Net load forecasting in presence of renewable power curtailment

Fonte, P. M.; Monteiro, Cláudio

doi:10.1109/eem.2016.7521281

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…Very often, in this specific case study, during the off-peak periods with low load and high RES, the thermal units are forced to work below the technical minimum. To increase artificially the necessity of thermal production, the system operators choose to cut the wind production which demands a special care with the RES forecasting [12]. The measured data of RES production and load demand were provided by the system operator.…”

Section: ) Probabilistic Forecastsmentioning

confidence: 99%

Analysis of Spinning Reserves in Systems with Variable Power Sources

Fonte

Monteiro

Barbosa

2018

2018 15th International Conference on the European Energy Market (EEM)

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In this paper is studied an approach based on risk assessment to solve the scheduling of a power production system with variable power sources. The spinning reserves resulting from the unit commitment are analyzed too. In this methodology there are no infeasible solutions, only more or less costly solutions associated to the operation risks, such as, load or renewable production curtailment. The uncertainty of forecasted production and load demand are defined by probability distribution functions. The methodology is tested in a real case study, an island with high penetration of renewable power production. Finally, forecasted and measured reserves are compared, once the reserves are strongly linked with the forecasting quality. The results of a real case study are presented and discussed. They show the difficulty to achieve complete robust solutions.

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Section: ) Probabilistic Forecastsmentioning

confidence: 99%

Analysis of Spinning Reserves in Systems with Variable Power Sources

Fonte

Monteiro

Barbosa

2018

2018 15th International Conference on the European Energy Market (EEM)

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“…Similar to load forecasting, these models have limitations for very short-term applications in real time due to massive training data requirements, forecasts biased to input data, time consuming learning and hyperparameter optimization procedures. Attempts are being made to reduce operational complexity and associated forecasting errors arising out of considering three different forecasts of load, wind and solar, by consideration of net load forecast and forecasting errors by power markets [6,10,18,31]. In such markets, system operations such as economic dispatch [16,22] and generation ramping requirement estimations [8,29,30] are planned based on net load forecasts.…”

Section: Introductionmentioning

confidence: 99%

“…In such markets, system operations such as economic dispatch [16,22] and generation ramping requirement estimations [8,29,30] are planned based on net load forecasts. Even though accurate net load forecasts are vital in modern power system operational planning, it secured little research attention [6,10,18,27,31]. Also, most of the NLF approaches focused on micro grids [18,31], distribution networks [6] and residential loads [27].…”

Section: Introductionmentioning

confidence: 99%

Grey System Theory Based Net Load Forecasting for High Renewable Penetrated Power Systems

Sreekumar

Sharma

Bhakar

2020

Technol Econ Smart Grids Sustain Energy

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Net-load is the imbalance between aggregated load and renewable generation. System operations like economic dispatch necessitate accurate forecasting of net-load. There has been significant progress in load and renewable generation forecasting, however, little research focus has been there on Net-Load Forecasting (NLF). Therefore, this paper proposes three Direct Grey index net-load forecasting models (DGM (1, 1), DGM (1, 2) and DGM (1, 3)) using Grey System Theory (GST). GST based models are suitable for accurate and fast very short-term (five minutes ahead) forecasting due to their momentum transfer behavior. Proposed NLF models are implemented for the Bonneville Power Administration (BPA) balancing area. Forecasts obtained from proposed models are compared with actual net load data and forecasts obtained from reference Artificial Neural Network (ANN) model. Comparison with actual net load shows that proposed models have strong potential for very short-term NLF. At very short time frames, net load shows a very high correlation with previous time steps data. Proposed models utilize such characteristics for forecasting, compared to continuous error reduction procedure in ANN. Continuous error reduction in a very short time frame can lead to under/overestimation of ANN weights and that lowers the forecasting accuracy. Proposed NLF models, especially DGM (1, 3) show superior performance over ANN.

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“…Some papers take advantage of the measurements of distributed generation through smart meters and of the total load to make a separate forecast of production and consumption, and thus of the net load [38,39].…”

Section: Introductionmentioning

confidence: 99%

Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System

Massidda

Marrocu

2017

Energies

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Abstract:The balance between production and consumption in a smart grid with high penetration of renewable sources and in the presence of energy storage systems benefits from an accurate load prediction. A general approach to load forecasting is not possible because of the additional complication due to the increasing presence of distributed and usually unmeasured photovoltaic production. Various methods are proposed in the literature that can be classified into two classes: those that predict by separating the portion of load due to consumption habits from the part of production due to local weather conditions, and those that attempt to predict the load as a whole. The characteristic that should lead to a preference for one approach over another is obviously the percentage of penetration of distributed production. The study site discussed in this document is the grid of Borkum, an island located in the North Sea. The advantages in terms of reducing forecasting errors for the electrical load, which can be obtained by using weather information, are explained. In particular, when comparing the results of different approaches gradually introducing weather forecasts, it is clear that the correct functional dependency of production has to be taken into account in order to obtain maximum yield from the available information. Where possible, this approach can significantly improve the quality of the forecasts, which in turn can improve the balance of a network-especially if energy storage systems are in place.

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Net load forecasting in presence of renewable power curtailment

Cited by 8 publications

References 12 publications

Analysis of Spinning Reserves in Systems with Variable Power Sources

Analysis of Spinning Reserves in Systems with Variable Power Sources

Grey System Theory Based Net Load Forecasting for High Renewable Penetrated Power Systems

Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System

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