Estimating the Spinning Reserve Requirements in Systems With Significant Wind Power Generation Penetration

Ortega‐Vazquez, Miguel A.; Kirschen, Daniel

doi:10.1109/tpwrs.2008.2004745

Cited by 569 publications

(180 citation statements)

References 19 publications

Supporting

Mentioning

179

Contrasting

Order By: Relevance

“…The sizing of the battery is an optimisation problem, described by Equations (3-6) aimed at identifying the optimal power and energy rating of the storage Rp opt , Re opt that maximise a selected objective function f obj under a series of constraints cons. The objective function is considered to be equal to ROI, calculated as in Equation (1). The terms Vb [€] and Cb [€] represent the value of the action of the battery and the cost of the battery respectively.…”

Section: Methodsmentioning

confidence: 99%

Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation

et al. 2018

View full text Add to dashboard Cite

International audienceThis paper describes a research on the influence of wind power prediction error autocorrelation on the sizing of storage coupled with a wind farm. The stochastic nature of renewable energies resources such as wind speed or solar radiation represents a challenge for the grid integration of renewable energy plants. The imbalances between renewable power predictions and realised production are generally penalised by system operators since additional reserves are required to maintain the stability of the grid. The coupling of storage devices with renewable energy plants is one of the solutions studied to reduce those imbalances. In this work, a methodology to manage imbalances and to size storage in order to achieve a determined level of controllability is proposed. It is applied to a specific use case: the integration of a combined wind-storage plant in French Guyana. The influence of the autocorrelations of errors on the battery size is investigated in detail and a methodology for producing wind prediction errors time series is presented

show abstract

Section: Methodsmentioning

confidence: 99%

Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation

et al. 2018

View full text Add to dashboard Cite

show abstract

“…It is assumed that the wind forecasting error obeys a normal distribution with a certain deviation [22]. Assuming that the wind prediction was made 24 h prior to the first hour of the schedule for an ensemble of wind farms contained in a region with a diameter of 140 km, the standard deviation of the wind forecasting error can be approximated by:…”

Section: Wind and Wpfe Modelmentioning

confidence: 99%

“…∆P lj = P lj − P lj0 + P aj − P f j (22) where ∆P lj is the load fluctuation of the jth household; P lj is the total power after DR of smart appliances in the jth household; P lj0 is the prediction load power of smart appliances in the jth household; P aj is the actual power of non-smart appliances in the jth household; and P fj is the forecasting power of non-smart appliances in the jth household. The active power balance constraint is shown in Equation (23).…”

Section: Optimization Modelmentioning

confidence: 99%

A Time-Varying Potential-Based Demand Response Method for Mitigating the Impacts of Wind Power Forecasting Errors

2017

View full text Add to dashboard Cite

Abstract:The uncertainty of wind power results in wind power forecasting errors (WPFE) which lead to difficulties in formulating dispatching strategies to maintain the power balance. Demand response (DR) is a promising tool to balance power by alleviating the impact of WPFE. This paper offers a control method of combining DR and automatic generation control (AGC) units to smooth the system's imbalance, considering the real-time DR potential (DRP) and security constraints. A schematic diagram is proposed from the perspective of a dispatching center that manages smart appliances including air conditioner (AC), water heater (WH), electric vehicle (EV) loads, and AGC units to maximize the wind accommodation. The presented model schedules the AC, WH, and EV loads without compromising the consumers' comfort preferences. Meanwhile, the ramp constraint of generators and power flow transmission constraint are considered to guarantee the safety and stability of the power system. To demonstrate the performance of the proposed approach, simulations are performed in an IEEE 24-node system. The results indicate that considerable benefits can be realized by coordinating the DR and AGC units to mitigate the WPFE impacts.

show abstract

“…Of course, that impact will be higher as wind penetration grows. Independent System Operators (ISO) can take different general approaches to accommodate the additional uncertainty at the unit commitment level, such as improving forecasting models for the wind (Mahoney et al, 2012), adjusting reserve requirements for the system (NERC, 2010;Ortega-Vazquez & Kirschen, 2009;Wang & Hedman, 2015;Luna-Ramírez, Torres-Sánchez, & Pavas-Martínez, 2015), implementing stochastic unit commitment (Ruiz, Philbrick, Zak, Cheung, & Sauer, 2009;Papavasiliou, Oren, & O'Neill, 2011;Holttinen et al, 2012), and/or using a rolling-planning scheme (Tuohy, Meibom, Denny, & O'Malley, 2009). Thus, among the ancillary services needing revision as wind prominence grows are operational reserves, that is, the extra generation capacity put online in the day-ahead unit commitment.…”

Section: Introductionmentioning

confidence: 99%

Power system reliability impacts of wind generation and operational reserve requirements

Gil

2015

ing.inv.

View full text Add to dashboard Cite

Due to its variability, wind generation integration presents a significant challenge to power system operators in order to maintain adequate reliability levels while ensuring least cost operation. This paper explores the trade-off between the benefits associated to a higher wind penetration and the additional operational reserve requirements that they impose. Such exploration is valued in terms of its effect on power system reliability, measured as an amount of unserved energy. The paper also focuses on how changing the Value of Lost Load (VoLL) can be used to attain different reliability targets, and how wind power penetration and the diversity of the wind energy resource will impact quality of supply (in terms of instances of unserved energy). The evaluation of different penetrations of wind power generation, different wind speed profiles, wind resource diversity, and different operational reserve requirements, is conducted on the Chilean Northern Interconnected System (SING) using statistical modeling of wind speed time series and computer simulation through a 24-hour ahead unit commitment algorithm and a Monte Carlo simulation scheme. Results for the SING suggest that while wind generation can significantly reduce generation costs, it can also imply higher security costs to reach acceptable reliability levels.Keywords: Wind power, uncertainty modeling, variable generation, reserve requirements, value of lost load. RESUMENDebido a su variabilidad, la integración de generación eólica presenta desafíos significativos para los operadores de los sistemas eléctricos a la hora de mantener niveles de confiabilidad adecuados asegurando, de forma simultánea, una operación a mínimo costo. Este artículo explora los beneficios asociados a una mayor penetración de generación eólica y los requerimientos adicionales de reservas operacionales que esta impone. Dicha exploración se realiza en términos de los efectos de la energía eólica en la confiabilidad del sistema, medida como cantidad de energía no servida. El artículo, además, se enfoca en cómo es que al cambiar el costo de falla se puede motivar el alcance de diferentes metas de confiabilidad, y cómo la penetración y diversidad del recurso eólico impactan la calidad de servicio (en términos de instancias de energía no servida). La evaluación de diferentes niveles de penetración, diferentes perfiles de velocidad de viento, diversidad del recurso eólico y distintos requerimientos de reservas operacionales, se lleva a cabo en el Sistema Interconectado del Norte Grande (SING) chileno usando modelos estadísticos de velocidad de viento y simulación computacional mediante un algoritmo de pre-despacho y un esquema de Monte Carlo. Los resultados para el SING sugieren que mientras la generación eólica puede reducir significativamente los costos de generación del sistema, también implica mayores costos de seguridad para alcanzar niveles de confiabilidad adecuados.

show abstract

Estimating the Spinning Reserve Requirements in Systems With Significant Wind Power Generation Penetration

Cited by 569 publications

References 19 publications

Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation

Storage sizing for grid connected hybrid wind and storage power plants taking into account forecast errors autocorrelation

A Time-Varying Potential-Based Demand Response Method for Mitigating the Impacts of Wind Power Forecasting Errors

Power system reliability impacts of wind generation and operational reserve requirements

Contact Info

Product

Resources

About