Measurement-based Method for Wind Farm Power System Oscillations Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This study presents a measurement-based method for the early detection of power system oscillations, with consideration of mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet-based support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in frequency bands, whereas the SVDD method is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude, or that are resonant, can be alarmed to the system operator, to reduce the risk of system instability. The proposed method is exemplified using measured data from a chosen wind farm site.

A Tower-Shadow Model for Wind Turbines Using a Wavelet-Prony Method

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency pulsations contained within active power flow. A primary concern is excitation of low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of interconnection between the Northern and Southern power system networks. In order to determine whether the prevalence of wind generation has a negative effect (excites modes) or positive impact (damping of modes) on the power system, oscillations must be measured and characterised. Using time – frequency methods, this paper presents work that has been conducted to extract features from low-frequency active power pulsations to determine the composition of oscillatory modes which may impact on dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Robust Dynamic Pricing Over Infinite Horizon in The Presence of Model Uncertainty( 2* Journal)

This paper studies a problem of dynamic pricing faced by a retailer with limited inventory, uncertain about the demand rate model, aiming to maximize expected discounted revenue over an infinite time horizon. The retailer doubts his demand model which is generated by historical data and views it as an approximation. Uncertainty in the demand rate model is represented by a notion of generalized relative entropy process, and the robust pricing problem is formulated as a two-player zero-sum stochastic differential game. The pricing policy is obtained through the Hamilton-Jacobi-Isaacs (HJI) equation. The existence and uniqueness of the solution of the HJI equation is shown and a verification theorem is proved to show that the solution of the HJI equation is indeed the value function of the pricing problem. The results are illustrated by an example with exponential nominal demand rate.

Large‐scale wind deployment, social acceptance

The public is typically in agreement with the renewable energy targets established in many national states and generally supports the idea of increased reliance on wind energy. Nevertheless, many specific wind power projects face significant local opposition. A key question for the wind energy sector is, therefore, how to better engage local people to foster support for specific projects. IEA Wind Task 28 on Social Acceptance of Wind Energy Projects aims to facilitate wind energy development by reviewing current practices, emerging ideas, and exchanging successful practices among the participating countries. It also aims to disseminate the insights of leading research to a nontechnical audience, including project developers, local planning officials, and the general public. The interdisciplinary approach adopted by Task 28 enables an in-depth understanding of the nature of opposition to wind projects and a critical assessment of emerging strategies for social acceptance. Task 28 has analyzed a range of key issues related to social acceptance of wind energy, including the impacts on landscapes and ecosystems, on standard of living and well-being, the implementation of energy policy and spatial planning, the distribution of costs and benefits, and procedural justice. It is clear that although wind energy has many benefits; however, specific projects do impact local communities. As such the concerns of the affected people have to be taken seriously. Moreover, as opposition is rarely without foundation, it is in the interests of developers and advocates to engage local people and to improve projects for the benefit of all.

Can we meet targets for biofuels and renewable energy in transport given the constraints imposed by policy in agriculture and energy?

The deployment of biofuels is significantly affected by policy in energy and agriculture. In the energy arena, concerns regarding the sustainability of biofuel systems and their impact on food prices led to a set of sustainability criteria in EU Directive 2009/28/EC on Renewable Energy. In addition, the 10% biofuels target by 2020 was replaced with a 10% renewable energy in transport target. This allows the share of renewable electricity used by electric vehicles to contribute to the mix in achieving the 2020 target. Furthermore, only biofuel systems that effect a 60% reduction in greenhouse gas emissions by 2020 compared with the fuel they replace are allowed to contribute to meeting the target. In the agricultural arena, cross-compliance (which is part of EU Common Agricultural Policy) dictates the allowable ratio of grassland to total agricultural land, and has a significant impact on which biofuels may be supported. This paper outlines the impact of these policy areas and their implications for the production and use of biofuels in terms of the 2020 target for 10% renewable transport energy, focusing on Ireland. The policies effectively impose constraints on many conventional energy crop biofuels and reinforce the merits of using biomethane, a gaseous biofuel. The analysis shows that Ireland can potentially satisfy 15% of renewable energy in transport by 2020 (allowing for double credit for biofuels from residues and ligno-cellulosic materials, as per Directive 2009/28/EC) through the use of indigenous biofuels: grass biomethane, waste and residue derived biofuels, electric vehicles and rapeseed biodiesel. © 2010 Elsevier Ltd. All rights reserved.

Energy: lessons from devolution

Geraint Ellis and Richard Cowell explain the findings of the ‘Delivering renewable energy under devolution’ project, including some reasons for Scotland’s lead.

The UK has seen massive increases in renewable energy since 1998, with installed capacity growing from 2,600 MW to 12,300 MW in 2011. This has coincided with devolution and it is within Northern Ireland, Scotland and Wales that the greatest increases have been seen.

As devolved administrations now host half of the UK’s renewable energy capacity, their policies are critical to achieving the broader UK targets. This also provides a fascinating insight into what sort of approach works best, and why. This has been the focus of a two-year study, funded by the Economic and Social Research Council, involving universities from across the UK, which indicates that Scotland is leading the way on renewable energy.

All devolved governments have offered significant support to renewable energy but have different degrees of powers in relation to energy. Scotland’s success seems to be based on the centrality of energy issues to current political aspirations, particularly the SNP, but also has cross-party support. The research suggests that the consensus on the importance of renewable energy amongst élite interests in Scotland helps to explain why Scottish governments have been empowered and enabled to make robust use of the powers available.

As it has achieved successful growth in the sector, this too helps cultivate credibility among key business interests and gives increased leverage to its position in policy discussions with the UK Government. Scotland has been more consistent over time in presenting the expansion of renewable energy as a national economic agenda, rather than just an environmental or rural development agenda. The availability of larger, windy, but relatively less contested sites for onshore wind in Scotland has meant that more projects went through central consenting procedures rather than local planning authorities. Its enhanced support for wave and tidal power technologies is also notable. These political conditions have been harder to find in the rest of the UK, making progress a little more uncertain.

Northern Ireland has used its powers (which are more extensive than Scotland’s) to facilitate small-scale renewables and bio-fuel processes, with its liberalised planning regime offering an initial boost to expanding capacity.

This has contrasted with the position in Wales, which has least control over energy but the Welsh Government has adopted a more innovative approach to strategic spatial zoning; this appears to have pulled in a larger volume of onshore wind development interest than could be expected in a comparable region of England. A downside of the Welsh approach appears to be the fact that the concentration of these wind projects in these zones has triggered public opposition and political conflict.

It therefore appears that the powers available to the devolved governments do not seem to determine which country has been able to make greatest headway, with broader political commitments being more significant. Despite this, the research does not conclude that the actions and activities undertaken by the devolved governments are necessarily the most important factors in shaping the development of renewable energy in the UK. This is because devolution is still a relatively new dimension of energy governance in the UK and decisions affecting key drivers for renewable energy investment are still made mainly in Westminster, with the Treasury exercising close budgetary control. In all areas of the UK, grid capacity expansion remains slow to achieve. The major growth in offshore wind to date has been driven mainly by Westminster and cross-UK bodies with the most significant capacity growth being in English territorial waters.

Active use of DFIG based Wind Farms for Transient Stability Improvement during Grid Disturbances

The doubly-fed induction generator (DFIG) now represents the dominant technology in wind turbine design. One consequence of this is limited damping and inertial response during transient grid disturbances. A dasiadecoupledpsila strategy is therefore proposed to operate the DFIG grid-side converter (GSC) as a static synchronous compensator (STATCOM) during a fault, supporting the local voltage, while the DFIG operates as a fixed-speed induction generator (FSIG) providing an inertial response. The modeling aspects of the decoupled control strategy, the selection of protection control settings, the significance of the fault location and operation at sub- and super-synchronous speeds are analyzed in detail. In addition, a case study is developed to validate the proposed strategy under different wind penetrations levels. The simulations show that suitable configuration of the decoupled strategy can be deployed to improve system voltage stability and inertial response for a range of scenarios, especially at high wind penetration. The conclusions are placed in context of the practical limitations of the technology employed and the system conditions.

Measurement-based Method for Wind Farm Power System Oscillation Monitoring

The global increase in the penetration of renewable energy is pushing electrical power systems into uncharted territory, especially in terms of transient and dynamic stability. In particular, the greater penetration of wind generation in European power networks is, at times, displacing a significant capacity of conventional synchronous generation with fixed-speed induction generation and now more commonly, doubly-fed induction generators. The impact of such changes in the generation mix requires careful monitoring to assess the impact on transient and dynamic stability. This paper presents a measurement based method for the early detection of power system oscillations, with attention to mode damping, in order to raise alarms and develop strategies to actively improve power system dynamic stability and security. A method is developed based on wavelet transform and support vector data description (SVDD) to detect oscillation modes in wind farm output power, which may excite dynamic instabilities in the wider system. The wavelet transform is used as a filter to identify oscillations in different frequency bands, while SVDD is used to extract dominant features from different scales and generate an assessment boundary according to the extracted features. Poorly damped oscillations of a large magnitude or that are resonant can be alarmed to the system operator, to reduce the risk of system instability. Method evaluation is exemplified used real data from a chosen wind farm.

Impact of Wind Generation Mix on Transient Stability for an Interconnected Power System

The rapid growth of wind generation in many European countries is pushing power systems into
uncharted territory. As additional wind generators are installed, the changing generation mix may
impact on power system stability. This paper adopts the New England 39 bus system as a test
system for transient stability analysis. Thermal generator models are based on a likely future plant
mix for existing systems, while varying capacities of fixed-speed induction generators (FSIG) and
doubly-fed induction generators (DFIG) are considered. The main emphasis here has been placed
on the impact of wind technology mix on inter-area oscillations following transient grid
disturbances. In addition, both rotor angle stability and transient voltage stability are examined, and
results are compared with current grid code requirements and standards. Results have shown that
FSIGs can reduce tie-line oscillations and improve damping following a transient disturbance, but
they also cause voltage stability and rotor angle stability problems at high wind penetrations. In
contrast, DFIGs can improve both voltage and rotor angle stability, but their power output
noticeably oscillates during disturbances.

Offshore wind power forecasting error and electricity market implications

Wind energy has been identified as key to the European Union’s 2050 low carbon economy. However, as wind is a variable resource and stochastic by nature, it is difficult to plan and schedule the power system under varying wind power generation. This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact of the magnitude and variance of the offshore wind power forecast error on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price is analysed. The main findings of this research are that the magnitude of the offshore wind power forecast error has the largest impact on system generation costs and dispatch-down of wind, but the variance of the offshore wind power forecast error has the biggest impact on emissions costs and system marginal price. Overall offshore wind power forecast error variance results in a system marginal price increase of 9.6% in 2050.

Momentum Trading in New York Stock Exchange (NYSE) Energy Stocks

This paper investigates whether the momentum effect exists in the NYSE energy sector. Momentum is defined as the strategy that buys (sells) these stocks that are best (worst) performers, over a pre-specified past period of time (the 'look-back' period), by constructing equally weighted portfolios. Different momentum strategies are obtained by changing the number of stocks included in these portfolios, as well as the look-back period. Next, their performance is compared against two benchmarks: the equally weighted portfolio consisting of most stocks in the NYSE energy index and the market portfolio, and the S&P500 index. The results indicate that the momentum effect is strongly present in the energy sector, and leads to highly profitable portfolios, improving the risk-reward measures and easily outperforming both benchmarks.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

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.

What do high penetrations of wind power mean for gas generation?

Dependency on thermal generation and continued wind power growth in Europe due to renewable energy and greenhouse gas emissions targets has resulted in an interesting set of challenges for power systems. The variability of wind power impacts dispatch and balancing by grid operators, power plant operations by generating companies and market wholesale costs. This paper quantifies the effects of high wind power penetration on power systems with a dependency on gas generation using a realistic unit commitment and economic dispatch model. The test system is analyzed under two scenarios, with and without wind, over one year. The key finding of this preliminary study is that despite increased ramping requirements in the wind scenario, the unit cost of electricity due to sub-optimal operation of gas generators does not show substantial deviation from the no wind scenario.

Hierarchical energy management system for multi-source multi-product microgrids

This paper proposes a hierarchical energy management system for multi-source multi-product (MSMP) microgrids. Traditional energy hub based scheduling method is combined with a hierarchical control structure to incorporate transient characteristics of natural gas flow and dynamics of energy converters in microgrids. The hierarchical EMS includes a supervisory control layer, an optimizing control layer, and an execution control layer. In order to efficiently accommodate the systems multi time-scale characteristics, the optimizing control layer is decomposed into three sub-layers: slow, medium and fast. Thermal, gas and electrical management systems are integrated into the slow, medium, and fast control layer, respectively. Compared with wind energy, solar energy is easier to integrate and more suitable for the microgrid environment, therefore, potential impacts of the hierarchical EMS on MSMP microgrids is investigated based on a building energy system integrating photovoltaic and microturbines. Numerical studies indicate that by using a hierarchical EMS, MSMP microgrids can be economically operated. Also, interactions among thermal, gas, and electrical system can be effectively managed.