95 resultados para Wind power plants


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Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

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A grid-connected DFIG for wind power generation can affect power system small-signal angular stability in two ways: by changing the system load flow condition and dynamically interacting with synchronous generators (SGs). This paper presents the application of conventional method of damping torque analysis (DTA) to examine the effect of DFIG’s dynamic interactions with SGs on the small-signal angular stability. It shows that the effect is due to the dynamic variation of power exchange between the DFIG and power system and can be estimated approximately by the DTA. Consequently, if the DFIG is modelled as a constant power source when the effect of zero dynamic interactions is assumed, the impact of change of load flow brought about by the DFIG can be determined. Thus the total effect of DFIG can be estimated from the result of DTA added on that of constant power source model. Applications of the DTA method proposed in the paper are discussed. An example of multi-machine power systems with grid-connected DFIGs are presented to demonstrate and validate the DTA method proposed and conclusions obtained in the paper.

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In many countries wind energy has become an indispensable part of the electricity generation mix. The opportunity for ground based wind turbine systems are becoming more and more constrained due to limitations on turbine hub heights, blade lengths and location restrictions linked to environmental and permitting issues including special areas of conservation and social acceptance due to the visual and noise impacts. In the last decade there have been numerous proposals to harness high altitude winds, such as tethered kites, airfoils and dirigible based rotors. These technologies are designed to operate above the neutral atmospheric boundary layer of 1,300 m, which are subject to more powerful and persistent winds thus generating much higher electricity capacities. This paper presents an in-depth review of the state-of-the-art of high altitude wind power, evaluates the technical and economic viability of deploying high altitude wind power as a resource in Northern Ireland and identifies the optimal locations through considering wind data and geographical constraints. The key findings show that the total viable area over Northern Ireland for high altitude wind harnessing devices is 5109.6 km2, with an average wind power density of 1,998 W/m2 over a 20-year span, at a fixed altitude of 3,000 m. An initial budget for a 2MW pumping kite device indicated a total cost £1,751,402 thus proving to be economically viable with other conventional wind-harnessing devices.

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Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.

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This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

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This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

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This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

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Wind power is one of the most developed renewable energy resources worldwide. To integrate offshore wind farms to onshore grids, the high-voltage direct current (HVDC) transmission cables interfaced with voltage source converters (VSCs) are considered to be a better solution than conventional approaches. Proper DC voltage indicates successive power transfer. To connect more than one onshore grid, the DC voltage droop control is one of the most popular methods to share the control burden between different terminals. However, the challenges are that small droop gains will cause voltage deviations, while higher droop gain settings will cause large oscillations. This study aims to enhance the performance of the traditional droop controller by considering the DC cable dynamics. Based on the backstepping control concept, DC cables are modelled with a series of capacitors and inductors. The final droop control law is deduced step-by-step from the original remote side. At each step the control error from the previous step is considered. Simulation results show that both the voltage deviations and oscillations can be effectively reduced using the proposed method. Further, power sharing between different terminals can be effectively simplified such that it correlates linearly with the droop gains, thus enabling simple yet accurate system operation and control.

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This paper presents transient stability analysis for a power system with high wind penetration. The transient stability has been evaluated based on two stability criteria: rotor angle stability and voltage stability. A modified IEEE-14 bus system has been used as the main study network and simulations have been conducted at several wind power penetration levels, defined as a fraction of total system generation. A wide range of scenarios have been presented based on the wind farm voltage at the point of connection, i.e. low voltage (LV) distribution level and high voltage (HV) transmission level, and the type of wind generator technology, i.e. fixed speed induction generator (FSIG) and doubly-fed induction generator (DFIG).

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The small signal stability of interconnected power systems is one of the important aspects that need to be investigated since the oscillations caused by this kind of instability have caused many incidents. With the increasing penetration of wind power in the power system, particularly doubly fed induction generator (DFIG), the impact on the power system small signal stability performance should be fully investigated. Because the DFIG wind turbine integration is through a fast action converter and associated control, it does not inherently participate in the electromechanical small signal oscillation. However, it influences the small signal stability by impacting active power flow paths in the network and replacing synchronous generators that have power system stabilizer (PSS). In this paper, the IEEE 39 bus test system has been used in the analysis. Furthermore, four study cases and several operation scenarios have been conducted and analysed. The selective eigenvalue Arnoldi/lanczos's method is used to obtain the system eigenvalue in the range of frequency from 0.2 Hz to 2 Hz which is related to electromechanical oscillations. Results show that the integration of DFIG wind turbines in a system during several study cases and operation scenarios give different influence on small signal stability performance.

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At least 34 % of the United Kingdom’s power must come from renewable energy sources to meet planned European Union targets in 2030. Wind power will provide the majority of this renewable electricity with an estimated 36 GW offshore and 21 GW onshore. The success of the Crown Estate’s leasing rounds 1 and 2 in offshore wind has meant the United Kingdom is now one of the world leaders in offshore wind power development. Leasing round 3 will see offshore wind in the United Kingdom surpass 36 GW of installed capacity. This is a significant increase from the current installed offshore wind capacity of 3.6 GW. This research investigates the power system performance of offshore wind power in the United Kingdom in 2030.

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Social acceptance for wind turbines is variable, providing a challenge to the implementation of this energy source. Psychological research could contribute to the science of climate change. Here we focus on the emotional responses to the visual impact of wind turbines on the landscape, a factor which dominates attitudes towards this technology. Participants in the laboratory viewed images of turbines and other constructions (churches, pylons and power-plants) against rural scenes, and provided psychophysiological and self-report measures of their emotional reactions. We hypothesised that the emotional response to wind turbines would be more negative and intense than to control objects, and that this difference would be accentuated for turbine opponents. As predicted, the psychophysiological response to turbines was stronger than the response to churches, but did not differ from that of other industrial constructions. In contrast with predictions, turbines were rated as less aversive and more calming compared with other industrial constructions, and equivalent to churches. Supporters and non-supporters did not differ significantly from each other. We discuss how a methodology using photo manipulations and emotional self-assessments can help estimate the emotional reaction to the visual impact on the landscape at the planning stage for new wind turbine applications.

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Large scale wind power generation complicated with restrictions on the tie line plans may lead to significant wind power curtailment and deep cycling of coal units during the valley load periods. This study proposes a dispatch strategy for interconnected wind-coal intensive power systems (WCISs). Wind power curtailment and cycling of coal units are included in the economic dispatch analysis of regional systems. Based on the day-ahead dispatch results, a tie line power plan adjustment strategy is implemented in the event of wind power curtailment or deep cycling occurring in the economic dispatch model, with the objective of reducing such effects. The dispatch strategy is designed based on the distinctive operation characteristics of interconnected WCISs, and dispatch results for regional systems in China show that the proposed strategy is feasible and can improve the overall system operation performance.

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Recent cold winters and prolonged periods of low wind speeds have prompted concerns about the increasing penetration of wind generation in the Irish and other northern European power systems. On the combined Republic of Ireland and Northern Ireland system there was in excess of 1.5 GW of installed wind power in January 2010. As the penetration of these variable, non-dispatchable generators increases, power systems are becoming more sensitive to weather events on the supply side as well as on the demand side. In the temperate climate of Ireland, sensitivity of supply to weather is mainly due to wind variability while demand sensitivity is driven by space heating or cooling loads. The interplay of these two weather-driven effects is of particular concern if demand spikes driven by low temperatures coincide with periods of low winds. In December 2009 and January 2010 Ireland experienced a prolonged spell of unusually cold conditions. During much of this time, wind generation output was low due to low wind speeds. The impacts of this event are presented as a case study of the effects of weather extremes on power systems with high penetrations of variable renewable generation.