Residual load probabilistic forecast for reserve assessment: A real case study

Pierro, Marco; Felice, Matteo De; Maggioni, Enrico; Moser, David; Perotto, Alessandro; Spada, Francesco; Cornaro, Cristina

doi:10.1016/j.renene.2019.12.056

Cited by 22 publications

(15 citation statements)

References 31 publications

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“…Joos et al [11] suggest possible reforms of the German and UK balancing regulation systems to reduce wind and solar integration costs. Pierro et al in [12,13] evaluate the energy and economic benefit for a local distribution system operator in the north of Italy in improving their TSO transmission scheduling and reducing the reserves by the use of accurate probabilistic PV generation forecasts. In [14], Pierro et al extend these studies to the Italian national scale, proposing an innovative strategy to reduce the imbalance and its related costs.…”

Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

“…Afterward, they propose the use of a new kind of solar system, called "flexible" PV plants, able to provide dispatching services for solar-induced imbalance regulations by proactive curtailment and battery storage additional power. These studies [12][13][14] were conducted considering the current and future solar penetration at regional and national levels. Perez et al [15,16] showed how flexible plants can be used at first to provide a "perfect forecast", removing the prediction uncertainty and then providing a full dispatchable, firm PV generation 24/365, removing solar intermittency for several US states.…”

Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

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The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

et al. 2020

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One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms’ generation is important both for the producers/traders to minimize the imbalance costs and for the transmission system operators to ensure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale photovoltaic (PV) plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of the forecast accuracy and accuracy improvement in the context of the Italian energy market’s regulatory framework. Through this study, we further point out several important criticisms of the Italian “single pricing” system that brings paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome the undesired effects of the current dispatching regulations.

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Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Pierro et al in [12,13] evaluate the energy and economic benefit for a local distribution system operator in the north of Italy in improving their TSO transmission scheduling and reducing the reserves by the use of accurate probabilistic PV generation forecast. In [14], Pierro et al extend these studies to the Italian national scale, proposing an innovative strategy to reduce the imbalance and its related costs.…”

Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

“…Afterward, they propose the use of a new kind of solar systems, called 'flexible" PV plants, able to provide dispatching services for solar-induced imbalance regulation by proactive curtailment and battery storage additional power. These studies [12,13,14] were conducted considering current and future solar penetration at regional and national levels. Perez et al [15,16] showed how flexible plants can be used at first to provide a "perfect forecast" removing the prediction uncertainty and then to provide a full dispatchable, firm PV generation 24/365 removing solar intermittency, for several US states.…”

Section: Existing Literature and Novelty Of The Workmentioning

confidence: 99%

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

Pierro¹,

Moser²,

Perez³

et al. 2020

Preprint

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One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms generation is important both for the producers/traders to minimize the imbalance costs and for the Transmission System Operators to insure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale PV plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of forecast accuracy and accuracy improvement in the context of the Italian energy market regulatory framework. Through this study, we further point out some several important criticisms of the Italian “single pricing” system that brings to paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome these undesired effects of the current dispatching regulations.

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“…A very short‐term forecast is done from real‐time to a few minutes, which helps to estimate intra‐day scheduling of power for the distribution companies and contingency analysis for the security of the system [6]. Short‐term forecast is done from half an hour to the upcoming day, which is useful for the allocation of spinning reserve, operational planning, unit commitment, and maintenance scheduling [9–12]. Medium‐term forecast is done from a few days to a few weeks, which is useful for seasonal planning such as peak‐summer and winter [7].…”

Section: Introductionmentioning

confidence: 99%