Small Signal Stability Performance of Power System during High Penetration of Wind Generation

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.

Flexible fault ride through strategy for wind farm clusters in power systems with high wind power penetration

This paper investigates a flexible fault ride through strategy for power systems in China with high wind power penetration. The strategy comprises of adaptive fault ride through requirements and maximum power restrictions of the wind farms with weak fault ride through capabilities. The slight faults and moderate faults with high probability are the main defending objective of the strategy. The adaptive fault ride through requirement in the strategy consists of two sub fault ride through requirements, a temporary slight voltage ride through requirement corresponding to a slight fault incident, with a moderate voltage ride through requirement corresponding to a moderate fault. The temporary overloading capability of the wind farm is reflected in both requirements to enhance the capability to defend slight faults and to avoid tripping when the crowbar is disconnected after moderate faults are cleared. For those wind farms that cannot meet the adaptive fault ride through requirement, restrictions are put on the maximum power output. Simulation results show that the flexible fault ride through strategy increases the fault ride through capability of the wind farm clusters and reduces the wind power curtailment during faults.

Hybrid probabilistic wind power forecasting using temporally local Gaussian process

The demand for sustainable development has resulted in a rapid growth in wind power worldwide. Despite various approaches have been proposed to improve the accuracy and to overcome the uncertainties associated with traditional methods, the stochastic and variable nature of wind still remains the most challenging issue in accurately forecasting wind power. This paper presents a hybrid deterministic-probabilistic method where a temporally local ‘moving window’ technique is used in Gaussian Process to examine estimated forecasting errors. This temporally local Gaussian Process employs less measurement data while faster and better predicts wind power at two wind farms, one in the USA and the other in Ireland. Statistical analysis on the results shows that the method can substantially reduce the forecasting error while more likely generate Gaussian-distributed residuals, particularly for short-term forecast horizons due to its capability to handle the time-varying characteristics of wind power.

The importance of gas infrastructure in power systems with high wind power penetrations

Gas fired generation currently plays an integral support role ensuring security of supply in power systems with high wind power penetrations due to its technical and economic attributes. However, the increase in variable wind power has affected the gas generation output profile and is pushing the boundaries of the design and operating envelope of gas infrastructure. This paper investigates the mutual dependence and interaction between electricity generation and gas systems through the first comprehensive joined-up, multi-vector energy system analysis for Ireland. Key findings reveal the high vulnerability of the Irish power system to outages on the Irish gas system. It has been shown that the economic operation of the power system can be severely impacted by gas infrastructure outages, resulting in an average system marginal price of up to €167/MWh from €67/MWh in the base case. It has also been shown that gas infrastructure outages pose problems for the location of power system reserve provision, with a 150% increase in provision across a power system transmission bottleneck. Wind forecast error was shown to be a significant cause for concern, resulting in large swings in gas demand requiring key gas infrastructure to operate at close to 100% capacity. These findings are thought to increase in prominence as the installation of wind capacity increases towards 2020, placing further stress on both power and gas systems to maintain security of supply.

Gas generation in interconnected power systems with high wind power penetration

Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

Managing Future offshore wind power variability in a European Supergrid

The future European power system will have a hierarchical structure created by layers of system control from a Supergrid via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the context of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called 'back-up generation' needed to support an 80% renewable energy portfolio in Europe by 2050. © 2013 IEEE.

A methodology to analyse the impact of offshore wind forecasting error on electricity markets

Currently wind power is dominated by onshore wind farms in the British Isles, but both the United Kingdom and the Republic of Ireland have high renewable energy targets, expected to come mostly from wind power. However, as the demand for wind power grows to ensure security of energy supply, as a potentially cheaper alternative to fossil fuels and to meet greenhouse gas emissions reduction targets offshore wind power will grow rapidly as the availability of suitable onshore sites decrease. However, wind is variable and stochastic by nature and thus difficult to schedule. In order to plan for these uncertainties market operators use wind forecasting tools, reserve plant and ancillary service agreements. Onshore wind power forecasting techniques have improved dramatically and continue to advance, but offshore wind power forecasting is more difficult due to limited datasets and knowledge. So as the amount of offshore wind power increases in the British Isles robust forecasting and planning techniques are even more critical. This paper presents a methodology to investigate the impacts of better offshore wind forecasting on the operation and management of the single wholesale electricity market in the Republic of Ireland and Northern Ireland using PLEXOS for Power Systems. © 2013 IEEE.

Offshore wind resource estimation using wave buoy data

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys. © 2012 IEEE.

A review of offshore wind power development in the United Kingdom

Currently wind power is dominated by onshore wind farms. However, as the demand for power grows driven by security of energy supply issues, dwindling fossil fuel supplies and greenhouse gas emissions reduction targets, offshore wind power will develop rapidly because of the decline of viable onshore sites. The United Kingdom has a target of 21% renewable electricity by 2020 and this is expected to come mostly from wind power. Britain is the most active internationally in terms of offshore wind farm development with almost 48GW in some stage of development. In addition the Scottish Government, the Northern Ireland Executive and the Government of Ireland undertook the 'Irish-Scottish Links on Energy Study' (ISLES), which examined the feasibility of creating an offshore interconnected transmission network and subsea electricity grid based on renewable energy sources off the coast of western Scotland and the Irish Sea. The aim of this paper is to provide an appraisal of offshore wind power development with a focus on the United Kingdom. © 2013 IEEE.

Managing the variability of supply in the European power system with high wind energy penetration

The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

Characteristics of Offshore Wind Speeds using Buoy Measurements

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys

Wind generation and electricity demand during the severe winter of 2009/10 in Ireland

Throughout the world the share of wind power in the generation mix is increasing. In the All Island Grid, of the Republic of Ireland and Northern Ireland there is now over 1.5 GW of installed wind power. 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.

Special condition wind power forecasting based on Gaussian process and similar historical data

Due to the variability of wind power, it is imperative to accurately and timely forecast the wind generation to enhance the flexibility and reliability of the operation and control of real-time power. Special events such as ramps, spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken from both the local time and historic dataset is proposed and applied to make short-term predictions from 10 minutes to one hour ahead. A key idea is that the similar pattern data in history are properly selected and embedded in Gaussian Process model to make predictions. The results of the proposed algorithms are compared to those of standard Gaussian Process model and the persistence model. It is shown that the proposed method not only reduces magnitude error but also phase error.