Control of active filters to attenuate harmonic resonance in power distribution networks

Harmonic resonance occurs when the network equivalent shunt harmonic capacitive reactance is associated with the network series harmonic inductive reactance. When such resonance occurs, it amplifies harmonic components with frequency close to the resonance point. Solutions used to solve harmonic resonance problems can be divided into two main categories. One is to reduce the content of harmonic components in the network (e.g. by using active or passive harmonic filters, etc.) and the other is to remove the resonance stimulating factor by shifting away the resonance frequency to a non-critical frequency range (e.g. detuning PFC capacitors, redesigning feeder transformers, etc.). Studies show that these techniques are not adequate to solve harmonic resonance problems in power distribution networks which are dynamic by their nature and with complex interconnections. Due to this, solutions in the category one are designed for localised harmonic distortion compensation, while solutions in the category two lack real-time operation feature. Therefore, it was identified that there is a need for real-time harmonic resonance attenuation that is suitable for power distribution networks. In this thesis, a new real-time Harmonic Resonance Attenuation (HRA) technique is proposed. This technique may be used with ordinary shunt harmonic filters to make them behave like a virtual shunt capacitor or inductor. Thus, looking from the harmonic current source side, the filter alters the network harmonic impedance and hence results in harmonic resonance attenuation. In order to implement the HRA technique, fast measurement of system harmonics in real-time is required. Therefore, in this work, a fast individual harmonic extraction (FIHE) technique is developed to enhance the desired real-time operation of the HRA. The proposed FIHE needs only one sixth of the fundamental cycle to extract any individual harmonic component which is faster than other methods currently available. In addition to the speed, the proposed FIHE provides overshoot free, oscillation free and ripple free extraction characteristics. The proposed HRA and FIHE techniques are described in this thesis with detailed analysis to illustrate their operating principles. A series of simulations and experiments are conducted to evaluate their functionality and performance. Results of the evaluation are presented and discussed in this thesis together with details of the experimental HRA model developed to verify the theoretical and simulation results.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Treating the Impacts of Connecting HVDC Link Converters with AC Power System Using Real-Time Active Power Quality Unit

The High Voltage Direct Current (HVDC) systems have been applied worldwide, due to important roles, technical benefits, and high efficiency. Usually, the HVDC network is a joining link between two separate and different technical properties of HVAC systems, which enhances its use. The joinpoint system that used to connect HVDC and HVAC links is a controlled converter circuit. Despite the importance of use and the significant benefits of the HVDC link, there are negative effects on the power quality of the electrical power of both systems connected on both ends of the HVDC network. The low quality of electric power has been addressed by known methods, whether traditional or modern. But the improvement is usually made with the assumption of load conditions and the need for the system to synthesize it. This research presents an innovative method based on real-time control strategy. This is performed by proposing dSPACE for controlling the Active Power Quality Unit (APQU). The proposed control strategy of the APQU includes a Modified Harmonics Pulse Width Modulation (MHPWM) algorithm in order to mitigate the line current THD and improve the effective power factor of the AC converter sides. The MHPWM is applicable for different nonlinear loads and can be implemented with APQU based on different topologies of H-bridge voltage source inverter. Simulation and practical results have been presented in this paper. The Experimental results are done based on real-time laboratory tests using dSPACE DS1103 board as a controller circuit. The presented results, under different operating loading conditions, show that the APQU provides almost unity power factor and significantly improving THD of the AC supply currents at both sides of the HVDC link controlled converters

Autonomous energy management system with self-healing capabilities for green buildings (microgrids)

Nowadays, distributed energy resources are widely used to supply demand in micro grids specially in green buildings. These resources are usually connected by using power electronic converters, which act as actuators, to the system and make it possible to inject desired active and reactive power, as determined by smart controllers. The overall performance of a converter in such system depends on the stability and robustness of the control techniques. This paper presents a smart control and energy management of a DC microgrid that split the demand among several generators. In this research, an energy management system ( EMS) based on multi-agent system ( MAS) controllers is developed to manage energy, control the voltage and create balance between supply and demand in the system with the aim of supporting the reliability characteristic. In the proposed approach, a reconfigurated hierarchical algorithm is implemented to control interaction of agents, where a CAN bus is used to provide communication among them. This framework has ability to control system, even if a failure appears into decision unit. Theoretical analysis and simulation results for a practical model demonstrate that the proposed technique provides a robust and stable control of a microgrid

Short-term performance variations of different photovoltaic system technologies under the humid subtropical climate of Kanpur in India

The study discusses the short-term performance variations of grid-connected photovoltaic (PV) systems installed in Kanpur, India. The analysis presents a holistic view of the performance variations of three PV array technologies [multi-crystalline (multi-Si), copper indium gallium diselenide and amorphous silicon] and two inverter types (high-frequency transformer and low-frequency transformer). The analysis considers the DC–AC conversion efficiency of the inverter, system performance through performance ratio (PR) calculations, energy variations between fixed and tracking systems and the comparison between calculated and simulated data for the examined period. The energy output difference between the tracking and fixed systems of the same PV technology show that these are dependent on differences in temperature coefficient, shading and other system related issues. The PR analysis shows the effect of temperature on the multi-Si system. The difference between the simulated and measured values of the systems was mostly attributed to the irradiance differences. Regarding the inverter evaluation, the results showed that both inverter types underperformed in terms of the conversion efficiency compared with nameplate values

A bidirectional power flow controller for EVs to support the grid

The spreading of electrical vehicles leads to a positive impact on the mobility field from the ecological, economical and efficiency point of view. Unfortunately this diffusion is also potentially capable of negative reverberations on distribution and transmission networks, since EVs can be considered as a new load category. Rather than preventing this virtually negative situation, it is possible for the grid to take advantage of the capabilities of EVs' batteries to implement ancillary services: for this reason the proposed vehicle's battery charger is designed to operate with bidirectional power flow (implementing V2G - Vehicle to Grid- and G2V -Grid to Vehicle- modes). The target is pursued through grid manager request towards grid connected EVs. If the power flow's direction and amount is enabled by the EV controller (depending on the SOC of the battery), the control system acquires the reference signal, which is the network sinusoidal voltage wave. This synchronization between the device and the grid is followed by the battery charger's modulation of a voltage sine wave with a certain amplitude and phase displacement with respect to the reference signal, in order to reach the desired working point which provides ancillary services to the grid. This paper analyses both the control strategy and the profiles of the transient states that take place when the switch between working points is request

Impact of distribution network voltage rise on PV system energy yield

Economic viability is one of the important factors in determining the rate of customer adoption of photovoltaic (PV) systems. A decrease in energy yield reduces their viability. At times of high PV production and low electricity demand, network voltage rises and may exceed limits resulting in a consequent curtailment of PV generation and reducing the energy yield. In this paper, a computational sequence was developed to investigate the impact of voltage rise at different nodes of the network on PV systems' annual energy yield for different PV penetration scenarios. The results of analysis conducted for Newcastle upon Tyne using UK generic urban distribution network are presented. It was found that the use of monthly averaged PV generation profiles resulted in the most optimistic PV system annual energy yield estimates. These profiles were under scenarios of very high PV penetration in the distribution network. A closer assessment of the PV generation profiles showed that there is a substantial number of days per year with high PV generation and therefore a large PV power curtailment may result unless adequate measures are put in place to capture maximum PV energy

Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming

The optimum design of Hybrid Renewable Energy Systems (HRES) depends on different economical, environmental and performance related criteria which are often conflicting objectives. The Non-dominated Sorting Genetic Algorithm (NSGA-II) provides a decision support mechanism in solving multi-objective problems and providing a set of non-dominated solutions where finding an absolute optimum solution is not possible. The present study uses NSGA-II algorithm in the design of a standalone HRES comprising wind turbine, PV panel and battery bank with the (economic) objective of minimum system total cost and (performance) objective of maximum reliability. To address the uncertainties in renewable resources (wind speed and solar irradiance), an innovative method is proposed which is based on Chance Constrained Programming (CCP). A case study is used to validate the proposed method, where the results obtained are compared with the conventional method of incorporating uncertainties using Monte Carlo simulation

An investigation of the switched-capacitor circuit as a solid-state fault current limiting and interrupting device (FCLID) with power factor correction suitable for low-voltage distribution networks

The Switched Capacitor (SC) Circuit is investigated in this paper as a Solid-State Fault Current Limiter and interrupting device (FCLID) with power factor correction suitable for low-voltage distribution networks. It was applied so far successfully as a power factor and harmonic current compensator and as a Switched Capacitor Circuit inverter. In this application it is inserted in series with the supply line, providing both power factor correction and limitation of the current to a pre-set value in the event of a fault. Interruption of the fault is also possible by setting both semiconductor switches in the off state. Overvoltage is present in SC Circuits and they appear across both the passive and active components. The problem can be alleviated by optimising the system operation and system components

Generation of synthetic benchmark electrical load profiles using publicly available load and weather data

Electrical load profiles of a particular region are usually required in order to study the performance of renewable energy technologies and the impact of different operational strategies on the power grid. Load profiles are generally constructed based on measurements and load research surveys which are capital and labour-intensive. In the absence of true load profiles, synthetically generated load profiles can be a viable alternative to be used as benchmarks for research or renewable energy investment planning. In this paper, the feasibility of using publicly available load and weather data to generate synthetic load profiles is investigated. An artificial neural network (ANN) based method is proposed to synthesize load profiles for a target region using its typical meteorological year 2 (TMY2) weather data as the input. To achieve this, the proposed ANN models are first trained using TMY2 weather data and load profile data of neighbouring regions as the input and targeted output. The limited number of data points in the load profile dataset and the consequent averaging of TMY2 weather data to match its period resulted in limited data availability for training. This challenge was tackled by incorporating generalization using Bayesian regularization into training. The other major challenge was facilitating ANN extrapolation and this was accomplished by the incorporation of domain knowledge into the input weather data for training. The performance of the proposed technique has been evaluated by simulation studies and tested on three real datasets. Results indicate that the generated synthetic load profiles closely resemble the real ones and therefore can be used as benchmarks