some of the issues in the analysis of the impact of renewable DG systems on such a network, and (3) designed a framework for streamlining the future development and the smooth integration of renewable DG systems into the urban distribution network. For this purpose, in Task 1, using the backward and forward sweep method implemented in MATLAB, this study developed an algorithm for three-phase power flow that models power system components, including distribution systems, transformers, and PV systems. To model the influence of the inherent uncertainty of the input, the location, and the capacity of the PV system, this study implemented a stochastic simulation algorithm combined with the power-flow algorithm. It also accelerated the stochastic algorithm using a method of variance reduction, including importance sampling, and the sampling of representative clusters and extreme points, which reduced the extremely heavy computational burden that the stochastic simulation inevitably imposed. Then this study analyzed inherent uncertainties such as the inputs, the locations, and the capacities of residential PV systems stochastically installed on urban distribution networks by performing several stochastic simulations. In Task 2, this study developed a genetic algorithm in MATLAB that solves an optimization problem that maximizes the reliability (or minimizes the frequency and the duration of failure) of urban distribution networks enhanced by protection devices (i.e., the recloser, the fuse, and the switch) and renewable DG. Using the backward and forward method, this study implemented an analytical method that simulates all possible permanent and transient faults and evaluated the reliability of an urban distribution network housing a combination of fuses, switches, reclosers, and DG systems. Then it analyzed the impact of both the DG system, including the effect of the islanded operation of the DG system, and the protection device, on the reliability of the urban distribution network. The objective of Task 3 of this study was to present a useful method for analyzing the impact of geographically dispersed DG systems, particularly PV systems, on statewide and nationwide power grids. Using the methods of Lagrangian optimization and hydrothermal coordination, this study developed an algorithm for environmentally constrained generation resource allocation that minimizes both fuel costs and ecological impact, including the cost and the impact of water consumption. Then, this study (1) analyzed, as an example of the statewide power grid of the future, the power system of the state of Georgia in 2010, (2) modeled the load consumption and the water inflow of the power system, (3) synthesized third-order power output functions for costs, emissions, and water consumption from actual heat-rate data, and (4) estimated the power output of PV systems geographically dispersed throughout the state and hydroelectric resources of the state in hourly intervals. Lastly, it performed simulations for the generation resource allocation of the power system in hourly and minute intervals.

Human beings are facing instant and serious chemical fuel shortage and global warming subjects. We have being relying on the central power system, but causing low power efficiency and series environmental issues. Distributed power system can affect efficiently on the large investment on capital and land for central power system. It can backup the central power system for power management to maximize the power efficiency. It is one of the options for power system. Therefore, we expect to build up a reasonable measurer to the micro gas turbine thermal efficiency when the fat becomes power.

Distributed generation (defined as the production of power in small quantities at the point of use) has recently gained significant interest due to its benefits over a centralized approach. This thesis investigates the integration of a natural gas fed solid-oxide fuel cell (SOFC) and compressed air energy storage (CAES) technologies for distributed generation at the building-level scale. The SOFC/CAES system is also integrated with multiple vital sub-systems (including on-site solar panels) for the building to provide the heat, through an in-floor heating system, hot water, and power demanded by the building. This thesis investigates the models for the SOFC/CAES system, and implements them in a generic analysis tool providing a means for rapid analysis of a wide variety of case studies. The analysis tool determines the ability of the SOFC/CAES system to follow the power and heat loads demanded by the building, and evaluates its performance with an assortment of metrics, including efficiencies, CO2 emissions and grid-independence. The SOFC/CAES system was investigated for the new ExCEL building at McMaster University. It was found that the system was able to produce upwards 75% of the heat and hot water demand, and upwards of 94% of the power demand of the building. When compared to the current state-of-the-art natural gas based power producing technology and high efficiency furnace, the SOFC/CAES system reduces the CO2 emissions associated with the building by a minimum of 8.7% and a maximum of 26.95%. The cost of electricity for the system is significantly (21% to 150%) more costly than current market prices; however the SOFC/CAES system is the least costly of all other distributed generation technologies investigated for the case of the ExCEL building. / Thesis / Master of Applied Science (MASc)

Abstract The most common application of Distributed Generation (DG) is for reliability reasons. After experiencing an interruption, backup generators can be started to supply electricity to critical loads. The next most common application for DG is peak load shaving. During time periods of high energy demand or high energy prices, on-site generators are started up and used to serve part of the on-site loads. So DG can increase reliability of power supply, reduce loss of interruption and solve the problem of peak loads. Due to the high costs, only a few were installed. In order to investigate their economic values, in this thesis, several economic assessment methods are used to evaluate the cost-benefit of DG. Test results have revealed that, unless it is for environment protection reasons, the investment of DG is of little value if the fuel cost is high, and the electricity and the customer interruption costs are low. Keyword : Distributed Generation¡Mpeak load shaving.

One of the consequences of competitive electricity markets and international commitments to green energy is the fast development and increase in the amount of distributed generation (DG) in distribution grids. These DGs are resulting in a change in the nature of distribution systems from being "passive", containing only loads, to "active", including loads and DGs. This will affect the dynamic behavior of both transmission and distribution systems. There are many technical aspects and challenges of DGs that have to be properly understood and addressed. One of them is the need for adequate static and dynamic models for DG units, particularly under unbalanced conditions, to perform proper studies of distribution systems with DGs (e.g., microgrids). The primary objective of this thesis is the development and implementation of dynamic and static models of various DG technologies for stability analysis. These models allow studying systems with DGs both in the long- and short-term; thus, differential and algebraic equations of various DGs are formulated and discussed in order to integrate these models into existing power system analysis software tools. The presented and discussed models are generally based on dynamic models of different DGs for stability studies considering the dynamics of the primary governor, generators, and their interfaces and controls. A new comprehensive investigation is also presented of the effects of system unbalance on the stability of distribution grids with DG units based on synchronous generator (SG) and doubly-fed induction generator (DFIG) at different loading levels. Detailed steady-state and dynamic analyses of the system are performed. Based on voltage and angle stability studies, it is demonstrated that load unbalance can significantly affect the distribution system dynamic performance. Novel, simple, and effective control strategies based on an Unbalanced Voltage Stabilizer (UVS) are also proposed to improve the system control and the stability of unbalanced distribution systems with SG- and DFIG-based DGs.

This thesis experimentally validates the performance of an active islanding detection method under various scenarios. It is also analytically shown that the islanding detection method has a non-detection zone (NDZ), and a method to eliminate the NDZ is proposed. Moreover, the performance of an autonomous mode controller for islanded DG units is experimentally evaluated. Based on a robustness analysis, it is shown that the controller, which is basically designed for the nominal plant, can maintain the stability of the system despite of significant load uncertainties. The feasibility of the islanding detection method for islanding detection in two-DG systems is also experimentally investigated. Moreover, a control strategy for autonomous operation of two-DG systems is proposed, and its performance is experimentally evaluated. Then, adopting the islanding detection method and the proposed control strategy, the viability of smooth transitions from grid-connected modes to autonomous (islanded) modes in two-parallel DG systems is experimentally validated.

This thesis experimentally validates the performance of an active islanding detection method under various scenarios. It is also analytically shown that the islanding detection method has a non-detection zone (NDZ), and a method to eliminate the NDZ is proposed. Moreover, the performance of an autonomous mode controller for islanded DG units is experimentally evaluated. Based on a robustness analysis, it is shown that the controller, which is basically designed for the nominal plant, can maintain the stability of the system despite of significant load uncertainties. The feasibility of the islanding detection method for islanding detection in two-DG systems is also experimentally investigated. Moreover, a control strategy for autonomous operation of two-DG systems is proposed, and its performance is experimentally evaluated. Then, adopting the islanding detection method and the proposed control strategy, the viability of smooth transitions from grid-connected modes to autonomous (islanded) modes in two-parallel DG systems is experimentally validated.

Climate change has brought about legally-binding targets for Scotland, the U.K. and the E.U. to reduce greenhouse gas emissions and source a share of overall energy consumption from renewable energy resources by 2020. With severe limitations in the transport and heating sectors the onus is on the electricity sector to provide a significant reduction in greenhouse gas emissions and introduce a substantial increase in renewable energy production. The most attractive renewable energy resources are located in the geographic extremes of the country, far from the large population densities and high voltage, high capacity transmission networks. This means that the majority of renewable generation technologies will need to connect to the conventionally passive, lower voltage distribution networks. The integration of Distributed Generation (DG) is severely restricted by the technical limitations of the passively managed lower voltage infrastructure. Long lead times and the capital expenditure of traditional electricity network reinforcement can significantly delay or make the economics of some renewable generation schemes unviable. To be able to quickly and cost-effectively integrate significant levels of DG, the conventional fit-and-forget approach will have to be evolved into a ‘connect-and-manage’ system using active network management (ANM) techniques. ANM considers the real-time variation in generation and demand levels and schedules electricity network control settings to alleviate system constraints and increase connectable capacity of DG. This thesis explores the extent to which real time adjustments to DG and network asset controller set-points could allow existing networks to accommodate more DG. This thesis investigates the use of a full AC OPF technique to operate and schedule in real time variables of ANM control in distribution networks. These include; DG real and reactive power output and on-load-tap-changing transformer set-points. New formulations of the full AC OPF problem including multi-objective functions, penalising unnecessary deviation of variable control settings, and a Receding-Horizon formulation are assessed. This thesis also presents a methodology and modelling environment to explore the new and innovative formulations of OPF and to assess the interactions of various control practices in real time. Continuous time sequential, single scenario, OPF analyses at a very short control cycle can lead to the discontinuous and unnecessary switching of network control set-points, particularly during the less onerous network operating conditions. Furthermore, residual current flow and voltage variation can also gave rise to undesirable network effects including over and under voltage excursion and thermal overloading of network components. For the majority of instances, the magnitude of constraint violation was not significant but the levels of occurrence gave occasional cause for concern. The new formulations of the OPF problem were successful in deterring any extreme and unsatisfactory effects. Results have shown significant improvements in the energy yield from non-firm renewable energy resources. Initial testing of the real time OPF techniques in a simple demonstration network where voltage rise restricted the headroom for installed DG capacity and energy yield, showed that the energy yield for a single DG increased by 200% from the fit-and-forget scenario. Extrapolation of the OPF technique to a network with multiple DGs from different types of renewable energy resources showed an increase of 216% from the fit-and-forget energy yield. In a much larger network case study, where thermal loading limits constrained further DG capacity and energy yield, the increase in energy yield was more modest with an average increase of 45% over the fit-and-forget approach. In the large network where thermal overloading prevailed there was no immediate alternative to real power curtailment. This work has demonstrated that the proposed ANM OPF schemes can provide an intelligent, more cost effective and quicker alternative to network upgrades. As a result, DNOs can have a better knowledge and understanding of the capabilities and technical limitations of their networks to absorb DG safely and securely, without the expense of conventional network reinforcement.

<p>The topic of this thesis is the study of energy storage systems operating with wind power plants. The motivation for applying energy storage in this context is that wind power generation is intermittent and generally difficult to predict, and that good wind energy resources are often found in areas with limited grid capacity. Moreover, energy storage in the form of hydrogen makes it possible to provide clean fuel for transportation. The aim of this work has been to evaluate how local energy storage systems should be designed and operated in order to increase the penetration and value of wind power in the power system. Optimization models and sequential and probabilistic simulation models have been developed for this purpose.</p><p>Chapter 3 presents a sequential simulation model of a general windhydrogen energy system. Electrolytic hydrogen is used either as a fuel for transportation or for power generation in a stationary fuel cell. The model is useful for evaluating how hydrogen storage can increase the penetration of wind power in areas with limited or no transmission capacity to the main grid. The simulation model is combined with a cost model in order to study how component sizing and choice of operation strategy influence the performance and economics of the wind-hydrogen system. If the stored hydrogen is not used as a separate product, but merely as electrical energy storage, it should be evaluated against other and more energy efficient storage options such as pumped hydro and redox flow cells. A probabilistic model of a grid-connected wind power plant with a general energy storage unit is presented in chapter 4. The energy storage unit is applied for smoothing wind power fluctuations by providing a firm power output to the grid over a specific period. The method described in the chapter is based on the statistical properties of the wind speed and a general representation of the wind energy conversion system and the energy storage unit. This method allows us to compare different storage solutions.</p><p>In chapter 5, energy storage is evaluated as an alternative for increasing the value of wind power in a market-based power system. A method for optimal short-term scheduling of wind power with energy storage has been developed. The basic model employs a dynamic programming algorithm for the scheduling problem. Moreover, different variants of the scheduling problem based on linear programming are presented. During on-line operation, the energy storage is operated to minimize the deviation between the generation schedule and the actual power output of the wind-storage system. It is shown how stochastic dynamic programming can be applied for the on-line operation problem by explicitly taking into account wind forecast uncertainty. The model presented in chapter 6 extends and improves the linear programming model described in chapter 5. An operation strategy based on model predictive control is developed for effective management of uncertainties. The method is applied in a simulation model of a wind-hydrogen system that supplies the local demand for electricity and hydrogen. Utilization of fuel cell heat and electrolytic oxygen as by-products is also considered. Computer simulations show that the developed operation method is beneficial for grid-connected as well as for isolated systems. For isolated systems, the method makes it possible to minimize the usage of backup power and to ensure a secure supply of hydrogen fuel. For grid-connected wind-hydrogen systems, the method could be applied for maximizing the profit from operating in an electricity market.</p><p>Comprehensive simulation studies of different example systems have been carried out to obtain knowledge about the benefits and limitations of using energy storage in conjunction with wind power. In order to exploit the opportunities for energy storage in electricity markets, it is crucial that the electrical efficiency of the storage is as high as possible. Energy storage combined with wind power prediction tools makes it possible to take advantage of varying electricity prices as well as reduce imbalance costs. Simulation results show that the imbalance costs of wind power and the electricity price variations must be relatively high to justify the installation of a costly energy storage system. Energy storage is beneficial for wind power integration in power systems with high-cost regulating units, as well as in areas with weak grid connection.</p><p>Hydrogen can become an economically viable energy carrier and storage medium for wind energy if hydrogen is introduced into the transportation sector. It is emphasized that seasonal wind speed variations lead to high storage costs if compressed hydrogen tanks are used for long-term storage. Simulation results indicate that reductions in hydrogen storage costs are more important than obtaining low-cost and high-efficient fuel cells and electrolyzers. Furthermore, it will be important to make use of the flexibility that the hydrogen alternative offers regarding sizing, operation and possibly the utilization of oxygen and heat as by-products.</p><p>The main scientific contributions from this thesis are the development of</p><p>- a simulation model for estimating the cost and energy efficiency of wind-hydrogen systems,</p><p>- a probabilistic model for predicting the performance of a gridconnected wind power plant with energy storage,</p><p>- optimization models for increasing the value of wind power in electricity markets by the use of hydrogen storage and other energy storage solutions and the system knowledge about wind energy and energy storage that has been obtained by the use of these models.</p> / Paper 1 is reprinted with kind permission of ACTA Press. Paper 2 is reprinted with kind permission of Elsevier/ Science Direct. http://www.elsevier.com, http://www.sciencedirect.com Paper 3 is reprinted with kind permission of IEEE.

The topic of this thesis is the study of energy storage systems operating with wind power plants. The motivation for applying energy storage in this context is that wind power generation is intermittent and generally difficult to predict, and that good wind energy resources are often found in areas with limited grid capacity. Moreover, energy storage in the form of hydrogen makes it possible to provide clean fuel for transportation. The aim of this work has been to evaluate how local energy storage systems should be designed and operated in order to increase the penetration and value of wind power in the power system. Optimization models and sequential and probabilistic simulation models have been developed for this purpose. Chapter 3 presents a sequential simulation model of a general windhydrogen energy system. Electrolytic hydrogen is used either as a fuel for transportation or for power generation in a stationary fuel cell. The model is useful for evaluating how hydrogen storage can increase the penetration of wind power in areas with limited or no transmission capacity to the main grid. The simulation model is combined with a cost model in order to study how component sizing and choice of operation strategy influence the performance and economics of the wind-hydrogen system. If the stored hydrogen is not used as a separate product, but merely as electrical energy storage, it should be evaluated against other and more energy efficient storage options such as pumped hydro and redox flow cells. A probabilistic model of a grid-connected wind power plant with a general energy storage unit is presented in chapter 4. The energy storage unit is applied for smoothing wind power fluctuations by providing a firm power output to the grid over a specific period. The method described in the chapter is based on the statistical properties of the wind speed and a general representation of the wind energy conversion system and the energy storage unit. This method allows us to compare different storage solutions. In chapter 5, energy storage is evaluated as an alternative for increasing the value of wind power in a market-based power system. A method for optimal short-term scheduling of wind power with energy storage has been developed. The basic model employs a dynamic programming algorithm for the scheduling problem. Moreover, different variants of the scheduling problem based on linear programming are presented. During on-line operation, the energy storage is operated to minimize the deviation between the generation schedule and the actual power output of the wind-storage system. It is shown how stochastic dynamic programming can be applied for the on-line operation problem by explicitly taking into account wind forecast uncertainty. The model presented in chapter 6 extends and improves the linear programming model described in chapter 5. An operation strategy based on model predictive control is developed for effective management of uncertainties. The method is applied in a simulation model of a wind-hydrogen system that supplies the local demand for electricity and hydrogen. Utilization of fuel cell heat and electrolytic oxygen as by-products is also considered. Computer simulations show that the developed operation method is beneficial for grid-connected as well as for isolated systems. For isolated systems, the method makes it possible to minimize the usage of backup power and to ensure a secure supply of hydrogen fuel. For grid-connected wind-hydrogen systems, the method could be applied for maximizing the profit from operating in an electricity market. Comprehensive simulation studies of different example systems have been carried out to obtain knowledge about the benefits and limitations of using energy storage in conjunction with wind power. In order to exploit the opportunities for energy storage in electricity markets, it is crucial that the electrical efficiency of the storage is as high as possible. Energy storage combined with wind power prediction tools makes it possible to take advantage of varying electricity prices as well as reduce imbalance costs. Simulation results show that the imbalance costs of wind power and the electricity price variations must be relatively high to justify the installation of a costly energy storage system. Energy storage is beneficial for wind power integration in power systems with high-cost regulating units, as well as in areas with weak grid connection. Hydrogen can become an economically viable energy carrier and storage medium for wind energy if hydrogen is introduced into the transportation sector. It is emphasized that seasonal wind speed variations lead to high storage costs if compressed hydrogen tanks are used for long-term storage. Simulation results indicate that reductions in hydrogen storage costs are more important than obtaining low-cost and high-efficient fuel cells and electrolyzers. Furthermore, it will be important to make use of the flexibility that the hydrogen alternative offers regarding sizing, operation and possibly the utilization of oxygen and heat as by-products. The main scientific contributions from this thesis are the development of - a simulation model for estimating the cost and energy efficiency of wind-hydrogen systems, - a probabilistic model for predicting the performance of a gridconnected wind power plant with energy storage, - optimization models for increasing the value of wind power in electricity markets by the use of hydrogen storage and other energy storage solutions and the system knowledge about wind energy and energy storage that has been obtained by the use of these models. / Paper 1 is reprinted with kind permission of ACTA Press. Paper 2 is reprinted with kind permission of Elsevier/ Science Direct. http://www.elsevier.com, http://www.sciencedirect.com Paper 3 is reprinted with kind permission of IEEE.