Real-Time Economic Dispatch Considering Renewable Power Generation Variability and Uncertainty Over Scheduling Period

Reddy, S. Surender; Bijwe, P.R.; Abhyankar, A. R.

doi:10.1109/jsyst.2014.2325967

Cited by 206 publications

(58 citation statements)

References 25 publications

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“…The OPF is performed only at the beginning of each scheduling interval, while also satisfying all the constraints of the subintervals by incorporating the generating costs of the subintervals. The operation strategies obtained in this way are named 'best-fit' participation factors [209,210]. They are then utilized to correct the decision variables of subintervals based on forecasted values of REG and demand.…”

Section: Opf-based Rt-emssmentioning

confidence: 99%

A Survey of Real-Time Optimal Power Flow

et al. 2018

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There has been a strong increase of penetration of renewable energies into power systems. However, the renewables pose new challenges for the operation of the networks. Particularly, wind power is intermittently fluctuating, and, therefore, the network operator has to fast update the operations correspondingly. This task should be performed by an online optimization. Therefore, real-time optimal power flow (RT-OPF) has become an attractive topic in recent years. This paper presents an overview of recent studies on RT-OPF under wind energy penetration, offering a critical review of the major advancements in RT-OPF. It describes the challenges in the realization of the RT-OPF and presents available approaches to address these challenges. The paper focuses on a number of topics which are reviewed in chronological order of appearance: offline energy management systems (EMSs) (deterministic and stochastic approaches) and real-time EMSs (constraint satisfaction-based and OPF-based methods). The particular challenges associated with the incorporation of battery storage systems in the networks are explored, and it is concluded that the current research on RT-OPF is not sufficient, and new solution approaches are needed.Energies 2018, 11, 3142 2 of 20 time. However, the incorporation of BSSs into the network leads to dynamic state operations and thus introduces dynamic model equations to the OPF, which makes the problem more complex to solve. This complexity is due to the fact that the dynamic optimization is described by differential/difference equations, whereas static optimization requires only algebraic equations [30].Another issue is that the REG rate is uncertain. It means their output cannot be forecasted accurately, and there may be discrepancies between the forecasted and actually realized values. The uncertainties can lead to constraint violations and thus safety problems if they are not handled properly. Therefore, deterministic OPF methods are not suitable for the real operation of the networks, or their solutions need further modifications before realization. Besides, owing to fast fluctuating REG, in particular wind power, the network operators need to fast update-i.e., in real-time-the operation strategies correspondingly, in order for the network to operate economically and in its feasible region. Therefore, the real-time energy management systems (RT-EMSs) have attracted increasing interest from many researchers. In this paper, we classify the RT-EMSs into two main categories: (1) constraint satisfaction-based RT-EMSs, and (2) OPF-based RT-EMSs. The former can satisfy the technical constraints of the network in real time, but the solutions may not be optimal. The latter provides optimal solutions in real time while satisfying the constraints. It is noted that the technical constraints could be different for these two categories, depending on the components of the network (details can be seen in Section 2).The remainder of the paper is organized as follows: Section 2 provides the general formulation of OPF...

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Section: Opf-based Rt-emssmentioning

confidence: 99%

A Survey of Real-Time Optimal Power Flow

et al. 2018

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“…Wind power is one of the fastest-growing sources, however it is uncertain and cannot be scheduled due to its intrinsic dependence on varying weather conditions over many years [2,3]. Solar power is less uncertain, but has higher variability compared to wind power [4]. Unlike wind energy, hydropower can be scheduled and has already played an important role in electricity supply all over the world.…”

Section: Introductionmentioning

confidence: 99%

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Yang

Zhou

et al. 2018

Algorithms

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Abstract:In this paper, a gradient-based cuckoo search algorithm (GCS) is proposed to solve a reservoir-scheduling problem. The classical cuckoo search (CS) is first improved by a self-adaptive solution-generation technique, together with a differential strategy for Lévy flight. This improved CS is then employed to solve the reservoir-scheduling problem, and a two-way solution-correction strategy is introduced to handle variants' constraints. Moreover, a gradient-based search strategy is developed to improve the search speed and accuracy. Finally, the proposed GCS is used to obtain optimal schemes for cascade reservoirs in the Jinsha River, China. Results show that the mean and standard deviation of power generation obtained by GCS are much better than other methods. The converging speed of GCS is also faster. In the optimal results, the fluctuation of the water level obtained by GCS is small, indicating the proposed GCS's effectiveness in dealing with reservoir-scheduling problems.

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“…La principal desventaja de este tipo de energía es la aleatoriedad de la velocidad del viento y la radiación solar que hace que no sea certero programar con antelación un despacho económico. Es entonces necesario utilizar algoritmos rápidos que programen un despacho económico óptimo cuando hay una alta incertidumbre de las inyecciones de energía por parte de los paneles solares y los aerogeneradores eólicos, y así se permitan simular una alta cantidad de posibles escenarios [1], [2].…”

Section: Introductionunclassified

“…De esta manera el problema corresponde a una optimización de una función objetivo y unas restricciones que se deben cumplir, para los diferentes escenarios aleatorios de las potencias inyectadas renovables [1], [2], [3], [4]. En el presente escrito se propone el uso de la función f mincon de M atlab para realizar el despacho económico de un sistema de potencia con penetración de energías renovables.…”

Section: Introductionunclassified

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Despacho económico en microredes con penetración de energía renovable usando algoritmo de punto interior y restricciones lineales

2017

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ResumenA lo largo de este artículo se muestran simulaciones de posibles despachos económicos para un sistema con penetración de energías renovables cuando hay variaciones de la velocidad del viento y de radiación solar para diferentes horas del día. Para ello se prueba y se valida una metodología para minimizar el costo total del sistema a partir del uso del método de punto interior utilizado por la función f mincon de M atLab. Uno de los aportes de este articulo, es que se propone una adaptación de las restricciones del sistema de potencia a la sintaxis de la función que requiere que estas restricciones sean lineales.

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Real-Time Economic Dispatch Considering Renewable Power Generation Variability and Uncertainty Over Scheduling Period

Cited by 206 publications

References 25 publications

A Survey of Real-Time Optimal Power Flow

A Survey of Real-Time Optimal Power Flow

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Despacho económico en microredes con penetración de energía renovable usando algoritmo de punto interior y restricciones lineales

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