Enhanced frequency response strategy for PMSG based wind energy conversion system using ultracapacitor in remote area power supply systems

The high penetration level of wind energy, and non-responsive nature of power electronic interfaced wind energy conversion system (WECS) during frequency variations may create significant stress on conventional generators in a wind-diesel hybrid remote area power supply (RAPS) system. Hence, it is a necessity for WECS to provide frequency support. However, conventional frequency control strategies being used for WECS may impose a severe stress to wind turbines. In this paper, an enhanced frequency response strategy is proposed for the permanent magnet synchronous generator (PMSG) based WECS to regulate RAPS system frequency jointly with its integrated ultracapacitors. The proposed frequency response strategy utilizes the droop control and virtual inertial techniques while suboptimal power point tracking (SOPPT) is implemented in WECS. It can effectively regulate RAPS system frequency while alleviating high rate of change of power (ROCOP) and thus torque stress on both the conventional generators and wind turbines under frequency disturbances

The simultaneous mitigation of slow and fast voltage fluctuations caused by rooftop solar PV by controlling the charging/discharging of an integrated battery energy storage system

Both slow and fast voltage fluctuations in the connected low voltage (LV) distribution feeder are caused by intermittent variations in solar PV power output, in addition to the variations in load demand where rooftop solar photo-voltaic (PV) unit penetration is higher. A single energy storage system integrated with the solar PV unit can mitigate these fluctuations in voltage profile. A novel analytical approach to mitigate both slow and fast voltage fluctuations simultaneously in the connected LV distribution feeder is proposed, which has not explicitly been addressed in the literature. Integrated battery energy storage systems will be dynamically charged during mid-day to alleviate the voltage rise and discharged during the evening peak hours to alleviate the voltage drop, while simultaneously controlling the fast fluctuations of the PV inverter output to a specified value. The proposed control strategy has been validated using a hypothetical distribution feeder system and results have demonstrated that both the slow and the fast voltage fluctuations in the voltage profile can effectively be alleviated, if the proposed strategy is implemented

A novel control strategy for a variable speed wind turbine with a permanent magnet synchronous generator

This paper presents a novel control strategy for the operation of a direct drive permanent magnet synchronous generator (PMSG) based stand alone variable speed wind turbine. The control strategy for the generator side converter with maximum power extraction is discussed. The stand alone control is featured with output voltage and frequency controller capable of handling variable load. The potential excess of power is dissipated in the damp resistor with the chopper control and the dc link voltage is maintained. Dynamic representation of dc bus and small signal analysis are presented. Simulation results show that the controllers can extract maximum power and regulate the voltage and frequency under varying wind and load conditions. The controller shows very good dynamic and steady state performance

Response analysis of saturable reactors and tap changer in an aluminium smelting plant

Aluminium smelters are one of the peculiar loads, which typically represent a series of electrolytic cells supplied by a multi-pulse rectifier system. In order to address the complexity involved in the modelling of a smelting plant, the impact of multipulse configurations and its connection to HV networks and control aspects of load current should be considered. This paper addresses the issues related to the control of DC current using saturable reactors for different alumina feeding mechanisms in a typical smelter. The saturable reactors are modelled as variable inductors of which the magnitude is controlled using a proportional-integral control scheme. A smelting plant with a twelve pulse rectifier system and variable DC load has been modelled in PSCAD®/EMTDC©. The plant is connected to the AC network through 220 kV/110 kV transformer with tap changing facilities to control the secondary voltage and associated load current of the smelter. The simulation results are reported for the control of DC current under varying load conditions

Climate change mitigation with integration of renewable energy resources in the electricity grid of new south wales, Australia

The implementation of climate change mitigation strategies may significantly affect the current practices for electricity network operation. Increasing penetration of renewable energy generation technologies into electricity networks is one of the key mitigation strategies to achieve greenhouse gas emission reduction targets. Additional climate change mitigation strategies can also contribute to emission reduction thereby supplementing the renewable energy generation participation, which may be limited due to technical constraints of the network. In this paper, the penetration requirements for different renewable energy generation resources are assessed while concurrently examining other mitigation strategies to reduce overall emissions from electricity networks and meet requisite targets. The impacts of climate change mitigation strategies on the demand and generation mix are considered for facilitating the penetration of renewable generation. New climate change mitigation indices namely change in average demand, change in peak demand, generation flexibility and generation mix have been proposed to measure the level of emission reduction by incorporating different mitigation strategies. The marginal emissions associated with the individual generation technologies in the state of New South Wales (NSW) are modelled and the total emissions associated with the electricity grid of NSW are evaluated. 2013 Elsevier Ltd

The state of the art of battery charging infrastructure for electrical vehicles: Topologies, power control strategies, and future trend

Electric vehicle battery (EVB) charger topologies play a vital role to increase the penetration of EVs. This paper reviews the status quo of EV battery (EVB) chargers in term of converter topologies, operation modes, and power control strategies for EVs. EVB Chargers are classified based on their power levels and power flow direction. Referring to power ratings, EV chargers can be divided into Level 1, Level 2 and Level 3. Level 1 and Level 2 are normally compatible with on-board chargers while Level 3 is used for an off-board charger. Unidirectional/bidirectional power flow can be obtained at all power levels. However, bidirectional power flow is usually designed for Level 3 chargers as it can provide the huge benefit of transferring power back to grid when needed. Moreover, the different operation modes of an EVB charger are also presented. There are two main modes: Grid-to-Vehicle (V1G or G2V) and Vehicle-to-Grid (V2G). The V2G mode helps bring EV batteries to become active distributed sources in smart grids and is the crucial solution for a high EV penetration. Future trend and authors\u27 recommendations with preliminary simulation and experimental results are demonstrated in this paper

Online coordinated voltage control in distribution systems subjected to structural changes and DG availability

The responses of multiple DG units and voltage regulating devices such as tap changers and capacitor banks for correcting the voltage may lead to operational conflicts and oscillatory transients, where distribution systems are subjected to network reconfiguration and changes in availability of the DG units. Therefore, coordinated voltage control is required to minimize control interactions while accounting for the impact of structural changes associated with the network. This paper proposes a strategy for coordinating the operation of multiple voltage regulating devices and DG units in medium voltage (MV) distribution systems, under structural changes and DG availability, for effective voltage control. The proposed strategy aids to minimize the operational conflicts by allowing the farthest voltage regulating device to operate first on a priority scheme designed based on the electrical-distance between voltage regulating devices and DG units, while maximizing the voltage support by the DG units. The proposed coordination scheme is designed to enact with an aid of a substation centered distribution management system (DMS) for online voltage control. The control actions of proposed coordination strategy are tested on a MV distribution system, derived from the state of New South Wales, Australia, through simulations, and results are reported

Assessing the influence of climatic variables on electricity demand

The electricity demand is significantly dependent on the weather information. Such weather information is comprised of different climatic variables such as temperature, humidity, wind speed, evaporation, rain fall and solar exposure which constantly change. Therefore, analysing the impacts of these variables on demand is necessary for predicting the future change in demand. In this paper, the cooling and heating degree days are utilised to capture the relationship between the per capita demand to temperature, which is one of the key climatic variables. In addition, Pearson correlation analysis has been employed to investigate the interdependency between different climatic variables and electricity demand. Finally, back-ward elimination based multiple regression is used to exclude non-significant climatic variables and evaluate the sensitivity of significant variables to the electricity demand. A case study has been reported in this paper by acquiring the data from the state of New South Wales, Australia. The results reveal that the climatic variables such as heating degree days, humidity, evaporation, and wind speed predominantly affect the electricity demand of the state of New South Wales

Short-term load forecasting using regression based moving windows with adjustable window-sizes

This paper presents a regression based moving window model for solving the short-term electricity forecasting problem. Moving window approach is employed to trace the demand pattern based on the past history of load and weather data. Regression equation is then formed and least square method is used to determine the parameters of the model. In this paper, a new concept associated with cooling and heating degree is used to establish the relationship between electricity demand and temperature, which is one of the key climatic variables. In addition, Pearson\u27s correlation has been employed to investigate the interdependency of electricity demand between different time periods. These analyses together with the data in the holiday period provide the supportive information for the appropriate selection of the window size. A case study has been reported in this paper by acquiring the relevant data for the state of New South Wales, Australia. The results are then compared with a neural network based model. The comparison shows that the proposed moving window approach with the different window sizes outperforms conventional neural network technique in small time scales i.e., from 30 minuntes to 1 day ahead

Accurate range estimation for an electric vehicle including changing environmental conditions and traction system efficiency

Range anxiety is an obstacle to the acceptance of electric vehicles (EVs), caused by drivers\u27 uncertainty regarding their vehicle\u27s state of charge (SoC) and the energy required to reach their destination. Most estimation methods for these variables use simplified models with many assumptions that can result in significant error, particularly if dynamic and environmental conditions are not considered. For example, the combined efficiency of the inverter drive and electric motor varies throughout the route and is not constant as assumed in most range estimation methods. This study proposes an improved method for SoC and range estimation by taking into account location-dependent environmental conditions and time-varying drive system losses. To validate the method, an EV was driven along a selected route and the measured EV battery SoC at the destination was compared with that predicted by the algorithm. The results demonstrated excellent accuracy in the SoC and range estimation, which should help alleviate range anxiety