Wind-generated Electricity Research Articles

Impact of deep wind power penetration on variability at load centers

Increasingly, variable renewable energy capacity will be added distant from load centers in much of the world. How such intraregional heterogeneity in variable supply and load will impact the energy system in a deep renewable penetration scenario is studied here. Heterogeneous reliability requirements imposed by such scenarios are not well understood. Some unique geographic settings, such as the Nordic grid with weeks of pumped hydro backup, manage to circumvent this issue without significant curtailment, but most regions have yet to achieve the renewable energy levels at which the issue will arise. Using simulations of wind power expansion in New York State, we illustrate the intraregional effects by quantifying the net load, net load ramping, operating reserve and regulation requirements, and the associated distribution of infrastructure investments and ancillary services. The study finds that only at wind capacities exceeding 100% of the average statewide load does the wind-generated electricity meet significant portions of the distant demands. However, the peak net load in these areas is not reduced, requiring that dispatchable generation capacity be maintained. Moreover, the net load becomes highly variable, with large ramp rates that increase ancillary service requirements (operating reserves and frequency regulation) to ensure reliable system operation. A major finding is that the additional ancillary service requirements become more concentrated in the distant load centers. A second significant finding is that while transmission capacity upgrades greatly increase the wind-generated electricity that reaches load centers, the increased variability in that supply can exacerbate both the magnitude and heterogeneity of ancillary service requirements. These services would presumably be provided by the same local dispatchable resources that would now be operating at lower capacity factors but with higher variability. Such changes in the scale and distribution of intraregional integration measures and infrastructure investments may require new energy planning approaches and market structures to achieve anticipated future renewable energy targets.

The Cost of Reducing Greenhouse Gas Emissions

Most countries, including the United States, have an array of greenhouse gas mitigation policies, which provide subsidies or restrictions typically aimed at specific technologies or sectors. Such climate policies range from automobile fuel economy standards, to gasoline taxes, to mandating that a certain amount of electricity in a state comes from renewables, to subsidizing solar and wind electrical generation, to mandates requiring the blending of biofuels into the surface transportation fuel supply, to supply-side restrictions on fossil fuel extraction. This paper reviews the costs of various technologies and actions aimed at reducing greenhouse gas emissions. Our aim is twofold. First, we seek to provide an up-to-date summary of costs of actions that can be taken now using currently available technology. These costs focus on expenditures and emissions reductions over the life of a project compared to some business-as-usual benchmark—for example, replacing coal-fired electricity generation with wind, or weatherizing a home. We refer to these costs as static because they are costs over the life of a specific project undertaken now, and they ignore spillovers. Our second aim is to distinguish between dynamic and static costs and to argue that some actions taken today with seemingly high static costs can have low dynamic costs, and vice versa. We make this argument at a general level and through two case studies, of solar panels and of electric vehicles, technologies whose costs have fallen sharply. Under the right circumstances, dynamic effects will offer a justification for policies that have high costs according to a myopic calculation.

ON THE POSSIBILITY OF SUPERCAPACITOR USING IN AUTONOMOUS WIND-DIESEL COMPLEXES

The paper deals with the features of wind-diesel units operation at a high frequency of wind speed variations. Various options of the wind farm complex layout are considered on the basis of the following input data: 1) consumer load schedule (Ust-Voyampolka village in the Kamchatka Territory); 2) the characteristics of domestic diesel-generator sets and supercapacitors; 3) characteristics of wind power generators of Chinese production. We have made the estimates using a balance model and two calculation algorithms which differ in the details of the initial data on the wind regime (the periodicity of the data is 3 hours and 2 seconds respectively). It is proposed to optimize the energy complex composition by partitioning the diesel generator set and by using a supercapacitor battery to compensate for the variable output of wind generators. It is shown that under the typical wind conditions and daily load graphs of the consumer, the optimum capacity of the supercapacitor battery in the wind farm is 324 Wh. Moreover, increasing the capacity of supercapacitor does not reduce fuel consumption. Comparison of technical and economic characteristics of the supercapacitors and batteries with a similar energy capacity suggests that the supercapacitor module can have an advantage over the battery due to cost and resource parameters, as well as higher permissible charge-discharge currents. It is shown that the introduction of a wind-electric generator into the system can lead not only to a decrease in the consumption of diesel fuel, but also to a deterioration of the technical and economic indicators of the diesel generator set due to its operation at low power.

An improved wavelet transform and multi-block forecast engine based on a novel training mechanism

In this paper, a novel prediction technique is proposed to predict wind-power generation. Because of the growth of wind-generated electricity as a component of power grids, various wind-power prediction methods have been proposed recently by researchers. To achieve accurate prediction, a novel approach using a dual-tree complex wavelet transform, a new feature selection procedure, and a combinatorial prediction engine has been implemented to forecast wind-power generation. To improve feature selection to reduce diagnostic efficiency degradation caused by outliers in data-driven diagnostics, an outlier-insensitive combinatorial feature selection procedure has been used to determine candidate subgroup characteristics. Furthermore, a multi-stage forecast engine equipped with a new training mechanism for optimizing free parameters and based on the Elman neural network (ENN) is presented in this work. This training mechanism was developed using an efficient stochastic search method to attain the high learning capabilities of the proposed ENN-based forecast engine. The proposed model has been applied to real-world engineering data from Alberta, Canada, and Oklahoma, United States. The outcomes achieved by the different forecasting methods are compared, proving the effectiveness of the proposed procedure.

Linking greenhouse gas emissions footprint and energy return on investment in electricity generation planning

This paper aims to relate total greenhouse gas emissions footprint with Energy Return on Energy Invested for Coal, Natural Gas, Hydro, Geothermal, Wind and Solar PV electricity generation methods. Emissions from construction, decommissioning, operations and maintenance, and fuel, are all included in the analysis. Often the generation equipment is imported so much of the emissions associated with construction are “virtual” emissions (i.e. imported). These virtual emissions contribute to a peak emission as renewable generation is installed at the start to ultimately lead to a lower emissions factor for a countries’ electricity system over time. The peak occurs due to the short-term emissions resulting from construction and a long-term emissions reduction due to the low/zero carbon renewable generation installed. The electricity sector in New Zealand is used as a case study for projected new generation through to 2050 for four scenarios (a) Global Low Carbon, (b) Mixed Renewables, (c) High Grid and (d) High Solar. The study demonstrates that as total greenhouse gas footprints are included an emissions peak occurs due to new construction, mainly because of renewable generation, especially solar and high energy emissions factors in countries manufacturing generation equipment.

ISO.Wind – A monitoring system for wind parks using passive radar

Intelligent wind park monitoring systems may allow cutting the levelized cost of wind-generated electricity by deploying maintenance personnel more efficiently. The non-contacting passive radar technology and advanced sensing technologies on the plant side offer significant potential for such monitoring systems. The goal of the 3-year-long project ISO.Wind is to identify the most cost-efficient sensing technologies to detect maintenance-relevant damages and to use them for a wind park monitoring system. For this purpose a commercial 3MW wind turbine is instrumented with strain gauges following IEC standard 61400-13 and a network of accelerometers. It is also monitored by passive radar technology. A learning algorithm is developed and fed with available data from the sensor systems and operational data from the instrumented wind turbine. The algorithm is capable of detecting operational patterns and damage cases of the wind turbine. A graphic user interface illustrates these conditions in a comprehensible way. First field measurements show the suitability of the passive radar technology to detect the damage-relevant dynamics of the instrumented wind turbine. Validated simulations of typical damage cases prove that both instrumentation on the plant side and the passive radar sensing technology allow reliable damage detection for the examined wind turbine.

Decomposition Analysis And Renewables In CO2 Emission Trends

The decline in carbon dioxide emissions in the United States between 2007 and 2013 is actually more complex than previously thought. During that period, carbon dioxide emissions from United States energy use decreased sharply and unexpectedly, after rising for nearly two decades. At the end of the six-year period, U.S. annual carbon dioxide emissions had fallen by 11 percent– a drop the nation hadn’t experienced since the 1979 oil crisis. Experts have typically attributed this decline to two factors: the drop in energy demand during the recession that began in 2007 and the surge in inexpensive natural gas that displaced coal in the energy mix during the same time. However, they missed another critical influence that hastened the decline in emissions just as much: the rapid rise in renewable energy production. Between 2007 and 2013, wind-generated electricity grew nearly five times, to 168 terawatt hours, enough to power 15 million average American homes, while utility-scale solar grew to 8.7 TWh. During the same period, bioenergy production grew to 4,800 trillion BTUs, or 39 percent, which includes biofuels in the transportation sector.

Economic viability and production capacity of wind generated renewable hydrogen

Generally, wind to power conversion is calculated by assuming the quality of wind as measured with a Weibull probability distribution at wind speed during power generation. We build on this method by modifying the Weibull distributions to reflect the actual range of wind speeds and wind energy density. This was combined with log law that modifies wind speed based on the height from the ground, to derive the wind power potential at windy sites. The study also provides the Levelized cost of renewable energy and hydrogen conversion capacity at the proposed sites. We have also electrolyzed the wind-generated electricity to measure the production capacity of renewable hydrogen. We found that all the sites considered are commercially viable for hydrogen production from wind-generated electricity. Wind generated electricity cost varies from $0.0844 to $0.0864 kW h, and the supply cost of renewable hydrogen is $5.30 to $ 5.80/kg-H2. Based on the findings, we propose a policy on renewable hydrogen fueled vehicles so that the consumption of fossil fuels could be reduced. This paper shall serve as a complete feasibility study on renewable hydrogen production and utilization.

A wireless rainwater collecting, filtering, and storing system using a cell-phone

Because of the greenhouse effect, global climate considerably changes and will worsen the water supply situations in future. Also, as can be seen in traditional reservoir, the crisis of water lacking will exacerbate due to the reservoir sedimentation. In order to widen the storage of water resources, a design of portable rain-collecting system used for irritation and daily use for people is presented. To facilitate the monitoring and manipulating, a rainwater collecting and storing system with green energy/automation /monitoring/control function is established. Considering the electricity shortage in remote island/mountain regions, two kinds of green energy generators (wind electrical generator and solar-board electrical device) are built and linked with the system. Here, a rain detector installed onto the roof can actuate the rainwater collecting board to raise and to collect water when raining event occurs. For the purpose of water purity, water filter is also set at the entrance of the water tank. In order to efficiently store/use the rainwater, several water storage tanks in conjunction with ecological pool are preset and adjusted via the water level gauge sensors and the pipe‘s solenoid valve. To meet the weather-proof ability, PLC is adopted as the controller. Moreover, a human-machine-interface is login on the internet and remotely communicated with the cell phone.Consequently, a prototype of the cell-phone base automatic rainwater collecting and storing system is established.

The impact of an ETS on the Australian energy sector: An integrated CGE and electricity modelling approach

This paper utilises a new computable general equilibrium (CGE) model which integrates an electricity supply model to gauge the effects of a national emissions trading scheme (ETS) on the Australian energy sector and the broader economy. The modelling results show that an ETS can reduce emissions effectively and with a relatively small impact on the overall economy. But the impact of the ETS on individual sectors varies. Wind electricity generation is projected to benefit greatly. Brown coal electricity and gas electricity are expected to be adversely affected substantially. Somewhat surprisingly, the impact on black coal electricity is negative but relatively small.

Wind-generated Electricity in China: Decreasing Potential, Inter-annual Variability and Association with Changing Climate

China hosts the world’s largest market for wind-generated electricity. The financial return and carbon reduction benefits from wind power are sensitive to changing wind resources. Wind data derived from an assimilated meteorological database are used here to estimate what the wind generated electricity in China would have been on an hourly basis over the period 1979 to 2015 at a geographical resolution of approximately 50 km × 50 km. The analysis indicates a secular decrease in generating potential over this interval, with the largest declines observed for western Inner Mongolia (15 ± 7%) and the northern part of Gansu (17 ± 8%), two leading wind investment areas. The decrease is associated with long-term warming in the vicinity of the Siberian High (SH), correlated also with the observed secular increase in global average surface temperatures. The long-term trend is modulated by variability relating to the Pacific Decadal Oscillation (PDO) and the Arctic Oscillation (AO). A linear regression model incorporating indices for the PDO and AO, as well as the declining trend, can account for the interannual variability of wind power, suggesting that advances in long-term forecasting could be exploited to markedly improve management of future energy systems.

Converting Wind Energy to Ammonia at Lower Pressure

Renewable wind energy can be used to make ammonia. However, wind-generated ammonia costs about twice that made from a traditional fossil-fuel driven process. To reduce the production cost, we replace the conventional ammonia condensation with a selective absorber containing metal halides, e.g., calcium chloride, operating at near synthesis temperatures. With this reaction-absorption process, ammonia can be synthesized at 20 bar from air, water, and wind-generated electricity, with rates comparable to the conventional process running at 150–300 bar. In our reaction-absorption process, the rate of ammonia synthesis is now controlled not by the chemical reaction but largely by the pump used to recycle the unreacted gases. The results suggest an alternative route to distributed ammonia manufacture which can locally supply nitrogen fertilizer and also a method to capture stranded wind energy as a carbon-neutral liquid fuel.

Does the lower stratosphere provide predictability for month‐ahead wind electricity generation in Europe?

Wind power is playing an increasingly important role in Europe's electricity generation. Accurate forecasts of wind‐power output on various spatial and temporal scales are therefore of high interest for the energy industry. However, predictability of near‐surface wind on subseasonal time‐scales has received relatively little attention. The stratosphere is an important source of subseasonal predictability in winter. Here, we study the implications of the lower stratospheric circulation for month‐ahead wind electricity generation in Europe in winter. Using ERA‐Interim reanalysis and the novel wind‐power dataset Renewables.ninja, we demonstrate a strong relationship between the lower stratospheric circulation and month‐ahead wind electricity generation in different parts of Europe in the period 1985–2014. This relationship exists due to episodes of troposphere–stratosphere coupling, which lead to prolonged periods of either the positive or negative phase of the North Atlantic Oscillation (NAO). Since these persistent NAO periods are associated with strong surface wind anomalies, they have an important impact on wind electricity generation, in particular in Northern Europe. The state of the lower stratospheric circulation also determines the exact latitudinal position of these prolonged NAO patterns, with contrasting implications for wind electricity generation in specific countries. Using simple statistical forecasts, we show that the observed relationship between the lower stratosphere and wind electricity generation can be used for skilful forecasts of month‐ahead wind electricity generation. Particularly high forecast skill is found when the circulation in the lower stratosphere differs strongly from its climatological mean. Anomalous states of the lower stratospheric circulation therefore provide windows of subseasonal‐range predictability for wind‐power output in many European countries.

Control Strategy Used in DFIG and PMSG Based Wind Turbines an Overview

<p class="Abstract">Nowadays, the fossil combustibles are replaced by renewable energies sources .These renewable energies are nontoxic, dirt free, and protected and reasonably cheep for the user. Renewable energy resources like bio-gas, geothermal, solar, tidal waves and wind have been found as the best alternatives energy source. Among those renewable energy sources, wind energy stands foremost for generating electricity. In order to have a constant utilization of wind energy and to extract maximum power from wind energy. In this paper, various control strategies prevalent to both the Doubly Fed Induction Generator (DFIG)and Permanent Magnet Synchronous Generator(PMSG) have been analyzed . In addition, control topology applicable to power electronics converter/inverter used in wind electric generators are discussed.</p>

Wind speed characteristics and implications for wind power generation: Cape regions, South Africa


 
 
 Spatio-temporal dynamics of near-surface wind speeds were examined across the Northern, Western and Eastern Cape regions of South Africa. The regions assessed were geographically subdivided into three zones: coastal, coastal hinterland and inland. Wind speed data (10 m) were evaluated at monthly, seasonal, annual and zonal resolutions, with the aim to establish wind speed attributes and trends. Data from 19 weather stations with high-resolution wind records between 1995 and 2014 were evaluated. The majority of stations (79%) recorded a decrease in mean annual wind speed over the study period. The mean rate of decrease across all stations over the 20-year period equates to -1.25%, quantifying to an annual decrease of -0.002 m/s/year (-0.06% pa). The largest seasonal decline of -0.006 m/s/year (-0.15% pa) was recorded in summer. Statistically significant declines in mean annual wind speed are somewhat more pronounced for the coastal zone (-0.003 m/s/year, -0.08% pa) than over interior regions (-0.002 m/s/year, -0.06% pa) for the study period. The largest decrease (-0.08% pa) was recorded for the coastal zone, followed by the inland zone (-0.06% pa), equating to an annual reduction in available energy of 0.18% pa and 0.09% pa, respectively. When considering all stations over the study period, the mean inter-annual variability is 3.11%. Despite such decreases in wind speed, the variance identified in this study would not have posed any risk to power generation from wind across the assessed stations, based on the period 1995 to 2014.
 
 
 
 
 Significance: 
 
 
 
 Mean recorded wind speed decreases have been marginal under recent (last 20 years) climatic conditions and change, thus adding confidence to the justification by the South African government to procure additional wind-generated electricity capacity.
 Wind speed trends and variance measured over the research period (1995–2014) for the Cape stations in this study, would not have posed any risk to power generation from wind.
 Only four stations (28.6%) recorded statistically significant trends at the 0.05% level; of these 75% were decreasing trends.
 Coastal zones recorded a statistically larger decrease in mean wind speed compared to inland regions.
 When considering all stations over the period 1995–2014, the mean inter-annual variability is 3.11%.
 
 
 

Possible role of power-to-heat and power-to-gas as flexible loads in German medium voltage networks

Germany’s energy transition triggered a rapid and unilateral growth of renewable energy sources (RES) in the electricity sector. With increasing shares of intermittent RES, overcapacities during periods of strong wind and photovoltaic electricity generation occur. In the face of insufficient transmission capacities, due to an inhibited network extension, the electricity generation has to be curtailed. This curtailment of RES leads to economic losses and could be avoided through flexible loads. As an option to cope with those problems, the technologies of power-to-gas (PtG) and power-to-heat (PtH) are presented in this paper. First, the alkaline electrolyzer (AEL), polymer electrolyte membrane electrolyzer (PEMEL), and solid oxide electrolyzer cell (SOEC) are investigated regarding their operational parameters. Second, the electric boiler, electrode heating boiler, and heat pumps are considered. Ultimately, the network-supporting abilities and the potential to provide ancillary services, such as control power, load sequence operation, cold start and part load capability, are compared among one another.

Capacity Allocation of Hydrogen Production and Fuel Cells in Wind Farm Based on Stochastic Prediction Error

Hydrogen production system is special energy storage device. Hydrogen production using wind power and electricity generation using hydrogen fuel cells can reduce wind power grid-connected power fluctuation. The optimal capacity allocation is determined based on the hydrogen production and fuel cells energy conversion efficiency. With the target of hydrogen throughput and stabilizing power fluctuation effect, the optimal internal configuration of electrolyzers and fuel cells is determined by comparing the different parameters of them. In the case studies, without the aid of other sources of energy, the system can achieve the goal of reducing wind power fluctuation by the optimal capacity allocation and the internal configuration, which verifies the accuracy and effectiveness of the method in this paper.

Stochastic model of wind-fuel cell for a semi-dispatchable power generation

Hybrid systems are implemented to improve the efficiency of individual generation technologies by complementing each other. Intermittence is a challenge to overcome especially for renewable energy sources for electric generation, as in the case of wind power. This paper proposes a hybrid system as an approach for reducing and overcoming the volatility of wind power, by implementing storage technology, forecasts and predictive control. The proposed hybrid system, which is suitable for the distributed generation level, consists of a wind generator, an electrolyzer, hydrogen storage and a polymer electrolyte membrane fuel cell, which are embedded in one complete system with the wind power. This study uses historic wind speed data from Mexico; the forecasts are obtained using the recursive least square algorithm with a forgetting factor. The proposed approach provides probabilistic information for short-term wind power generation and electric generation as the outcome of the hybrid system. A method for a semi-dispatchable electric generation based on time series analysis is presented, and the implementation of wind power and polymer electrolyte membrane fuel cell models controlled by a model predictive control approach is developed.

Lessons from wind policy in Portugal

Wind capacity and generation grew rapidly in several European countries, such as Portugal. Wind power adoption in Portugal began in the early 2000s, incentivized by a continuous feed-in tariff policy mechanism, coupled with public tenders for connection licenses in 2001, 2002, and 2005. These policies led to an enormous success in terms of having a large share of renewables providing electricity services: wind alone accounts today for ~23.5% of electricity demand in Portugal. We explain the reasons wind power became a key part of Portugal’s strategy to comply with European Commission climate and energy goals, and provide a detailed review of the wind feed-in tariff mechanism. We describe the actors involved in wind power production growth. We estimate the environmental and energy dependency gains achieved through wind power generation, and highlight the correlation between wind electricity generation and electricity exports. Finally, we compare the Portuguese wind policies with others countries’ policy designs and discuss the relevance of a feed-in tariff reform for subsequent wind power additions.

Sizing procedures for sun-tracking PV system with batteries

Deciding optimum number of PV panels, wind turbines and batteries (i.e. a complete renewable energy system) for minimum cost and complete energy balance is a challenging and interesting problem. In the literature, some rough data models or limited recorded data together with low resolution hourly averaged meteorological values are used to test the sizing strategies. In this study, active sun tracking and fixed PV solar power generation values of ready-to-serve commercial products are recorded throughout 2015–2016. Simultaneously several outdoor parameters (solar radiation, temperature, humidity, wind speed/direction, pressure) are recorded with high resolution. The hourly energy consumption values of a standard 4-person household, which is constructed in our campus in Eskisehir, Turkey, are also recorded for the same period. During sizing, novel parametric random process models for wind speed, temperature, solar radiation, energy demand and electricity generation curves are achieved and it is observed that these models provide sizing results with lower LLP through Monte Carlo experiments that consider average and minimum performance cases. Furthermore, another novel cost optimization strategy is adopted to show that solar tracking PV panels provide lower costs by enabling reduced number of installed batteries. Results are verified over real recorded data.