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.

Thesis (M.S.)--Tennessee Technological University, 2008. / Title from title page screen (viewed on Mar. 18, 2010). Includes bibliographical references.

As utilities become more interested in using renewable energy to power the grid, the problem becomes how to size and locate the generation facilities. This thesis approaches the idea of using distributed medium scale generation facilities at the distribution feeder level. We propose an algorithm to determine the optimum size of a photovoltaic(PV) array and an energy storage system for a distribution feeder. The cost of operating a feeder is quantified by considering the net load at the substation, voltage changes, load following, and the initial cost of implementing a photovoltaic system and a battery energy storage system. The PV inverter is utilized in order to improve the voltage on the circuit and is sized proportionally to the array size. The energy storage system operates in peak shaving and load following capacities in order to reduce stress on current generation facilities. The algorithm then operates to minimize the total cost of the feeder operation for a year by sizing these distributed generation resources utilizing particle swarm optimization. Optimization of a real-world system yielding results where the power at the substation (including all losses) is reduced by 5.39% over the course of a year and the average voltage drop on the circuit is improved by 50.17% using the proposed photovoltaic inverter control scheme.

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)

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / Due to the ongoing changes in the structure of the electricity markets, distribution networks have developed an appealing potential for housing distributed generation (DG). In order to make the most out of the present distribution network, this project report verifies the results and method developed in a paper (Optimal Allocation of Embedded Generation on Distribution Networks) by A. Kean and M. O’Malley, which discusses an efficient way of incorporating DG in the current power system. The methodology under consideration elaborates on how certain constraints should be adopted that will lead toward optimally sizing and placing DG in the network under examination. Along with that, the effect of voltage rise and short circuit current are observed which shows that a certain allocation to some buses will cause a sudden rise in voltage and short circuit levels throughout the network. Furthermore, the adopted methodology with its relative constraints is solved using linear programming. Linear programming provides a more accurate allocation than its heuristic counterparts when it comes to embedding DG in smaller networks. The adopted methodology is then applied to a section of the Irish rural distribution network and the results pinpoint that appropriate placement of the DG will pave the way toward higher levels of penetration. The results obtained showed the same pattern as those recorded in the aforementioned source paper, there were only minor differences that are the result of using different software’s than those that were used by the authors of the paper.

The future of electric power distribution systems (DSs) is one that incorporates extensive amounts of advanced metering, distribution automation, and distributed generation technologies. Most DSs were designed to be radial systems and the major philosophies of their protection, namely, selectivity and sensitivity, were easily achieved. Settings for overcurrent protective devices (OCPDs) were static and based on the maximum load downstream of its location, with little concern of major configuration changes. However, the integration of distribution generators (DGs) in radial distributions systems (RDSs) causes bidirectional power flows and varying short circuit currents to be sensed by protective devices, thereby affecting these established protection principles. Several researchers have investigated methods to preserve the selectivity of overcurrent protection coordination in RDSs with DGs, but at the expense of protective device sensitivity due to an inherent change in system configuration. This thesis presents an investigation to adapt the pickup settings of the substation relay, based on configuration changes in a DS with DGs, using smart meter data from the prior year. An existing protection scheme causes the faulted areas of DSs with DGs to revert to a radial configuration, thereby allowing conventional OCPDs to isolate faults. Based on the location of the fault, the created radial segments are known and vary in length. The proposed methodology involves using demand information available via smart metering, to determine the seasonal maximum diversified demands in each of the radial segments that are formed. These seasonal maximum diversified demands are used to yield several pickup settings for the substation overcurrent relay of the DS. The existing protection approach enables the selectivity of radial overcurrent protection coordination to be maintained; the sensitivity of the substation relay is improved by adapting its pickup settings based on seasonal demand and system configuration changes. The results of the studies are reported through simulation in EMTP™ /PSCAD® using a multi-feeder test system that includes DGs and smart meters located at the secondary distribution load level. The results show that using seasonal settings for the substation relay based on configuration changes in a DS with DGs can improve the sensitivity of the substation relay.

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.

Environmentally friendly renewable energy technologies such as wind and solar energy systems are among the fleet of new generating technologies driving the demand for distributed generation of electricity. Power Electronics has initiated the next tech¬nological revolution and enables the connection of distributed generation (DG) systems to the grid. The challenge is to achieve system functionality without extensive custom engineering, yet still have high system reliability and generation placement flexibility. Nowadays, it is a general trend to increase the electricity production using DG systems. If these systems are not properly controlled, their connection to the utility network can generate problems on the grid side. Therefore, considerations about power generation, safe running and grid synchronization must be done before connecting these systems to the utility network. This thesis introduces a new grid-synchronization, or more visibly a new “power signal processor” adaptive notch filtering (ANF) tool that can potentially stimulate much interest in the field and provide improvement solutions for grid-connected operation of DG systems. The processor is simple and offers high degree of immunity and insensitivity to power system disturbances, harmonics and other types of pollutions that exist in the grid signal. The processor is capable of decomposing three-phase quantities into symmetrical components, extracting harmonics, tracking the frequency variations, and providing means for voltage regulation and reactive power control. In addition, this simple and powerful synchronization tool will simplify the control issues currently challenging the integration of distributed energy technologies onto the electricity grid. All converter-interfaced equipments like FACTS (flexible ac transmission systems) and Custom Power Controllers will benefit from this technique. The theoretical analysis is presented, and simulation and experimental results confirm the validity of the analytical work. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2009-01-27 11:37:07.279

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.