Distributed generation (DG) has received much attention recently due to environmental consciousness and rising of the energy efficiency. However, DG interconnecting to low-voltage distribution system may cause voltage variation, and a lot of single-phase DG or single-phase load may result in voltage unbalance. This thesis presents a distributed-STATCOM (D-STATCOM) to alleviate variation of both positive-sequence and negative-sequence voltages at the fundamental frequency. The D-STATCOM operates as susceptance and conductance at the fundamental positive-and negative-sequence frequency, respectively. The susceptance and conductance commands are dynamically tuned according to voltage fluctuation at the installation location. Therefore, the positive-sequence voltage can be restored to the nominal value as well as the negative-sequence voltage can be suppressed to an allowable level. Computer simulations and experimental results verify the effectiveness of the proposed control strategy.

The integration of cogeneration technologies in residential communities has the potential of reducing energy demand and harmful emissions. This study investigated the impact of selected design parameters on the environmental and economic performances of cogeneration systems integrated into residential communities in cold U.S. climates following a centralized or a decentralized integration approach. Parameters investigated include: 1) density, 2) use mix, 3) street configuration, 4) housing typology, 5) envelope and building systems' efficiencies, 6) renewable energy utilization, 7) cogeneration system type, 8) size, and 9) operation strategy. Based on this, combinations of design characteristics achieving an optimum system performance were identified. The study followed a two-phased mixed research model: first, studies of residential community design and three case studies of sustainable residential communities were analyzed to identify key design parameters; subsequently, simulation tools were utilized to assess the impact of each parameter on cogeneration system performance and to optimize the community design to improve that performance. Assessment procedures included: developing a base-line model representing typical design characteristics of U.S. residential communities; assessing the system performance within this model, for each integration approach, using three performance indicators: reduction in primary energy use, reduction in CO2 emissions; and internal rate of return; assessing the impact of each parameter on the system performance through developing 46 design variations of the base-line model representing changes in these parameters and calculating the three indicators for each variation; using a multi-attribute decision analysis methodology to evaluate the relative impact of each parameter on the system performance; and finally, developing two design optimization scenarios for each integration approach. Results show that, through design optimization, existing cogeneration technologies can be economically feasible and cause reductions of up to 18% in primary energy use and up to 42% in CO2 emissions, with the centralized approach offering a higher potential for performance improvements. A significant correlation also existed between design characteristics identified as favorable for cogeneration system performance and those of sustainable residential communities. These include high densities, high mix of uses, interconnected street networks, and mixing of housing typologies. This indicates the higher potential for integrating cogeneration systems in sustainable residential communities.

This thesis presents the applications of a series interconnection scheme for small distributed generation (DG) systems in distribution networks. The concept uses one set of voltage source converter (VSC) to control the injected voltage magnitude and phase angle for power injection and voltage sag mitigation. Through an energy storage device and the VSC, DG outputs vary concurrently with the line loading and provide load leveling functions. Under voltage sag situations, it provides missing voltages to effectively deal with power quality problems. Due to its series connection characteristic, it is convenient in preventing islanding operation and good for fault current limiting. The concept is suitable for locations where the voltage phase shift is not a major concern. Due to the use of only one set of converter, it is economic for customer site distributed energy resource applications and its control strategy would depend on the types of load connected.

This thesis investigates the impact of high-level penetration of distributed generation especially from the renewable energy sources on the transient stability of the transmission system. Distributed generation is a source of electric power connected to the distribution network or on the consumer side. It is expected that distributed generation grows significantly by the increasing environmental concerns and deregulation in the market. As soon as the increasing penetration level, distributed generation starts to influence the distribution system as well as the transmission system. To investigate the impact of distributed generation with different penetration levels on the transmission system transient stability, simulation scenarios are created and simulations are run on the basis of these scenarios by the implementation of the different distributed generation technologies to the &ldquo / New England&rdquo / test system. Stability indicators are observed to assess the impact on the transient stability. Results are presented throughout the thesis and the impact of the different distributed generation technologies and the different penetration levels on the transient stability is discussed by comparing the stability indicators.

With increasing level of distributed generation¡]DG¡^on radial feeders in electric distribution systems, it could cause over-voltages as well as under-voltages depending on several factors including DG capacity, locations, and the strategy of voltage regulation. This thesis describes the typical and proposed voltage control strategies that could allow the increase of DG interconnection capacity. By using probabilistic load flow technique, voltage regulation performance for cases with different levels of DG outputs, demands and voltage control strategies are presented. They are compared by using a voltage profile improvement index and a risk assessment technique.

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.

Distribution system voltage and VAR control (VVC) is a technique that combines conservation voltage reduction and reactive power compensation to operate a distribution system at its optimal conditions. Coordinated VVC can provide major economic benefits for distribution utilities. Incorporating distributed generation (DG) to VVC can improve the system efficiency and reliability. The first part of this dissertation introduces a direct optimization formulation for VVC with DG. The control is formulated as a mixed integer non-linear programming (MINLP) problem. The formulation is based on a three-phase power flow with accurate component models. The VVC problem is solved with a state of the art open-source academic solver utilizing an outer approximation algorithm. Applying the approach to several test feeders, including IEEE 13-node and 37-node radial test feeders, with variable load demand and DG generation, validates the proposed control. Incorporating renewable energy can provide major benefits for efficient operation of the distribution systems. However, when the number of renewables increases the system control becomes more complex. Renewable resources, particularly wind and solar, are often highly intermittent. The varying power output can cause significant fluctuations in feeder voltages. Traditional feeder controls are often too slow to react to these fast fluctuations. DG units providing reactive power compensation they can be utilized in supplying voltage support when fluctuations in generation occur. The second part of this dissertation focuses on two new approaches for dual-layer VVC. In these approaches the VVC is divided into two control layers, slow and fast. The slow control obtains optimal voltage profile and set points for the distribution control. The fast control layer is utilized to maintain the optimal voltage profile when the generation or loading suddenly changes. The MINLP based VVC formulation is utilized as the slow control. Both local reactive power control of DG and coordinated quadratic programming (QP) based reactive power control is considered as the fast control approaches. The effectiveness of these approaches is studied with test feeders, utility load data, and fast-varying solar irradiance data. The simulation results indicate that both methods achieve good results for VVC with DG.

Electricity networks are undergoing a period of rapid change and transformation, with increased penetration levels of renewable-based distributed generation, and new influences on electricity end-use patterns from demand-manageable loads and micro-generation. This creates a number of new challenges for the delivery of a reliable supply of electrical energy. The main aim of this PhD research is to provide a methodology for a more detailed and accurate assessment of the effects of wind-based distributed generation (DG) and demand side management (DSM) on transmission network operation. In addition, the work investigates the potential for co-ordinated implementation and control of DG and DSM to improve overall system performance. A significant amount of previous literature on network integration of DG and DSM resources has focused on the effects at the distribution level, where their impact is direct and often easily observed. However, as penetration levels increase, DG and DSM will have a growing influence on the operation and management of the bulk transmission system. Modelling and analysis of the impact of embedded and highly-dispersed DG and DSM resources at transmission voltage levels will present a significant challenge for transmission network operators in the future. Accordingly, this thesis presents a number of new approaches and methodologies allowing for a more accurate modelling and aggregation of DG and DSM resources in power system studies. The correct representation of input wind energy resources is essential for accurate estimation of power and energy outputs of wind-based DG. A novel modelling approach for a simple and accurate representation of the statistical and temporal characteristics of the wind energy resources is presented in the thesis. An "all-scale" approach to modelling and aggregation of wind-based generation is proposed, which is specifically intended for assessing the impact of embedded wind generation on the steady state performance of transmission systems. The methodology allows to include in the analysis wind-based generation at all scales and all levels of implementation, from micro and small LV-connected units, through medium-size wind plants connected at MV, up to large HV-connected wind farms. The thesis also presents an assessment of the potential for DSM in the UK residential and commercial sectors, based on the analysis and decomposition of measured demands at system bulk supply points into the corresponding load types. Using a section of the Scottish transmission network as a case study, a number of DG and DSM scenarios are investigated in detail. These results demonstrate the importance of accurately modelling the interactions between the supply system and various DG and DSM schemes, and show that the aggregated effects of highly-distributed DG and DSM resources can have significant impacts on the operation of the bulk transmission system.