Techno-Economic Study of Wind Farm Forecast Error Compensation by Flexible Heat-Driven CHP Units

2017 ◽  
Author(s):  
Thomas Bexten ◽  
Manfred Wirsum ◽  
Björn Roscher ◽  
Ralf Schelenz ◽  
Georg Jacobs ◽  
...  
Keyword(s):  
Power Generation ◽  
Error Compensation ◽  
Wind Farm ◽  
Storage Capacity ◽  
Heat Storage ◽  
Forecast Error ◽  
Economic Viability ◽  
Forecast Errors ◽  
Energy Costs ◽  
Balance Energy

Many energy supply systems around the world are currently undergoing a phase of transition that is mainly characterized by a continuing increase in installed renewable power generation capacities. Aiming at a better integration of these additional capacities, operators of wind farms in Germany are obliged to bindingly forecast their power production. In order to maintain the continuous stability of the electricity grid, deviations from these forecasts have to be compensated by the grid operator, who charges the wind farm operators accordingly. An alternative way to compensate for forecast errors is the utilization of flexible and dispatchable energy conversion and storage units by the wind farm operator. Heat-driven combined heat and power (CHP) units with heat storage systems offer the potential of limited short-term load adjustments to compensate forecast errors while simultaneously fulfilling their main task of providing heat. The main objectives of the present study are the evaluation of the main technical parameters and the economic viability of the described application. The study utilizes a theoretical scenario incorporating a gas turbine as a CHP unit providing heat for an industrial process, a heat storage and an associated wind farm. A generic wind farm power generation forecast error model is developed, providing realistic forecast errors for the study. Detailed models of all system components are developed and integrated into a common simulation environment, allowing for simulations of the overall system operation with varying heat storage capacities. The simulation results show that the combination of a heat-driven CHP gas turbine and a heat storage system makes a significant contribution to the compensation of the wind farm power generation forecast errors. Distinct correlations between the heat storage capacity and the remaining forecast errors are identified. The net balance energy costs resulting from the remaining demand for balance energy after the partial forecast error compensation are investigated as the main parameter for the economic viability. No distinctive correlation between the heat storage capacity and the net balance energy costs can be identified. This is the result of the stochastic character of the net balance energy price.

Ground Mass Heat-Accumulating Capacity Evaluation at the Protective Structure Conditioning System Design Stage

2018 ◽  
Vol 931 ◽  
pp. 940-945
Author(s):  
Oleg A. Gubeladze ◽  
Avtandil R. Gubeladze ◽  
Larisa F. Kirilchik
Keyword(s):  
System Design ◽  
Air Conditioning ◽  
Storage Capacity ◽  
Heat Storage ◽  
Design Stage ◽  
Energy Costs ◽  
Protective Structure ◽  
Capacity Evaluation ◽  
Ground Mass

The possibility of using the heat-storage capacity of the soil massif surrounding the underground protective structure is under consideration with the purpose to minimize the energy costs of the projected system for technological air conditioning of the facility.

Impact of Forecast Uncertainty on Wind Farm Profitability

2020 ◽  
Vol 142 (4) ◽  
Author(s):  
Guido Francesco Frate ◽  
Lorenzo Ferrari ◽  
Umberto Desideri
Keyword(s):  
Power Plants ◽  
Wind Farm ◽  
Forecast Error ◽  
Market Competition ◽  
Renewable Energy Sources ◽  
Power Level ◽  
Point Of View ◽  
Energy Market ◽  
Forecast Errors ◽  
Forecast Lead Time

Abstract The great amount of support schemes that initially fueled the fast and often uncontrollable, renewable energy sources (RESs) growth have been strongly reduced or revoked in many countries. Currently, the general trend is to try to equate RESs to traditional power plants. From the energy market point of view, this entails exposing RESs to market competition and mechanics. For example, it could be requested that RESs submit a production schedule in advance and are financially responsible for any deviation from it. This could push the wind farm (WF) operators to make accurate forecasts, thus fostering the electric system resiliency and an efficient use of balancing resources. From the forecasting point of view, this is not a trivial problem since the schedule submission is often due 10–12 h before the actual delivery. Since forecast errors are unavoidable, the submitted schedule could turn out to be infeasible, thus forcing the WF to adopt correcting actions, which are generally costly. This study estimates the revenue reduction that would affect a WF operating in the energy market due to forecast errors. To do this in a realistic way, a case study is selected, and realistic forecast scenarios are generated by using a copula approach. Relevant forecast error features, like autocorrelation and dependency on forecasted power level and forecast lead time, are modeled. The revenue reduction due to balancing actions is calculated on an annual basis, by using typical days. These were derived through a clustering procedure based on production data. Losses ranging from 5% to 35% have been found, depending on the days and market prices. A sensitivity analysis to the costs of balancing actions is performed. The effect of different market architectures and different RESs penetration level is considered in the analysis. Finally, the effectiveness of two techniques (i.e., curtailment and batteries) to reduce forecast error impact in highly penalizing market environments is assessed.

Impact of Forecast Uncertainty on Wind Farm Profitability

2019 ◽  
Author(s):  
Guido Francesco Frate ◽  
Lorenzo Ferrari ◽  
Umberto Desideri
Keyword(s):  
Power Plants ◽  
Wind Farm ◽  
Forecast Error ◽  
Market Competition ◽  
Renewable Energy Sources ◽  
Point Of View ◽  
Energy Market ◽  
Forecast Errors ◽  
Forecast Lead Time ◽  
The Impact

Abstract The great amount of support schemes that initially fueled the fast, and often uncontrollable, Renewable Energy Sources (RESs) growth have been strongly reduced or revoked in many countries. Currently, the general trend is to try to equate the RESs to the traditional power plants. From the energy market point of view, this entails exposing the RESs more to the market competition and mechanics. This could be done, for example, requiring the stochastic RESs to submit a production schedule in advance and to be financially responsible for any deviation from this. This could push the Wind Farm (WF) operators to make accurate forecasts, fostering the electric system resiliency and an efficient use of balancing resources. From the forecasting point of view this is not a trivial problem, since the schedule submission is often due 10–12 hours before the actual delivery. Since forecast errors are unavoidable, the submitted schedule could turn out to be infeasible, forcing the WF to recur to correcting actions which are generally costly. Focusing on this, the analysis estimates the revenue reduction which would affect a WF operating in the energy market due to forecast errors. To do this in a realistic way, a case study is selected, and realistic forecast scenarios are generated using a copula approach. Important forecast error features like autocorrelation and dependency on forecasted power level and forecast lead-time are modeled. The revenue reduction due to balancing actions is calculated on an annual basis, using typical days, derived through the production data clustering. Losses ranging from 5% to 35% has been found, depending on the days and on the market prices. A sensitivity analysis to the costs of balancing actions is performed. In this way, the effect of different market architectures and, possibly, of different RESs penetration level is considered in the analysis. Finally, the effectiveness of the curtailment as a technique to reduce the impact of forecast errors in highly penalizing market environments is assessed.

scholarly journals Energy Storage Sizing Optimization and Sensitivity Analysis Based on Wind Power Forecast Error Compensation

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4755 ◽  
Author(s):  
Xiaodong Yu ◽  
Xia Dong ◽  
Shaopeng Pang ◽  
Luanai Zhou ◽  
Hongzhi Zang
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Error Compensation ◽  
Wind Farm ◽  
Forecast Error ◽  
Wind Farms ◽  
Optimization Method ◽  
Future Market ◽  
Penalty Cost ◽  
Wind Power Forecast

To better track the planned output (forecast output), energy storage systems (ESS) are used by wind farms to compensate the forecast error of wind power and reduce the uncertainty of wind power output. When the error compensation degree is the same, the compensation interval is not unique, different compensation intervals need different ESS sizing. This paper focused on finding the optimal compensation interval not only satisfied the error compensation degree but also obtained the max profit of the wind farm. First, a mathematical model was proposed as well as a corresponding optimization method aiming at maximizing the profit of the wind farm. Second, the effect of the influencing factors (compensation degree, electricity price, ESS cost, and wind penalty cost) on the optimal result was fully analyzed and deeply discussed. Through the analysis, the complex relationship between the factors and the optimal results was found. Finally, the comparison between the proposed and traditional method was given, and the simulation results showed that the proposed method can provide a powerful decision-making basis for ESS planning in current and future market.

ANÁLISE DA MORFODINÂMICA COSTEIRA E DOS IMPACTOS SOCIOAMBIENTAIS DE GRANDES EMPREENDIMENTOS LITORÂNEOS: ESTUDO DE CASO, PRAIA DE VOLTA DO RIO, ACARAÚ/CE

2019 ◽  
Vol 21 (2) ◽  
pp. 745-754
Author(s):  
Otávio Augusto de Oliveira Lima Barra ◽  
Fábio Perdigão Vasconcelos ◽  
Danilo Vieira dos Santos ◽  
Adely Pereira Silveira
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Wind Farm ◽  
Dynamic Environment ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Natural Phenomenon ◽  
Human Intervention ◽  
Del Rio ◽  
Natural Dynamic

O Brasil é um país com uma extensa linha de costa, são cerca de 7.367 km de extensão do seu litoral, com um potencial natural para a geração de energia eólica. O estado do Ceará é um dos maiores produtores de energia eólica para o país, obtendo notoriedade e a necessidade de manutenção dos seus parques eólicos, especialmente se instalados em zonas de costa, onde há uma grande dinâmica natural. O presente trabalho, busca o acompanhamento das dinâmicas morfológicas na praia de Volta do Rio, localizada em Acaraú/CE, que fica a cerca de 238 km de Fortaleza/CE. Os dados coletados em idas à campo, constataram que há um forte processo erosivo atuante na praia de Volta do Rio, o que alerta para a contenção do avanço marinho sob o parque eólico presente no local. A erosão é um fenômeno natural que trabalha na modelação de demasiadas formas terrestres. No litoral, isso não é diferente, por ser um ambiente altamente dinâmico onde há a interação entre continente, atmosfera e oceano, sendo possível encontrar diversos atuantes que podem intensificar os processos erosivos, sejam eles o vento, maré, ou por intervenções humanas, como construções e ocupações indevidas ao longo da linha de costa.Palavras Chave: Volta do Rio; Energia Eólica; Erosão. ABSTRACTBrazil is a country with an extensive coastline, about 7,367 km of coastline, with a natural potential for wind power generation. The state of Ceará is one of the largest producers of wind energy for the country, obtaining notoriety and required maintenance of its wind farms, especially if located in coastal areas, where there is a great natural dynamic. The present work seeks the movement of morphological dynamics in the beach of Volta do Rio, located in Acaraú/CE, which is about 238 km from Fortaleza/CE. The data collected in the field found that there is a strong erosive process on the Beach of Volta do Rio, which warns about the expansion of advanced marine on the wind farm present on site. Erosion is a natural phenomenon that works in the modeling of many hearth forms. On the coast, this is not different, considering a highly dynamic environment in which there is an interaction between continent, atmosphere and ocean, being possible to find many factors that can intensify the erosive processes, such as wind, tide, or human intervention, as constructions and improper occupations along the coast line.Key words: Volta do Rio; Wind Energy; Erosion. RESUMENBrasil es un país con una extensa costa, cerca de 7.367 km de costa, con un potencial natural para la generación de energía eólica. El estado del Ceará es uno de los mayores productores de energía eólica del país, ganando notoriedad y la necesidad de mantener sus parques eólicos, especialmente si está instalado en zonas costeras, donde existe una gran dinámica natural. La presente investigación tiene como objetivo monitorear la dinámica morfológica en la playa de Vuelta del Rio, ubicada en Acaraú / CE, que está a unos 238 km de Fortaleza / CE. Los datos recopilados en los viajes de campo, encontraron que hay un fuerte proceso erosivo en la playa de Vuelta del Rio, que advierte sobre la contención del avance marino bajo el parque eólico presente en el sitio. La erosión es un fenómeno natural que funciona en el modelado de muchas formas terrestres. En la costa, esto no es diferente, ya que es un entorno altamente dinámico donde existe la interacción entre el continente, la atmósfera y el océano, permitiendo encontrar varios actores que pueden intensificar los procesos erosivos, ya sea viento, marea o intervenciones humanas, como edificios y ocupaciones inadecuadas a lo largo de la costa.Palabras clave: Vuelta del Río; Energía Eólica; Erosión.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

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