A case study of outlier event on solar irradiance forecasts from the two NWPs with different horizontal resolutions

Ohtake, Hideaki; Takashima, Takumi; Oozeki, Takashi; Fonseca, Joao Gari da Silva; Yamada, Yoshiyuki

doi:10.1051/rees/2016049

Cited by 5 publications

(3 citation statements)

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“…In the figure, the top panel demonstrates nine predicted PV profiles sampled from a given prediction region. Note that the PV profile prediction is not the primary interest of this paper; readers may refer to [17] for more details. The second panel depicts the prosumption curve x generated based on the adjustment of the SMS and the generator described by the bottom two panels, respectively.…”

Section: Illustrative Examplementioning

confidence: 99%

“…However, the above demonstration does not reflect enough information about the distribution of the profit. To this end, let us discuss more details about the solutions by selecting 1000 PV profiles from the given predictions region; see [17]. Note that, to keep consistency, profiles demonstrated in Fig.…”

Section: Acs-based Dtc Analysismentioning

confidence: 99%

“…2 are also incorporated within the new-generated 1000 PV profiles. By solving (17), we obtain the associated optimal decision variable as…”

Section: Acs-based Dtc Analysismentioning

confidence: 99%

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Analysis of Profit Maximization Problem in Multiperiod Energy Markets with Uncertain Photovoltaics Power

Ishizaki

Imura

2020

SICE Journal of Control, Measurement, and System Integration

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We formulate and analyze a profit maximization problem for one participant (aggregator) in a multiperiod electricity market with the consideration of profit fluctuations caused by uncertain photovoltaics (PV) output. We first introduce an aggregator's prosumption model, whereby an energy demand/supply profile can be achieved by adjusting the dispatchable devices, e.g., energy storage management systems and fossil fuel generators. Then, the uncertainty issue stemming from the PV profiles is handled by a classical stochastic programming framework and a robust optimization framework. A dispatchable tuning cost function is discussed based on the two frameworks above, and the distribution of the particular cost is analyzed. The simulation results show that although both of the two frameworks are able to overcome the PV uncertainty, an average strategy gives a higher expected value of profits with a higher risk (a larger variance) while a worst-case strategy gives a lower expected value of profits with a smaller risk.

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Section: Illustrative Examplementioning

confidence: 99%

Section: Acs-based Dtc Analysismentioning

confidence: 99%